From d1137ab46f09047c212e4414bf4fefa9fe65aebe Mon Sep 17 00:00:00 2001 From: Nishad Gothoskar Date: Mon, 22 Jul 2024 22:43:47 +0000 Subject: [PATCH 01/16] save --- notebooks/bayes3d_paper/interactive.ipynb | 3529 ++++++++------------- 1 file changed, 1400 insertions(+), 2129 deletions(-) diff --git a/notebooks/bayes3d_paper/interactive.ipynb b/notebooks/bayes3d_paper/interactive.ipynb index e1fce884..973f4558 100644 --- a/notebooks/bayes3d_paper/interactive.ipynb +++ b/notebooks/bayes3d_paper/interactive.ipynb @@ -1,2132 +1,1403 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Todos\n", - "- investigate how to handle missing data\n", - "- marginalize out is_outlier\n", - "- handle the different scalings of the l,a,b,d, spaces" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "import b3d\n", - "import jax.numpy as jnp\n", - "import os\n", - "from b3d import Mesh, Pose\n", - "import jax\n", - "import genjax\n", - "from genjax import Pytree\n", - "import rerun as rr\n", - "from b3d.modeling_utils import uniform_discrete, uniform_pose, gaussian_vmf\n", - "import matplotlib.pyplot as plt\n", - "from functools import partial\n", - "import importlib\n", - "from ipywidgets import interact\n", - "import ipywidgets as widgets\n", - "\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 86, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " 0%| | 0/20 [00:00" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b3d.viz_rgb(rendered_rgbds[0])" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [], + "source": [ + "@Pytree.dataclass\n", + "class MaskedKImageLikelihoodMarginalizeOutlier(genjax.ExactDensity):\n", + " def sample(self, key,\n", + " row_coordinates,\n", + " column_coordinates,\n", + " rendered_color_space_d,\n", + " inlier_variances,\n", + " outlier_variances,\n", + " outlier_probability,\n", + " lower_bound, upper_bound,\n", + " image_height, image_width\n", + " ):\n", + " observed_image = jnp.zeros((image_height.const, image_width.const, 4))\n", + "\n", + " no_mesh_surface = (rendered_color_space_d[..., 3] == 0)[row_coordinates, column_coordinates]\n", + " outlier_probability_adjusted = outlier_probability * (1 - no_mesh_surface) + no_mesh_surface * 1.0\n", + "\n", + " is_outlier = jax.vmap(genjax.bernoulli.sample,in_axes=(0, 0))(\n", + " jax.random.split(key, len(row_coordinates)), jax.scipy.special.logit(outlier_probability_adjusted)\n", + " )\n", + "\n", + " sampled_inlier_values = jax.vmap(genjax.truncated_normal.sample, in_axes=(0, 0, None, None, None))(\n", + " jax.random.split(key, len(row_coordinates)), rendered_color_space_d[row_coordinates, column_coordinates], inlier_variances,\n", + " lower_bound, upper_bound\n", + " )\n", + " sampled_outlier_values = jax.vmap(genjax.truncated_normal.sample, in_axes=(0, 0, None, None, None))(\n", + " jax.random.split(key, len(row_coordinates)), rendered_color_space_d[row_coordinates, column_coordinates], outlier_variances,\n", + " lower_bound, upper_bound\n", + " )\n", + " sampled_values = (\n", + " is_outlier[...,None] * sampled_outlier_values + (1 - is_outlier[...,None]) * sampled_inlier_values\n", + " )\n", + " # sampled_values = jnp.where(is_outlier, sampled_outlier_values, sampled_inlier_values)\n", + "\n", + " observed_image = observed_image.at[row_coordinates, column_coordinates, :].set(sampled_values)\n", + " return observed_image\n", + "\n", + " def logpdf(self,\n", + " observed_color_space_d,\n", + " row_coordinates,\n", + " column_coordinates,\n", + " rendered_color_space_d,\n", + " inlier_variances,\n", + " outlier_variances,\n", + " outlier_probability,\n", + " lower_bound, upper_bound,\n", + " image_height, image_width\n", + " ):\n", + " no_mesh_surface = (rendered_color_space_d[..., 3] == 0)[row_coordinates, column_coordinates]\n", + " subset_observed = observed_color_space_d[row_coordinates, column_coordinates]\n", + "\n", + " outlier_probability_adjusted = outlier_probability * (1 - no_mesh_surface) + no_mesh_surface * 1.0\n", + "\n", + " subset_observed_rescaled = (subset_observed - lower_bound) / (upper_bound - lower_bound)\n", + " rendered_values_rescaled = (rendered_color_space_d[row_coordinates, column_coordinates] - lower_bound) / (upper_bound - lower_bound)\n", + "\n", + " scores_inlier = jax.vmap(genjax.truncated_normal.logpdf, in_axes=(0, 0, None, None, None))(\n", + " subset_observed_rescaled, rendered_values_rescaled, inlier_variances / (upper_bound - lower_bound),\n", + " 0.0, 1.0\n", + " )\n", + " scores_outlier = jax.vmap(genjax.truncated_normal.logpdf, in_axes=(0, None, None, None, None))(\n", + " subset_observed_rescaled, 0.5, outlier_variances / (upper_bound - lower_bound),\n", + " 0.0, 1.0\n", + " )\n", + "\n", + " scores_inlier_merged = jax.nn.logsumexp(scores_inlier[..., 1:3] + jnp.log(1/3), axis=-1) + scores_inlier[..., 3] + jnp.log(1.0 - outlier_probability_adjusted) \n", + " scores_outlier_merged = jax.nn.logsumexp(scores_outlier[..., 1:3] + jnp.log(1/3), axis=-1) + scores_outlier[..., 3] + jnp.log(outlier_probability_adjusted)\n", + " return jnp.logaddexp(scores_inlier_merged, scores_outlier_merged).sum()\n", + "\n", + "masked_k_image_likelihood_marginalize_outlier_prob = MaskedKImageLikelihoodMarginalizeOutlier()\n", + "\n", + "\n", + "# k = 10\n", + "# masked_k_image_likelihood.logpdf(\n", + "# jnp.zeros((renderer.height, renderer.width, 4)),\n", + "# jnp.arange(k),\n", + "# jnp.arange(k),\n", + "# jnp.ones(k) * 0.1,\n", + "# jnp.zeros(k),\n", + "# jnp.zeros(4)- 0.1,\n", + "# jnp.ones(4),\n", + "# renderer.height,\n", + "# renderer.width\n", + "# )\n", + "# masked_k_image_likelihood.sample(\n", + "# key,\n", + "# jnp.arange(k),\n", + "# jnp.arange(k),\n", + "# jnp.ones(k) * 0.1,\n", + "# jnp.zeros(k),\n", + "# jnp.zeros(4)- 0.1,\n", + "# jnp.ones(4),\n", + "# renderer.height,\n", + "# renderer.width\n", + "# );" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "metadata": {}, + "outputs": [], + "source": [ + "def plot_trace(trace):\n", + " fig, ax = plt.subplots(1, 5, figsize=(10, 5))\n", + "\n", + " ax[0].imshow(trace.get_retval()[\"rendered_rgbd\"][..., :3])\n", + " ax[0].axis('off')\n", + "\n", + " ax[1].imshow(trace.get_retval()[\"sampled_rgbd\"][..., :3])\n", + " ax[1].axis('off')\n", + "\n", + " ax[2].matshow(trace.get_retval()[\"sampled_rgbd\"][..., 3])\n", + " ax[2].axis('off')\n", + "\n", + "\n", + " ax[3].imshow(trace.get_retval()[\"observed_rgbd\"][..., :3])\n", + " ax[3].axis('off')\n", + "\n", + "\n", + " ax[4].imshow(trace.get_retval()[\"observed_rgbd\"][..., :3],alpha=1.0)\n", + " ax[4].imshow(trace.get_retval()[\"rendered_rgbd\"][..., :3],alpha=0.5)\n", + " ax[4].axis('off')\n", + " return fig\n" + ] + }, + { + "cell_type": "code", + "execution_count": 132, + "metadata": {}, + "outputs": [], + "source": [ + "lower_bound = jnp.array([0.0, -100.0, -100.0, 0.0])\n", + "upper_bound = jnp.array([100.0, 100.0, 100.0, 4.0])\n", + "convert_rgbd_to_color_space = lambda x: b3d.colors.rgbd_to_labd(x)\n", + "convert_color_space_to_rgbd = lambda x: b3d.colors.labd_to_rgbd(x)\n", + "\n", + "@genjax.gen\n", + "def ray_model(args):\n", + " likelihood_args = args[\"likelihood_args\"]\n", + " pose = (\n", + " uniform_pose(jnp.ones(3) * -100.0, jnp.ones(3) * 100.0) @ f\"object_pose_0\"\n", + " )\n", + " rendered_rgbd = renderer.render_rgbd_from_mesh(meshes[IDX].transform(pose))\n", + " rendered_color_space_d = convert_rgbd_to_color_space(rendered_rgbd)\n", + "\n", + " k = likelihood_args[\"k\"].const\n", + " image_height, image_width = rendered_color_space_d.shape[0], rendered_color_space_d.shape[1]\n", + " image_height = Pytree.const(image_height)\n", + " image_width = Pytree.const(image_width)\n", + "\n", + " row_coordinates = genjax.categorical.vmap(in_axes=(0,))(\n", + " jnp.ones((k, image_height.const))\n", + " ) @ \"row_coordinates\"\n", + " column_coordinates = genjax.categorical.vmap(in_axes=(0,))(\n", + " jnp.ones((k, image_width.const))\n", + " ) @ \"column_coordinates\"\n", + "\n", + "\n", + " outlier_probability = genjax.uniform(0.0, 1.0) @ \"outlier_probability\"\n", + " inlier_color_variance = genjax.uniform(0.01, 100.0) @ \"inlier_color_variance\"\n", + " inlier_lightness_variance = genjax.uniform(0.01, 100.0) @ \"inlier_lightness_variance\"\n", + " inlier_depth_variance = genjax.uniform(0.01, 1000.0) @ \"inlier_depth_variance\"\n", + "\n", + " inlier_variances = jnp.array([inlier_lightness_variance, inlier_color_variance, inlier_color_variance, inlier_depth_variance])\n", + " outlier_variances = jnp.array([1000000.0, 1000000.0, 1000000.0, 1000000.0])\n", + "\n", + "\n", + " sampled_color_space_d = masked_k_image_likelihood_marginalize_outlier_prob.sample(\n", + " key,\n", + " row_coordinates,\n", + " column_coordinates,\n", + " rendered_color_space_d,\n", + " inlier_variances,\n", + " outlier_variances,\n", + " outlier_probability,\n", + " lower_bound, upper_bound,\n", + " image_height, image_width\n", + " )\n", + "\n", + " observed_color_space_d = masked_k_image_likelihood_marginalize_outlier_prob(\n", + " row_coordinates,\n", + " column_coordinates,\n", + " rendered_color_space_d,\n", + " inlier_variances,\n", + " outlier_variances,\n", + " outlier_probability,\n", + " lower_bound, upper_bound,\n", + " image_height, image_width\n", + " ) @ \"observed_color_space_d\"\n", + "\n", + " observed_rgbd = convert_color_space_to_rgbd(observed_color_space_d)\n", + " sampled_rgbd = convert_color_space_to_rgbd(sampled_color_space_d)\n", + "\n", + " return {\n", + " \"rendered_rgbd\": rendered_rgbd,\n", + " \"sampled_rgbd\": sampled_rgbd,\n", + " \"observed_rgbd\": observed_rgbd,\n", + "\n", + " \"rendered_color_space_d\": rendered_color_space_d,\n", + " \"sampled_color_space_d\": sampled_color_space_d,\n", + " \"observed_color_space_d\": observed_color_space_d,\n", + " }\n", + "\n", + "importance_jit = jax.jit(ray_model.importance)\n", + "update_jit = jax.jit(ray_model.update)\n", + "\n", + "\n", + "\n", + "\n", + "def plot_interactive(trace):\n", + " def _make_viz(outlier_probability, inlier_lightness_variance, inlier_color_variance, inlier_depth_variance):\n", + " choicemap = genjax.ChoiceMap.d(\n", + " {\n", + " \"outlier_probability\": outlier_probability,\n", + " \"inlier_lightness_variance\": inlier_lightness_variance,\n", + " \"inlier_color_variance\": inlier_color_variance,\n", + " \"inlier_depth_variance\": inlier_depth_variance,\n", + " }\n", + " )\n", + " modified_trace = update_jit(\n", + " key,\n", + " trace,\n", + " choicemap\n", + " )[0]\n", + " plot_trace(modified_trace)\n", + "\n", + " interact(_make_viz,\n", + " k = widgets.IntSlider(value=10000, min=1, max=100000, step=1),\n", + " outlier_probability = widgets.FloatSlider(\n", + " value=trace.get_choices()[\"outlier_probability\"],\n", + " min=outlier_probability_sweep.min(),\n", + " max=outlier_probability_sweep.max(),\n", + " step=0.01\n", + " ),\n", + " inlier_lightness_variance = widgets.FloatSlider(\n", + " value=trace.get_choices()[\"inlier_lightness_variance\"],\n", + " min=inlier_lightness_variance_sweep.min(),\n", + " max=inlier_lightness_variance_sweep.max(),\n", + " step=0.01\n", + " ),\n", + " inlier_color_variance = widgets.FloatSlider(\n", + " value=trace.get_choices()[\"inlier_color_variance\"],\n", + " min=inlier_color_variance_sweep.min(),\n", + " max=inlier_color_variance_sweep.max(),\n", + " step=0.01\n", + " ),\n", + " inlier_depth_variance = widgets.FloatSlider(\n", + " value=trace.get_choices()[\"inlier_depth_variance\"],\n", + " min=inlier_depth_variance_sweep.min(),\n", + " max=inlier_depth_variance_sweep.max(),\n", + " step=0.01\n", + " ),\n", + " )\n", + "\n", + "@jax.jit\n", + "def update_parameters(\n", + " trace,\n", + " key,\n", + " outlier_probability,\n", + " inlier_lightness_variance,\n", + " inlier_color_variance,\n", + " inlier_depth_variance,\n", + "):\n", + " choicemap = genjax.ChoiceMap.d(\n", + " {\n", + " \"outlier_probability\": outlier_probability,\n", + " \"inlier_lightness_variance\": inlier_lightness_variance,\n", + " \"inlier_color_variance\": inlier_color_variance,\n", + " \"inlier_depth_variance\": inlier_depth_variance,\n", + " }\n", + " )\n", + " return trace.update(\n", + " key, \n", + " choicemap,\n", + " )[0]\n", + "\n", + "@jax.jit\n", + "def update_parameters_get_score(\n", + " trace,\n", + " key,\n", + " outlier_probability,\n", + " inlier_lightness_variance,\n", + " inlier_color_variance,\n", + " inlier_depth_variance,\n", + "):\n", + " return update_parameters(\n", + " trace,\n", + " key,\n", + " outlier_probability,\n", + " inlier_lightness_variance,\n", + " inlier_color_variance,\n", + " inlier_depth_variance,\n", + " ).get_score()\n", + "\n", + "vmapped_grid = jax.jit(b3d.multivmap(update_parameters_get_score, args=(False, False, True, True, True, True)))\n", + "\n", + "\n", + "outlier_probability_sweep = jnp.linspace(0.0, 1.0, 30)\n", + "inlier_lightness_variance_sweep = jnp.linspace(1.0, 60.0, 20)\n", + "inlier_color_variance_sweep = jnp.linspace(1.0, 20.0, 20)\n", + "inlier_depth_variance_sweep = jnp.linspace(0.005, 0.04, 15)\n", + "\n", + "\n", + "key = jax.random.split(key, 2)[-1]\n", + "likelikood_args = {\n", + " \"fx\": fx,\n", + " \"fy\": fy,\n", + " \"k\": Pytree.const(20000),\n", + "}\n", + "\n", + "choicemap = genjax.ChoiceMap.d(\n", + " {\n", + " \"outlier_probability\": 0.1,\n", + " \"inlier_lightness_variance\": 0.1,\n", + " \"inlier_color_variance\": 0.1,\n", + " \"inlier_depth_variance\": 0.1,\n", + " \"observed_color_space_d\": convert_rgbd_to_color_space(observed_rgbd_scaled_down),\n", + " }\n", + ")\n", + "\n", + "trace = importance_jit(\n", + " key, \n", + " choicemap,\n", + " ({\"likelihood_args\": likelikood_args},)\n", + ")[0]" + ] + }, + { + "cell_type": "code", + "execution_count": 133, + "metadata": {}, + "outputs": [], + "source": [ + "T = 5\n", + "trace = b3d.update_choices(\n", + " trace,\n", + " key,\n", + " Pytree.const((\"object_pose_0\",)),\n", + " all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][IDX]\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 134, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0.03448275849223137, 38.26315689086914, 20.0, 0.03999999910593033]\n", + "-164811.3\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "be0a4bf032a54aeea1d7d8464fe2e185", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "interactive(children=(FloatSlider(value=0.03448275849223137, description='outlier_probability', max=1.0, step=…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "key = jax.random.split(key, 2)[-1]\n", + "\n", + "sweeps = [\n", + " outlier_probability_sweep,\n", + " inlier_lightness_variance_sweep,\n", + " inlier_color_variance_sweep,\n", + " inlier_depth_variance_sweep,\n", + "]\n", + "scores = vmapped_grid(\n", + " trace,\n", + " key,\n", + " *sweeps\n", + ")\n", + "sampled_indices = jax.vmap(\n", + " jnp.unravel_index,\n", + " in_axes=(0,None)\n", + ")(jax.random.categorical(key, scores.reshape(-1),shape=(100,)), scores.shape)\n", + "sampled_parameters = [\n", + " sweep[indices]\n", + " for indices, sweep in zip(sampled_indices, sweeps)\n", + "]\n", + "trace = update_parameters(\n", + " trace,\n", + " key,\n", + " *[param[0] for param in sampled_parameters]\n", + ")\n", + "print([i[0].item() for i in sampled_parameters])\n", + "print(trace.get_score())\n", + "plot_interactive(trace)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 128, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-157607.31\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "b52d53845b7741069069c2a62b68b87a", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "interactive(children=(FloatSlider(value=0.0, description='outlier_probability', max=1.0, step=0.01), FloatSlid…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from b3d.bayes3d.enumerative_proposals import gvmf_and_select_best_move\n", + "\n", + "saved_trace = trace\n", + "potential_traces = []\n", + "for var in [0.03, 0.02, 0.01, 0.005, 0.03, 0.02, 0.01, 0.005]:\n", + " trace = saved_trace\n", + " trace, key = gvmf_and_select_best_move(\n", + " trace, key, var, 700.0, \"object_pose_0\", 700\n", + " )\n", + " trace, key = gvmf_and_select_best_move(\n", + " trace, key, var, 700.0, \"object_pose_0\", 700\n", + " )\n", + " trace, key = gvmf_and_select_best_move(\n", + " trace, key, var, 1000.0, \"object_pose_0\", 700\n", + " )\n", + " trace, key = gvmf_and_select_best_move(\n", + " trace, key, var, 1000.0, \"object_pose_0\", 700\n", + " )\n", + " potential_traces.append(trace)\n", + "scores = jnp.array([t.get_score() for t in potential_traces])\n", + "trace = potential_traces[scores.argmax()]\n", + "print(trace.get_score())\n", + "plot_interactive(trace)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [], + "source": [ + "rendered_rgbd = trace.get_retval()[\"rendered_rgbd\"]\n", + "observed_rgbd = trace.get_retval()[\"observed_rgbd\"]\n", + "rendered_color_space_d = trace.get_retval()[\"rendered_color_space_d\"]\n", + "observed_color_space_d = trace.get_retval()[\"observed_color_space_d\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-4.6051702\n", + "-4.528345\n" + ] + } + ], + "source": [ + "w = 100.0\n", + "print(jnp.log(1/w))\n", + "print(genjax.truncated_normal.logpdf(\n", + " 0.2 *w, 0.3 * w, 0.05 * w, -w/2, w/2\n", + "))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "trace.get_retval()[\"observed_color_space_d\"].shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "no_mesh_surface = (rendered_labd[...,3] == 0.0)\n", + "\n", + "inlier_variances = jnp.array([60.0, 60.0, 60.0, 0.6])\n", + "\n", + "lower_bound = jnp.array([0.0, -100.0, -100.0, 0.0])\n", + "upper_bound = jnp.array([100.0, 100.0, 100.0, 20.0])\n", + "\n", + "outlier_variances = jnp.ones(4) * 1000000.0\n", + "\n", + "scores_inlier = jax.vmap(genjax.truncated_normal.logpdf, in_axes=(0, 0, None, None, None))(\n", + " observed_labd.reshape(-1, 4), rendered_labd.reshape(-1,4), inlier_variances,\n", + " lower_bound, upper_bound\n", + ")\n", + "scores_outlier = jax.vmap(genjax.truncated_normal.logpdf, in_axes=(0, None, None, None, None))(\n", + " observed_labd.reshape(-1, 4), (lower_bound + upper_bound) / 2.0, outlier_variances,\n", + " lower_bound, upper_bound\n", + ")\n", + "\n", + "scores_inlier_merged = jax.nn.logsumexp(scores_inlier[..., :3] + jnp.log(1/3), axis=-1) + scores_inlier[..., 3]\n", + "scores_outlier_merged = jax.nn.logsumexp(scores_outlier[..., :3] + jnp.log(1/3), axis=-1) + scores_outlier[..., 3]\n", + "\n", + "plt.imshow((scores_inlier_merged - scores_outlier_merged).reshape(renderer.height, renderer.width))\n", + "plt.colorbar()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "rendered_labd = trace.get_retval()[\"rendered_color_space_d\"]\n", + "observed_labd = trace.get_retval()[\"observed_color_space_d\"]\n", + "\n", + "rendered_labd = trace.get_retval()[\"rendered_color_space_d\"]\n", + "observed_labd = trace.get_retval()[\"observed_color_space_d\"]\n", + "rr.set_time_sequence(\"time\", 0)\n", + "rr.log(\n", + " \"image\", rr.Image(trace.get_retval()[\"observed_rgbd\"][...,:3]),\n", + ")\n", + "rr.log(\n", + " \"image/rendered_rgbd\", rr.Image(trace.get_retval()[\"rendered_rgbd\"][...,:3]),\n", + ")\n", + "rr.log(\n", + " \"image/sampled_rgbd\", rr.Image(trace.get_retval()[\"sampled_rgbd\"][...,:3]),\n", + ")\n", + "\n", + "rr.log(\n", + " \"image/labd\", rr.Image(trace.get_retval()[\"observed_color_space_d\"][...,:3]),\n", + ")\n", + "rr.log(\n", + " \"image/rendered_labd\", rr.Image(trace.get_retval()[\"rendered_color_space_d\"][...,:3]),\n", + ")\n", + "\n", + "rr.log(\n", + " \"image/error\", rr.DepthImage((rendered_labd[..., 0] - observed_labd[..., 0]) * (rendered_labd[..., 3] > 0))\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "rendered_labd = trace.get_retval()[\"rendered_color_space_d\"]\n", + "observed_labd = trace.get_retval()[\"observed_color_space_d\"]\n", + "rr.set_time_sequence(\"time\", 0)\n", + "rr.log(\n", + " \"image\", rr.Image(trace.get_retval()[\"observed_rgbd\"][...,:3]),\n", + ")\n", + "rr.log(\n", + " \"image/rendered_rgbd\", rr.Image(trace.get_retval()[\"rendered_rgbd\"][...,:3]),\n", + ")\n", + "rr.log(\n", + " \"image/sampled_rgbd\", rr.Image(trace.get_retval()[\"sampled_rgbd\"][...,:3]),\n", + ")\n", + "\n", + "rr.log(\n", + " \"image/labd\", rr.Image(trace.get_retval()[\"observed_color_space_d\"][...,:3]),\n", + ")\n", + "rr.log(\n", + " \"image/rendered_labd\", rr.Image(trace.get_retval()[\"rendered_color_space_d\"][...,:3]),\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "rr.set_time_sequence(\"time\", 0)\n", + "rr.log(\n", + " \"image\", rr.Image(trace.get_retval()[\"observed_rgbd\"][...,:3]),\n", + ")\n", + "rr.log(\n", + " \"image/rendered_rgbd\", rr.Image(trace.get_retval()[\"rendered_rgbd\"][...,:3]),\n", + ")\n", + "rr.log(\n", + " \"image/sampled_rgbd\", rr.Image(trace.get_retval()[\"sampled_rgbd\"][...,:3]),\n", + ")\n", + "\n", + "rr.log(\n", + " \"image/labd\", rr.Image(trace.get_retval()[\"observed_labd\"][...,:3]),\n", + ")\n", + "rr.log(\n", + " \"image/rendered_labd\", rr.Image(trace.get_retval()[\"rendered_labd\"][...,:3]),\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "rr.set_time_sequence(\"time\", 0)\n", + "rr.log(\n", + " \"image\", rr.Image(trace.get_retval()[\"observed_rgbd\"][...,:3]),\n", + ")\n", + "rr.log(\n", + " \"image/rendered_rgbd\", rr.Image(trace.get_retval()[\"rendered_rgbd\"][...,:3]),\n", + ")\n", + "rr.log(\n", + " \"image/sampled_rgbd\", rr.Image(trace.get_retval()[\"sampled_rgbd\"][...,:3]),\n", + ")\n", + "\n", + "rr.log(\n", + " \"image/labd\", rr.Image(trace.get_retval()[\"observed_labd\"][...,:3]),\n", + ")\n", + "rr.log(\n", + " \"image/rendered_labd\", rr.Image(trace.get_retval()[\"rendered_labd\"][...,:3]),\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "b3d.rr_init()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "b3d.rr_init()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sampled_indices" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "rendered_rgbd = trace.get_retval()[\"rendered_rgbd\"]\n", + "observed_rgbd = trace.get_retval()[\"observed_rgbd\"]\n", + "mask = rendered_rgbd[..., 3] > 0.0\n", + "rendered_depth= rendered_rgbd[..., 3]\n", + "observed_depth = observed_rgbd[..., 3]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "b3d.rr_init(\"interactive\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import rerun as rr\n", + "rr.log(\"depth\", rr.DepthImage(rendered_rgbd[..., 3]))\n", + "rr.log(\"depth/observed\", rr.DepthImage(observed_rgbd[..., 3]))\n", + "rr.log(\"depth/error\", rr.DepthImage((rendered_depth- observed_depth) * mask))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "inlier_color_variance_sweep" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "outlier_probability_sweep" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plot_interactive(trace)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "sampled_indices.shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "scores = vmapped_grid(\n", + " trace,\n", + " key,\n", + " outlier_probability_sweep,\n", + " inlier_lightness_variance_sweep,\n", + " inlier_color_variance_sweep,\n", + " inlier_depth_variance_sweep\n", + ")\n", + "print(scores.shape)\n", + "samples = jax.random.categorical(key, scores.reshape(-1),shape=(100,))\n", + "print(samples)\n", + "\n", + "\n", + "sample_index=1\n", + "print(\n", + " \"Outlier Probability\", outlier_probability_sweep[indices[0][sample_index]], \"\\n\",\n", + " \"Inlier Lightness Variance\", inlier_lightness_variance_sweep[indices[1][sample_index]], \"\\n\",\n", + " \"Inlier Color Variance\", inlier_color_variance_sweep[indices[2][sample_index]], \"\\n\",\n", + " \"Inlier Depth Variance\", inlier_depth_variance_sweep[indices[3][sample_index]], \"\\n\",\n", + ")\n", + "interact(\n", + " plot,\n", + " k = widgets.IntSlider(value=10000, min=1, max=100000, step=1),\n", + " outlier_probability = widgets.FloatSlider(value=outlier_probability_sweep[indices[0][sample_index]], min=0.01, max=1.0, step=0.01),\n", + " inlier_lightness_variance = widgets.FloatSlider(value=inlier_lightness_variance_sweep[indices[1][sample_index]], min=0.1, max=100.0, step=0.01),\n", + " inlier_color_variance = widgets.FloatSlider(value=inlier_color_variance_sweep[indices[2][sample_index]], min=0.1, max=100.0, step=0.01),\n", + " inlier_depth_variance = widgets.FloatSlider(value=inlier_depth_variance_sweep[indices[3][sample_index]], min=0.0001, max=100.0, step=0.01),\n", + ")\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "b3d.en" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "for sample_index in range(len(indices[0])):\n", + " print(\n", + " \"Outlier Probability\", outlier_probability_sweep[indices[0][sample_index]], \"\\n\",\n", + " \"Inlier Lightness Variance\", inlier_lightness_variance_sweep[indices[1][sample_index]], \"\\n\",\n", + " \"Inlier Color Variance\", inlier_color_variance_sweep[indices[2][sample_index]], \"\\n\",\n", + " \"Inlier Depth Variance\", inlier_depth_variance_sweep[indices[3][sample_index]], \"\\n\",\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Matched\n", + "Outlier Probability 0.120000005 \n", + " Inlier Lightness Variance 50.0 \n", + " Inlier Color Variance 32.14286 \n", + " Inlier Depth Variance 0.1 \n", + "\n", + "# Mismatched\n", + "Outlier Probability 0.120000005 \n", + " Inlier Lightness Variance 100.0 \n", + " Inlier Color Variance 52.500004 \n", + " Inlier Depth Variance 0.1 " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "trace.get_choices()[\"noisy_lab_color\",...].shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "b3d", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.4" + } }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████| 20/20 [00:06<00:00, 3.02it/s]\n" - ] - } - ], - "source": [ - "b3d.rr_init(\"interactive\")\n", - "key = jax.random.PRNGKey(0)\n", - "ycb_dir = os.path.join(b3d.get_assets_path(), \"bop/ycbv\")\n", - "scene_id = 49\n", - "image_id = 100\n", - "\n", - "all_data = b3d.io.get_ycbv_test_images(ycb_dir, scene_id, range(1,1000,50))\n", - "\n", - "meshes = [\n", - " Mesh.from_obj_file(os.path.join(ycb_dir, f'models/obj_{f\"{id + 1}\".rjust(6, \"0\")}.ply')).scale(0.001)\n", - " for id in all_data[0][\"object_types\"]\n", - "]\n", - "\n", - "height, width = all_data[0][\"rgbd\"].shape[:2]\n", - "fx,fy,cx,cy = all_data[0][\"camera_intrinsics\"]\n", - "scaling_factor = 0.2\n", - "renderer = b3d.renderer.renderer_original.RendererOriginal(\n", - " width * scaling_factor, height * scaling_factor, fx * scaling_factor, fy * scaling_factor, cx * scaling_factor, cy * scaling_factor, 0.01, 2.0\n", - ")\n", - "\n", - "IDX = 0\n", - "rendered_rgbds = [\n", - " renderer.render_rgbd_from_mesh(meshes[IDX].transform(all_data[T][\"camera_pose\"].inv() @ all_data[T][\"object_poses\"][IDX]))\n", - " for T in range(len(all_data))\n", - "]\n", - "\n", - "observed_rgbd_scaled_down = b3d.resize_image(all_data[0][\"rgbd\"], renderer.height, renderer.width)" - ] - }, - { - "cell_type": "code", - "execution_count": 87, - "metadata": {}, - "outputs": [ - { - "data": { - "image/jpeg": 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- "text/plain": [ - "" - ] - }, - "execution_count": 87, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "b3d.viz_rgb(rendered_rgbds[0])" - ] - }, - { - "cell_type": "code", - "execution_count": 88, - "metadata": {}, - "outputs": [], - "source": [ - "# @Pytree.dataclass\n", - "# class MaskedKImageLikelihood(genjax.ExactDensity):\n", - "# def sample(self, key, row_coordinates, column_coordinates, variances, center_points, lower_bound, upper_bound, image_height, image_width):\n", - "# observed_image = jnp.zeros((image_height.const, image_width.const, 4))\n", - "\n", - "# sampled_values = jax.vmap(genjax.truncated_normal.sample, in_axes=(0, 0, 0, None, None))(\n", - "# jax.random.split(key, len(row_coordinates)), center_points, variances,\n", - "# lower_bound, upper_bound\n", - "# )\n", - "# observed_image = observed_image.at[row_coordinates, column_coordinates, :].set(sampled_values)\n", - "# return observed_image\n", - "\n", - "# def logpdf(self, observed_labd, row_coordinates, column_coordinates, variances, center_points, lower_bound, upper_bound, image_height, image_width):\n", - "# subset_observed_labd = observed_labd[row_coordinates, column_coordinates]\n", - "# scores = jax.vmap(genjax.truncated_normal.logpdf, in_axes=(0, 0, 0, None, None))(\n", - "# subset_observed_labd, center_points, variances,\n", - "# lower_bound, upper_bound\n", - "# )\n", - "# return scores.sum()\n", - "\n", - "# masked_k_image_likelihood = MaskedKImageLikelihood()\n", - "\n", - "@Pytree.dataclass\n", - "class MaskedKImageLikelihoodMarginalizeOutlier(genjax.ExactDensity):\n", - " def sample(self, key,\n", - " row_coordinates,\n", - " column_coordinates,\n", - " rendered_color_space_d,\n", - " inlier_variances,\n", - " outlier_variances,\n", - " outlier_probability,\n", - " lower_bound, upper_bound,\n", - " image_height, image_width\n", - " ):\n", - " observed_image = jnp.zeros((image_height.const, image_width.const, 4))\n", - "\n", - " no_mesh_surface = (rendered_color_space_d[..., 3] == 0)[row_coordinates, column_coordinates]\n", - " outlier_probability_adjusted = outlier_probability * (1 - no_mesh_surface) + no_mesh_surface * 1.0\n", - "\n", - " is_outlier = jax.vmap(genjax.bernoulli.sample,in_axes=(0, 0))(\n", - " jax.random.split(key, len(row_coordinates)), jax.scipy.special.logit(outlier_probability_adjusted)\n", - " )\n", - "\n", - " sampled_inlier_values = jax.vmap(genjax.truncated_normal.sample, in_axes=(0, 0, None, None, None))(\n", - " jax.random.split(key, len(row_coordinates)), rendered_color_space_d[row_coordinates, column_coordinates], inlier_variances,\n", - " lower_bound, upper_bound\n", - " )\n", - " sampled_outlier_values = jax.vmap(genjax.truncated_normal.sample, in_axes=(0, 0, None, None, None))(\n", - " jax.random.split(key, len(row_coordinates)), rendered_color_space_d[row_coordinates, column_coordinates], outlier_variances,\n", - " lower_bound, upper_bound\n", - " )\n", - " sampled_values = (\n", - " is_outlier[...,None] * sampled_outlier_values + (1 - is_outlier[...,None]) * sampled_inlier_values\n", - " )\n", - " # sampled_values = jnp.where(is_outlier, sampled_outlier_values, sampled_inlier_values)\n", - "\n", - " observed_image = observed_image.at[row_coordinates, column_coordinates, :].set(sampled_values)\n", - " return observed_image\n", - "\n", - " def logpdf(self,\n", - " observed_color_space_d,\n", - " row_coordinates,\n", - " column_coordinates,\n", - " rendered_color_space_d,\n", - " inlier_variances,\n", - " outlier_variances,\n", - " outlier_probability,\n", - " lower_bound, upper_bound,\n", - " image_height, image_width\n", - " ):\n", - " no_mesh_surface = (rendered_color_space_d[..., 3] == 0)[row_coordinates, column_coordinates]\n", - " subset_observed = observed_color_space_d[row_coordinates, column_coordinates]\n", - "\n", - " outlier_probability_adjusted = outlier_probability * (1 - no_mesh_surface) + no_mesh_surface * 1.0\n", - "\n", - " subset_observed_rescaled = (subset_observed - lower_bound) / (upper_bound - lower_bound)\n", - " rendered_values_rescaled = (rendered_color_space_d[row_coordinates, column_coordinates] - lower_bound) / (upper_bound - lower_bound)\n", - "\n", - " scores_inlier = jax.vmap(genjax.truncated_normal.logpdf, in_axes=(0, 0, None, None, None))(\n", - " subset_observed_rescaled, rendered_values_rescaled, inlier_variances / (upper_bound - lower_bound),\n", - " 0.0, 1.0\n", - " )\n", - " scores_outlier = jax.vmap(genjax.truncated_normal.logpdf, in_axes=(0, None, None, None, None))(\n", - " subset_observed_rescaled, 0.5, outlier_variances / (upper_bound - lower_bound),\n", - " 0.0, 1.0\n", - " )\n", - "\n", - " scores_inlier_merged = jax.nn.logsumexp(scores_inlier[..., :3] + jnp.log(1/3), axis=-1) + scores_inlier[..., 3] + jnp.log(1.0 - outlier_probability_adjusted) \n", - " scores_outlier_merged = jax.nn.logsumexp(scores_outlier[..., :3] + jnp.log(1/3), axis=-1) + scores_outlier[..., 3] + jnp.log(outlier_probability_adjusted)\n", - " return jnp.logaddexp(scores_inlier_merged, scores_outlier_merged).sum()\n", - "\n", - "masked_k_image_likelihood_marginalize_outlier_prob = MaskedKImageLikelihoodMarginalizeOutlier()\n", - "\n", - "\n", - "# k = 10\n", - "# masked_k_image_likelihood.logpdf(\n", - "# jnp.zeros((renderer.height, renderer.width, 4)),\n", - "# jnp.arange(k),\n", - "# jnp.arange(k),\n", - "# jnp.ones(k) * 0.1,\n", - "# jnp.zeros(k),\n", - "# jnp.zeros(4)- 0.1,\n", - "# jnp.ones(4),\n", - "# renderer.height,\n", - "# renderer.width\n", - "# )\n", - "# masked_k_image_likelihood.sample(\n", - "# key,\n", - "# jnp.arange(k),\n", - "# jnp.arange(k),\n", - "# jnp.ones(k) * 0.1,\n", - "# jnp.zeros(k),\n", - "# jnp.zeros(4)- 0.1,\n", - "# jnp.ones(4),\n", - "# renderer.height,\n", - "# renderer.width\n", - "# );" - ] - }, - { - "cell_type": "code", - "execution_count": 92, - "metadata": {}, - "outputs": [], - "source": [ - "lower_bound = jnp.array([0.0, -100.0, -100.0, 0.0])\n", - "upper_bound = jnp.array([100.0, 100.0, 100.0, 20.0])\n", - "convert_rgbd_to_color_space = lambda x: b3d.colors.rgbd_to_labd(x)\n", - "convert_color_space_to_rgbd = lambda x: b3d.colors.labd_to_rgbd(x)\n", - "\n", - "@genjax.gen\n", - "def ray_model(rendered_rgbd, likelihood_args):\n", - " rendered_color_space_d = convert_rgbd_to_color_space(rendered_rgbd)\n", - "\n", - " k = likelihood_args[\"k\"].const\n", - " image_height, image_width = rendered_color_space_d.shape[0], rendered_color_space_d.shape[1]\n", - " image_height = Pytree.const(image_height)\n", - " image_width = Pytree.const(image_width)\n", - "\n", - " row_coordinates = genjax.categorical.vmap(in_axes=(0,))(\n", - " jnp.ones((k, image_height.const))\n", - " ) @ \"row_coordinates\"\n", - " column_coordinates = genjax.categorical.vmap(in_axes=(0,))(\n", - " jnp.ones((k, image_width.const))\n", - " ) @ \"column_coordinates\"\n", - "\n", - "\n", - " outlier_probability = genjax.uniform(0.0, 1.0) @ \"outlier_probability\"\n", - " inlier_color_variance = genjax.uniform(0.01, 100.0) @ \"inlier_color_variance\"\n", - " inlier_lightness_variance = genjax.uniform(0.01, 100.0) @ \"inlier_lightness_variance\"\n", - " inlier_depth_variance = genjax.uniform(0.01, 1000.0) @ \"inlier_depth_variance\"\n", - "\n", - " inlier_variances = jnp.array([inlier_lightness_variance, inlier_color_variance, inlier_color_variance, inlier_depth_variance])\n", - " outlier_variances = jnp.array([1000000.0, 1000000.0, 1000000.0, 1000000.0])\n", - "\n", - "\n", - " sampled_color_space_d = masked_k_image_likelihood_marginalize_outlier_prob.sample(\n", - " key,\n", - " row_coordinates,\n", - " column_coordinates,\n", - " rendered_color_space_d,\n", - " inlier_variances,\n", - " outlier_variances,\n", - " outlier_probability,\n", - " lower_bound, upper_bound,\n", - " image_height, image_width\n", - " )\n", - "\n", - " observed_color_space_d = masked_k_image_likelihood_marginalize_outlier_prob(\n", - " row_coordinates,\n", - " column_coordinates,\n", - " rendered_color_space_d,\n", - " inlier_variances,\n", - " outlier_variances,\n", - " outlier_probability,\n", - " lower_bound, upper_bound,\n", - " image_height, image_width\n", - " ) @ \"observed_color_space_d\"\n", - "\n", - " observed_rgbd = convert_color_space_to_rgbd(observed_color_space_d)\n", - " sampled_rgbd = convert_color_space_to_rgbd(sampled_color_space_d)\n", - "\n", - " return {\n", - " \"rendered_rgbd\": rendered_rgbd,\n", - " \"sampled_rgbd\": sampled_rgbd,\n", - " \"observed_rgbd\": observed_rgbd,\n", - "\n", - " \"rendered_color_space_d\": rendered_color_space_d,\n", - " \"sampled_color_space_d\": sampled_color_space_d,\n", - " \"observed_color_space_d\": observed_color_space_d,\n", - " }\n", - "\n", - "importance_jit = jax.jit(ray_model.importance)\n", - "update_jit = jax.jit(ray_model.update)\n", - "\n", - "def plot_trace(trace):\n", - " fig, ax = plt.subplots(1, 4, figsize=(10, 5))\n", - "\n", - " ax[0].imshow(trace.get_retval()[\"rendered_rgbd\"][..., :3])\n", - " ax[0].axis('off')\n", - "\n", - " ax[1].imshow(trace.get_retval()[\"sampled_rgbd\"][..., :3])\n", - " ax[1].axis('off')\n", - "\n", - " ax[2].matshow(trace.get_retval()[\"sampled_rgbd\"][..., 3])\n", - " ax[2].axis('off')\n", - "\n", - "\n", - " ax[3].imshow(trace.get_retval()[\"observed_rgbd\"][..., :3])\n", - " ax[3].axis('off')\n", - " return fig\n", - "\n", - "\n", - "\n", - "def plot_interactive(trace):\n", - " def _make_viz(outlier_probability, inlier_lightness_variance, inlier_color_variance, inlier_depth_variance):\n", - " choicemap = genjax.ChoiceMap.d(\n", - " {\n", - " \"outlier_probability\": outlier_probability,\n", - " \"inlier_lightness_variance\": inlier_lightness_variance,\n", - " \"inlier_color_variance\": inlier_color_variance,\n", - " \"inlier_depth_variance\": inlier_depth_variance,\n", - " }\n", - " )\n", - " modified_trace = update_jit(\n", - " key,\n", - " trace,\n", - " choicemap\n", - " )[0]\n", - " plot_trace(modified_trace)\n", - "\n", - " interact(_make_viz,\n", - " k = widgets.IntSlider(value=10000, min=1, max=100000, step=1),\n", - " outlier_probability = widgets.FloatSlider(\n", - " value=trace.get_choices()[\"outlier_probability\"],\n", - " min=outlier_probability_sweep.min(),\n", - " max=outlier_probability_sweep.max(),\n", - " step=0.01\n", - " ),\n", - " inlier_lightness_variance = widgets.FloatSlider(\n", - " value=trace.get_choices()[\"inlier_lightness_variance\"],\n", - " min=inlier_lightness_variance_sweep.min(),\n", - " max=inlier_lightness_variance_sweep.max(),\n", - " step=0.01\n", - " ),\n", - " inlier_color_variance = widgets.FloatSlider(\n", - " value=trace.get_choices()[\"inlier_color_variance\"],\n", - " min=inlier_color_variance_sweep.min(),\n", - " max=inlier_color_variance_sweep.max(),\n", - " step=0.01\n", - " ),\n", - " inlier_depth_variance = widgets.FloatSlider(\n", - " value=trace.get_choices()[\"inlier_depth_variance\"],\n", - " min=inlier_depth_variance_sweep.min(),\n", - " max=inlier_depth_variance_sweep.max(),\n", - " step=0.01\n", - " ),\n", - " )\n", - "\n", - "@jax.jit\n", - "def update_parameters(\n", - " trace,\n", - " key,\n", - " outlier_probability,\n", - " inlier_lightness_variance,\n", - " inlier_color_variance,\n", - " inlier_depth_variance,\n", - "):\n", - " choicemap = genjax.ChoiceMap.d(\n", - " {\n", - " \"outlier_probability\": outlier_probability,\n", - " \"inlier_lightness_variance\": inlier_lightness_variance,\n", - " \"inlier_color_variance\": inlier_color_variance,\n", - " \"inlier_depth_variance\": inlier_depth_variance,\n", - " }\n", - " )\n", - " return trace.update(\n", - " key, \n", - " choicemap,\n", - " )[0]\n", - "\n", - "@jax.jit\n", - "def update_parameters_get_score(\n", - " trace,\n", - " key,\n", - " outlier_probability,\n", - " inlier_lightness_variance,\n", - " inlier_color_variance,\n", - " inlier_depth_variance,\n", - "):\n", - " return update_parameters(\n", - " trace,\n", - " key,\n", - " outlier_probability,\n", - " inlier_lightness_variance,\n", - " inlier_color_variance,\n", - " inlier_depth_variance,\n", - " ).get_score()\n", - "\n", - "vmapped_grid = jax.jit(b3d.multivmap(update_parameters_get_score, args=(False, False, True, True, True, True)))\n", - "\n", - "\n", - "outlier_probability_sweep = jnp.linspace(0.0, 1.0, 30)\n", - "inlier_lightness_variance_sweep = jnp.linspace(5.0, 60.0, 20)\n", - "inlier_color_variance_sweep = inlier_lightness_variance_sweep\n", - "inlier_depth_variance_sweep = jnp.linspace(0.02, 0.2, 15)\n", - "\n", - "\n", - "key = jax.random.split(key, 2)[-1]\n", - "likelikood_args = {\n", - " \"fx\": fx,\n", - " \"fy\": fy,\n", - " \"k\": Pytree.const(5000),\n", - "}\n", - "\n", - "choicemap = genjax.ChoiceMap.d(\n", - " {\n", - " \"outlier_probability\": 0.1,\n", - " \"inlier_lightness_variance\": 0.1,\n", - " \"inlier_color_variance\": 0.1,\n", - " \"inlier_depth_variance\": 0.1,\n", - " \"observed_color_space_d\": convert_rgbd_to_color_space(observed_rgbd_scaled_down),\n", - " }\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 94, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[0.10344827175140381, 60.0, 22.36842155456543, 0.08428572118282318]\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "332d8409145343aaad534ddccb814080", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "interactive(children=(FloatSlider(value=0.10344827175140381, description='outlier_probability', max=1.0, step=…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "trace = importance_jit(\n", - " key, \n", - " choicemap,\n", - " # (rendered_rgbds[0], likelikood_args,),\n", - " (rendered_rgbds[19], likelikood_args,),\n", - " # (observed_rgbd_scaled_down, likelikood_args,),\n", - " # (jnp.ones_like(observed_rgbd_scaled_down) * jnp.array([1.0, 0.0, 0.0, 1.5]), likelikood_args,),\n", - ")[0]\n", - "\n", - "key = jax.random.split(key, 2)[-1]\n", - "sweeps = [\n", - " outlier_probability_sweep,\n", - " inlier_lightness_variance_sweep,\n", - " inlier_color_variance_sweep,\n", - " inlier_depth_variance_sweep,\n", - "]\n", - "scores = vmapped_grid(\n", - " trace,\n", - " key,\n", - " *sweeps\n", - ")\n", - "sampled_indices = jax.vmap(\n", - " jnp.unravel_index,\n", - " in_axes=(0,None)\n", - ")(jax.random.categorical(key, scores.reshape(-1),shape=(100,)), scores.shape)\n", - "sampled_parameters = [\n", - " sweep[indices]\n", - " for indices, sweep in zip(sampled_indices, sweeps)\n", - "]\n", - "trace = update_parameters(\n", - " trace,\n", - " key,\n", - " *[param[0] for param in sampled_parameters]\n", - ")\n", - "print([i[0].item() for i in sampled_parameters])\n", - "plot_interactive(trace);\n", - "\n", - "# partial at gt pose explanation\n", - "# [0.13793103396892548, 57.105262756347656, 13.684210777282715, 0.019999999552965164]\n", - "\n", - "\n", - "# partial at wrong pose explanation\n", - "# [0.10344827175140381, 60.0, 22.36842155456543, 0.08428572118282318]\n", - "\n", - "\n", - "# full_explanation\n", - "# [0.009999999776482582, 5.0, 5.0, 0.019999999552965164]\n", - "\n", - "# all red\n", - "# [0.9658620357513428, 5.0, 20.0, 0.4442857503890991]" - ] - }, - { - "cell_type": "code", - "execution_count": 91, - "metadata": {}, - "outputs": [ - { - "ename": "TypeError", - "evalue": "cannot reshape array of shape (3072,) (size 3072) into shape (96, 128) (size 12288)", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[91], line 22\u001b[0m\n\u001b[1;32m 19\u001b[0m scores_inlier_merged \u001b[38;5;241m=\u001b[39m jax\u001b[38;5;241m.\u001b[39mnn\u001b[38;5;241m.\u001b[39mlogsumexp(scores_inlier[\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m, :\u001b[38;5;241m3\u001b[39m] \u001b[38;5;241m+\u001b[39m jnp\u001b[38;5;241m.\u001b[39mlog(\u001b[38;5;241m1\u001b[39m\u001b[38;5;241m/\u001b[39m\u001b[38;5;241m3\u001b[39m), axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m) \u001b[38;5;241m+\u001b[39m scores_inlier[\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m, \u001b[38;5;241m3\u001b[39m]\n\u001b[1;32m 20\u001b[0m scores_outlier_merged \u001b[38;5;241m=\u001b[39m jax\u001b[38;5;241m.\u001b[39mnn\u001b[38;5;241m.\u001b[39mlogsumexp(scores_outlier[\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m, :\u001b[38;5;241m3\u001b[39m] \u001b[38;5;241m+\u001b[39m jnp\u001b[38;5;241m.\u001b[39mlog(\u001b[38;5;241m1\u001b[39m\u001b[38;5;241m/\u001b[39m\u001b[38;5;241m3\u001b[39m), axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m) \u001b[38;5;241m+\u001b[39m scores_outlier[\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m, \u001b[38;5;241m3\u001b[39m]\n\u001b[0;32m---> 22\u001b[0m plt\u001b[38;5;241m.\u001b[39mimshow(\u001b[43m(\u001b[49m\u001b[43mscores_inlier_merged\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m-\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mscores_outlier_merged\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mreshape\u001b[49m\u001b[43m(\u001b[49m\u001b[43mrenderer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mheight\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrenderer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwidth\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[1;32m 23\u001b[0m plt\u001b[38;5;241m.\u001b[39mcolorbar()\n", - " \u001b[0;31m[... skipping hidden 1 frame]\u001b[0m\n", - "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/jax/_src/numpy/array_methods.py:137\u001b[0m, in \u001b[0;36m_compute_newshape\u001b[0;34m(a, newshape)\u001b[0m\n\u001b[1;32m 134\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 135\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (\u001b[38;5;28mall\u001b[39m(\u001b[38;5;28misinstance\u001b[39m(d, \u001b[38;5;28mint\u001b[39m) \u001b[38;5;28;01mfor\u001b[39;00m d \u001b[38;5;129;01min\u001b[39;00m (\u001b[38;5;241m*\u001b[39mnp\u001b[38;5;241m.\u001b[39mshape(a), \u001b[38;5;241m*\u001b[39mnewshape)) \u001b[38;5;129;01mand\u001b[39;00m\n\u001b[1;32m 136\u001b[0m np\u001b[38;5;241m.\u001b[39msize(a) \u001b[38;5;241m!=\u001b[39m math\u001b[38;5;241m.\u001b[39mprod(newshape)):\n\u001b[0;32m--> 137\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcannot reshape array of shape \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnp\u001b[38;5;241m.\u001b[39mshape(a)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m (size \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnp\u001b[38;5;241m.\u001b[39msize(a)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m) \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 138\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124minto shape \u001b[39m\u001b[38;5;132;01m{\u001b[39;00morig_newshape\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m (size \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mmath\u001b[38;5;241m.\u001b[39mprod(newshape)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m)\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 139\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mtuple\u001b[39m(\u001b[38;5;241m-\u001b[39mcore\u001b[38;5;241m.\u001b[39mdivide_shape_sizes(np\u001b[38;5;241m.\u001b[39mshape(a), newshape)\n\u001b[1;32m 140\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m core\u001b[38;5;241m.\u001b[39mdefinitely_equal(d, \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m) \u001b[38;5;28;01melse\u001b[39;00m d \u001b[38;5;28;01mfor\u001b[39;00m d \u001b[38;5;129;01min\u001b[39;00m newshape)\n", - "\u001b[0;31mTypeError\u001b[0m: cannot reshape array of shape (3072,) (size 3072) into shape (96, 128) (size 12288)" - ] - } - ], - "source": [ - "no_mesh_surface = (rendered_labd[...,3] == 0.0)\n", - "\n", - "inlier_variances = jnp.array([60.0, 60.0, 60.0, 0.6])\n", - "\n", - "lower_bound = jnp.array([0.0, -100.0, -100.0, 0.0])\n", - "upper_bound = jnp.array([100.0, 100.0, 100.0, 20.0])\n", - "\n", - "outlier_variances = jnp.ones(4) * 1000000.0\n", - "\n", - "scores_inlier = jax.vmap(genjax.truncated_normal.logpdf, in_axes=(0, 0, None, None, None))(\n", - " observed_labd.reshape(-1, 4), rendered_labd.reshape(-1,4), inlier_variances,\n", - " lower_bound, upper_bound\n", - ")\n", - "scores_outlier = jax.vmap(genjax.truncated_normal.logpdf, in_axes=(0, None, None, None, None))(\n", - " observed_labd.reshape(-1, 4), (lower_bound + upper_bound) / 2.0, outlier_variances,\n", - " lower_bound, upper_bound\n", - ")\n", - "\n", - "scores_inlier_merged = jax.nn.logsumexp(scores_inlier[..., :3] + jnp.log(1/3), axis=-1) + scores_inlier[..., 3]\n", - "scores_outlier_merged = jax.nn.logsumexp(scores_outlier[..., :3] + jnp.log(1/3), axis=-1) + scores_outlier[..., 3]\n", - "\n", - "plt.imshow((scores_inlier_merged - scores_outlier_merged).reshape(renderer.height, renderer.width))\n", - "plt.colorbar()" - ] - }, - { - "cell_type": "code", - "execution_count": 82, - "metadata": {}, - "outputs": [], - "source": [ - "rendered_labd = trace.get_retval()[\"rendered_color_space_d\"]\n", - "observed_labd = trace.get_retval()[\"observed_color_space_d\"]\n", - "\n", - "rendered_labd = trace.get_retval()[\"rendered_color_space_d\"]\n", - "observed_labd = trace.get_retval()[\"observed_color_space_d\"]\n", - "rr.set_time_sequence(\"time\", 0)\n", - "rr.log(\n", - " \"image\", rr.Image(trace.get_retval()[\"observed_rgbd\"][...,:3]),\n", - ")\n", - "rr.log(\n", - " \"image/rendered_rgbd\", rr.Image(trace.get_retval()[\"rendered_rgbd\"][...,:3]),\n", - ")\n", - "rr.log(\n", - " \"image/sampled_rgbd\", rr.Image(trace.get_retval()[\"sampled_rgbd\"][...,:3]),\n", - ")\n", - "\n", - "rr.log(\n", - " \"image/labd\", rr.Image(trace.get_retval()[\"observed_color_space_d\"][...,:3]),\n", - ")\n", - "rr.log(\n", - " \"image/rendered_labd\", rr.Image(trace.get_retval()[\"rendered_color_space_d\"][...,:3]),\n", - ")\n", - "\n", - "rr.log(\n", - " \"image/error\", rr.DepthImage((rendered_labd[..., 0] - observed_labd[..., 0]) * (rendered_labd[..., 3] > 0))\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 77, - "metadata": {}, - "outputs": [], - "source": [ - "rendered_labd = trace.get_retval()[\"rendered_color_space_d\"]\n", - "observed_labd = trace.get_retval()[\"observed_color_space_d\"]\n", - "rr.set_time_sequence(\"time\", 0)\n", - "rr.log(\n", - " \"image\", rr.Image(trace.get_retval()[\"observed_rgbd\"][...,:3]),\n", - ")\n", - "rr.log(\n", - " \"image/rendered_rgbd\", rr.Image(trace.get_retval()[\"rendered_rgbd\"][...,:3]),\n", - ")\n", - "rr.log(\n", - " \"image/sampled_rgbd\", rr.Image(trace.get_retval()[\"sampled_rgbd\"][...,:3]),\n", - ")\n", - "\n", - "rr.log(\n", - " \"image/labd\", rr.Image(trace.get_retval()[\"observed_color_space_d\"][...,:3]),\n", - ")\n", - "rr.log(\n", - " \"image/rendered_labd\", rr.Image(trace.get_retval()[\"rendered_color_space_d\"][...,:3]),\n", - ")\n" - ] - }, - { - "cell_type": "code", - "execution_count": 66, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 66, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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")\n", - "rr.log(\n", - " \"image/sampled_rgbd\", rr.Image(trace.get_retval()[\"sampled_rgbd\"][...,:3]),\n", - ")\n", - "\n", - "rr.log(\n", - " \"image/labd\", rr.Image(trace.get_retval()[\"observed_labd\"][...,:3]),\n", - ")\n", - "rr.log(\n", - " \"image/rendered_labd\", rr.Image(trace.get_retval()[\"rendered_labd\"][...,:3]),\n", - ")\n" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "metadata": {}, - "outputs": [], - "source": [ - "b3d.rr_init()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 104, - "metadata": {}, - "outputs": [], - "source": [ - "b3d.rr_init()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 140, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(Array([5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5,\n", - 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"execution_count": 125, - "metadata": {}, - "outputs": [], - "source": [ - "rendered_rgbd = trace.get_retval()[\"rendered_rgbd\"]\n", - "observed_rgbd = trace.get_retval()[\"observed_rgbd\"]\n", - "mask = rendered_rgbd[..., 3] > 0.0\n", - "rendered_depth= rendered_rgbd[..., 3]\n", - "observed_depth = observed_rgbd[..., 3]" - ] - }, - { - "cell_type": "code", - "execution_count": 121, - "metadata": {}, - "outputs": [], - "source": [ - "b3d.rr_init(\"interactive\")" - ] - }, - { - "cell_type": "code", - "execution_count": 126, - "metadata": {}, - "outputs": [], - "source": [ - "import rerun as rr\n", - "rr.log(\"depth\", rr.DepthImage(rendered_rgbd[..., 3]))\n", - "rr.log(\"depth/observed\", rr.DepthImage(observed_rgbd[..., 3]))\n", - "rr.log(\"depth/error\", rr.DepthImage((rendered_depth- observed_depth) * mask))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - 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"source": [ - "inlier_color_variance_sweep" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 87, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Array([0.01 , 0.12 , 0.23 , 0.34 , 0.45000002,\n", - " 0.56 , 0.67 , 0.78000003, 0.89 , 1. ], dtype=float32)" - ] - }, - "execution_count": 87, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "outlier_probability_sweep" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 78, - "metadata": {}, - "outputs": [ - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "831b532e2e7149f3b96ac40555cca5d9", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "interactive(children=(FloatSlider(value=0.12000000476837158, description='outlier_probability', max=1.0, min=0…" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plot_interactive(trace)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - 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" 4.5545454, 4.5545454, 4.5545454, 4.5545454], dtype=float32))" - ] - }, - "execution_count": 49, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 44, - "metadata": {}, - "outputs": [ - { - "ename": "AttributeError", - "evalue": "'tuple' object has no attribute 'shape'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[44], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43msampled_indices\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mshape\u001b[49m\n", - "\u001b[0;31mAttributeError\u001b[0m: 'tuple' object has no attribute 'shape'" - ] - } - ], - "source": [ - "sampled_indices.shape" - ] - }, - { - "cell_type": "code", - "execution_count": 42, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 186, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 188, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(10, 20, 15, 12)\n", - "[5279 5279 5279 5459 5279 5279 5819 5459 5279 5459 5099 5279 5459 5279\n", - " 5279 5279 5459 5279 5279 5279 5279 5639 5279 5459 5279 5459 5279 5279\n", - " 5639 5279 5279 5279 5099 5459 5639 5099 5459 5459 5279 5099 5459 5099\n", - " 5459 5459 5279 5279 5279 5279 5279 5099 5279 5279 5279 5099 5279 5459\n", - " 5099 5279 5099 5099 5279 5279 5279 5279 5279 5279 5099 5459 5279 5459\n", - " 5279 5279 5459 5279 5279 5279 5279 5099 5279 5279 5279 5459 5279 5279\n", - " 5279 5279 5279 5279 5459 5279 5279 5279 5099 5459 5279 5459 5279 5279\n", - " 5459 5279]\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n" - ] - }, - { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "ebde26e813ea4ef8a2a8df530f03ea33", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "interactive(children=(IntSlider(value=10000, description='k', max=100000, min=1), FloatSlider(value=0.12000000…" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 188, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "\n", - "scores = vmapped_grid(\n", - " trace,\n", - " key,\n", - " outlier_probability_sweep,\n", - " inlier_lightness_variance_sweep,\n", - " inlier_color_variance_sweep,\n", - " inlier_depth_variance_sweep\n", - ")\n", - "print(scores.shape)\n", - "samples = jax.random.categorical(key, scores.reshape(-1),shape=(100,))\n", - "print(samples)\n", - "\n", - "\n", - "sample_index=1\n", - "print(\n", - " \"Outlier Probability\", outlier_probability_sweep[indices[0][sample_index]], \"\\n\",\n", - " \"Inlier Lightness Variance\", inlier_lightness_variance_sweep[indices[1][sample_index]], \"\\n\",\n", - " \"Inlier Color Variance\", inlier_color_variance_sweep[indices[2][sample_index]], \"\\n\",\n", - " \"Inlier Depth Variance\", inlier_depth_variance_sweep[indices[3][sample_index]], \"\\n\",\n", - ")\n", - "interact(\n", - " plot,\n", - " k = widgets.IntSlider(value=10000, min=1, max=100000, step=1),\n", - " outlier_probability = widgets.FloatSlider(value=outlier_probability_sweep[indices[0][sample_index]], min=0.01, max=1.0, step=0.01),\n", - " inlier_lightness_variance = widgets.FloatSlider(value=inlier_lightness_variance_sweep[indices[1][sample_index]], min=0.1, max=100.0, step=0.01),\n", - " inlier_color_variance = widgets.FloatSlider(value=inlier_color_variance_sweep[indices[2][sample_index]], min=0.1, max=100.0, step=0.01),\n", - " inlier_depth_variance = widgets.FloatSlider(value=inlier_depth_variance_sweep[indices[3][sample_index]], min=0.0001, max=100.0, step=0.01),\n", - ")\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "b3d.en" - ] - }, - { - "cell_type": "code", - "execution_count": 189, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 65.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 45.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 60.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 60.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 45.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 60.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 45.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 45.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 45.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 45.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 45.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 45.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 45.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 45.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 45.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 45.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 45.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 54.999996 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n" - ] - } - ], - "source": [ - "for sample_index in range(len(indices[0])):\n", - " print(\n", - " \"Outlier Probability\", outlier_probability_sweep[indices[0][sample_index]], \"\\n\",\n", - " \"Inlier Lightness Variance\", inlier_lightness_variance_sweep[indices[1][sample_index]], \"\\n\",\n", - " \"Inlier Color Variance\", inlier_color_variance_sweep[indices[2][sample_index]], \"\\n\",\n", - " \"Inlier Depth Variance\", inlier_depth_variance_sweep[indices[3][sample_index]], \"\\n\",\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": 160, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Array([1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949,\n", - " 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949,\n", - " 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949,\n", - " 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949,\n", - " 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949,\n", - " 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949,\n", - " 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949,\n", - " 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949,\n", - " 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949, 1949,\n", - " 1949], dtype=int32)" - ] - }, - "execution_count": 160, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Matched\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 50.0 \n", - " Inlier Color Variance 32.14286 \n", - " Inlier Depth Variance 0.1 \n", - "\n", - "# Mismatched\n", - "Outlier Probability 0.120000005 \n", - " Inlier Lightness Variance 100.0 \n", - " Inlier Color Variance 52.500004 \n", - " Inlier Depth Variance 0.1 " - ] - }, - { - "cell_type": "code", - "execution_count": 41, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(10000, 3)" - ] - }, - "execution_count": 41, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "trace.get_choices()[\"noisy_lab_color\",...].shape" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "b3d", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.4" - } - }, - "nbformat": 4, - "nbformat_minor": 2 + "nbformat": 4, + "nbformat_minor": 2 } From d32bf87401a4a11f00b0abbb65112185f826675c Mon Sep 17 00:00:00 2001 From: Nishad Gothoskar Date: Tue, 23 Jul 2024 01:51:26 +0000 Subject: [PATCH 02/16] optimization --- .../gradient_based_pose_estimation.py | 94 ++++++++++--------- 1 file changed, 48 insertions(+), 46 deletions(-) diff --git a/demos/differentiable_renderer/gradient_based_pose_estimation.py b/demos/differentiable_renderer/gradient_based_pose_estimation.py index 9025ab94..8066157b 100644 --- a/demos/differentiable_renderer/gradient_based_pose_estimation.py +++ b/demos/differentiable_renderer/gradient_based_pose_estimation.py @@ -2,15 +2,18 @@ from functools import partial import b3d -import b3d.chisight.dense.differentiable_renderer as rendering +from jax.scipy.spatial.transform import Rotation as Rot +from b3d import Pose, Mesh +import rerun as rr +import functools +import genjax +from tqdm import tqdm import jax import jax.numpy as jnp import optax -import rerun as rr -import trimesh -from b3d import Pose -from b3d.renderer_original import RendererOriginal -from tqdm import tqdm +import b3d.chisight.dense.differentiable_renderer as rendering +import demos.differentiable_renderer.utils as utils +from functools import partial rr.init("gradients") rr.connect("127.0.0.1:8812") @@ -28,28 +31,6 @@ def map_fn(nested_dict): return map_fn -# Set up OpenGL renderer -image_width = 200 -image_height = 200 -fx = 150.0 -fy = 150.0 -cx = 100.0 -cy = 100.0 -near = 0.001 -far = 16.0 -renderer = RendererOriginal(image_width, image_height, fx, fy, cx, cy, near, far) - -WINDOW = 5 - -mesh_path = os.path.join( - b3d.get_root_path(), - "assets/shared_data_bucket/ycb_video_models/models/006_mustard_bottle/textured_simple.obj", -) -mesh = trimesh.load(mesh_path) -object_library = b3d.MeshLibrary.make_empty_library() -object_library.add_trimesh(mesh) - - def render_to_dist_params( renderer, vertices, @@ -75,7 +56,7 @@ def render_to_dist_params( The remaining weights are those assigned to some triangles in the scene. The attributes measured on those triangles are contained in `attributes`. """ - image = renderer.rasterize(vertices[None, ...], faces) + image = renderer.rasterize_many(vertices[None, ...], faces) triangle_id_image = image[0, ..., -1].astype(jnp.int32) triangle_intersected_padded = jnp.pad( @@ -151,35 +132,58 @@ def render_to_average_rgbd( hyperparams = rendering.DifferentiableRendererHyperparams(3, 5e-5, 0.25, -1) -def render(params): +def render(params, mesh_params): image = render_to_average_rgbd( renderer, b3d.Pose(params["position"], params["quaternion"]).apply( - object_library.vertices + mesh_params["vertices"] ), - object_library.faces, - object_library.attributes, + mesh_params["faces"], + mesh_params["vertex_attributes"], background_attribute=jnp.array([0.0, 0.0, 0.0, 0]), hyperparams=hyperparams, ) return image -render_jit = jax.jit(render) +# Set up OpenGL renderer +image_width = 200 +image_height = 200 +fx = 150.0 +fy = 150.0 +cx = 100.0 +cy = 100.0 +near = 0.001 +far = 16.0 +renderer = b3d.RendererOriginal(image_width, image_height, fx, fy, cx, cy, near, far) +WINDOW = 5 -vertices, faces = object_library.vertices, object_library.faces -image = renderer.rasterize(vertices[None, ...], faces) +mesh_path = os.path.join( + b3d.get_root_path(), + "assets/shared_data_bucket/ycb_video_models/models/006_mustard_bottle/textured_simple.obj", +) +mesh = Mesh.from_obj(mesh_path) + +render_jit = jax.jit(render) + +mesh_params = { + "vertices": mesh.vertices, + "faces": mesh.faces, + "vertex_attributes": mesh.vertex_attributes, +} gt_pose = Pose.from_position_and_target( jnp.array([0.3, 0.3, 0.0]), jnp.array([0.0, 0.0, 0.0]), ).inv() -gt_image = render_jit({"position": gt_pose.position, "quaternion": gt_pose.quaternion}) +gt_image = render_jit( + {"position": gt_pose.position, "quaternion": gt_pose.quaternion}, mesh_params +) -def loss_func_rgbd(params, gt): - image = render(params) +def loss_func_rgbd(params, mesh_params, gt): + image = render(params, mesh_params) return jnp.mean(jnp.abs(image[..., :3] - gt[..., :3])) # + jnp.mean(jnp.abs(image[...,3] - gt[...,3])) @@ -190,7 +194,7 @@ def loss_func_rgbd(params, gt): @partial(jax.jit, static_argnums=(1,)) def step(carry, tx): (params, gt_image, state) = carry - _loss, (gradients,) = loss_func_rgbd_grad(params, gt_image) + loss, (gradients,) = loss_func_rgbd_grad(params, mesh_params, gt_image) updates, state = tx.update(gradients, state, params) params = optax.apply_updates(params, updates) return ((params, gt_image, state), None) @@ -217,21 +221,19 @@ def step(carry, tx): } rr.log("image", rr.Image(gt_image[..., :3]), timeless=True) -rr.log("cloud", rr.Points3D(gt_pose.apply(object_library.vertices)), timeless=True) +rr.log("cloud", rr.Points3D(gt_pose.apply(mesh.vertices)), timeless=True) pbar = tqdm(range(200)) state = tx.init(params) -images = [render_jit(params)] +images = [render_jit(params, mesh_params)] for t in pbar: (params, gt_image, state), _ = step((params, gt_image, state), tx) rr.set_time_sequence("frame", t) - image = render_jit(params) + image = render_jit(params, mesh_params) rr.log("image/reconstruction", rr.Image(image[..., :3])) rr.log( "cloud/reconstruction", rr.Points3D( - b3d.Pose(params["position"], params["quaternion"]).apply( - object_library.vertices - ) + b3d.Pose(params["position"], params["quaternion"]).apply(mesh.vertices) ), ) From fe39e8226d0f6bc51db71f6d41212a41d838acca Mon Sep 17 00:00:00 2001 From: Nishad Gothoskar Date: Tue, 23 Jul 2024 02:03:25 +0000 Subject: [PATCH 03/16] save --- .../gradient_based_pose_estimation.py | 60 ++++++++++++------- 1 file changed, 37 insertions(+), 23 deletions(-) diff --git a/demos/differentiable_renderer/gradient_based_pose_estimation.py b/demos/differentiable_renderer/gradient_based_pose_estimation.py index 8066157b..4c3c58f9 100644 --- a/demos/differentiable_renderer/gradient_based_pose_estimation.py +++ b/demos/differentiable_renderer/gradient_based_pose_estimation.py @@ -146,25 +146,41 @@ def render(params, mesh_params): return image -# Set up OpenGL renderer -image_width = 200 -image_height = 200 -fx = 150.0 -fy = 150.0 -cx = 100.0 -cy = 100.0 -near = 0.001 -far = 16.0 -renderer = b3d.RendererOriginal(image_width, image_height, fx, fy, cx, cy, near, far) - WINDOW = 5 -mesh_path = os.path.join( - b3d.get_root_path(), - "assets/shared_data_bucket/ycb_video_models/models/006_mustard_bottle/textured_simple.obj", + +ycb_dir = os.path.join(b3d.get_assets_path(), "bop/ycbv") + +# image_ids = [image] if image is not None else range(1, num_scenes, FRAME_RATE) +scene_id = 48 +print(f"Scene {scene_id}") +num_scenes = b3d.io.data_loader.get_ycbv_num_test_images(ycb_dir, scene_id) +image_ids = range(1, num_scenes + 1, 50) +all_data = b3d.io.get_ycbv_test_images(ycb_dir, scene_id, image_ids) + +meshes = [ + Mesh.from_obj_file( + os.path.join(ycb_dir, f'models/obj_{f"{id + 1}".rjust(6, "0")}.ply') + ).scale(0.001) + for id in all_data[0]["object_types"] +] + +height, width = all_data[0]["rgbd"].shape[:2] +fx, fy, cx, cy = all_data[0]["camera_intrinsics"] +scaling_factor = 0.3 +renderer = b3d.renderer.renderer_original.RendererOriginal( + width * scaling_factor, + height * scaling_factor, + fx * scaling_factor, + fy * scaling_factor, + cx * scaling_factor, + cy * scaling_factor, + 0.01, + 2.0, ) -mesh = Mesh.from_obj(mesh_path) +IDX = 1 +mesh = meshes[IDX] render_jit = jax.jit(render) @@ -177,14 +193,14 @@ def render(params, mesh_params): jnp.array([0.3, 0.3, 0.0]), jnp.array([0.0, 0.0, 0.0]), ).inv() -gt_image = render_jit( - {"position": gt_pose.position, "quaternion": gt_pose.quaternion}, mesh_params -) +gt_image = b3d.resize_image(all_data[0]["rgbd"], renderer.height, renderer.width) def loss_func_rgbd(params, mesh_params, gt): image = render(params, mesh_params) - return jnp.mean(jnp.abs(image[..., :3] - gt[..., :3])) + rendered_depth = image[..., 3] + rendered_areas = (rendered_depth / fx) * (rendered_depth / fy) + return jnp.mean(jnp.abs(image[..., :3] - gt[..., :3]) * rendered_areas[..., None]) # + jnp.mean(jnp.abs(image[...,3] - gt[...,3])) @@ -210,10 +226,7 @@ def step(carry, tx): label_fn, ) -pose = Pose.from_position_and_target( - jnp.array([0.6, 0.3, 0.6]), - jnp.array([0.0, 0.0, 0.0]), -).inv() +pose = all_data[0]["camera_pose"].inv() @ all_data[0]["object_poses"][IDX] params = { "position": pose.position, @@ -230,6 +243,7 @@ def step(carry, tx): (params, gt_image, state), _ = step((params, gt_image, state), tx) rr.set_time_sequence("frame", t) image = render_jit(params, mesh_params) + pbar.set_description(f"Loss: {loss_func_rgbd(params, mesh_params, gt_image)}") rr.log("image/reconstruction", rr.Image(image[..., :3])) rr.log( "cloud/reconstruction", From dd99f8ef5be9ba0b89c03083321a86fc6200a1e1 Mon Sep 17 00:00:00 2001 From: Nishad Gothoskar Date: Tue, 23 Jul 2024 02:20:51 +0000 Subject: [PATCH 04/16] save kitti progress --- notebooks/bayes3d_paper/kitti.ipynb | 108 ++++++++++++-------------- notebooks/bayes3d_paper/kitti_data.py | 6 +- 2 files changed, 54 insertions(+), 60 deletions(-) diff --git a/notebooks/bayes3d_paper/kitti.ipynb b/notebooks/bayes3d_paper/kitti.ipynb index e8095f56..19b16e29 100644 --- a/notebooks/bayes3d_paper/kitti.ipynb +++ b/notebooks/bayes3d_paper/kitti.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 62, + "execution_count": 20, "metadata": {}, "outputs": [], "source": [ @@ -21,7 +21,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -33,7 +33,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -56,7 +56,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -70,7 +70,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 17, "metadata": {}, "outputs": [], "source": [ @@ -79,7 +79,7 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ @@ -144,87 +144,77 @@ }, { "cell_type": "code", - "execution_count": 48, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "11199.132\n" - ] - } - ], - "source": [ - "trace, _ = importance_jit(\n", - " jax.random.PRNGKey(2),\n", - " choicemap,\n", - " ({\"meshes\": [mesh], \"likelihood_args\": likelihood_args},),\n", - ")\n", - "print(trace.get_score())\n", - "viz_trace(trace, 0)" - ] - }, - { - "cell_type": "code", - "execution_count": 50, + "execution_count": 21, "metadata": {}, "outputs": [], "source": [ - "t = 1\n", - "trace = b3d.update_choices_jit(trace, jax.random.PRNGKey(0), Pytree.const((\"image\",)),\n", - " b3d.utils.resize_image(rgbd[t], renderer.height, renderer.width),\n", - ")\n", - "viz_trace(trace,t)" + "mesh.rr_visualize(\"mesh\")" ] }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 23, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "10318.408\n" + "8846.404\n" ] } ], "source": [ - "trace, key = b3d.bayes3d.enumerative_proposals.gvmf_and_select_best_move(\n", - " trace, key, 1.0, 700.0, \"object_pose_0\", 700\n", - ")\n", - "trace, key = b3d.bayes3d.enumerative_proposals.gvmf_and_select_best_move(\n", - " trace, key, 0.5, 1000.0, \"object_pose_0\", 700\n", - ")\n", - "trace, key = b3d.bayes3d.enumerative_proposals.gvmf_and_select_best_move(\n", - " trace, key, 0.1, 2000.0, \"object_pose_0\", 700\n", + "trace, _ = importance_jit(\n", + " jax.random.PRNGKey(2),\n", + " choicemap,\n", + " ({\"meshes\": [mesh], \"likelihood_args\": likelihood_args},),\n", ")\n", "print(trace.get_score())\n", - "viz_trace(trace,t)" + "viz_trace(trace, 0)" ] }, { "cell_type": "code", - "execution_count": 76, + "execution_count": 25, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "13969.692\n", - "16488.252\n", - "10029.43\n", - "10629.677\n", - "12003.404\n", - "13170.253\n", - "10754.463\n", - "10117.536\n", - "6347.37\n", - "3223.3906\n", - "13184.921\n" + "8846.404\n", + "11013.862\n", + "11611.759\n", + "12070.877\n", + "10622.367\n", + "11471.874\n", + "8870.875\n", + "9299.528\n", + "5552.7026\n", + "4944.132\n", + "13057.334\n", + "2642.6655\n", + "3540.0493\n", + "3779.468\n", + "5258.7427\n", + "2151.1301\n", + "3045.7324\n", + "2346.7327\n", + "2053.8494\n", + "2083.748\n", + "2666.7578\n", + "2977.49\n", + "2807.3442\n", + "-6.0253487\n", + "-6.0253487\n", + "-6.0253487\n", + "-6.0253487\n", + "-6.0253487\n", + "-6.0253487\n", + "885.59656\n", + "1548.4434\n", + "1639.1842\n" ] } ], @@ -238,7 +228,7 @@ "viz_trace(trace, 0)\n", "traces = []\n", "for t in range(0,len(rgbd)):\n", - " trace = b3d.update_choices_jit(trace, jax.random.PRNGKey(0), Pytree.const((\"image\",)),\n", + " trace = b3d.update_choices(trace, jax.random.PRNGKey(0), Pytree.const((\"image\",)),\n", " b3d.utils.resize_image(rgbd[t], renderer.height, renderer.width),\n", " )\n", " trace, key = b3d.bayes3d.enumerative_proposals.gvmf_and_select_best_move(\n", diff --git a/notebooks/bayes3d_paper/kitti_data.py b/notebooks/bayes3d_paper/kitti_data.py index decc9f48..88045ac4 100644 --- a/notebooks/bayes3d_paper/kitti_data.py +++ b/notebooks/bayes3d_paper/kitti_data.py @@ -13,7 +13,7 @@ basedir = os.path.join(b3d.get_assets_path(), "kitti") date = "2011_09_26" drive = "0005" -frames = range(0, 50, 5) +frames = range(0, 153, 5) dataset = pykitti.raw(basedir, date, drive, frames=frames) @@ -78,6 +78,10 @@ colors = rgbs[0][mask] colors = colors[xyzs.sum(-1) > 0] xyzs = xyzs[xyzs.sum(-1) > 0] +m = b3d.segment_point_cloud(xyzs, threshold=0.2) == 0 + +xyzs = xyzs[m] +colors = colors[m] resolution = 0.05 meshes = b3d.mesh.transform_mesh( From cbe8982bc4065127f98bcbe92a8e2d1b4500904f Mon Sep 17 00:00:00 2001 From: Nishad Gothoskar Date: Tue, 23 Jul 2024 14:21:13 +0000 Subject: [PATCH 05/16] save --- notebooks/bayes3d_paper/interactive.ipynb | 34 +---------------------- src/b3d/chisight/dense/dense_model.py | 28 ++++++++++--------- 2 files changed, 16 insertions(+), 46 deletions(-) diff --git a/notebooks/bayes3d_paper/interactive.ipynb b/notebooks/bayes3d_paper/interactive.ipynb index 973f4558..ea73eb4b 100644 --- a/notebooks/bayes3d_paper/interactive.ipynb +++ b/notebooks/bayes3d_paper/interactive.ipynb @@ -25,13 +25,6 @@ "import numpy as np\n" ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, { "cell_type": "code", "execution_count": 2, @@ -172,32 +165,7 @@ " scores_outlier_merged = jax.nn.logsumexp(scores_outlier[..., 1:3] + jnp.log(1/3), axis=-1) + scores_outlier[..., 3] + jnp.log(outlier_probability_adjusted)\n", " return jnp.logaddexp(scores_inlier_merged, scores_outlier_merged).sum()\n", "\n", - "masked_k_image_likelihood_marginalize_outlier_prob = MaskedKImageLikelihoodMarginalizeOutlier()\n", - "\n", - "\n", - "# k = 10\n", - "# masked_k_image_likelihood.logpdf(\n", - "# jnp.zeros((renderer.height, renderer.width, 4)),\n", - "# jnp.arange(k),\n", - "# jnp.arange(k),\n", - "# jnp.ones(k) * 0.1,\n", - "# jnp.zeros(k),\n", - "# jnp.zeros(4)- 0.1,\n", - "# jnp.ones(4),\n", - "# renderer.height,\n", - "# renderer.width\n", - "# )\n", - "# masked_k_image_likelihood.sample(\n", - "# key,\n", - "# jnp.arange(k),\n", - "# jnp.arange(k),\n", - "# jnp.ones(k) * 0.1,\n", - "# jnp.zeros(k),\n", - "# jnp.zeros(4)- 0.1,\n", - "# jnp.ones(4),\n", - "# renderer.height,\n", - "# renderer.width\n", - "# );" + "masked_k_image_likelihood_marginalize_outlier_prob = MaskedKImageLikelihoodMarginalizeOutlier()" ] }, { diff --git a/src/b3d/chisight/dense/dense_model.py b/src/b3d/chisight/dense/dense_model.py index 2e992583..9f9e244d 100644 --- a/src/b3d/chisight/dense/dense_model.py +++ b/src/b3d/chisight/dense/dense_model.py @@ -7,24 +7,20 @@ from b3d.modeling_utils import uniform_pose -def make_dense_multiobject_model(renderer, image_likelihood_func): - image_likelihood = ( - b3d.chisight.dense.likelihoods.image_likelihood.make_image_likelihood( - image_likelihood_func - ) - ) - +def make_dense_multiobject_model(renderer, image_likelihood): @genjax.gen def dense_multiobject_model(args_dict): meshes = args_dict["meshes"] likelihood_args = args_dict["likelihood_args"] num_objects = args_dict["num_objects"] - outlier_probability = genjax.uniform(0.001, 1.0) @ "outlier_probability" - color_variance = genjax.uniform(0.0, 1.0) @ "color_variance" - depth_variance = genjax.uniform(0.0, 1.0) @ "depth_variance" + outlier_probability = genjax.uniform(0.0001, 0.9999) @ "outlier_probability" + lightness_variance = genjax.uniform(0.0001, 1.0) @ "lightness_variance" + color_variance = genjax.uniform(0.0001, 1.0) @ "color_variance" + depth_variance = genjax.uniform(0.0001, 1.0) @ "depth_variance" likelihood_args["outlier_probability"] = outlier_probability + likelihood_args["lightness_variance"] = lightness_variance likelihood_args["color_variance"] = color_variance likelihood_args["depth_variance"] = depth_variance @@ -37,15 +33,21 @@ def dense_multiobject_model(args_dict): all_poses.append(object_pose) all_poses = Pose.stack_poses(all_poses) - scene_mesh = Mesh.transform_and_merge_meshes(meshes, all_poses) + camera_pose = ( + uniform_pose(jnp.ones(3) * -100.0, jnp.ones(3) * 100.0) @ "camera_pose" + ) + + scene_mesh = Mesh.transform_and_merge_meshes(meshes, all_poses).transform( + camera_pose.inv() + ) latent_rgbd = renderer.render_rgbd_from_mesh(scene_mesh) - image = image_likelihood(latent_rgbd, likelihood_args) @ "image" + image = image_likelihood(latent_rgbd, likelihood_args) @ "rgbd" return { "likelihood_args": likelihood_args, "scene_mesh": scene_mesh, "latent_rgbd": latent_rgbd, - "image": image, + "rgbd": image, } return dense_multiobject_model From 7cc029117ab2562ff11545e03acb79e4891a88d2 Mon Sep 17 00:00:00 2001 From: Nishad Gothoskar Date: Tue, 23 Jul 2024 15:05:30 +0000 Subject: [PATCH 06/16] refactoring --- notebooks/bayes3d_paper/interactive.ipynb | 314 ++++++++++-------- notebooks/bayes3d_paper/kitti.ipynb | 198 ++++------- src/b3d/chisight/dense/dense_model.py | 42 ++- .../dense/likelihoods/image_likelihood.py | 14 - 4 files changed, 286 insertions(+), 282 deletions(-) diff --git a/notebooks/bayes3d_paper/interactive.ipynb b/notebooks/bayes3d_paper/interactive.ipynb index ea73eb4b..f28a33d6 100644 --- a/notebooks/bayes3d_paper/interactive.ipynb +++ b/notebooks/bayes3d_paper/interactive.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -27,14 +27,14 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 20/20 [00:09<00:00, 2.20it/s]\n" + "100%|██████████| 10/10 [00:05<00:00, 1.68it/s]\n" ] } ], @@ -44,8 +44,7 @@ "ycb_dir = os.path.join(b3d.get_assets_path(), \"bop/ycbv\")\n", "scene_id = 49\n", "image_id = 100\n", - "\n", - "all_data = b3d.io.get_ycbv_test_images(ycb_dir, scene_id, range(1,1000,50))\n", + "all_data = b3d.io.get_ycbv_test_images(ycb_dir, scene_id, range(1,1000,100))\n", "\n", "meshes = [\n", " Mesh.from_obj_file(os.path.join(ycb_dir, f'models/obj_{f\"{id + 1}\".rjust(6, \"0\")}.ply')).scale(0.001)\n", @@ -70,102 +69,154 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 22, + "metadata": {}, + "outputs": [], + "source": [ + "lower_bound = jnp.array([0.0, -128.0, -128.0, 0.0])\n", + "upper_bound = jnp.array([100.0, 128.0, 128.0, 10.0])\n", + "convert_rgbd_to_color_space = lambda x: b3d.colors.rgbd_to_labd(x)\n", + "convert_color_space_to_rgbd = lambda x: b3d.colors.labd_to_rgbd(x)\n", + "\n", + "def intermediate_likelihood_func(observed_rgbd, rendered_rgbd, likelihood_args):\n", + " k = likelihood_args[\"k\"].const\n", + " outlier_probability = likelihood_args[\"outlier_probability\"]\n", + " lightness_variance = likelihood_args[\"lightness_variance\"]\n", + " color_variance = likelihood_args[\"color_variance\"]\n", + " depth_variance = likelihood_args[\"depth_variance\"]\n", + "\n", + " image_height, image_width = observed_rgbd.shape[:2]\n", + "\n", + " row_coordinates = jax.vmap(genjax.categorical.sample,in_axes=(0, 0,))(\n", + " jax.random.split(key, k),\n", + " jnp.ones((k, image_height))\n", + " )\n", + " column_coordinates = jax.vmap(genjax.categorical.sample, in_axes=(0, 0,))(\n", + " jax.random.split(key, k),\n", + " jnp.ones((k, image_width))\n", + " )\n", + "\n", + " no_mesh_surface = (rendered_rgbd[..., 3] == 0)[row_coordinates, column_coordinates]\n", + " outlier_probability_adjusted = outlier_probability * (1 - no_mesh_surface) + no_mesh_surface * 1.0\n", + " \n", + " observed_color_space_d = convert_rgbd_to_color_space(observed_rgbd)\n", + " rendered_color_space_d = convert_rgbd_to_color_space(rendered_rgbd)\n", + "\n", + " subset_observed = observed_color_space_d[row_coordinates, column_coordinates]\n", + " subset_observed_rescaled = (subset_observed - lower_bound) / (upper_bound - lower_bound)\n", + " rendered_values_rescaled = (rendered_color_space_d[row_coordinates, column_coordinates] - lower_bound) / (upper_bound - lower_bound)\n", + "\n", + " inlier_variances = jnp.array([lightness_variance, color_variance, color_variance, depth_variance])\n", + " outlier_variances = jnp.array([1000000.0, 1000000.0, 1000000.0, 1000000.0])\n", + "\n", + " scores_inlier = jax.vmap(genjax.truncated_normal.logpdf, in_axes=(0, 0, None, None, None))(\n", + " subset_observed_rescaled, rendered_values_rescaled, inlier_variances / (upper_bound - lower_bound),\n", + " 0.0, 1.0\n", + " )\n", + " scores_outlier = jax.vmap(genjax.truncated_normal.logpdf, in_axes=(0, None, None, None, None))(\n", + " subset_observed_rescaled, 0.5, outlier_variances / (upper_bound - lower_bound),\n", + " 0.0, 1.0\n", + " )\n", + "\n", + " scores_inlier_merged = jax.nn.logsumexp(scores_inlier[..., 1:3] + jnp.log(1/3), axis=-1) + scores_inlier[..., 3] + jnp.log(1.0 - outlier_probability_adjusted) \n", + " scores_outlier_merged = jax.nn.logsumexp(scores_outlier[..., 1:3] + jnp.log(1/3), axis=-1) + scores_outlier[..., 3] + jnp.log(outlier_probability_adjusted)\n", + " return {\n", + " \"score\": jnp.logaddexp(scores_inlier_merged, scores_outlier_merged).sum()\n", + " }" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [], + "source": [ + "import b3d.chisight.dense.dense_model\n", + "model, viz_trace = b3d.chisight.dense.dense_model.make_dense_multiobject_model(renderer, intermediate_likelihood_func)\n", + "importance_jit = jax.jit(model.importance)" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [], + "source": [ + "key = jax.random.split(key, 2)[-1]\n", + "likelikood_args = {\n", + " \"fx\": fx,\n", + " \"fy\": fy,\n", + " \"k\": Pytree.const(20000),\n", + "}\n", + "\n", + "choicemap = genjax.ChoiceMap.d(\n", + " {\n", + " \"outlier_probability\": 0.1,\n", + " \"inlier_lightness_variance\": 0.1,\n", + " \"inlier_color_variance\": 0.1,\n", + " \"inlier_depth_variance\": 0.1,\n", + " \"observed_color_space_d\": convert_rgbd_to_color_space(observed_rgbd_scaled_down),\n", + " \"rgbd\": observed_rgbd_scaled_down,\n", + " \"object_pose_0\": all_data[0][\"object_poses\"][IDX],\n", + " \"camera_pose\": all_data[0][\"camera_pose\"]\n", + " }\n", + ")\n", + "\n", + "trace = importance_jit(\n", + " key, \n", + " choicemap,\n", + " ({\"num_objects\": Pytree.const(1), \"meshes\": [meshes[IDX]], \"likelihood_args\": likelikood_args},)\n", + ")[0]\n", + "viz_trace(trace)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, "metadata": {}, "outputs": [ { "data": { - "image/jpeg": 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"text/plain": [ - "" + "Array(-11196.005, dtype=float32)" ] }, - "execution_count": 3, + "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "b3d.viz_rgb(rendered_rgbds[0])" + "b3d.update_choices_get_score(\n", + " trace, key,\n", + " Pytree.const((\"outlier_probability\", \"color_variance\")),\n", + " 0.1,0.2\n", + ")" ] }, { "cell_type": "code", - "execution_count": 47, + "execution_count": 43, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "(3, 2, 1)" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "@Pytree.dataclass\n", - "class MaskedKImageLikelihoodMarginalizeOutlier(genjax.ExactDensity):\n", - " def sample(self, key,\n", - " row_coordinates,\n", - " column_coordinates,\n", - " rendered_color_space_d,\n", - " inlier_variances,\n", - " outlier_variances,\n", - " outlier_probability,\n", - " lower_bound, upper_bound,\n", - " image_height, image_width\n", - " ):\n", - " observed_image = jnp.zeros((image_height.const, image_width.const, 4))\n", - "\n", - " no_mesh_surface = (rendered_color_space_d[..., 3] == 0)[row_coordinates, column_coordinates]\n", - " outlier_probability_adjusted = outlier_probability * (1 - no_mesh_surface) + no_mesh_surface * 1.0\n", - "\n", - " is_outlier = jax.vmap(genjax.bernoulli.sample,in_axes=(0, 0))(\n", - " jax.random.split(key, len(row_coordinates)), jax.scipy.special.logit(outlier_probability_adjusted)\n", - " )\n", - "\n", - " sampled_inlier_values = jax.vmap(genjax.truncated_normal.sample, in_axes=(0, 0, None, None, None))(\n", - " jax.random.split(key, len(row_coordinates)), rendered_color_space_d[row_coordinates, column_coordinates], inlier_variances,\n", - " lower_bound, upper_bound\n", - " )\n", - " sampled_outlier_values = jax.vmap(genjax.truncated_normal.sample, in_axes=(0, 0, None, None, None))(\n", - " jax.random.split(key, len(row_coordinates)), rendered_color_space_d[row_coordinates, column_coordinates], outlier_variances,\n", - " lower_bound, upper_bound\n", - " )\n", - " sampled_values = (\n", - " is_outlier[...,None] * sampled_outlier_values + (1 - is_outlier[...,None]) * sampled_inlier_values\n", - " )\n", - " # sampled_values = jnp.where(is_outlier, sampled_outlier_values, sampled_inlier_values)\n", - "\n", - " observed_image = observed_image.at[row_coordinates, column_coordinates, :].set(sampled_values)\n", - " return observed_image\n", - "\n", - " def logpdf(self,\n", - " observed_color_space_d,\n", - " row_coordinates,\n", - " column_coordinates,\n", - " rendered_color_space_d,\n", - " inlier_variances,\n", - " outlier_variances,\n", - " outlier_probability,\n", - " lower_bound, upper_bound,\n", - " image_height, image_width\n", - " ):\n", - " no_mesh_surface = (rendered_color_space_d[..., 3] == 0)[row_coordinates, column_coordinates]\n", - " subset_observed = observed_color_space_d[row_coordinates, column_coordinates]\n", - "\n", - " outlier_probability_adjusted = outlier_probability * (1 - no_mesh_surface) + no_mesh_surface * 1.0\n", - "\n", - " subset_observed_rescaled = (subset_observed - lower_bound) / (upper_bound - lower_bound)\n", - " rendered_values_rescaled = (rendered_color_space_d[row_coordinates, column_coordinates] - lower_bound) / (upper_bound - lower_bound)\n", - "\n", - " scores_inlier = jax.vmap(genjax.truncated_normal.logpdf, in_axes=(0, 0, None, None, None))(\n", - " subset_observed_rescaled, rendered_values_rescaled, inlier_variances / (upper_bound - lower_bound),\n", - " 0.0, 1.0\n", - " )\n", - " scores_outlier = jax.vmap(genjax.truncated_normal.logpdf, in_axes=(0, None, None, None, None))(\n", - " subset_observed_rescaled, 0.5, outlier_variances / (upper_bound - lower_bound),\n", - " 0.0, 1.0\n", - " )\n", - "\n", - " scores_inlier_merged = jax.nn.logsumexp(scores_inlier[..., 1:3] + jnp.log(1/3), axis=-1) + scores_inlier[..., 3] + jnp.log(1.0 - outlier_probability_adjusted) \n", - " scores_outlier_merged = jax.nn.logsumexp(scores_outlier[..., 1:3] + jnp.log(1/3), axis=-1) + scores_outlier[..., 3] + jnp.log(outlier_probability_adjusted)\n", - " return jnp.logaddexp(scores_inlier_merged, scores_outlier_merged).sum()\n", - "\n", - "masked_k_image_likelihood_marginalize_outlier_prob = MaskedKImageLikelihoodMarginalizeOutlier()" + "f = b3d.multivmap(b3d.update_choices_get_score, (False, False, False, True, True, True))\n", + "f(\n", + " trace, key,\n", + " Pytree.const((\"outlier_probability\", \"color_variance\", \"object_pose_0\")),\n", + " jnp.array([0.1, 0.2, 0.3]), jnp.array([0.2, 0.01]), all_data[0][\"object_poses\"][IDX][None,...]\n", + ").shape" ] }, { @@ -194,7 +245,53 @@ " ax[4].imshow(trace.get_retval()[\"observed_rgbd\"][..., :3],alpha=1.0)\n", " ax[4].imshow(trace.get_retval()[\"rendered_rgbd\"][..., :3],alpha=0.5)\n", " ax[4].axis('off')\n", - " return fig\n" + " return fig\n", + "\n", + "\n", + "def plot_interactive(trace):\n", + " def _make_viz(outlier_probability, inlier_lightness_variance, inlier_color_variance, inlier_depth_variance):\n", + " choicemap = genjax.ChoiceMap.d(\n", + " {\n", + " \"outlier_probability\": outlier_probability,\n", + " \"inlier_lightness_variance\": inlier_lightness_variance,\n", + " \"inlier_color_variance\": inlier_color_variance,\n", + " \"inlier_depth_variance\": inlier_depth_variance,\n", + " }\n", + " )\n", + " modified_trace = update_jit(\n", + " key,\n", + " trace,\n", + " choicemap\n", + " )[0]\n", + " plot_trace(modified_trace)\n", + "\n", + " interact(_make_viz,\n", + " k = widgets.IntSlider(value=10000, min=1, max=100000, step=1),\n", + " outlier_probability = widgets.FloatSlider(\n", + " value=trace.get_choices()[\"outlier_probability\"],\n", + " min=outlier_probability_sweep.min(),\n", + " max=outlier_probability_sweep.max(),\n", + " step=0.01\n", + " ),\n", + " inlier_lightness_variance = widgets.FloatSlider(\n", + " value=trace.get_choices()[\"inlier_lightness_variance\"],\n", + " min=inlier_lightness_variance_sweep.min(),\n", + " max=inlier_lightness_variance_sweep.max(),\n", + " step=0.01\n", + " ),\n", + " inlier_color_variance = widgets.FloatSlider(\n", + " value=trace.get_choices()[\"inlier_color_variance\"],\n", + " min=inlier_color_variance_sweep.min(),\n", + " max=inlier_color_variance_sweep.max(),\n", + " step=0.01\n", + " ),\n", + " inlier_depth_variance = widgets.FloatSlider(\n", + " value=trace.get_choices()[\"inlier_depth_variance\"],\n", + " min=inlier_depth_variance_sweep.min(),\n", + " max=inlier_depth_variance_sweep.max(),\n", + " step=0.01\n", + " ),\n", + " )\n" ] }, { @@ -203,10 +300,6 @@ "metadata": {}, "outputs": [], "source": [ - "lower_bound = jnp.array([0.0, -100.0, -100.0, 0.0])\n", - "upper_bound = jnp.array([100.0, 100.0, 100.0, 4.0])\n", - "convert_rgbd_to_color_space = lambda x: b3d.colors.rgbd_to_labd(x)\n", - "convert_color_space_to_rgbd = lambda x: b3d.colors.labd_to_rgbd(x)\n", "\n", "@genjax.gen\n", "def ray_model(args):\n", @@ -281,51 +374,6 @@ "\n", "\n", "\n", - "def plot_interactive(trace):\n", - " def _make_viz(outlier_probability, inlier_lightness_variance, inlier_color_variance, inlier_depth_variance):\n", - " choicemap = genjax.ChoiceMap.d(\n", - " {\n", - " \"outlier_probability\": outlier_probability,\n", - " \"inlier_lightness_variance\": inlier_lightness_variance,\n", - " \"inlier_color_variance\": inlier_color_variance,\n", - " \"inlier_depth_variance\": inlier_depth_variance,\n", - " }\n", - " )\n", - " modified_trace = update_jit(\n", - " key,\n", - " trace,\n", - " choicemap\n", - " )[0]\n", - " plot_trace(modified_trace)\n", - "\n", - " interact(_make_viz,\n", - " k = widgets.IntSlider(value=10000, min=1, max=100000, step=1),\n", - " outlier_probability = widgets.FloatSlider(\n", - " value=trace.get_choices()[\"outlier_probability\"],\n", - " min=outlier_probability_sweep.min(),\n", - " max=outlier_probability_sweep.max(),\n", - " step=0.01\n", - " ),\n", - " inlier_lightness_variance = widgets.FloatSlider(\n", - " value=trace.get_choices()[\"inlier_lightness_variance\"],\n", - " min=inlier_lightness_variance_sweep.min(),\n", - " max=inlier_lightness_variance_sweep.max(),\n", - " step=0.01\n", - " ),\n", - " inlier_color_variance = widgets.FloatSlider(\n", - " value=trace.get_choices()[\"inlier_color_variance\"],\n", - " min=inlier_color_variance_sweep.min(),\n", - " max=inlier_color_variance_sweep.max(),\n", - " step=0.01\n", - " ),\n", - " inlier_depth_variance = widgets.FloatSlider(\n", - " value=trace.get_choices()[\"inlier_depth_variance\"],\n", - " min=inlier_depth_variance_sweep.min(),\n", - " max=inlier_depth_variance_sweep.max(),\n", - " step=0.01\n", - " ),\n", - " )\n", - "\n", "@jax.jit\n", "def update_parameters(\n", " trace,\n", diff --git a/notebooks/bayes3d_paper/kitti.ipynb b/notebooks/bayes3d_paper/kitti.ipynb index 19b16e29..73de69ae 100644 --- a/notebooks/bayes3d_paper/kitti.ipynb +++ b/notebooks/bayes3d_paper/kitti.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 20, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -21,104 +21,60 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "kitti_data_path = b3d.get_assets_path() / \"shared_data_bucket/foundation_pose_tracking_datasets/kitti_initial_data.npz\"\n", "kitti_mesh_path = b3d.get_assets_path() / \"shared_data_bucket/foundation_pose_tracking_datasets/kitti_initial_data.obj\"\n", "data = jnp.load(kitti_data_path)\n", - "mesh = b3d.Mesh.from_obj(kitti_mesh_path)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "key = jax.random.PRNGKey(0)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "import b3d.chisight.dense.likelihoods.image_likelihood\n", - "import b3d.chisight.dense.likelihoods.simple_likelihood\n", - "intermediate_likelihood_func = b3d.chisight.dense.likelihoods.simple_likelihood.simple_likelihood\n", - "image_likelihood = b3d.chisight.dense.likelihoods.image_likelihood.make_image_likelihood(\n", - " intermediate_likelihood_func,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [], - "source": [ + "mesh = b3d.Mesh.from_obj(kitti_mesh_path)\n", + "mesh.rr_visualize(\"mesh\")\n", + "rgbd = jnp.concatenate([data[\"rgb\"], data[\"depths\"][...,None]], axis=-1)\n", + "key = jax.random.PRNGKey(0)\n", + "\n", "height, width = data[\"rgb\"][0].shape[:2]\n", "fx,fy,cx,cy,near,far = data[\"camera_intrinsics\"]\n", "scaling_factor = 0.3\n", "renderer = b3d.renderer.renderer_original.RendererOriginal(\n", " width * scaling_factor, height * scaling_factor, fx * scaling_factor, fy * scaling_factor, cx * scaling_factor, cy * scaling_factor, 0.01, 2.0\n", - ")" + ")\n" ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ - "rgbd = jnp.concatenate([data[\"rgb\"], data[\"depths\"][...,None]], axis=-1)" + "import b3d.chisight.dense.likelihoods.image_likelihood\n", + "import b3d.chisight.dense.likelihoods.simple_likelihood\n", + "intermediate_likelihood_func = b3d.chisight.dense.likelihoods.simple_likelihood.simple_likelihood\n", + "b3d.reload(b3d.chisight.dense.dense_model)\n", + "model, viz_trace = b3d.chisight.dense.dense_model.make_dense_multiobject_model(renderer, intermediate_likelihood_func)\n", + "importance_jit = jax.jit(model.importance)" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 23, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "8796.027\n" + ] + } + ], "source": [ - "from b3d.modeling_utils import uniform_pose\n", - "@genjax.gen\n", - "def dense_model(args_dict):\n", - " meshes = args_dict[\"meshes\"]\n", - " likelihood_args = args_dict[\"likelihood_args\"]\n", - " object_pose = uniform_pose(jnp.ones(3)*-100.0, jnp.ones(3)*100.0) @ \"object_pose_0\"\n", - " all_poses = Pose.stack_poses([object_pose])\n", - "\n", - " scene_mesh = Mesh.transform_and_merge_meshes(meshes, all_poses)\n", - " latent_rgbd = renderer.render_rgbd_from_mesh(scene_mesh)\n", - " image = image_likelihood(latent_rgbd, likelihood_args) @ \"image\"\n", - " return {\"scene_mesh\": scene_mesh, \"latent_rgbd\": latent_rgbd, \"image\": image}\n", - "\n", - "def viz_trace(trace, t=0):\n", - " rr.set_time_sequence(\"time\", t)\n", - "\n", - " intermediate_info = intermediate_likelihood_func(\n", - " trace.get_choices()[\"image\"],\n", - " trace.get_retval()[\"latent_rgbd\"], \n", - " trace.get_args()[0][\"likelihood_args\"]\n", - " )\n", - "\n", - " rr.log(\"rgb\", rr.Image(trace.get_choices()[\"image\"][...,:3]))\n", - " rr.log(\"rgb/depth/observed\", rr.DepthImage(trace.get_choices()[\"image\"][...,3]))\n", - " rr.log(\"rgb/depth/latent\", rr.DepthImage(trace.get_retval()[\"latent_rgbd\"][...,3]))\n", - " rr.log(\"rgb/latent\", rr.Image(trace.get_retval()[\"latent_rgbd\"][...,:3]))\n", - " rr.log(\"rgb/is_match\", rr.DepthImage(intermediate_info[\"is_match\"] * 1.0))\n", - " rr.log(\"rgb/color_match\", rr.DepthImage(intermediate_info[\"color_match\"] * 1.0))\n", - "\n", - "importance_jit = jax.jit(dense_model.importance)\n", - "\n", "choicemap = genjax.ChoiceMap.d(\n", " dict(\n", " [\n", " (\"object_pose_0\", Pose(data[\"object_position\"][0], data[\"object_quaternion\"][0])),\n", - " (\"image\", \n", + " (\"camera_pose\", Pose.identity()),\n", + " (\"rgbd\", \n", " b3d.utils.resize_image(\n", " rgbd[0], renderer.height, renderer.width\n", " )\n", @@ -139,36 +95,12 @@ " \"fx\": renderer.fx,\n", " \"fy\": renderer.fy,\n", " \"far\": renderer.far,\n", - "}\n" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [], - "source": [ - "mesh.rr_visualize(\"mesh\")" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "8846.404\n" - ] - } - ], - "source": [ + "}\n", + "\n", "trace, _ = importance_jit(\n", " jax.random.PRNGKey(2),\n", " choicemap,\n", - " ({\"meshes\": [mesh], \"likelihood_args\": likelihood_args},),\n", + " ({\"num_objects\": Pytree.const(1), \"meshes\": [mesh], \"likelihood_args\": likelihood_args},),\n", ")\n", "print(trace.get_score())\n", "viz_trace(trace, 0)" @@ -176,45 +108,45 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 24, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "8846.404\n", - "11013.862\n", - "11611.759\n", - "12070.877\n", - "10622.367\n", - "11471.874\n", - "8870.875\n", - "9299.528\n", - "5552.7026\n", - "4944.132\n", - "13057.334\n", - "2642.6655\n", - "3540.0493\n", - "3779.468\n", - "5258.7427\n", - "2151.1301\n", - "3045.7324\n", - "2346.7327\n", - "2053.8494\n", - "2083.748\n", - "2666.7578\n", - "2977.49\n", - "2807.3442\n", - "-6.0253487\n", - "-6.0253487\n", - "-6.0253487\n", - "-6.0253487\n", - "-6.0253487\n", - "-6.0253487\n", - "885.59656\n", - "1548.4434\n", - "1639.1842\n" + "8796.027\n", + "11008.357\n", + "11606.063\n", + "12064.656\n", + "10615.998\n", + "11465.843\n", + "8864.728\n", + "9293.64\n", + "5547.0967\n", + "4936.7686\n", + "13050.074\n", + "2636.0881\n", + "3533.2173\n", + "3774.4438\n", + "5252.213\n", + "2145.0554\n", + "3039.5251\n", + "2340.28\n", + "2047.909\n", + "2077.874\n", + "2659.8708\n", + "2971.4863\n", + "2801.2527\n", + "-12.050198\n", + "-12.050198\n", + "-12.050198\n", + "-12.050198\n", + "-12.050198\n", + "-12.050198\n", + "879.7902\n", + "1542.2672\n", + "1633.2189\n" ] } ], @@ -222,13 +154,13 @@ "trace, _ = importance_jit(\n", " jax.random.PRNGKey(2),\n", " choicemap,\n", - " ({\"meshes\": [mesh], \"likelihood_args\": likelihood_args},),\n", + " ({\"num_objects\": Pytree.const(1), \"meshes\": [mesh], \"likelihood_args\": likelihood_args},),\n", ")\n", "print(trace.get_score())\n", "viz_trace(trace, 0)\n", "traces = []\n", "for t in range(0,len(rgbd)):\n", - " trace = b3d.update_choices(trace, jax.random.PRNGKey(0), Pytree.const((\"image\",)),\n", + " trace = b3d.update_choices(trace, jax.random.PRNGKey(0), Pytree.const((\"rgbd\",)),\n", " b3d.utils.resize_image(rgbd[t], renderer.height, renderer.width),\n", " )\n", " trace, key = b3d.bayes3d.enumerative_proposals.gvmf_and_select_best_move(\n", diff --git a/src/b3d/chisight/dense/dense_model.py b/src/b3d/chisight/dense/dense_model.py index 9f9e244d..c77c5c15 100644 --- a/src/b3d/chisight/dense/dense_model.py +++ b/src/b3d/chisight/dense/dense_model.py @@ -5,9 +5,30 @@ import b3d.chisight.dense.likelihoods.image_likelihood from b3d import Mesh, Pose from b3d.modeling_utils import uniform_pose +from genjax import Pytree +import rerun as rr -def make_dense_multiobject_model(renderer, image_likelihood): +def make_dense_multiobject_model(renderer, likelihood_func, sample_func=None): + if sample_func is None: + + def f(key, rendered_rgbd, likelihood_args): + return rendered_rgbd + + sample_func = f + + @Pytree.dataclass + class ImageLikelihood(genjax.ExactDensity): + def sample(self, key, rendered_rgbd, likelihood_args): + return sample_func(key, rendered_rgbd, likelihood_args) + + def logpdf(self, observed_rgbd, rendered_rgbd, likelihood_args): + return likelihood_func(observed_rgbd, rendered_rgbd, likelihood_args)[ + "score" + ] + + image_likelihood = ImageLikelihood() + @genjax.gen def dense_multiobject_model(args_dict): meshes = args_dict["meshes"] @@ -50,4 +71,21 @@ def dense_multiobject_model(args_dict): "rgbd": image, } - return dense_multiobject_model + def viz_trace(trace, t=0): + rr.set_time_sequence("time", t) + intermediate_info = likelihood_func( + trace.get_choices()["rgbd"], + trace.get_retval()["latent_rgbd"], + trace.get_retval()["likelihood_args"], + ) + + rr.log("rgb", rr.Image(trace.get_choices()["rgbd"][..., :3])) + rr.log("rgb/depth/observed", rr.DepthImage(trace.get_choices()["rgbd"][..., 3])) + rr.log( + "rgb/depth/latent", rr.DepthImage(trace.get_retval()["latent_rgbd"][..., 3]) + ) + rr.log("rgb/latent", rr.Image(trace.get_retval()["latent_rgbd"][..., :3])) + # rr.log("rgb/is_match", rr.DepthImage(intermediate_info["is_match"] * 1.0)) + # rr.log("rgb/color_match", rr.DepthImage(intermediate_info["color_match"] * 1.0)) + + return dense_multiobject_model, viz_trace diff --git a/src/b3d/chisight/dense/likelihoods/image_likelihood.py b/src/b3d/chisight/dense/likelihoods/image_likelihood.py index 2717e332..c75037b8 100644 --- a/src/b3d/chisight/dense/likelihoods/image_likelihood.py +++ b/src/b3d/chisight/dense/likelihoods/image_likelihood.py @@ -1,16 +1,2 @@ import genjax from genjax import Pytree - - -def make_image_likelihood(intermediate_func): - @Pytree.dataclass - class ImageLikelihood(genjax.ExactDensity): - def sample(self, key, rendered_rgbd, likelihood_args): - return rendered_rgbd - - def logpdf(self, observed_rgbd, rendered_rgbd, likelihood_args): - results = intermediate_func(observed_rgbd, rendered_rgbd, likelihood_args) - return results["score"] - - image_likelihood = ImageLikelihood() - return image_likelihood From 13b4fc5761f34d09e0ad4d58d8256819d6ffd3de Mon Sep 17 00:00:00 2001 From: Nishad Gothoskar Date: Tue, 23 Jul 2024 20:50:05 +0000 Subject: [PATCH 07/16] save --- notebooks/bayes3d_paper/interactive.ipynb | 206 +++++++++++++++++++--- notebooks/bayes3d_paper/kitti.ipynb | 36 ++++ notebooks/bayes3d_paper/kitti_data.py | 113 +++++++----- 3 files changed, 281 insertions(+), 74 deletions(-) diff --git a/notebooks/bayes3d_paper/interactive.ipynb b/notebooks/bayes3d_paper/interactive.ipynb index f28a33d6..ac7a940e 100644 --- a/notebooks/bayes3d_paper/interactive.ipynb +++ b/notebooks/bayes3d_paper/interactive.ipynb @@ -34,7 +34,14 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 10/10 [00:05<00:00, 1.68it/s]\n" + " 0%| | 0/10 [00:00" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "b3d.viz_rgb(data[\"rgb\"][0])" + ] + }, { "cell_type": "code", "execution_count": 16, diff --git a/notebooks/bayes3d_paper/kitti_data.py b/notebooks/bayes3d_paper/kitti_data.py index 88045ac4..8711655e 100644 --- a/notebooks/bayes3d_paper/kitti_data.py +++ b/notebooks/bayes3d_paper/kitti_data.py @@ -13,7 +13,7 @@ basedir = os.path.join(b3d.get_assets_path(), "kitti") date = "2011_09_26" drive = "0005" -frames = range(0, 153, 5) +frames = range(0, 153, 2) dataset = pykitti.raw(basedir, date, drive, frames=frames) @@ -72,41 +72,7 @@ CORRECT_MASK_INDEX = 0 -mask = jnp.array(masks[0]["segmentation"]) - -xyzs = b3d.xyz_from_depth(depths[0], fx, fy, cx, cy)[mask] -colors = rgbs[0][mask] -colors = colors[xyzs.sum(-1) > 0] -xyzs = xyzs[xyzs.sum(-1) > 0] -m = b3d.segment_point_cloud(xyzs, threshold=0.2) == 0 - -xyzs = xyzs[m] -colors = colors[m] - -resolution = 0.05 -meshes = b3d.mesh.transform_mesh( - jax.vmap(b3d.mesh.Mesh.cube_mesh)( - jnp.ones((xyzs.shape[0], 3)) * resolution * 2.0, colors / 255.0 - ), - b3d.Pose.from_translation(xyzs)[:, None], -) -full_mesh = b3d.mesh.Mesh.squeeze_mesh(meshes) -full_mesh.rr_visualize("mesh") - -pose = b3d.Pose.from_translation(full_mesh.vertices.mean(0)) -full_mesh.vertices = pose.inv().apply(full_mesh.vertices) -full_mesh.rr_visualize("mesh") - -renderer = b3d.RendererOriginal(width, height, fx, fy, cx, cy, 0.01, 100.0) -rgbd = renderer.render_rgbd_from_mesh(full_mesh.transform(pose)) -b3d.rr.log("rerender", b3d.rr.Image(rgbd[..., :3])) - -b3d.rr.log("rerender/depth", b3d.rr.DepthImage(rgbd[..., 3])) - -rgbs = jnp.array(rgbs) -depths = jnp.array(depths) -mask.shape - +masks_jnp = jnp.array([mask["segmentation"] for mask in masks]) kitti_data_path = ( b3d.get_assets_path() @@ -117,18 +83,67 @@ rgb=np.array(rgbs) / 255.0, depths=np.array(depths), camera_intrinsics=np.array([fx, fy, cx, cy, 0.001, 100.0]), - object_position=np.array(pose.pos[None, ...]), - object_quaternion=np.array(pose.quat[None, ...]), - mask=np.array(mask[None, ...]), -) - -kitti_mesh_path = ( - b3d.get_assets_path() - / "shared_data_bucket/foundation_pose_tracking_datasets/kitti_initial_data.obj" + masks=np.array(masks_jnp), ) -full_mesh.save(kitti_mesh_path) - -d = np.load(kitti_data_path) -for i, v in d.items(): - print(i, v.shape) +# xyzs = b3d.xyz_from_depth(depths[0], fx, fy, cx, cy)[mask] +# colors = rgbs[0][mask] +# colors = colors[xyzs.sum(-1) > 0] +# xyzs = xyzs[xyzs.sum(-1) > 0] +# m = b3d.segment_point_cloud(xyzs, threshold=0.2) == 0 + +# xyzs = xyzs[m] +# colors = colors[m] + +# resolution = 0.05 +# meshes = b3d.mesh.transform_mesh( +# jax.vmap(b3d.mesh.Mesh.cube_mesh)( +# jnp.ones((xyzs.shape[0], 3)) * resolution * 2.0, colors / 255.0 +# ), +# b3d.Pose.from_translation(xyzs)[:, None], +# ) +# full_mesh = b3d.mesh.Mesh.squeeze_mesh(meshes) +# full_mesh.rr_visualize("mesh") + +# pose = b3d.Pose.from_translation(full_mesh.vertices.mean(0)) +# full_mesh.vertices = pose.inv().apply(full_mesh.vertices) +# full_mesh.rr_visualize("mesh") + +# renderer = b3d.RendererOriginal(width, height, fx, fy, cx, cy, 0.01, 100.0) +# rgbd = renderer.render_rgbd_from_mesh(full_mesh.transform(pose)) +# b3d.rr.log("rerender", b3d.rr.Image(rgbd[..., :3])) + +# b3d.rr.log("rerender/depth", b3d.rr.DepthImage(rgbd[..., 3])) + +# rgbs = jnp.array(rgbs) +# depths = jnp.array(depths) +# mask.shape + + +# kitti_data_path = ( +# b3d.get_assets_path() +# / "shared_data_bucket/foundation_pose_tracking_datasets/kitti_initial_data.npz" +# ) +# np.savez( +# kitti_data_path, +# rgb=np.array(rgbs) / 255.0, +# depths=np.array(depths), +# camera_intrinsics=np.array([fx, fy, cx, cy, 0.001, 100.0]), +# object_position=np.array(pose.pos[None, ...]), +# object_quaternion=np.array(pose.quat[None, ...]), +# mask=np.array(mask[None, ...]), +# ) + +# kitti_mesh_path = ( +# b3d.get_assets_path() +# / "shared_data_bucket/foundation_pose_tracking_datasets/kitti_initial_data.obj" +# ) +# full_mesh.save(kitti_mesh_path) + +# import numpy as np +# import b3d + +# d = np.load(kitti_data_path) + +# for i, v in d.items(): +# print(i, v.shape) From 67ec5b36f7f81da90056240c1ceff6517ecd9686 Mon Sep 17 00:00:00 2001 From: Nishad Gothoskar Date: Wed, 24 Jul 2024 00:04:00 +0000 Subject: [PATCH 08/16] save --- notebooks/bayes3d_paper/interactive.ipynb | 23 ++---- notebooks/bayes3d_paper/kitti.ipynb | 89 +++++++++++------------ 2 files changed, 51 insertions(+), 61 deletions(-) diff --git a/notebooks/bayes3d_paper/interactive.ipynb b/notebooks/bayes3d_paper/interactive.ipynb index ac7a940e..88386485 100644 --- a/notebooks/bayes3d_paper/interactive.ipynb +++ b/notebooks/bayes3d_paper/interactive.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -27,21 +27,14 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - " 0%| | 0/10 [00:00" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "b3d.viz_rgb(data[\"rgb\"][0])" + "import b3d.chisight.dense.likelihoods.image_likelihood\n", + "import b3d.chisight.dense.likelihoods.simple_likelihood\n", + "import b3d.chisight.dense.dense_model\n", + "intermediate_likelihood_func = b3d.chisight.dense.likelihoods.simple_likelihood.simple_likelihood\n", + "b3d.reload(b3d.chisight.dense.dense_model)\n", + "model, viz_trace = b3d.chisight.dense.dense_model.make_dense_multiobject_model(renderer, intermediate_likelihood_func)\n", + "importance_jit = jax.jit(model.importance)" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 62, "metadata": {}, "outputs": [], "source": [ - "import b3d.chisight.dense.likelihoods.image_likelihood\n", - "import b3d.chisight.dense.likelihoods.simple_likelihood\n", - "intermediate_likelihood_func = b3d.chisight.dense.likelihoods.simple_likelihood.simple_likelihood\n", - "b3d.reload(b3d.chisight.dense.dense_model)\n", - "model, viz_trace = b3d.chisight.dense.dense_model.make_dense_multiobject_model(renderer, intermediate_likelihood_func)\n", - "importance_jit = jax.jit(model.importance)" + "\n", + "xyz = b3d.xyz_from_depth(data[\"depths\"][0], fx, fy, cx, cy)[data[\"masks\"][0]]\n", + "rgb = data[\"rgb\"][0][data[\"masks\"][0]]\n", + "m = xyz[...,2] > 0\n", + "xyz = xyz[m]\n", + "rgb = rgb[m]\n", + "m = b3d.segment_point_cloud(xyz, threshold=0.2) == 0\n", + "xyz = xyz[m]\n", + "rgb = rgb[m]\n", + "dimensions = jnp.ones((len(xyz), 3)) * (xyz[...,2] * 4.0 / fx)[...,None]\n", + "mesh = b3d.mesh.Mesh.voxel_mesh_from_xyz_colors_dimensions(xyz, dimensions, rgb)\n", + "mesh.rr_visualize(\"mesh\")" ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 14, "metadata": {}, "outputs": [ { - "name": "stdout", - "output_type": "stream", - "text": [ - "8796.027\n" + "ename": "KeyError", + "evalue": "'object_position is not a file in the archive'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[14], line 4\u001b[0m\n\u001b[1;32m 1\u001b[0m choicemap \u001b[38;5;241m=\u001b[39m genjax\u001b[38;5;241m.\u001b[39mChoiceMap\u001b[38;5;241m.\u001b[39md(\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28mdict\u001b[39m(\n\u001b[1;32m 3\u001b[0m [\n\u001b[0;32m----> 4\u001b[0m (\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mobject_pose_0\u001b[39m\u001b[38;5;124m\"\u001b[39m, Pose(\u001b[43mdata\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mobject_position\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m[\u001b[38;5;241m0\u001b[39m], data[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mobject_quaternion\u001b[39m\u001b[38;5;124m\"\u001b[39m][\u001b[38;5;241m0\u001b[39m])),\n\u001b[1;32m 5\u001b[0m (\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcamera_pose\u001b[39m\u001b[38;5;124m\"\u001b[39m, Pose\u001b[38;5;241m.\u001b[39midentity()),\n\u001b[1;32m 6\u001b[0m (\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrgbd\u001b[39m\u001b[38;5;124m\"\u001b[39m, \n\u001b[1;32m 7\u001b[0m b3d\u001b[38;5;241m.\u001b[39mutils\u001b[38;5;241m.\u001b[39mresize_image(\n\u001b[1;32m 8\u001b[0m rgbd[\u001b[38;5;241m0\u001b[39m], renderer\u001b[38;5;241m.\u001b[39mheight, renderer\u001b[38;5;241m.\u001b[39mwidth\n\u001b[1;32m 9\u001b[0m )\n\u001b[1;32m 10\u001b[0m )\n\u001b[1;32m 11\u001b[0m ]\n\u001b[1;32m 12\u001b[0m )\n\u001b[1;32m 13\u001b[0m )\n\u001b[1;32m 16\u001b[0m likelihood_args\u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m 17\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124minlier_score\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;241m20.0\u001b[39m,\n\u001b[1;32m 18\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcolor_tolerance\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;241m20.0\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 26\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfar\u001b[39m\u001b[38;5;124m\"\u001b[39m: renderer\u001b[38;5;241m.\u001b[39mfar,\n\u001b[1;32m 27\u001b[0m }\n\u001b[1;32m 29\u001b[0m trace, _ \u001b[38;5;241m=\u001b[39m importance_jit(\n\u001b[1;32m 30\u001b[0m jax\u001b[38;5;241m.\u001b[39mrandom\u001b[38;5;241m.\u001b[39mPRNGKey(\u001b[38;5;241m2\u001b[39m),\n\u001b[1;32m 31\u001b[0m choicemap,\n\u001b[1;32m 32\u001b[0m ({\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mnum_objects\u001b[39m\u001b[38;5;124m\"\u001b[39m: Pytree\u001b[38;5;241m.\u001b[39mconst(\u001b[38;5;241m1\u001b[39m), \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmeshes\u001b[39m\u001b[38;5;124m\"\u001b[39m: [mesh], \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlikelihood_args\u001b[39m\u001b[38;5;124m\"\u001b[39m: likelihood_args},),\n\u001b[1;32m 33\u001b[0m )\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/numpy/lib/npyio.py:263\u001b[0m, in \u001b[0;36mNpzFile.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 261\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mzip\u001b[38;5;241m.\u001b[39mread(key)\n\u001b[1;32m 262\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 263\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mkey\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m is not a file in the archive\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "\u001b[0;31mKeyError\u001b[0m: 'object_position is not a file in the archive'" ] } ], From 3e8e35b70d116a48f9c7604373b8d872a0a6acce Mon Sep 17 00:00:00 2001 From: Nishad Gothoskar Date: Wed, 24 Jul 2024 15:52:36 +0000 Subject: [PATCH 09/16] stop removing the background --- notebooks/aug1demos/slam_color_room.ipynb | 94 ++++++++ notebooks/bayes3d_paper/interactive.ipynb | 256 ++++++++++++++-------- src/b3d/chisight/dense/dense_model.py | 56 ++++- src/b3d/utils.py | 5 + 4 files changed, 321 insertions(+), 90 deletions(-) create mode 100644 notebooks/aug1demos/slam_color_room.ipynb diff --git a/notebooks/aug1demos/slam_color_room.ipynb b/notebooks/aug1demos/slam_color_room.ipynb new file mode 100644 index 00000000..fb3f9e71 --- /dev/null +++ b/notebooks/aug1demos/slam_color_room.ipynb @@ -0,0 +1,94 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import b3d\n", + "import jax.numpy as jnp\n", + "import os\n", + "from b3d import Mesh, Pose\n", + "import jax\n", + "import genjax\n", + "from genjax import Pytree\n", + "import rerun as rr\n", + "from b3d.modeling_utils import uniform_discrete, uniform_pose, gaussian_vmf\n", + "import matplotlib.pyplot as plt\n", + "from functools import partial\n", + "import importlib\n", + "from ipywidgets import interact\n", + "import ipywidgets as widgets\n", + "\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "b3d.rr_init(\"slam\")" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "ename": "TypeError", + "evalue": "unsupported operand type(s) for *: 'int' and 'NoneType'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[7], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m obj \u001b[38;5;241m=\u001b[39m \u001b[43mMesh\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_obj\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43midentical_rooms_single_mesh.obj\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 2\u001b[0m obj\u001b[38;5;241m.\u001b[39mrr_visualize(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmesh\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "File \u001b[0;32m~/b3d/src/b3d/mesh.py:110\u001b[0m, in \u001b[0;36mMesh.from_obj_file\u001b[0;34m(path)\u001b[0m\n\u001b[1;32m 107\u001b[0m \u001b[38;5;129m@staticmethod\u001b[39m\n\u001b[1;32m 108\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mfrom_obj_file\u001b[39m(path):\n\u001b[1;32m 109\u001b[0m trimesh_mesh \u001b[38;5;241m=\u001b[39m trimesh\u001b[38;5;241m.\u001b[39mload_mesh(path, process\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m, validate\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[0;32m--> 110\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mMesh\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfrom_trimesh\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtrimesh_mesh\u001b[49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m~/b3d/src/b3d/mesh.py:120\u001b[0m, in \u001b[0;36mMesh.from_trimesh\u001b[0;34m(trimesh_mesh)\u001b[0m\n\u001b[1;32m 117\u001b[0m faces \u001b[38;5;241m=\u001b[39m jnp\u001b[38;5;241m.\u001b[39marray(trimesh_mesh\u001b[38;5;241m.\u001b[39mfaces)\n\u001b[1;32m 118\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(trimesh_mesh\u001b[38;5;241m.\u001b[39mvisual, trimesh\u001b[38;5;241m.\u001b[39mvisual\u001b[38;5;241m.\u001b[39mcolor\u001b[38;5;241m.\u001b[39mColorVisuals):\n\u001b[1;32m 119\u001b[0m vertex_colors \u001b[38;5;241m=\u001b[39m (\n\u001b[0;32m--> 120\u001b[0m jnp\u001b[38;5;241m.\u001b[39marray(\u001b[43mtrimesh_mesh\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvisual\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mto_color\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvertex_colors\u001b[49m)[\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m, :\u001b[38;5;241m3\u001b[39m] \u001b[38;5;241m/\u001b[39m \u001b[38;5;241m255.0\u001b[39m\n\u001b[1;32m 121\u001b[0m )\n\u001b[1;32m 122\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 123\u001b[0m vertex_colors \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m 124\u001b[0m jnp\u001b[38;5;241m.\u001b[39marray(trimesh_mesh\u001b[38;5;241m.\u001b[39mvisual\u001b[38;5;241m.\u001b[39mvertex_colors)[\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;241m.\u001b[39m, :\u001b[38;5;241m3\u001b[39m] \u001b[38;5;241m/\u001b[39m \u001b[38;5;241m255.0\u001b[39m\n\u001b[1;32m 125\u001b[0m )\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/trimesh/visual/color.py:205\u001b[0m, in \u001b[0;36mColorVisuals.vertex_colors\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 196\u001b[0m \u001b[38;5;129m@property\u001b[39m\n\u001b[1;32m 197\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mvertex_colors\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m 198\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 199\u001b[0m \u001b[38;5;124;03m Return the colors for each vertex of a mesh\u001b[39;00m\n\u001b[1;32m 200\u001b[0m \n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 203\u001b[0m \u001b[38;5;124;03m colors: (len(mesh.vertices), 4) uint8, color for each vertex\u001b[39;00m\n\u001b[1;32m 204\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 205\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_colors\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mvertex\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/trimesh/visual/color.py:315\u001b[0m, in \u001b[0;36mColorVisuals._get_colors\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m 310\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 311\u001b[0m \u001b[38;5;66;03m# colors have never been accessed\u001b[39;00m\n\u001b[1;32m 312\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkind \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 313\u001b[0m \u001b[38;5;66;03m# no colors are defined, so create a (count, 4) tiled\u001b[39;00m\n\u001b[1;32m 314\u001b[0m \u001b[38;5;66;03m# copy of the default color\u001b[39;00m\n\u001b[0;32m--> 315\u001b[0m colors \u001b[38;5;241m=\u001b[39m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtile\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdefaults\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mmaterial_diffuse\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m(\u001b[49m\u001b[43mcount\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 316\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkind \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvertex\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mand\u001b[39;00m name \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mface\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m 317\u001b[0m colors \u001b[38;5;241m=\u001b[39m vertex_to_face_color(\n\u001b[1;32m 318\u001b[0m vertex_colors\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mvertex_colors, faces\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmesh\u001b[38;5;241m.\u001b[39mfaces\n\u001b[1;32m 319\u001b[0m )\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/numpy/lib/shape_base.py:1267\u001b[0m, in \u001b[0;36mtile\u001b[0;34m(A, reps)\u001b[0m\n\u001b[1;32m 1265\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (d \u001b[38;5;241m<\u001b[39m c\u001b[38;5;241m.\u001b[39mndim):\n\u001b[1;32m 1266\u001b[0m tup \u001b[38;5;241m=\u001b[39m (\u001b[38;5;241m1\u001b[39m,)\u001b[38;5;241m*\u001b[39m(c\u001b[38;5;241m.\u001b[39mndim\u001b[38;5;241m-\u001b[39md) \u001b[38;5;241m+\u001b[39m tup\n\u001b[0;32m-> 1267\u001b[0m shape_out \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mtuple\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mt\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43ms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mt\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mzip\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mc\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mshape\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtup\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1268\u001b[0m n \u001b[38;5;241m=\u001b[39m c\u001b[38;5;241m.\u001b[39msize\n\u001b[1;32m 1269\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m n \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n", + "File \u001b[0;32m/opt/conda/envs/b3d/lib/python3.12/site-packages/numpy/lib/shape_base.py:1267\u001b[0m, in \u001b[0;36m\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m 1265\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (d \u001b[38;5;241m<\u001b[39m c\u001b[38;5;241m.\u001b[39mndim):\n\u001b[1;32m 1266\u001b[0m tup \u001b[38;5;241m=\u001b[39m (\u001b[38;5;241m1\u001b[39m,)\u001b[38;5;241m*\u001b[39m(c\u001b[38;5;241m.\u001b[39mndim\u001b[38;5;241m-\u001b[39md) \u001b[38;5;241m+\u001b[39m tup\n\u001b[0;32m-> 1267\u001b[0m shape_out \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mtuple\u001b[39m(\u001b[43ms\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mt\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m s, t \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(c\u001b[38;5;241m.\u001b[39mshape, tup))\n\u001b[1;32m 1268\u001b[0m n \u001b[38;5;241m=\u001b[39m c\u001b[38;5;241m.\u001b[39msize\n\u001b[1;32m 1269\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m n \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n", + "\u001b[0;31mTypeError\u001b[0m: unsupported operand type(s) for *: 'int' and 'NoneType'" + ] + } + ], + "source": [ + "obj = Mesh.from_obj(\"identical_rooms_single_mesh.obj\")\n", + "obj.rr_visualize(\"mesh\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "b3d", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.4" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/notebooks/bayes3d_paper/interactive.ipynb b/notebooks/bayes3d_paper/interactive.ipynb index 88386485..0f90d195 100644 --- a/notebooks/bayes3d_paper/interactive.ipynb +++ b/notebooks/bayes3d_paper/interactive.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -27,14 +27,14 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 154, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 10/10 [00:06<00:00, 1.61it/s]\n" + "100%|██████████| 10/10 [00:03<00:00, 2.85it/s]\n" ] } ], @@ -53,7 +53,7 @@ "\n", "height, width = all_data[0][\"rgbd\"].shape[:2]\n", "fx,fy,cx,cy = all_data[0][\"camera_intrinsics\"]\n", - "scaling_factor = 0.1\n", + "scaling_factor = 0.2\n", "renderer = b3d.renderer.renderer_original.RendererOriginal(\n", " width * scaling_factor, height * scaling_factor, fx * scaling_factor, fy * scaling_factor, cx * scaling_factor, cy * scaling_factor, 0.01, 2.0\n", ")\n", @@ -69,7 +69,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 158, "metadata": {}, "outputs": [], "source": [ @@ -78,11 +78,19 @@ "convert_rgbd_to_color_space = lambda x: b3d.colors.rgbd_to_labd(x)\n", "convert_color_space_to_rgbd = lambda x: b3d.colors.labd_to_rgbd(x)\n", "\n", + "\n", + "# lower_bound = jnp.array([0.0, -0.0, -0.0, 0.0])\n", + "# upper_bound = jnp.array([1.0, 1.0, 1.0, 10.0])\n", + "# convert_rgbd_to_color_space = lambda x: x\n", + "# convert_color_space_to_rgbd = lambda x: x\n", + "\n", "# def sample_likelihood_func()\n", "\n", - "def intermediate_likelihood_func(observed_rgbd, rendered_rgbd, likelihood_args):\n", + "def intermediate_likelihood_func(observed_rgbd, latent_rgbd, likelihood_args):\n", " k = likelihood_args[\"k\"].const\n", " outlier_probability = likelihood_args[\"outlier_probability\"]\n", + " fx = likelihood_args[\"fx\"]\n", + " fy = likelihood_args[\"fy\"]\n", " lightness_variance = likelihood_args[\"lightness_variance\"]\n", " color_variance = likelihood_args[\"color_variance\"]\n", " depth_variance = likelihood_args[\"depth_variance\"]\n", @@ -98,15 +106,16 @@ " jnp.ones((k, image_width))\n", " )\n", "\n", - " no_mesh_surface = (rendered_rgbd[..., 3] == 0)[row_coordinates, column_coordinates]\n", + " no_mesh_surface = (latent_rgbd[..., 3] == 0)[row_coordinates, column_coordinates]\n", " outlier_probability_adjusted = outlier_probability * (1 - no_mesh_surface) + no_mesh_surface * 1.0\n", - " \n", + " outlier_probability_adjusted = outlier_probability * jnp.ones_like(no_mesh_surface)\n", + "\n", " observed_color_space_d = convert_rgbd_to_color_space(observed_rgbd)\n", - " rendered_color_space_d = convert_rgbd_to_color_space(rendered_rgbd)\n", + " latent_color_space_d = convert_rgbd_to_color_space(latent_rgbd)\n", "\n", " subset_observed = observed_color_space_d[row_coordinates, column_coordinates]\n", " subset_observed_rescaled = (subset_observed - lower_bound) / (upper_bound - lower_bound)\n", - " rendered_values_rescaled = (rendered_color_space_d[row_coordinates, column_coordinates] - lower_bound) / (upper_bound - lower_bound)\n", + " rendered_values_rescaled = (latent_color_space_d[row_coordinates, column_coordinates] - lower_bound) / (upper_bound - lower_bound)\n", "\n", " inlier_variances = jnp.array([lightness_variance, color_variance, color_variance, depth_variance])\n", " outlier_variances = jnp.array([1000000.0, 1000000.0, 1000000.0, 1000000.0])\n", @@ -120,41 +129,74 @@ " 0.0, 1.0\n", " )\n", "\n", - " scores_inlier_merged = jax.nn.logsumexp(scores_inlier[..., :3] + jnp.log(1/3), axis=-1) + scores_inlier[..., 3] + jnp.log(1.0 - outlier_probability_adjusted) \n", - " scores_outlier_merged = jax.nn.logsumexp(scores_outlier[..., :3] + jnp.log(1/3), axis=-1) + scores_outlier[..., 3] + jnp.log(outlier_probability_adjusted)\n", + " # scores_inlier_merged = jax.nn.logsumexp(scores_inlier[..., :3] + jnp.log(1/3), axis=-1) + scores_inlier[..., 3] + jnp.log(1.0 - outlier_probability_adjusted) \n", + " # scores_outlier_merged = jax.nn.logsumexp(scores_outlier[..., :3] + jnp.log(1/3), axis=-1) + scores_outlier[..., 3] + jnp.log(outlier_probability_adjusted)\n", + "\n", + " scores_inlier_merged = scores_inlier[...,:].sum(-1) + jnp.log(1.0 - outlier_probability_adjusted) \n", + " scores_outlier_merged = scores_outlier[...,:].sum(-1) + jnp.log(outlier_probability_adjusted)\n", + "\n", + " latent_depth = latent_rgbd[..., 3]\n", + " latent_areas = (latent_depth / fx) * (latent_depth / fy)\n", + "\n", + " pixelwise_score = jnp.logaddexp(scores_inlier_merged, scores_outlier_merged) \n", + " pixelwise_score_full = jnp.zeros((image_height, image_width))\n", + " pixelwise_score_full = pixelwise_score_full.at[row_coordinates, column_coordinates].set(pixelwise_score)\n", + "\n", " return {\n", - " \"score\": jnp.logaddexp(scores_inlier_merged, scores_outlier_merged).sum()\n", - " }" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ + " \"score\": pixelwise_score.sum(),\n", + " \"observed_color_space_d\": observed_color_space_d,\n", + " \"latent_color_space_d\": latent_color_space_d,\n", + " \"pixelwise_score\": pixelwise_score_full,\n", + " }\n", + "\n", "import b3d.chisight.dense.dense_model\n", - "model, viz_trace = b3d.chisight.dense.dense_model.make_dense_multiobject_model(renderer, intermediate_likelihood_func)\n", - "importance_jit = jax.jit(model.importance)" + "b3d.reload(b3d.chisight.dense.dense_model)\n", + "model, viz_trace, info_from_trace = b3d.chisight.dense.dense_model.make_dense_multiobject_model(\n", + " renderer, intermediate_likelihood_func\n", + ")\n", + "importance_jit = jax.jit(model.importance)\n", + "\n", + "\n", + "grid3 = b3d.multivmap(b3d.update_choices_get_score, (False, False, False, True, True, True))\n", + "grid4 = b3d.multivmap(b3d.update_choices_get_score, (False, False, False, True, True, True, True))" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 203, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0.1464138 0.5 0.05428571 0.12285715]\n", + "35190.03\n" + ] + } + ], "source": [ + "outlier_probability_sweep = jnp.linspace(0.01, 0.999, 30)\n", + "lightness_variance_sweep = jnp.linspace(0.02, 0.5, 20)\n", + "color_variance_sweep = jnp.linspace(0.02, 0.5, 15)\n", + "depth_variance_sweep = jnp.linspace(0.02, 0.5, 15)\n", + "arguments = Pytree.const((\"outlier_probability\", \"lightness_variance\", \"color_variance\", \"depth_variance\",))\n", + "sweeps = [outlier_probability_sweep, lightness_variance_sweep, color_variance_sweep, depth_variance_sweep]\n", + "\n", + "IDX = 2\n", "key = jax.random.split(key, 2)[-1]\n", "likelikood_args = {\n", - " \"fx\": fx,\n", - " \"fy\": fy,\n", - " \"k\": Pytree.const(20000),\n", + " \"fx\": renderer.fx,\n", + " \"fy\": renderer.fy,\n", + " \"cx\": renderer.cx,\n", + " \"cy\": renderer.cy,\n", + " \"k\": Pytree.const(10000),\n", "}\n", "\n", "choicemap = genjax.ChoiceMap.d(\n", " {\n", - " # \"rgbd\": observed_rgbd_scaled_down,\n", - " \"rgbd\": rendered_rgbds[0],\n", + " \"rgbd\": observed_rgbd_scaled_down,\n", + " # \"rgbd\": rendered_rgbds[0],\n", " \"object_pose_0\": all_data[0][\"object_poses\"][IDX],\n", " \"camera_pose\": all_data[0][\"camera_pose\"]\n", " }\n", @@ -165,103 +207,145 @@ " choicemap,\n", " ({\"num_objects\": Pytree.const(1), \"meshes\": [meshes[IDX]], \"likelihood_args\": likelikood_args},)\n", ")[0]\n", - "viz_trace(trace)\n", "\n", - "outlier_probability_sweep = jnp.linspace(0.001, 0.999, 30)\n", - "lightness_variance_sweep = jnp.linspace(0.001, 1.0, 20)\n", - "color_variance_sweep = jnp.linspace(0.001, 1.0, 15)\n", - "depth_variance_sweep = jnp.linspace(0.001, 1.0, 15)\n", - "arguments = Pytree.const((\"outlier_probability\", \"lightness_variance\", \"color_variance\", \"depth_variance\",))\n", - "sweeps = [outlier_probability_sweep, lightness_variance_sweep, color_variance_sweep, depth_variance_sweep]\n", + "scores = grid4(\n", + " trace, key,\n", + " arguments,\n", + " *sweeps\n", + ")\n", + "sampled_indices = jax.vmap(\n", + " jnp.unravel_index,\n", + " in_axes=(0,None)\n", + ")(jax.random.categorical(key, scores.reshape(-1),shape=(1000,)), scores.shape)\n", + "sampled_parameters = jnp.vstack([\n", + " sweep[indices]\n", + " for indices, sweep in zip(sampled_indices, sweeps)\n", + "]).T\n", "\n", - "grid3 = b3d.multivmap(b3d.update_choices_get_score, (False, False, False, True, True, True))\n", - "grid4 = b3d.multivmap(b3d.update_choices_get_score, (False, False, False, True, True, True, True))" + "print(sampled_parameters[0])\n", + "trace = b3d.update_choices(trace, key,\n", + " arguments,\n", + " 0.05, 1.0, 0.02, 0.01\n", + " # *sampled_parameters[0]\n", + ")\n", + "print(trace.get_score())\n", + "viz_trace(trace)\n", + "info_from_trace(trace)[\"score\"]" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 202, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "(100, 4)\n" + "[5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602\n", + " 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602\n", + " 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602\n", + " 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602\n", + " 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602\n", + " 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602\n", + " 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602\n", + " 5602 5602]\n", + "-19493.59\n" ] }, { "data": { "text/plain": [ - "Array([[0.03541379, 0.001 , 0.001 , 0.001 ],\n", - " [0.03541379, 0.001 , 0.001 , 0.001 ],\n", - " [0.03541379, 0.001 , 0.001 , 0.001 ],\n", - " [0.03541379, 0.001 , 0.001 , 0.001 ],\n", - " [0.03541379, 0.001 , 0.001 , 0.001 ],\n", - " [0.03541379, 0.001 , 0.001 , 0.001 ],\n", - " [0.03541379, 0.001 , 0.001 , 0.001 ],\n", - " [0.03541379, 0.001 , 0.001 , 0.001 ],\n", - " [0.03541379, 0.001 , 0.001 , 0.001 ],\n", - " [0.03541379, 0.001 , 0.001 , 0.001 ]], dtype=float32)" + "Array(-19764.145, dtype=float32)" ] }, - "execution_count": 6, + "execution_count": 202, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "scores = grid4(\n", - " trace, key,\n", - " arguments,\n", - " *sweeps\n", + "key = jax.random.split(key, 2)[-1]\n", + "N = 1000\n", + "B = 20\n", + "keys = jax.random.split(key, N*B)\n", + "\n", + "sampled_poses = Pose.sample_gaussian_vmf_pose_vmap(\n", + " keys, trace.get_choices()[\"object_pose_0\"], 0.1, 800.0\n", ")\n", - "sampled_indices = jax.vmap(\n", - " jnp.unravel_index,\n", - " in_axes=(0,None)\n", - ")(jax.random.categorical(key, scores.reshape(-1),shape=(100,)), scores.shape)\n", - "sampled_parameters = jnp.vstack([\n", - " sweep[indices]\n", - " for indices, sweep in zip(sampled_indices, sweeps)\n", - "]).T\n", - "print(sampled_parameters.shape)\n", - "sampled_parameters[:10]" + "\n", + "scores = jnp.concatenate([\n", + " b3d.enumerate_choices_get_scores(\n", + " trace,key, Pytree.const((\"object_pose_0\",)),\n", + " sampled_poses[k]\n", + " )\n", + " for k in jnp.split(jnp.arange(len(sampled_poses)), B)\n", + "])\n", + "\n", + "sampled_indices = jax.random.categorical(key, scores * 1.0 , shape=(100,))\n", + "print(sampled_indices)\n", + "new_trace = b3d.update_choices(trace, key, Pytree.const((\"object_pose_0\",)),\n", + " sampled_poses[sampled_indices[0]])\n", + "viz_trace(new_trace)\n", + "print(new_trace.get_score())\n", + "info_from_trace(new_trace)[\"score\"]" ] }, { "cell_type": "code", - "execution_count": 76, + "execution_count": 142, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(100, 4)\n" - ] - }, { "data": { "text/plain": [ - "Array([[0.79251724, 0.5267895 , 1. , 0.07235715],\n", - " [0.82693106, 0.001 , 1. , 0.07235715],\n", - " [0.82693106, 0.26389474, 1. , 0.07235715],\n", - " [0.82693106, 1. , 1. , 0.07235715],\n", - " [0.82693106, 1. , 1. , 0.07235715],\n", - " [0.82693106, 0.6845263 , 1. , 0.07235715],\n", - " [0.82693106, 0.001 , 1. , 0.07235715],\n", - " [0.79251724, 0.2113158 , 1. , 0.07235715],\n", - " [0.82693106, 0.8948421 , 1. , 0.07235715],\n", - " [0.82693106, 0.42163157, 1. , 0.07235715]], dtype=float32)" + "Array(0., dtype=float32)" ] }, - "execution_count": 76, + "execution_count": 142, "metadata": {}, "output_type": "execute_result" } ], "source": [] }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "XorChm(\n", + " c1=XorChm(\n", + " c1=XorChm(\n", + " c1=XorChm(c1=XorChm(c1=XorChm(c1=StaticChm(addr='outlier_probability', c=ValueChm(v=)), c2=StaticChm(addr='lightness_variance', c=ValueChm(v=))), c2=StaticChm(addr='color_variance', c=ValueChm(v=))), c2=StaticChm(addr='depth_variance', c=ValueChm(v=))),\n", + " c2=StaticChm(addr='object_pose_0', c=ValueChm(v=Pose(position=Array([-0.08521235, 0.00545534, 0.07130677], dtype=float32), quaternion=Array([ 0.6857101 , -0.02822381, 0.72732246, 0.00267684], dtype=float32)))),\n", + " ),\n", + " c2=StaticChm(\n", + " addr='camera_pose',\n", + " c=ValueChm(v=Pose(position=Array([-0.633828 , -0.20314899, 0.58637404], dtype=float32), quaternion=Array([ 0.72074157, -0.5602933 , 0.20024239, -0.3556768 ], dtype=float32))),\n", + " ),\n", + " ),\n", + " c2=StaticChm(\n", + " addr='rgbd',\n", + " c=ValueChm(\n", + " v=,\n", + " ),\n", + " ),\n", + ")" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "new_trace.get_choices()" + ] + }, { "cell_type": "code", "execution_count": 79, diff --git a/src/b3d/chisight/dense/dense_model.py b/src/b3d/chisight/dense/dense_model.py index c77c5c15..4a92e006 100644 --- a/src/b3d/chisight/dense/dense_model.py +++ b/src/b3d/chisight/dense/dense_model.py @@ -7,6 +7,7 @@ from b3d.modeling_utils import uniform_pose from genjax import Pytree import rerun as rr +import jax def make_dense_multiobject_model(renderer, likelihood_func, sample_func=None): @@ -39,11 +40,13 @@ def dense_multiobject_model(args_dict): lightness_variance = genjax.uniform(0.0001, 1.0) @ "lightness_variance" color_variance = genjax.uniform(0.0001, 1.0) @ "color_variance" depth_variance = genjax.uniform(0.0001, 1.0) @ "depth_variance" + blur = genjax.uniform(0.0001, 1.0) @ "blur" likelihood_args["outlier_probability"] = outlier_probability likelihood_args["lightness_variance"] = lightness_variance likelihood_args["color_variance"] = color_variance likelihood_args["depth_variance"] = depth_variance + likelihood_args["blur"] = blur all_poses = [] for i in range(num_objects.const): @@ -71,21 +74,66 @@ def dense_multiobject_model(args_dict): "rgbd": image, } - def viz_trace(trace, t=0): - rr.set_time_sequence("time", t) - intermediate_info = likelihood_func( + @jax.jit + def info_from_trace(trace): + return likelihood_func( trace.get_choices()["rgbd"], trace.get_retval()["latent_rgbd"], trace.get_retval()["likelihood_args"], ) + def viz_trace(trace, t=0): + rr.set_time_sequence("time", t) + likelihood_args = trace.get_retval()["likelihood_args"] + fx, fy, cx, cy = ( + likelihood_args["fx"], + likelihood_args["fy"], + likelihood_args["cx"], + likelihood_args["cy"], + ) + + info = info_from_trace(trace) rr.log("rgb", rr.Image(trace.get_choices()["rgbd"][..., :3])) rr.log("rgb/depth/observed", rr.DepthImage(trace.get_choices()["rgbd"][..., 3])) rr.log( "rgb/depth/latent", rr.DepthImage(trace.get_retval()["latent_rgbd"][..., 3]) ) rr.log("rgb/latent", rr.Image(trace.get_retval()["latent_rgbd"][..., :3])) + + rr.log( + "rgb/color_space/observed_color_space_d", + rr.Image(info["observed_color_space_d"][..., :3]), + ) + rr.log( + "rgb/color_space/latent_color_space_d", + rr.Image(info["latent_color_space_d"][..., :3]), + ) + rr.log( + "rgb/pixelwise_score", + rr.DepthImage(info["pixelwise_score"]), + ) + + b3d.rr_log_cloud( + "latent", + b3d.xyz_from_depth( + trace.get_retval()["latent_rgbd"][..., 3], + fx, + fy, + cx, + cy, + ), + ) + b3d.rr_log_cloud( + "observed", + b3d.xyz_from_depth( + trace.get_retval()["rgbd"][..., 3], + fx, + fy, + cx, + cy, + ), + ) # rr.log("rgb/is_match", rr.DepthImage(intermediate_info["is_match"] * 1.0)) # rr.log("rgb/color_match", rr.DepthImage(intermediate_info["color_match"] * 1.0)) - return dense_multiobject_model, viz_trace + return dense_multiobject_model, viz_trace, info_from_trace diff --git a/src/b3d/utils.py b/src/b3d/utils.py index 2503f332..27817ee7 100644 --- a/src/b3d/utils.py +++ b/src/b3d/utils.py @@ -85,6 +85,11 @@ def keysplit(key, *ns): return keys +@jax.jit +def split_key(key): + return jax.random.split(key, 2)[-1] + + # # # # # # # # # # # # # # Other From 04f75e509165d490752ec23dc86e2aef1bca6f43 Mon Sep 17 00:00:00 2001 From: Nishad Gothoskar Date: Wed, 24 Jul 2024 18:31:49 +0000 Subject: [PATCH 10/16] save before color exploration --- notebooks/aug1demos/slam_color_room.ipynb | 47 ++++- notebooks/bayes3d_paper/interactive.ipynb | 223 ++++++++++++++-------- src/b3d/chisight/dense/dense_model.py | 37 ++-- 3 files changed, 211 insertions(+), 96 deletions(-) diff --git a/notebooks/aug1demos/slam_color_room.ipynb b/notebooks/aug1demos/slam_color_room.ipynb index fb3f9e71..c8c0b96e 100644 --- a/notebooks/aug1demos/slam_color_room.ipynb +++ b/notebooks/aug1demos/slam_color_room.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -25,6 +25,51 @@ "import numpy as np" ] }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "b3d.rr_init(\"slma\")" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "room_h = 1.0\n", + "room_w = 0.8\n", + "\n", + "\n", + "def plane_mesh_from_plane_and_dimensions(pose, w, h, color):\n", + " vertices = jnp.array(\n", + " [\n", + " [-w / 2, -h / 2, 0],\n", + " [-w / 2, h / 2, 0],\n", + " [w / 2, h / 2, 0],\n", + " [w / 2, -h / 2, 0],\n", + " ]\n", + " )\n", + " vertices = pose.apply(vertices)\n", + " faces = jnp.array(\n", + " [\n", + " [0, 1, 3],\n", + " [3, 1, 2],\n", + " ]\n", + " )\n", + " vertex_attributes = jnp.ones((len(vertices), 3)) * color\n", + " return Mesh(vertices, faces, vertex_attributes)\n", + "\n", + "\n", + "m = plane_mesh_from_plane_and_dimensions(\n", + " Pose.identity(), room_w, room_h, jnp.array([1.0, 0.0, 0.0])\n", + ")\n", + "m.rr_visualize(\"mesh\")" + ] + }, { "cell_type": "code", "execution_count": 4, diff --git a/notebooks/bayes3d_paper/interactive.ipynb b/notebooks/bayes3d_paper/interactive.ipynb index 0f90d195..1271e64c 100644 --- a/notebooks/bayes3d_paper/interactive.ipynb +++ b/notebooks/bayes3d_paper/interactive.ipynb @@ -27,14 +27,14 @@ }, { "cell_type": "code", - "execution_count": 154, + "execution_count": 501, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 10/10 [00:03<00:00, 2.85it/s]\n" + "100%|██████████| 10/10 [00:03<00:00, 3.01it/s]\n" ] } ], @@ -69,12 +69,12 @@ }, { "cell_type": "code", - "execution_count": 158, + "execution_count": 488, "metadata": {}, "outputs": [], "source": [ "lower_bound = jnp.array([0.0, -128.0, -128.0, 0.0])\n", - "upper_bound = jnp.array([100.0, 128.0, 128.0, 10.0])\n", + "upper_bound = jnp.array([100.0, 128.0, 128.0, 3.0])\n", "convert_rgbd_to_color_space = lambda x: b3d.colors.rgbd_to_labd(x)\n", "convert_color_space_to_rgbd = lambda x: b3d.colors.labd_to_rgbd(x)\n", "\n", @@ -88,39 +88,53 @@ "\n", "def intermediate_likelihood_func(observed_rgbd, latent_rgbd, likelihood_args):\n", " k = likelihood_args[\"k\"].const\n", - " outlier_probability = likelihood_args[\"outlier_probability\"]\n", " fx = likelihood_args[\"fx\"]\n", " fy = likelihood_args[\"fy\"]\n", - " lightness_variance = likelihood_args[\"lightness_variance\"]\n", - " color_variance = likelihood_args[\"color_variance\"]\n", - " depth_variance = likelihood_args[\"depth_variance\"]\n", + " \n", + " outlier_probability_background = likelihood_args[f\"outlier_probability_background\"]\n", + " lightness_variance_background = likelihood_args[f\"lightness_variance_background\"]\n", + " color_variance_background = likelihood_args[f\"color_variance_background\"]\n", + " depth_variance_background = likelihood_args[f\"depth_variance_background\"]\n", + "\n", + " outlier_probability_0 = likelihood_args[f\"outlier_probability_0\"]\n", + " lightness_variance_0 = likelihood_args[f\"lightness_variance_0\"]\n", + " color_variance_0 = likelihood_args[f\"color_variance_0\"]\n", + " depth_variance_0 = likelihood_args[f\"depth_variance_0\"]\n", + "\n", + "\n", + " inlier_variances_background = jnp.array([lightness_variance_background, color_variance_background, color_variance_background, depth_variance_background])\n", + " inlier_variances_0 = jnp.array([lightness_variance_0, color_variance_0, color_variance_0, depth_variance_0])\n", + " outlier_variances = jnp.array([1000000.0, 1000000.0, 1000000.0, 1000000.0])\n", + "\n", + " all_inlier_variances = jnp.stack([inlier_variances_background, inlier_variances_0])\n", + " all_outlier_probabilities = jnp.array([outlier_probability_background, outlier_probability_0])\n", "\n", " image_height, image_width = observed_rgbd.shape[:2]\n", "\n", - " row_coordinates = jax.vmap(genjax.categorical.sample,in_axes=(0, 0,))(\n", - " jax.random.split(key, k),\n", - " jnp.ones((k, image_height))\n", - " )\n", - " column_coordinates = jax.vmap(genjax.categorical.sample, in_axes=(0, 0,))(\n", - " jax.random.split(key, k),\n", - " jnp.ones((k, image_width))\n", - " )\n", + " # row_coordinates = jax.vmap(genjax.categorical.sample,in_axes=(0, 0,))(\n", + " # jax.random.split(key, k),\n", + " # jnp.ones((k, image_height))\n", + " # )\n", + " # column_coordinates = jax.vmap(genjax.categorical.sample, in_axes=(0, 0,))(\n", + " # jax.random.split(key, k),\n", + " # jnp.ones((k, image_width))\n", + " # )\n", + "\n", + " mesh_index = 1 * (latent_rgbd[..., 3] > 0.)\n", + "\n", + " outlier_probability_adjusted = all_outlier_probabilities[mesh_index]\n", + " inlier_variances = all_inlier_variances[mesh_index]\n", "\n", - " no_mesh_surface = (latent_rgbd[..., 3] == 0)[row_coordinates, column_coordinates]\n", - " outlier_probability_adjusted = outlier_probability * (1 - no_mesh_surface) + no_mesh_surface * 1.0\n", - " outlier_probability_adjusted = outlier_probability * jnp.ones_like(no_mesh_surface)\n", "\n", " observed_color_space_d = convert_rgbd_to_color_space(observed_rgbd)\n", " latent_color_space_d = convert_rgbd_to_color_space(latent_rgbd)\n", "\n", - " subset_observed = observed_color_space_d[row_coordinates, column_coordinates]\n", + " subset_observed = observed_color_space_d\n", " subset_observed_rescaled = (subset_observed - lower_bound) / (upper_bound - lower_bound)\n", - " rendered_values_rescaled = (latent_color_space_d[row_coordinates, column_coordinates] - lower_bound) / (upper_bound - lower_bound)\n", + " rendered_values_rescaled = (latent_color_space_d - lower_bound) / (upper_bound - lower_bound)\n", "\n", - " inlier_variances = jnp.array([lightness_variance, color_variance, color_variance, depth_variance])\n", - " outlier_variances = jnp.array([1000000.0, 1000000.0, 1000000.0, 1000000.0])\n", "\n", - " scores_inlier = jax.vmap(genjax.truncated_normal.logpdf, in_axes=(0, 0, None, None, None))(\n", + " scores_inlier = jax.vmap(genjax.truncated_normal.logpdf, in_axes=(0, 0, 0, None, None))(\n", " subset_observed_rescaled, rendered_values_rescaled, inlier_variances,\n", " 0.0, 1.0\n", " )\n", @@ -140,10 +154,13 @@ "\n", " pixelwise_score = jnp.logaddexp(scores_inlier_merged, scores_outlier_merged) \n", " pixelwise_score_full = jnp.zeros((image_height, image_width))\n", - " pixelwise_score_full = pixelwise_score_full.at[row_coordinates, column_coordinates].set(pixelwise_score)\n", + " # pixelwise_score_full = pixelwise_score_full.at.set(pixelwise_score)\n", + " pixelwise_score_full = pixelwise_score * (observed_rgbd[..., 3] > 0.)\n", + "\n", + " # pixelwise_score_full = pixelwise_score_full * latent_areas\n", "\n", " return {\n", - " \"score\": pixelwise_score.sum(),\n", + " \"score\": pixelwise_score_full.sum(),\n", " \"observed_color_space_d\": observed_color_space_d,\n", " \"latent_color_space_d\": latent_color_space_d,\n", " \"pixelwise_score\": pixelwise_score_full,\n", @@ -163,28 +180,19 @@ }, { "cell_type": "code", - "execution_count": 203, + "execution_count": 503, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "[0.1464138 0.5 0.05428571 0.12285715]\n", - "35190.03\n" + "1622.2854\n" ] } ], "source": [ - "outlier_probability_sweep = jnp.linspace(0.01, 0.999, 30)\n", - "lightness_variance_sweep = jnp.linspace(0.02, 0.5, 20)\n", - "color_variance_sweep = jnp.linspace(0.02, 0.5, 15)\n", - "depth_variance_sweep = jnp.linspace(0.02, 0.5, 15)\n", - "arguments = Pytree.const((\"outlier_probability\", \"lightness_variance\", \"color_variance\", \"depth_variance\",))\n", - "sweeps = [outlier_probability_sweep, lightness_variance_sweep, color_variance_sweep, depth_variance_sweep]\n", - "\n", - "IDX = 2\n", - "key = jax.random.split(key, 2)[-1]\n", + "IDX = 0\n", "likelikood_args = {\n", " \"fx\": renderer.fx,\n", " \"fy\": renderer.fy,\n", @@ -198,7 +206,8 @@ " \"rgbd\": observed_rgbd_scaled_down,\n", " # \"rgbd\": rendered_rgbds[0],\n", " \"object_pose_0\": all_data[0][\"object_poses\"][IDX],\n", - " \"camera_pose\": all_data[0][\"camera_pose\"]\n", + " \"camera_pose\": all_data[0][\"camera_pose\"],\n", + " \"outlier_probability_background\": 1.0,\n", " }\n", ")\n", "\n", @@ -207,59 +216,98 @@ " choicemap,\n", " ({\"num_objects\": Pytree.const(1), \"meshes\": [meshes[IDX]], \"likelihood_args\": likelikood_args},)\n", ")[0]\n", - "\n", - "scores = grid4(\n", - " trace, key,\n", - " arguments,\n", - " *sweeps\n", - ")\n", - "sampled_indices = jax.vmap(\n", - " jnp.unravel_index,\n", - " in_axes=(0,None)\n", - ")(jax.random.categorical(key, scores.reshape(-1),shape=(1000,)), scores.shape)\n", - "sampled_parameters = jnp.vstack([\n", - " sweep[indices]\n", - " for indices, sweep in zip(sampled_indices, sweeps)\n", - "]).T\n", - "\n", - "print(sampled_parameters[0])\n", - "trace = b3d.update_choices(trace, key,\n", - " arguments,\n", - " 0.05, 1.0, 0.02, 0.01\n", - " # *sampled_parameters[0]\n", - ")\n", "print(trace.get_score())\n", - "viz_trace(trace)\n", - "info_from_trace(trace)[\"score\"]" + "viz_trace(trace)\n" ] }, { "cell_type": "code", - "execution_count": 202, + "execution_count": 504, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "[5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602\n", - " 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602\n", - " 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602\n", - " 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602\n", - " 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602\n", - " 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602\n", - " 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602 5602\n", - " 5602 5602]\n", - "-19493.59\n" + "[0.03172414 0.33631578 0.085 0.03 ]\n", + "5707.9937\n" + ] + } + ], + "source": [ + "for arguments in [\n", + " # Pytree.const((\"outlier_probability_background\", \"lightness_variance_background\", \"color_variance_background\", \"depth_variance_background\",)),\n", + " Pytree.const((\"outlier_probability_0\", \"lightness_variance_0\", \"color_variance_0\", \"depth_variance_0\",)),\n", + "]:\n", + " key = jax.random.split(key, 2)[-1]\n", + " outlier_probability_sweep = jnp.linspace(0.01, 0.1, 30)\n", + " lightness_variance_sweep = jnp.linspace(0.03, 1.0, 20)\n", + " color_variance_sweep = jnp.linspace(0.03, 0.1, 15)\n", + " depth_variance_sweep = jnp.linspace(0.03, 0.05, 15)\n", + " # arguments = Pytree.const((\"outlier_probability_background\", \"lightness_variance_background\", \"color_variance_background\", \"depth_variance_background\",))\n", + " sweeps = [outlier_probability_sweep, lightness_variance_sweep, color_variance_sweep, depth_variance_sweep]\n", + "\n", + " scores = grid4(\n", + " trace, key,\n", + " arguments,\n", + " *sweeps\n", + " )\n", + " sampled_indices = jax.vmap(\n", + " jnp.unravel_index,\n", + " in_axes=(0,None)\n", + " )(jax.random.categorical(key, scores.reshape(-1),shape=(1000,)), scores.shape)\n", + " sampled_parameters = jnp.vstack([\n", + " sweep[indices]\n", + " for indices, sweep in zip(sampled_indices, sweeps)\n", + " ]).T\n", + "\n", + " print(sampled_parameters[0])\n", + " trace = b3d.update_choices(trace, key,\n", + " arguments,\n", + " # 0.05, 1.0, 0.02, 0.01\n", + " *sampled_parameters[0]\n", + " )\n", + " print(trace.get_score())\n", + " viz_trace(trace)\n", + " info_from_trace(trace)[\"score\"]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 499, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[363945 366902 302418 302418 366902 254052 254052 366902 302418 363945\n", + " 171128 171128 43482 302418 171128 254052 363945 366902 190621 366902\n", + " 302418 302418 366902 363945 288074 440761 254052 254052 254052 363945\n", + " 302418 171128 363945 363945 171128 302418 43482 254052 302418 302418\n", + " 43482 302418 254052 302418 254052 295606 302418 288074 295606 254052\n", + " 366902 366902 295606 171128 43482 363945 366902 302418 302418 295606\n", + " 295606 295606 91590 302418 278459 254052 302418 363945 252563 302418\n", + " 366902 440761 254052 366902 366902 302418 302418 91590 302418 302418\n", + " 254052 363945 302418 254052 302418 302418 254052 302418 302418 254052\n", + " 295606 254052 366902 302418 302418 254052 366902 366902 91590 302418]\n", + "3044.147\n" ] }, { "data": { "text/plain": [ - "Array(-19764.145, dtype=float32)" + "Array(3056.1968, dtype=float32)" ] }, - "execution_count": 202, + "execution_count": 499, "metadata": {}, "output_type": "execute_result" } @@ -267,22 +315,26 @@ "source": [ "key = jax.random.split(key, 2)[-1]\n", "N = 1000\n", - "B = 20\n", + "B = 500\n", "keys = jax.random.split(key, N*B)\n", "\n", - "sampled_poses = Pose.sample_gaussian_vmf_pose_vmap(\n", - " keys, trace.get_choices()[\"object_pose_0\"], 0.1, 800.0\n", - ")\n", + "# sampled_poses = Pose.concatenate_poses([Pose.sample_gaussian_vmf_pose_vmap(\n", + "# keys, trace.get_choices()[\"object_pose_0\"], 0.05, 800.0,\n", + "# ), trace.get_choices()[\"object_pose_0\"][None,...]])\n", + "\n", + "sampled_poses = Pose.concatenate_poses([Pose.sample_gaussian_vmf_pose_vmap(\n", + " keys, trace.get_choices()[\"object_pose_0\"], 0.05, 800.0,\n", + ")])\n", "\n", "scores = jnp.concatenate([\n", " b3d.enumerate_choices_get_scores(\n", " trace,key, Pytree.const((\"object_pose_0\",)),\n", " sampled_poses[k]\n", " )\n", - " for k in jnp.split(jnp.arange(len(sampled_poses)), B)\n", + " for k in jnp.array_split(jnp.arange(len(sampled_poses)), B)\n", "])\n", "\n", - "sampled_indices = jax.random.categorical(key, scores * 1.0 , shape=(100,))\n", + "sampled_indices = jax.random.categorical(key, scores * 0.1 , shape=(100,))\n", "print(sampled_indices)\n", "new_trace = b3d.update_choices(trace, key, Pytree.const((\"object_pose_0\",)),\n", " sampled_poses[sampled_indices[0]])\n", @@ -293,21 +345,24 @@ }, { "cell_type": "code", - "execution_count": 142, + "execution_count": 466, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "Array(0., dtype=float32)" + "Array(0.47610688, dtype=float32)" ] }, - "execution_count": 142, + "execution_count": 466, "metadata": {}, "output_type": "execute_result" } ], - "source": [] + "source": [ + "print(((trace.get_retval()[\"latent_rgbd\"][...,3]>0) * info_from_trace(trace)[\"pixelwise_score\"]).mean())\n", + "print(((new_trace.get_retval()[\"latent_rgbd\"][...,3]>0) * info_from_trace(new_trace)[\"pixelwise_score\"]).mean())" + ] }, { "cell_type": "code", diff --git a/src/b3d/chisight/dense/dense_model.py b/src/b3d/chisight/dense/dense_model.py index 4a92e006..16008989 100644 --- a/src/b3d/chisight/dense/dense_model.py +++ b/src/b3d/chisight/dense/dense_model.py @@ -36,17 +36,19 @@ def dense_multiobject_model(args_dict): likelihood_args = args_dict["likelihood_args"] num_objects = args_dict["num_objects"] - outlier_probability = genjax.uniform(0.0001, 0.9999) @ "outlier_probability" - lightness_variance = genjax.uniform(0.0001, 1.0) @ "lightness_variance" - color_variance = genjax.uniform(0.0001, 1.0) @ "color_variance" - depth_variance = genjax.uniform(0.0001, 1.0) @ "depth_variance" - blur = genjax.uniform(0.0001, 1.0) @ "blur" - - likelihood_args["outlier_probability"] = outlier_probability - likelihood_args["lightness_variance"] = lightness_variance - likelihood_args["color_variance"] = color_variance - likelihood_args["depth_variance"] = depth_variance - likelihood_args["blur"] = blur + outlier_probability = ( + genjax.uniform(0.0001, 1.0) @ f"outlier_probability_background" + ) + lightness_variance = ( + genjax.uniform(0.0001, 1.0) @ f"lightness_variance_background" + ) + color_variance = genjax.uniform(0.0001, 1.0) @ f"color_variance_background" + depth_variance = genjax.uniform(0.0001, 1.0) @ f"depth_variance_background" + + likelihood_args[f"outlier_probability_background"] = outlier_probability + likelihood_args[f"lightness_variance_background"] = lightness_variance + likelihood_args[f"color_variance_background"] = color_variance + likelihood_args[f"depth_variance_background"] = depth_variance all_poses = [] for i in range(num_objects.const): @@ -54,6 +56,19 @@ def dense_multiobject_model(args_dict): uniform_pose(jnp.ones(3) * -100.0, jnp.ones(3) * 100.0) @ f"object_pose_{i}" ) + + outlier_probability = ( + genjax.uniform(0.0001, 1.0) @ f"outlier_probability_{i}" + ) + lightness_variance = genjax.uniform(0.0001, 1.0) @ f"lightness_variance_{i}" + color_variance = genjax.uniform(0.0001, 1.0) @ f"color_variance_{i}" + depth_variance = genjax.uniform(0.0001, 1.0) @ f"depth_variance_{i}" + + likelihood_args[f"outlier_probability_{i}"] = outlier_probability + likelihood_args[f"lightness_variance_{i}"] = lightness_variance + likelihood_args[f"color_variance_{i}"] = color_variance + likelihood_args[f"depth_variance_{i}"] = depth_variance + all_poses.append(object_pose) all_poses = Pose.stack_poses(all_poses) From 9e998dab9d89eeaa41f3b6a80196cc5f9a539a3e Mon Sep 17 00:00:00 2001 From: Nishad Gothoskar Date: Wed, 24 Jul 2024 22:15:06 +0000 Subject: [PATCH 11/16] color exploration in progress --- notebooks/bayes3d_paper/interactive.ipynb | 167 ++++++++++++++++++++-- 1 file changed, 158 insertions(+), 9 deletions(-) diff --git a/notebooks/bayes3d_paper/interactive.ipynb b/notebooks/bayes3d_paper/interactive.ipynb index 1271e64c..55f644fb 100644 --- a/notebooks/bayes3d_paper/interactive.ipynb +++ b/notebooks/bayes3d_paper/interactive.ipynb @@ -27,14 +27,14 @@ }, { "cell_type": "code", - "execution_count": 501, + "execution_count": 548, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 10/10 [00:03<00:00, 3.01it/s]\n" + "100%|██████████| 10/10 [00:04<00:00, 2.04it/s]\n" ] } ], @@ -42,7 +42,7 @@ "b3d.rr_init(\"interactive\")\n", "key = jax.random.PRNGKey(0)\n", "ycb_dir = os.path.join(b3d.get_assets_path(), \"bop/ycbv\")\n", - "scene_id = 49\n", + "scene_id = 48\n", "image_id = 100\n", "all_data = b3d.io.get_ycbv_test_images(ycb_dir, scene_id, range(1,1000,100))\n", "\n", @@ -69,7 +69,7 @@ }, { "cell_type": "code", - "execution_count": 488, + "execution_count": 549, "metadata": {}, "outputs": [], "source": [ @@ -180,19 +180,19 @@ }, { "cell_type": "code", - "execution_count": 503, + "execution_count": 610, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "1622.2854\n" + "1009.2521\n" ] } ], "source": [ - "IDX = 0\n", + "IDX = 4\n", "likelikood_args = {\n", " \"fx\": renderer.fx,\n", " \"fy\": renderer.fy,\n", @@ -220,6 +220,98 @@ "viz_trace(trace)\n" ] }, + { + "cell_type": "code", + "execution_count": 611, + "metadata": {}, + "outputs": [], + "source": [ + "b3d.rr_init(\"color_investigation\")" + ] + }, + { + "cell_type": "code", + "execution_count": 612, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/conda/envs/b3d/lib/python3.12/site-packages/matplotlib/cm.py:494: RuntimeWarning: invalid value encountered in cast\n", + " xx = (xx * 255).astype(np.uint8)\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "info = info_from_trace(trace)\n", + "latent_labd = info[\"latent_color_space_d\"]\n", + "observed_labd = info[\"observed_color_space_d\"]\n", + "\n", + "def normalize_lab(lab):\n", + " l = lab[...,0:1]\n", + " ab = lab[...,1:3]\n", + " length = jnp.linalg.norm(ab, axis=-1, keepdims=True)\n", + " black_or_white = length < 20.0\n", + " black = black_or_white * (l < 50.0)\n", + " white = black_or_white * (l >= 50.0)\n", + " ab_normalized = ab / length * 100.0\n", + "\n", + " return jnp.concatenate([(black * 0.0 + white * 100.0 + (1.0 - black_or_white)* 50.0), (~black) * ab_normalized + 0.001], axis=-1)\n", + "\n", + "\n", + "\n", + "\n", + "fig,ax = plt.subplots(1,4, figsize=(20,10))\n", + "ax[0].imshow(trace.get_retval()[\"rgbd\"][...,:3])\n", + "ax[1].imshow(b3d.colors.lab_to_rgb(normalize_lab(observed_labd)))\n", + "ax[2].imshow(trace.get_retval()[\"latent_rgbd\"][...,:3])\n", + "ax[3].imshow(b3d.colors.lab_to_rgb(normalize_lab(latent_labd)))\n", + "\n", + "normalized_observed_lab = normalize_lab(observed_labd)\n", + "normalized_latent_lab = normalize_lab(latent_labd)\n", + "\n", + "rr.log(\"img\", rr.Image(normalize_lab(observed_labd)))\n", + "rr.log(\"img/latent\", rr.Image(normalize_lab(latent_labd)))\n", + "rr.log(\"img/rgb\", rr.Image(trace.get_retval()[\"rgbd\"][...,:3]))\n", + "rr.log(\"img/rgb/latent\", rr.Image(trace.get_retval()[\"latent_rgbd\"][...,:3]))\n", + "angle = jnp.arctan2(normalized_observed_lab[...,1], normalized_observed_lab[...,2]) * 180.0 / jnp.pi\n", + "latent_angle = jnp.arctan2(normalized_latent_lab[...,1], normalized_latent_lab[...,2]) * 180.0 / jnp.pi\n", + "rr.log(\"img/angle\", rr.DepthImage(jnp.arctan2(normalized_observed_lab[...,1], normalized_observed_lab[...,2]) * 180.0 / jnp.pi) )\n", + "rr.log(\"img/angle/latent\", rr.DepthImage(jnp.arctan2(normalized_latent_lab[...,1], normalized_latent_lab[...,2]) * 180.0 / jnp.pi))\n", + "rr.log(\"img/angle/diff\", rr.DepthImage(jnp.minimum(jnp.abs(angle - latent_angle), 360.0 - jnp.abs(angle - latent_angle))))" + ] + }, + { + "cell_type": "code", + "execution_count": 597, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)" + ] + }, + "execution_count": 597, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "jnp.minimum(jnp.zeros(10), jnp.ones(10))" + ] + }, { "cell_type": "code", "execution_count": 504, @@ -274,11 +366,68 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 532, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 532, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "info = info_from_trace(trace)\n", + "latent_labd = info[\"latent_color_space_d\"]\n", + "observed_labd = info[\"observed_color_space_d\"]\n", + "plt.scatter(latent_labd[...,1].reshape(-1), latent_labd[...,2].reshape(-1), alpha=0.4, c=trace.get_retval()[\"latent_rgbd\"][...,:3].reshape(-1,3))\n", + "# plt.scatter(observed_labd[...,1].reshape(-1), observed_labd[...,2].reshape(-1), alpha=0.4)\n", + "plt.xlim(-128, 128)\n", + "plt.ylim(-128, 128)" + ] + }, { "cell_type": "code", "execution_count": 499, From 842a7e44b46aa183f6071f3976b387ae97ccd519 Mon Sep 17 00:00:00 2001 From: Nishad Gothoskar Date: Thu, 25 Jul 2024 00:36:30 +0000 Subject: [PATCH 12/16] save slam mesh --- notebooks/aug1demos/slam_color_room.ipynb | 291 +++++++++++++++++++-- notebooks/bayes3d_paper/interactive.ipynb | 300 ++++++++-------------- src/b3d/mesh.py | 21 ++ 3 files changed, 408 insertions(+), 204 deletions(-) diff --git a/notebooks/aug1demos/slam_color_room.ipynb b/notebooks/aug1demos/slam_color_room.ipynb index c8c0b96e..fe6a60a8 100644 --- a/notebooks/aug1demos/slam_color_room.ipynb +++ b/notebooks/aug1demos/slam_color_room.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -27,49 +27,306 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ - "b3d.rr_init(\"slma\")" + "b3d.rr_init(\"slam\")" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 40, "metadata": {}, "outputs": [], "source": [ - "room_h = 1.0\n", - "room_w = 0.8\n", + "room_h, room_w = 1.0, 1.0\n", + "line_segments = jnp.array(\n", + " [\n", + " [0.0, 0.0, room_w, 0.0, 1.0, 0.0, 0.0],\n", + " [0.0, 0.0, 0, room_h, 0.0, 1.0, 0.0],\n", + " [room_w, 0.0, room_w, room_h, 0.0, 0.0, 1.0],\n", + " [0.0, room_h, room_w, room_h, 1.0, 1.0, 0.0],\n", + " ]\n", + ")\n", + "line_segments = jnp.concatenate(\n", + " [\n", + " line_segments,\n", + " line_segments\n", + " + jnp.array([room_w + 0.002, 0.0, room_w + 0.002, 0.0, 0.0, 0.0, 0.0]),\n", + " line_segments\n", + " + jnp.array(\n", + " [room_w * 2.0 + 0.003, 0.0, room_w * 2.0 + 0.003, 0.0, 0.0, 0.0, 0.0]\n", + " ),\n", + " ],\n", + " axis=0,\n", + ")\n", + "world_height = 0.5\n", "\n", "\n", - "def plane_mesh_from_plane_and_dimensions(pose, w, h, color):\n", + "def line_segment_to_mesh(line_segment):\n", + " a, b, c, d, r1, g1, b1 = line_segment\n", " vertices = jnp.array(\n", " [\n", - " [-w / 2, -h / 2, 0],\n", - " [-w / 2, h / 2, 0],\n", - " [w / 2, h / 2, 0],\n", - " [w / 2, -h / 2, 0],\n", + " [a, world_height / 2, b],\n", + " [a, -world_height / 2, b],\n", + " [c, -world_height / 2, d],\n", + " [c, world_height / 2, d],\n", " ]\n", " )\n", - " vertices = pose.apply(vertices)\n", " faces = jnp.array(\n", " [\n", " [0, 1, 3],\n", " [3, 1, 2],\n", " ]\n", " )\n", - " vertex_attributes = jnp.ones((len(vertices), 3)) * color\n", + " vertex_attributes = jnp.ones((len(vertices), 3)) * jnp.array([r1, g1, b1])\n", " return Mesh(vertices, faces, vertex_attributes)\n", "\n", "\n", - "m = plane_mesh_from_plane_and_dimensions(\n", - " Pose.identity(), room_w, room_h, jnp.array([1.0, 0.0, 0.0])\n", - ")\n", - "m.rr_visualize(\"mesh\")" + "world_mesh = Mesh.squeeze_mesh(jax.vmap(line_segment_to_mesh)(line_segments))\n", + "world_mesh.rr_visualize(\"mesh\")" ] }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [], + "source": [ + "renderer = b3d.RendererOriginal()" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "data": { + "image/jpeg": 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diff --git a/notebooks/bayes3d_paper/interactive.ipynb b/notebooks/bayes3d_paper/interactive.ipynb index 55f644fb..b4724748 100644 --- a/notebooks/bayes3d_paper/interactive.ipynb +++ b/notebooks/bayes3d_paper/interactive.ipynb @@ -1,5 +1,15 @@ { "cells": [ + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# TODO\n", + "# - try tracking by making mesh of object and bacground from segmentation mask\n" + ] + }, { "cell_type": "code", "execution_count": 2, @@ -27,14 +37,14 @@ }, { "cell_type": "code", - "execution_count": 548, + "execution_count": 806, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 10/10 [00:04<00:00, 2.04it/s]\n" + "100%|██████████| 23/23 [00:09<00:00, 2.44it/s]\n" ] } ], @@ -44,7 +54,14 @@ "ycb_dir = os.path.join(b3d.get_assets_path(), \"bop/ycbv\")\n", "scene_id = 48\n", "image_id = 100\n", - "all_data = b3d.io.get_ycbv_test_images(ycb_dir, scene_id, range(1,1000,100))\n", + "\n", + "num_scenes = b3d.io.data_loader.get_ycbv_num_test_images(ycb_dir, scene_id)\n", + "\n", + "# image_ids = [image] if image is not None else range(1, num_scenes, FRAME_RATE)\n", + "image_ids = range(1, num_scenes + 1, 100)\n", + "all_data = b3d.io.get_ycbv_test_images(ycb_dir, scene_id, image_ids)\n", + "\n", + "\n", "\n", "meshes = [\n", " Mesh.from_obj_file(os.path.join(ycb_dir, f'models/obj_{f\"{id + 1}\".rjust(6, \"0\")}.ply')).scale(0.001)\n", @@ -69,13 +86,78 @@ }, { "cell_type": "code", - "execution_count": 549, + "execution_count": 622, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/conda/envs/b3d/lib/python3.12/site-packages/matplotlib/cm.py:494: RuntimeWarning: invalid value encountered in cast\n", + " xx = (xx * 255).astype(np.uint8)\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "info = info_from_trace(trace)\n", + "latent_labd = info[\"latent_color_space_d\"]\n", + "observed_labd = info[\"observed_color_space_d\"]\n", + "\n", + "def normalize_lab(lab):\n", + " l = lab[...,0:1]\n", + " ab = lab[...,1:3]\n", + " length = jnp.linalg.norm(ab + 0.0001, axis=-1, keepdims=True)\n", + " black_or_white = length < 20.0\n", + " black = black_or_white * (l < 50.0)\n", + " white = black_or_white * (l >= 50.0)\n", + " ab_normalized = ab / length * 100.0\n", + "\n", + " return jnp.concatenate([(black * 0.0001 + white * 99.99 + (1.0 - black_or_white)* 50.0), (~black) * ab_normalized + 0.001], axis=-1)\n", + "\n", + "def normalize_labd(labd):\n", + " return jnp.concatenate([normalize_lab(labd[..., :3]), labd[..., 3:4]], axis=-1)\n", + "\n", + "\n", + "\n", + "fig,ax = plt.subplots(1,4, figsize=(20,10))\n", + "ax[0].imshow(trace.get_retval()[\"rgbd\"][...,:3])\n", + "ax[1].imshow(b3d.colors.lab_to_rgb(normalize_lab(observed_labd)))\n", + "ax[2].imshow(trace.get_retval()[\"latent_rgbd\"][...,:3])\n", + "ax[3].imshow(b3d.colors.lab_to_rgb(normalize_lab(latent_labd)))\n", + "\n", + "normalized_observed_lab = normalize_lab(observed_labd)\n", + "normalized_latent_lab = normalize_lab(latent_labd)\n", + "\n", + "rr.log(\"img\", rr.Image(normalize_lab(observed_labd)))\n", + "rr.log(\"img/latent\", rr.Image(normalize_lab(latent_labd)))\n", + "rr.log(\"img/rgb\", rr.Image(trace.get_retval()[\"rgbd\"][...,:3]))\n", + "rr.log(\"img/rgb/latent\", rr.Image(trace.get_retval()[\"latent_rgbd\"][...,:3]))\n", + "angle = jnp.arctan2(normalized_observed_lab[...,1], normalized_observed_lab[...,2]) * 180.0 / jnp.pi\n", + "latent_angle = jnp.arctan2(normalized_latent_lab[...,1], normalized_latent_lab[...,2]) * 180.0 / jnp.pi\n", + "rr.log(\"img/angle\", rr.DepthImage(jnp.arctan2(normalized_observed_lab[...,1], normalized_observed_lab[...,2]) * 180.0 / jnp.pi) )\n", + "rr.log(\"img/angle/latent\", rr.DepthImage(jnp.arctan2(normalized_latent_lab[...,1], normalized_latent_lab[...,2]) * 180.0 / jnp.pi))\n", + "rr.log(\"img/angle/diff\", rr.DepthImage(jnp.minimum(jnp.abs(angle - latent_angle), 360.0 - jnp.abs(angle - latent_angle))))" + ] + }, + { + "cell_type": "code", + "execution_count": 815, "metadata": {}, "outputs": [], "source": [ "lower_bound = jnp.array([0.0, -128.0, -128.0, 0.0])\n", "upper_bound = jnp.array([100.0, 128.0, 128.0, 3.0])\n", - "convert_rgbd_to_color_space = lambda x: b3d.colors.rgbd_to_labd(x)\n", + "convert_rgbd_to_color_space = lambda x: normalize_labd(b3d.colors.rgbd_to_labd(x))\n", "convert_color_space_to_rgbd = lambda x: b3d.colors.labd_to_rgbd(x)\n", "\n", "\n", @@ -125,6 +207,7 @@ " outlier_probability_adjusted = all_outlier_probabilities[mesh_index]\n", " inlier_variances = all_inlier_variances[mesh_index]\n", "\n", + " observed_labd = b3d.colors_r\n", "\n", " observed_color_space_d = convert_rgbd_to_color_space(observed_rgbd)\n", " latent_color_space_d = convert_rgbd_to_color_space(latent_rgbd)\n", @@ -180,14 +263,14 @@ }, { "cell_type": "code", - "execution_count": 610, + "execution_count": 816, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "1009.2521\n" + "1193.9121\n" ] } ], @@ -201,12 +284,13 @@ " \"k\": Pytree.const(10000),\n", "}\n", "\n", + "T = 22\n", "choicemap = genjax.ChoiceMap.d(\n", " {\n", - " \"rgbd\": observed_rgbd_scaled_down,\n", + " \"rgbd\": b3d.resize_image(all_data[T][\"rgbd\"], renderer.height, renderer.width),\n", " # \"rgbd\": rendered_rgbds[0],\n", - " \"object_pose_0\": all_data[0][\"object_poses\"][IDX],\n", - " \"camera_pose\": all_data[0][\"camera_pose\"],\n", + " \"object_pose_0\": all_data[T][\"object_poses\"][IDX],\n", + " \"camera_pose\": all_data[T][\"camera_pose\"],\n", " \"outlier_probability_background\": 1.0,\n", " }\n", ")\n", @@ -222,107 +306,15 @@ }, { "cell_type": "code", - "execution_count": 611, - "metadata": {}, - "outputs": [], - "source": [ - "b3d.rr_init(\"color_investigation\")" - ] - }, - { - "cell_type": "code", - "execution_count": 612, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/conda/envs/b3d/lib/python3.12/site-packages/matplotlib/cm.py:494: RuntimeWarning: invalid value encountered in cast\n", - " xx = (xx * 255).astype(np.uint8)\n" - ] - }, - { - "data": { - "image/png": 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zBYR4+NnI2xb0sCCf5mQeoWh+TjFE8gaOza2j0XL4/uMvMS965oaJybF5CWluYZIqCkHUgCjeB8QoMS72sRgfL01WaN6kHh2OF2IxzRY7P5ynmq+Jl1B8hBBRBR8Unzt4jRGsNUQL1gVcBGPl6PoiXS837nvxc0n7jKnD/mZEzJVrczPLUG4ivNr1BD7/mmI8mMWKtyjI5q570WOX4+LfMREihcJAwEv6tw25498qsUi3BhPM4YW7mHvSJeFgU8P2LG3P14k8KS2My3TL6RTqkBbjcUxF18rBik13lSpPlUJg2UC5uB3lW5IJBokGFUVNoLBw0sGqg098Z1YPCnzokvC/flrYq4Xvvy3yp87ne1jMWkUPtjWYTjEa8oE5OiaUAssCxiJrI8zaKlFqhI71rS34MOnxEji/epLTODYmM4q/+94Xv6Cd8zMP/5f8zMP/5eFTq9U5mjCl9gcc/x0gKjQBvvvnAWqgZlJ/hJ/6zT/OX/mui4TY5hshBO3owox5mLIZ97lXH4YnHoYn/u4Nu/8Hf+zfYJeWMeU6UtUI86O5ERNJcfwh8egcqDkiP47PHV5wnuQYaSVk0suQTnj+1UVJ5yva9Mh8e95Ourkfbl/Tz254vdV0vo+P6dXg2PqxWG6iTSqVzoALR69pxRFNAcYmWZ1ApVlhsFi/FOYCB1n1tGJhvDhueTczgYP8+pUIozTtsAouX6eQVBudgSDpZ0U8+tnimEoediOwZaATCApDn8Zm8/ksIgw1ESErCquL3+P02Pkibb8CRvnrzXTXVo6IU0hjd/HmGuPNhtdyPenRo0ePHn+48VrVvHr06NGjx5cWrznpUZYlb3vb2/ilX/olvud7vgdIQU2/9Eu/xA/8wA+84u2IVIgGjKZed4tFxBCMgLWoyaoJDEYMlhEWzVZWTeI1tCDqaiqEBkW1Ax8Rn6q9oh40ImpwIZEmRguEAkTwKtkOKtkHKEpUi4YS1ZgLzAa0wIhiTaCUloEopVGWnTIolGgiUbpkeWUrrBkkiySniESSoRS57p6kHqOy4NRahTUFw0FJQJIipTNoFKKx+FzBUyJqIkGhaZSoEVd4iqJBMLQhItnCKLhkpPXo49t85HOPMKtbNrfnzGYdZ86d5fY7bmFjZY0T42XG5RjrdtkzkSs0xC4Qph1iDNNmTrF1kdiBbZcZs0To9tnWXYRAYWZYaRiUsDxOHpedBjwdFkehhkobWlpqnaGkApP1kdYPuBoGTINjJz5P1EdwxnLOnuLeYoU7ls6zduvbGZ9cpqg98blnUe8p3RqlXaIs1kneMoLGpCIJUam7OSZEgm/w2fpBUCQGIFdQJJ8Isq1ZVFCPiqA2WZBpiMTsGaILHkKBAGCwFFhboCiegojDmo6h6wBFpEZoc6HIEnGorcCNE79iS6I4MBFnIqKClRIYktpkX1DRVwgdRJ8LsCKIW3Bc+XMwACJ127G9u4sPkeVqzNJghCCUlUGJyXLNZPIlckgidF1SdLgCiuoG/gxjwBUGVUVjoG0DMULdJJFTWRqWlhz2WKHf+8je3oym7ghYvBaICKvLhmFVUDhwzuV9CkVp8z4NIaT9L4iUsnLJii0KMRpCHZFCwMpNVQHqOk9TpzbhalBSFPYPeEQ3P16r9QRgsAPVMHXdS4TB/IjAsCFd/tanorZTWJpC1cFXKWycTmKwOwLc+ny6Aq2mjv+isAgVRqHwkUETKCfC6LJFpsJny8hPl4EaKBtwHu5Zh2+6E1Yq+I0r8MGrcFLge4dwvwO7koq8XqFItx3OFfAn1uDOKlkhhSIRHuPrK1T7I3zZ0KzuoaXnwgiGIY1xUWx/S1vw3+qITgy3yQxja0znWL28TDGrsLHA+QpRxbNJsHsY0nFyBkrdQZYfh6UC80fPIW8cY02NdXvwP/zkyx77/9e3/z9407Ux5qefeMXn63te93f59OYH+J2rP4eP9eHzT+/Dv/zcS7/nVz/1N9idPEXj91ENfObSz3Jt/zMM211+bf7pz7uvr957P6ff/Q6GS++AZx/CP/PbSPAM96GyyUaqmHLYvCARfAnTrIBQOZpHLr82lNCuQCwyIZHvRcFlImE1vZcIOk7KIDXp3Db5eTcGWyoS5qjrCEWkrD1W0/59CRQQzwfqjUg3VGKpL+TTXzkCsLCbHgJlEi5O86NoYTSFfQb81MZb+Ojp21CzDMWYEvi2Xfj2LSgBU6X+g98t4F/fmsiN93XwLV26f7eSCIzfKuFnBmn9/959+PoprHbw1h1oLGxka6vWwNNLsDWAjQbuOEhzfAFvYHcEcwcPVfDzo+TQ9Z0H8LWzTF5mEuU9czh9kFb5NyrU43TuymzDNWgTQeIs/AUP3+HgQg0bN5m1VVckRQsKwybZ8/X4/Hgt15MePXr06PGHG/2a0qNHjx5fHviS2Fv94A/+IN///d/P29/+dt75znfy9//+32c6nfLn/tyfexVbSUTCopPPpZ51jBiCMUSV7BmdFBlGilyIUnzsciekAR2hMaJxnrT/URGfN2pSxUsAGzPxoA6oUISQ29sDHm8E1dxaqQ6NisaY2xVN7jSPWLE4UlPs0CpDqwSN+JjaH8vCYG2BSERMl4ruKCa30UdJ31WFwYwdzjrK0hEQJEqy4YqGGC3Blqm73nSpI1MjbaeEGFHxGJd8VGJQNOb2TGMJJnJpa8InPvs8rfeHRzwaOHnqBKfXNxhRUWmBsSVTIrv4nFWRXj+Z7wORkmVWuUDJgGnomIZdFMXQIsCSWspBiUPw2hHoMASsWgoCngbPPOdCFBAMXRT2YqSJykS3iTyBRVg3Z7nFrnF6WDE+scHg1Bnss08Suw5CwBUjjLUUbikV+zMjoSqpGO9bRDwx+Hw8BJVc1Rc9ElIsekZVAc+hiiNXkTRmGwkhmZcbQH32n0mqBiuLc+kSoSORwjbpHNCmMYkliE32WVIgNnV/qLikghGwJiJRMGJJpaSSlyI9YkjEBwZsmZtvzUJhcTTDYhfYm8xou45ytWB9tIRYSSbo5kjJFLNKgwghQNekrwCuenFBzeb9dFHx3hMCzOfQtDCKlvHI3TDsECLTScN02hBNQXRJ4bGslsI5cInMeCFCzgE5bOsVcM7inE1EyzQSOiUuWqlvItIj+Ehdd4iAK2xPerxCvDbrSbIocgKa4o8oFzkBcNTZnbv4jcKghtKnTvD7V9LzEkC2UuG6Xk7EgxoD4hDAeUPRQTEXyh0LB8JzKL8K7B8byx+p4M0VMIJPz+H9z8MdAt+6BsMBIClHoyYVYwE2LHzDMrx9nArq3QBsZ1g7GLG0v0rrpkyWJ/iBpy2hiUDubBeFO4LlQR1hMexLx4HUGG8Yb44Y7I4wDLAsoRKYLU0Igz0EKBqwVnFMYXgFyjHypg3EnwfbYKo9+B9e/th/71u/BX7uc/Dhp17x+Xrn+e9jv73Kw9f+A/7Y89fm6fFS+PQzP37D98/tfozndj/2Bff1+tnvMLj3P8acO0PrtzFPP4R0yZ4MctRXk46j5rAKlaSAaKtM2C/mTge2TqRVtImYOFSFkN8PaAlNtiAt2mRrFSxMl8AXaXu+Sq83XQu06X7XpZ+pSVZb0YAvNTU2mPwrDBwXx7xyBI48FSvApu3XJpEW6zERd8EWfOjE7fyr1dsP3zqMcGEPvuMg/2IZgRKeHcLPnEgWU6/fh/dO0rXmbSIyHhnATy2la+5tNXzdFEYe7vQ3Ds0LXB/CM+Ok+LhleiPpEQxMqpRr8dkSfm6QVFTv2IVTs2PXOvCG/IgGmnE6h9ql8yAxEY2Fh5GBb4okz7nuizymX0J4C/PcNFr49NtBj5fHa7We9OjRo0ePHv2a0qNHjx43P74kpMf3fd/3cf36df7W3/pbXLlyhQcffJD3v//9Lwp6enlknwGTOtWjScHQIcZDayGwqJgc3pysqWIOURajELK9DhFrW8R0qBaotSgCpsyVa5MK0BhEu5SwLCC5uhE14GPK/JAIRJ+te4QYHTEqvouEGJLVEwXWWAZDw3hgCN4S2lT5KAqLs9mOSwoQxYpiJaIIkQFRkxeEjizOOgZlkQpXkggS1SNvFoVcbE9+G4aSKIuQ90R0LP4v+XBGFUblgI3RKoqwurbCcDDg9rPnKIiob3LhvWQ4GPG6u+7FDYds7mxz6eo1jDXce+/dnD9/jkJGjDmF1ZLp9CKTyTNglGJpjK0qTOcx85roA85tE2WXkXPcu7bBRjVkr2m4OpvRhsi8CTRtxyB0DDWwLJELY2V8Llm8nFouKMoB1likS74xRjUFlocORFFS5clYg7U2W2gtyI9UdU9zZ9Gy2QFNsqnSLh1TTYqB9OIiTZFD36Rc9cjeF2I0uWnlOQSGbOxFVAXqpCYyEcnShKjHXES0y0+EQ68KWXh0SCqcBVFi0hvlhx5eIlET8SYiGCeLjPQXWVAtvnXWsjQc0hUFVVW8yDHr+NtCgNAlKzBjJREpNpMiHDqa3AAjJmduQFmkMRpjaLqIV8FZwZlk/1YNClShi0IdQp7HL19VWgSsHw9ab73SdjGTkovzcvP5WxlrKMt0yzU34fhuVrw268mCoMgkgDnK7bC5yLkgByRbxLg2cZkSU/e9aOaXFwXnMhVL3VKkWe/oInzOR57ehGKiLPmIIExGypuXoDl2yk8N4bFteP4gWdK8ax3WFJ4BfrWG1QZOd9n5KFsZBZcK4vsrpNwmC9FE6tUGiVP8oMYPY1IYVFBXacxVnRQs6iL1RoN4IbiAmydVwkK9oHgCcyBivMW1Y2S8BCcvEFfHmDCmfeI5TDXArd2GGZaEekp3/bkvfPCLPdQEIq9c1n/hXsODk5LmyRFtEZB7AnIqEjZX8Y+f59fmD7/oPV+7Bq5dppifwKvwONtcZI8VhNdh+W38i3cEmIOAPvoscXMfvbyJhLRuRpeXjwXZEcC1A1xXIT5Qrs4JxVHlXU0io+rlRFj4rJQw2SIr2ZGRbqD5/o4cneNDe6z8MP4oD0NCDkcfpLm8IFOO3QpRyXZXeSyvBG+690386F//0XwgSAV+8kZjsrRaaTIJkPorqFR4UwNb0/xZQsrcuLtNFnKLNUyBMx6+bgYTCxe6pO4w+bMVgC2OxqLHdn2IvH2rsNam684DHx6lY3lXC7e3iau5YuG6S6TI3fl6PqE3HqPjENI4nDkKqlfg6RKeLNNYKQELZwRe18LolR3W3xfYCGV3pDLq8YXxWq0nPXr06NGjR7+m9OjRo8fNjy9ZkPkP/MAP/B6lfclSCFOiEulMCzakwmbU7Jldpk55cmEqVwqMyRkRixq1eJw9AKnxZkxrKlQtxoxABsmGyOZicpig84NEnLgBYgp8dDShImIwsUNiA2oIsUCjxXctMdSEGAjeIjKiLIX1EwXry4bYVsTaAUJhUyBzIj2SZY9zjqIwqFq6bokQKorCUFYFzlk2VgbZOgkkpp59QQ+rVdoFNARULMYs44zBSsQt3pT/5DdGcU6wxnB6eZ17TtzOcDjiwbe+kXPnzzAsYCiBMNsnFAWhGHFi7RR//Ju+jVlo+Y2PfZif/cV/TzUc8H3f9728733vIxmMFaDK5KlHOHjs05jCsnzPnVSnTrL59CaPf/BJDrYnPPz8pxldfoSTywO+/cG7uefMGhevN3zmmSn704bfefIxHn3+ImMPJ/Cclsja2ciJW8FiCHFEjGtUtsJMD6C0WFWqpTU63xCaPUJoQEaUpcO5Ag0F6i0qHUHnqCwUGT4flSkLIkEIWTVR4EOJiMUWA6wtiTEQuy5RSCYmssMo1iliFRVLjA5VIWgOlqdDdRdoETNE7BhE0JjstpAAYZ7UM9EftgCLAWMjUSLeKB4lSgfMSd4j6bxHjXifCDjnLEWZ3/95KjwCDMuSMyc2UFWctUnlwY2vXxAmXRupZxHrhOHY4Ao5VIKovjS5Yq3FGEOMipFswaLKpA4oytLQsTRIyozVtTFLy8pk2uB352hQJBa8HMwLSBoFDmYdW/sdRmB1ZBiWyd4rZd7cPFKPorBYm1J8+0yPV4ff+3oC7RiGkrr3FZhVsL8KVQurB5nsiOnnEqGYARH8ANqlVEQuSIVWb2F/CeZj8NKBCxw08O+uRj5wCfCKaT1O4O2nle+/J+V0ACDwuW3490/AQQPvPQH/9d2w3cC/uwiP7sE3OvhzqylgfaE2aEq4eg6ePZUCrsc12BDpij3c2QlIRPAgiRw5WE5WWuU8qTX8oGX77r1kdrcfGW4n9YLpNFkkUhOZgCqmKaja08jJe+D1fxpuuY3m4vs5+MWfQgaWpa9+D4N7V2m3r7Lz2x/8wgd/9DTBRTwrr/h8fc13Ot7UjPnuh06gayX2z8yQ97Q0v/E6Dv7h+3jPc3/tRe/57+6A8c4trF76Gg46yz/mw/wED3M7hr/MgD/P5MU7AuyljvjvfgMtDFpdRgYBbLIv8yUUJh0ri6HaX2cwOUmzVFMvX0LMFF+k8xMdzNaP5kvIpElVg2vS3ClmKXxc81xA0hzzg3xPXaiOfHqP7RbnCbyDg7U0l21M53dBWkEiPTqXraO+mNuf40iRZwAPgwC3domgcTHtd03hP96FP76fiEHmibg5aaAcHXs/8GANf/N6UmqsltBmFUtRQxFSGPvxvJMXoQPqZDN21xAuCPxWAf/wBGwK/Bfb8J91MDXwyRIeGab8jm+NMA5w78tYfUlWrhTdEeHZCfziGP7ZRsojWXyOb57AfzuD0U1ELpTdEdlhbzLrrZsZr8V60qNHjx49ekC/pvTo0aPHzY4vGenxe8VRQSCHdUvWLEhWNZC/19zdmLu8RTQVPF+wNWMCSIdkxUgKA7cIDoi56BNyx32TshGiRUWImvM0NKlKTO6uT2HqJgVCa7aViiBqMJKsrKpKiJLsuEQFZw3WgiAYY0GEovAUpUPVYKUghJKiNAxHLhEizh0WBRZ/vMvxZFTVbPmzUMZYBJ8KYC9CaiktjGXsBiwNxpzZOMmtZ85BmEG7m4rwLiltyqLk7OoZghU++/ijOGsoCsctt9zCAw88gCyq3hqZ2Dn79Q6mdKzeexfDc2e5JCtMHqmpwh6ru88xrCqWhwNOr485f2oFH1u29yoqN2dQlkRN/kUlykCUjYHl9uUSwbJTD5h2QwpXIBohdGmKOIfRZEEWQ0RFc3i2EIMcKj2EQ/3QsVkWQDLhpYuWZ3so6ABLlnKk1y58cCQriiTmwn9mAHRhWMYxe6wOyKoiMXnmStqexjznFhWLG8szevhYzPtFSzApQyM/ELu4VG58/w3FJMWIUBXFyxbDFqRGjJryM4wmyy6b+CL/ckUfyaoTJFleWQgh0AUlqhJyBzWyIAGgaDwmX4EvVHqkIPQX7+P4AfJBqduANelazdKcF5zrP3iICNbeTCP6wwW1+frPl3G0qYjsssjq6IXpIeGICIkmv/8Y2RZsLjBXSrcUqC1cV3h2dnTNOgsPDuDCKoyPFXevHcDuFDanUG3A3WMoDWwrfM7D67tkWWc1OegNEJxRfAn1IClABh0g0A09ofI5E4lDVYh3R2OVCFoo3cijAoOJYFuL7SwSJb8uEKUBBBsdlhJhGTO8BVm6nTaO8dsHmIFBmxZECU3DdGubT31dyfjZP8Xo4p/End5g+c+8nurNp1D3OJQfhPkEpUQpmd/5cxT/6Ttwf+elg4P14Xx/8x2ry5ZzpkBKh73VYu431M8ssTe8wOfcB/hH8cf4n+K/5o5hxw/fAfcNhfGkYkPW2MOxTiIZK4RbMGyywcGdHTuvbzDRcv5zp1m/tIJqIG7vohLQjSlaJTvDaBORcRgqLmCiw7YVto1Yb7AhzYXFzSYUJJVDVl0szoHJwejGJwLjkLgVMMUxpZFyo+oo/3vxu85C5SFdWrpeRBjIoWjwFeHhxx7mvf/5e9NxF9LkOnYtWE3WVUpSPrR5u+c93KppHMxJy+OQxAwe49JXAiwnISqNS6RCzNuWnKVTHO2OzmQlyGIzi2tREuGgAWIJzxRwycJmkQiVVmDbwjULZyJc8LCsKbB8se3jZPnxzyip3wFPUmRdLeAzVbL0Wpza17tErNSSfnG2L0Om/H4harpPwLHj1aNHjx49evTo0aNHjx49gJuY9EAF0YihRSWFKEQiRCFKsuVJf+Cl7vtISGVTcaDpr26ViJVU+lStUJQuCLNujmpLZZTCtEnpQUBFsRacG6chhOSToEHRdp672xNpktgNDyaisaPrPCEEyqZmuZ6zNKgY6ZgBFUEi3iSvLWPSwI0xFEWFMQYjERM7FJNtbwQjggYhIqgOQFYTp7EofFuOgrVthAgxdvh6l6BghiW2SOELPkZiiMzmLfvTA5q248qVKxzsXkJ0Dd/OQWMK8jU2hdeWBaNBSbSOtijxxrA8XOLs2irVaMiofAn3aO0wcYaJDtE5MMcULeVypKwjUz/lueubTPcsH6Pl+sqQwfoZbr9wF2f8Kk9uPcNT14YsjQcUgwGmGjI++SbO3vb1FGXBmWKd6JZYXVllcO4MlCXxusXHGT62qTBZFAQRWl8TNRDbSPSp2mSqNrWqqmRFgYAZoFJlwiurKIzgkr8ZohM0CMSjLmojA5wZgEDMciINgRhSAqyYAiR56cQwQrUkxArJlbGgMZMVhqgF3gshSM6cyRUhzXZcC65DF5TNUbnGmGQltfj3C3Ew9+xNu6TqiB1WA1VVsLQ8wrqXzpNo28Bk2qVCSpCUVYNJOSYxER7dgktTcC5nfrTp50UBVZlG2Xaeto20QenaZNDVutTpuwgiF0nZHSurI0CT5RbgvTKbRDqvDAaG0dgcqrfigpuSRIqEaAAHCl1naCR14vsYERFKJxTuD74cFKLifVKhOWd6tcfvM1wDWqUcBJ+d3QbtkT0MJLKgHR8VeHXBmTqOLj1NRVkXUuZHzKqPtoJ3nIO1Kr035K75+0+TAqEVlg5SMPgbDuA/VZhZeGuEqkl2WseDsm0NYyN8kx9xhgEr3nP/3pQN5ym7NHYhFdxDvpwXweU2pBB2G9IYQglIUn2IGgaTWxgenMV4xfoaQ6Be6phu1Kgoo22oDiLsP4N+4qfg2XVksM34rV+DGZa4E7dALHhubvnZy8LW5cjX7T/P1+rHqTiH1XOonoLndtHHPwP7e8jj57B6GrFLyPCVtKUrflDTrO8iawcMxi2m8rjzwvjrV4h3rVE+MYAnwXjDcGvI0rTANROa6repHYT2EnjlCpF/Q8MHCbxu9zbe8uR9jIaG8qt2Md86RYND2gEahLD3NPOdPYIo7TCfx5jVFZWibp9mWWmHHZPVljrnaiz4cNcl5UDIeR/R5Ecmzdq1F1K76bxUu+k10mVSQ6EdggzAFWDzWAbztH0bco4IR+HozsNglp4rW168o98DFHhoAL8xTqHg3zSHBxbkTbagwnFD5V2BaQFbw3QMlknqCw9sDtPnWynhW/Jz+2P4Dw6WIpwLMFJYsbCuiXSclNAUSXnzdoWtCLaCh9bhmoOHC/gscFHgSQtrwGkDrycdn3mZ1oZOoMnjLDQN+7qBTxewbeCTo7QULwH3RzijibT88TVYDikY/Z3zG3NCfr+hwKcG8KujdC97zxTeXP/BjadHjx49evTo0aNHjx49bjbcvKQHghAx0pIq+qkbXtWCcbkgHBDtMuXRAh5lQNIJpEBxJwHF4LVCMXQhMu3mKZ/DeSz1YVpCFMGUBWawhETws4h2SvQRrZsUXl5YKFJw+aJdM8aOzgdi5ymaOSv1hJVGGcaKIUt04jEmkTNqjjInyrLEWgfBo6FBMFhjEJMyPzTkAGodILKCiOJsjeCJzhNsyHZLpO5O7ejmB/jgEbuOGY0RFUJs0BA5mMx56vlNptM5ly9fYn/neaw0+HaGxlSMLYzFiTAsCkaDimAdFCNEDMujFc6urVENK0ZVeWNXoYJk0kOiRXQGzDCuoVqJlG3kwE949uo1NkNgePE5nhLhLV/9Dr7lnW9DypJPPr3G2lNDlsdD3HCAGQxZOv0g5+57D8NxxfBkS7nsk+2UVMQYCZWlCzN87FInti0IBppujvctsZsT2gZTGKphgXE2VTOkRNSgZkgKru9Q7YCk3HA2kQxRZ2hosuJAEQQrBVbK1JUaQg6KDxBrQDFWEOdy4PwIVU2ZMN4hwqGiIUbBx4LOG2IwED0Sk/2VRpNflUmQeJz0SJUWEcG5z38JH8w9FzdrYvAMw5wytiwvjxgMB5+X9GiawPZ2Q/CR8aBkWDoETR2lMYmAuhx0azJx0XUwnYH3MB5DWSYVStN55nOPj0LTpUD5tkhFK2tT5ocxUJUOt+YOSRRIpMferqeuI6trjsHQJLssn8aw6GRWhRAMgkM1/bxRTTYxPiZiYWhuDtIjRJrWI8ihEqnH7x9cDTpIwcXBZrVEmwrFJtfgQ5k66YNNigrvUoF50KQOfchCr5wDErqk9tgbpOfeJfANq0fvjxZClbfbwvAAVndgbQJvUsCkpS20mfTIRVTj03iXjPAtfolvYw3vaw72Wjr1Ke8hK1DmOdj80BYpj61akCg5TNt4qOZgvGV4cIHR/oOgc1SfBHbplifs3z5HJaT9H0R07ym6hz6HVkr1tV/L0td9MzIaJjVlFJ6dOn7ieXjmuciqPs979WMMuR30Hek2dXEH/fefhu0tjI8YXQJTI6NX5sXjBzX1+i5m/YBirLgBuFth/I0rcH2d6gMDeFownWV4fYllGeKrA5rxR5gT8Jqq6ZeI/DgNBR3/t93becf+d7NyGqrv/QjybY8i7RJMzqCNIzw0YfaxpwkhErLCAxLBYILSLO8DB3SFMllV2urIasrERHqUdSLWFqSHmiO10CwHZy8mkwRYfw6WdtJ8cC3EKhECs9X0HjtIKh4TEqlhFnaXmrbdDZPaYaH2cTGHcv8erpcXIgr89hD+PydgrHB2Bx6YcGSHlXNKXohpAReXobNw1xw26kQ8XB/BXgGrAt/uk4LisRH8/DKcivC2FjZCsrNaDen47VewX0Jh4Z0K05jIoI8N4KrAJx08ypHodR14t2QVh4GDYbIhmxo4yEvgKEIV4ZEC/u0QnrPwvCQOZ1XhHQHeHOFTDv7FBrQK9jq8bX6jKOb3Gwp8YgB//0RSypwI8Ka6V3v06NGjR48ePXr06NGjxwI3Lemh2SYoGTktAqjNUff7ovDLwv4qEwQ58eIGHwMRBIuQOr9tthcyYg6teIzY3NVeINHlrs1kmG1Ecg6HIlaQRbFSQ863DqjGHFytSPaoEEkppIcWSAoLG6Q07ohqQFDEWFQNgsGQSZVjvj7JsilpWm60OdKkhMnB5mKOuoXRiIpBsCCGiKNuYdpE5l2kiYFOI9E4sCWiioQCJbI3nbA3C5hyQHXiLFINiSp0wWDCIrPihecsFcZNJJMAHtEU5ivkwHkinQamXtkD9lvPQaMYFSJDCruKtSNUh3it6LxQNy3Ggq1bpOwQLF6SnZj3Ic+P1DkvAtbmf5tsi2GTRZOqJnInW40tfEBUFl4gi0f2ZcoEyJHF0pGBhGqu8OS5KEi2S8uVzMPt5dZrJO0f0nmXkK2gyPuIxBiyaiF5jCSdz+HRfdnrJcakHknF9HRNWJNUDlEshVhcdIhYui5Zc1mXyIc8VbKtVQobF0ye5+kTxaD4JHjJRmFHWEzTY1fd4ZDzJYHN14ygxBgQhLDY/uL4SlKNxABtm5QaIQbiouooN+5DSIfZWaF0Jo9UCTFZa1kjGAPmFZaB0vyNycLOvDJSQiGRofk4mBd5cR0/TknB9eID1eP3A6bNj2wBVc5cVrZFRLNPULYTMvk0Hdr0HN1i079jKjzbSEpQ7tJzwwhDAzNgv02F3LEvGbclpQfraxCPceAGQICuSMoQZ+BMCbcP4ESVAqEBCklUfi2KOqUrksrELFQdXXYUyhZE0eYCex6+hKMw7MWTsmIRW6K+I8wDwbeEyqM2Eo3SDQLNsocKZL3ADAxmxZFisAR0CFpi7Cnc4E524lX+Jo/xN3kMrgD/3/+Z+C8jjAewcprYObansDffpJIBp6Qj/Grgn37gJ/jhH/tRrLP8vb/4g/y5b/+TN5wziQbjHbSOZs/jryt2K1LstrDXoE3yJWqByxp5Un2qgo+W2TdplT1hjurxVoWB36BoPbaL6LQm7NXQWMz+HK0dMulSP0M4EtrBkVJDjaKieMehhdTCisoceywsqVAQL9haUAMyiodESl4aDhVFInk7OcDcLmzOWrCdYFQPya3jHHiUI7UPizH/Hu4xQWDLwr6BgcJJn35ZHEc465OLVUUm9zrYmyQFYBxBGEEpcDIrNYxAGdLqafJYFy6ElnTNuJiUF+vATGElExEFmVg4dpyNpsyO1Zj2E/MyPNZkazUXmAjsSHLdulLDE/tJMdMtpWsjkK8hstJDYRBhw0OTz12lsAKM81iHCqc9+JiUKK/k8C4sznQx9lfwvlZg0yZiZjkmMqP4PMu/F5iZ9HPfryk9evTo0aNHjx49evTocQNuYtLDElWSZZWCZlNtocMwJVWnHCIloKgxQECkxIiFTIAEVcBh7BBjKoY2ojaRFa4osUUBOAoZATYVFGqAiJM5lC2utJSj5NkTc3E6hkjTzIneE4LSqRJJnaGxhFh6tNyDssGow3VlGpOpwJQIntBOiBKxhcWVg/T5fIXGIhfD01/balqCmRBFUWkwBNTkDARVMDW4NhVVQ4F1JcYKxBoRh3VrmGKMF8vVyVW29oQrtXBVAevwow3cyjmsn2HqHbpmzoc/9Tt84nOPcObseb75W76bWy/cwaSD57aFaihMmqOi2gIhWuquwCKEuoXZBOYN0lpMVyCS/jpvRbmisA/YA0/12JSigK3JrayNxgxKQxMG7DeWK1emPMZHGZTC8kZgsBQxboAbrIIYdrcmRJYQGxiXSumgKEuG4wpjhdBFgk95Ej4E1AcKYyltgWCSgkFTJUKsS8c8VmgcZRKpw0gEsUiKMUaiPbKyipl2MxaxK4l8U0PsUiKtsaT5GZUQAhARW5PyZUzKJ3Gg0jFtpgR1LEeDNQPQjpQSu6hWfr5rRZnXDU3T4JxjPBpirWV1VFCcNWhUJAyRGPGdYWdL0OhZXjcsr6WKTDeH2IERx4kTQwB8K4TOEEJkPk9t6NaalDFjSPk0RlALVZGKO84ezQmNqSJVWGEwzEQeHW0dMCKErsAYi3WCLVKOysEEZtOUA9K2NVE7lCFQJuosWw2JcBi1smYM40oIQTmYReo2MrKG8cDgrGTVzheG94GD/RrvA6NRyXhp8OI8kWPHXFWJUakbjw9KWViGA3eUc/MCWGuoBumWa1/CjqzHlxbF9YKBj4gGBEt5sIGrl2mWZ+yd38QPOsomWQ0Fm7rRVZLSo2iPBUvXuUhap4JuMYVqh0TyjZOF1uU5/MRVeL4Rvl3O8KfMnQycp119nGbpGoxAV9N7SEsQGxa+9zx8k4dzDgYlNEEp9mochrrouLYRODgJy1NY209d/eMtsHPoRjA9Bb5KChXvkmqgmMBwD2IBYZDGp2+0cFeBP4DdT27TXH+ebtgRXSSKsnNbw/Z5z3BjgzMPvInB2jrmzApsXAWzArN3QXsPa0tv5MEH3sVvP/ptLz7gdwH2Poz5L5hv7/LzH/sP/Pwn/z136uv5C/pu7tfb4cwfgXetgRU4ff8LNiAU8xGjzVM0k5Lnfm2Pve05q09PueXDzxB2JoRrOxCVq3j+Gfv8LJaN1a/j3D1/GlutU83gO5IAD6OKVeWrrj3P6vOPMJjt0/7Gp5ldeho7qyivX8Y0FtdeY6UJBAvNclLqRAPNIM2HsCCVMjFWdDkwvs0qmyaRFDETGKJQ7TmWn66ITqmLBkYpg6XoEnkmBXRr+d8+Lelll84rgJ0Y7NwSK6U7EfADxWQySw3UQ5gvpdeaCF2Etvzi3a2mAv92Bf7PJXhdA39hB+5pk63TqZDm/V0WDkp4bBN+4RNwdQKTB2FyO5wX+PPTpNZYVrhrPxExRQFzl1QXKzHl0hRdUiWppikzIyk5RiU4SZkgJv+yMc5KljKmrJtOMvkHNMDrBSbAhwr4qQFMPfwfz8AnPgWnTsE71uDUGpyfwZ2TTHi4pAoZ1nBiH+YKTQt1m1SJl07BlSW4UMNf34eRT8fklVhbeQuzYZozVZP28bKh7cBVB//rGnx8CF8/g+/fTaRTjx49evTo0aNHjx49evR4dbiJSQ9BsShFUm5okXweEAwTEI+qA3GHvh4iixDvrPY4VIsYjBQgSiHKUELq0LQlWItIhWUJcKiPxC4AAVO0YAxicjUXwXcdoVNCDtKOXYsugs5RotFssxTA1qgNiBlgxaaxSAFUuav8AKHDFkPEJdLDRJcIHoFFWLaKJ0qTlCaSM04OP5+C6RAaRC3GDVHjcl52st+yrsKYZSITDhrL7lzY93AALIsllCPMYAVpDdLVBO144vnn+PVPfIS777qXd37te7jVKE2A3Vnq/Gy6F5+zEIUu2pTL3XloG6TziDcQXFK32ORtvx+hBi41kcevt1RFxaxZZVisUtiI10jtI/sHDdf1GaoiUs9gOFZsOaJcqsEWzKcNkQprIqWLDAtwpaOsXLIJMxZxjhAi3TwQQjxSgmTS48guKgfFSAEUoBERl7YhDpGKpOIAVZ86eKNJygdxYCpEUvE9CUEixqUW4FQgTwodsR6hQ4zFOgcRlEDnW4Jq1o045LA1O75spUQB7zvqpqGMkeGgwlrLoDQMylRcDzkrfXKgbG95ulYphso4b8B3EBooBsJonEi32QTmXSrw+zaiBKrSYgqDEUnd8JIsqpxNRS2zEKocdiEndcOgNBhDyvjoWqIkz5ekpjDYnGRb17B3kAYldAgtSiI2kUR6CEf7RdK+h6XQdcJkHvEhaT5KZyhexR0uBqWuO9rG45xl/JIp6seOuya1UdsFOp9UQQN1n/ctRkBsVq298mH1eI1gp5aiBB0GTDQsbY4Z7K8xOWk4OLODSoeERGwYlwrZIecmGJ/thTxIl+d8B+pgdABL19MlOicVSg9qeOg6PD6Bt7HCOrcyqlquj56nXjvKeEDytkPqJH9w9djc0GTlFqwn0tDZwGSk7K2kzviVaS4AT1MexDzC/umsHDlWmLcNFLNEeISKtOrfYeCPOOIWzHdnzNg/sowzMF8KNFVAzzrkzRcoT51LflvlQW7vX4N4B8MKzp9900sf8JNAPI10Z/A7u3z66V/k5+UzvIWC92lOe1++HW67PbXzL5PFc3qoJjNtSTFdoqs9e09MuaTgn2o4+Ts7sK8oM0A5QPkIiYjm+Q+kxzH8v7874qJiNHJr/QGGlz9C0V5n/uRl6u3rFJMCc3mKbSxmdU61psQy/drRSbIHa6sjMizkJdr6bG0Vsr3VYr6EpKxZBJPbuWWwVRBKxbbdYef/4v1iMiHlkzXZQunhcsyU2zPYicGPI916+lVI9XCa4B00KcILk7OXjoerv1q0kvIi/t0yvNvBn9hPqoi72/QIFg6WoK7gSgMfeg6e2oGd18H2Etwr8B1JKMvAJ4IwKsxNspeKJCVFoTDuYHmexn0+C1hDkbPRXVJ8pFUiER0Sc5C4T8SSzUoNgHvy8ZgK/LzCboSHt+HhZ+COkJQcODitsFYndQcVUMBSgPN1Ot7MQWawOYCfW4OLJr3/j07gxEv87vP5EE3KsOqKnK/zCjAx8KERvH8pkTzf2y8WPXr06NGjR48ePXr06PFF4aYlPXzb4BDEdqmGamKqxtDmGrWQ0hEaRAUrJHJCk02UkiLOOw0IERs8RiNeA9H49H4xIBbVjhj3QQ3qA9FHRJTCBaxJnfJx5nOR0xM0EHyHb1t8UxONw5iChZ9PsuixaDtG2iHBCyEHUYt6RDqUQFw4QkcHXTKBIia7q4V7VVRDU8+ZTvZJ2SYzUE9VjRkOVzFGiLEiRtLnjpYYE2GESS2MicIJaGyp2imjdsoqLbGEFWmZbj/PpecfY9kKJ0qDLUruvHCBr/2qB9k4cZpuPuXK8xdZdSO+6c1fj1jDtWd2+Omffj+nTp3gLW+5n9Xlceq+N5K6dm2REkZti9gaY2c4IpWWRDWHgbvTyYTnnnuUwXCVcyfu54677gI8mAOgxTSX2J5u4cTTtJZhZRgsedaKEa4qsXSMnGJEsVYzJxHxPhmaq+/Ae0SFwpZYI4mAygSaqhDJ1kghV/GJIEnZkDiRpEIwkkgkUZdkBosKE9lzIytzRBRjFDHJakrEEWLIrzVAUv0QDTHYRIaIw5ZlmgtGieKJmpgKUUUWFa6XgABFUTAYRJx1Lw4111TQDwFElNHI4Ks0xnbeoRHaWggNSSGk6bMly7ZEuBRlUmpYJzmTJKsdFsVJe4yIIM2DcpDmt3VCURjEgI822ccBKimNBwEj6fiNhougcoNQIViGg+JQPbGwwVKFtk3MirWCtcnObDQwiESGg5QB8mpgrDAcFhTOUpbuZQmPNBbBGkNZWowxFM5+XpVHj5sDvoB6CZBIZEq9JNTLc6ILh8XWZnyMMAiZNNhLRdZgwa+mDI2uSsXM+RLEU+l+1i2nn42X4KvOwbk5XAj71P4iWnTEYpYK443F1kXKXKo8oeqS/U0uFKs9slMSSiwjBnXg5CVhOPNUdERpU27EGIjQjXNfAHncPhM3FbRLiaARAK+0164x+dwjdJMD/HxKNFDMHeWkAgVXtbSuY4TDTsewukJiGJtccU/zfKU+4IHLz7/ksf637/+3XHAXeFPxJorC8uY7b+V9734ra8un+d0nP87VnWtc2ruNB6/fhzHKc5/4HD998SKnNk7ylte9hdXhOK+TydZw44JF3jBgJc6wn3gYfzBC9RKvRM/w8AhMFGyElaUpb169zNDvYHzBcP80hEC36mnVE4aeMEpzoasS4eFdDitfHNt4RFqIJgLMZaWHzWqgQlP+hneAC8xOt0SnqIsUXXpfFrBSyFFOR73EoYPnoW1WFTHLoNnnyDbpebJl0iBxP+lXJJtyJ5x/RYfmJVEqvHUOf8LC63K2xguxsNlaWYYHXgcbU+hOQtvBLcDpBWd/bAydJOJDNKtcFJ4z8ORSGvOhXZfLuScG7u/gzQtyIxMOC0fKTuCxEp4oc+xV3sQ2iaBoWhKZdgecPgFvinB2AiebrB4BFqFumq9/1SPiqnRwRwP2AG6bp+PyamBiUrHYkMisV4LlmBQ145jC0oefJ/5GgDtb+K6DxBne/hpnuPTo0aNHjx49evTo0aPHlztuWtKjnk5xIpQu5VQk32ZBNGZCYEFWNBhjqMwQ5wpitARviQozVabqEQ0UOsfgQT1qWxCDGodKiWqD73bQ6LMvRMAaS1Gu4swQ33b43TnRR0IR8UXAdx3tbEo7nyNlhRmZ9Id4WHTNlzA7AdUKkZqWKaAUNFhNAeStFEQpcKHANwYDOG0x6FHLrRimk13qbk4Mnq7eJ4SWE+vnGZ49gXUlMRo0VomcCZEYFXCIq0AcrUQiLernLM92iNNthszZGCmVmbF58WF8vcP5k2dZvvM+BsMh737rW/iqN97JvPFc2dnks9evcuvyG/j67/w25k3Lv/7wT/JPf+zHePe738oP//APsHrfXWAEcZK62d0A3BLiZhh3gHV7DCSwHIf4EA4LNtubm1zZ+zWWltd44599G9/ybd9EU8+5eulZ5tMDdp/a4pnPPA1tzXIYMNSStTOrlMsVIxlSSk0xSEb7ttCU3UGkqVN1xPoOEzzWFLhqJRExIUDnk7UVlkg69hpsyn9wAYrkK5IUOQWCP+wqtixhpQJRoq1TOD2SlTVgrSJWESkwZil91Q6jWfHBKClBSOoPHz1iSorhCIlCdJGOGlWPxIhEfdnilYgwGAyoyvKGTI8FFAhe6boU7L26kX7ufctsvyUG6GZCbJPF1zimPI+ogRA7rDOJDCgMPgY6H4hRMWoSGSPgyqSuWDhJGQPjJcdoZDOpkVRJHkcr6cCmLJxkrG5tgTGwvpqKaOnWtIygN+RrSLok6FplPvPEAIORYTi0OAdry4aVpUR4LPJKXimcs6ysDg8zPV6OvxBZhJHDyJjDTI8vxHn0Rak/SCjtCPZPQiwC5tQ2EndBIiIBo9AOoB4ddfG7DsoJDK8k26GDCzA5lzrQuzKRIPMK9ASJLMj858YY/uQGtKqcmV/hYLrNTBVosR2U+wVLl1YxnWVy/oDJ2S69v0k5Dr6EME7qMysjCtZZmkTu+t05wXkOzk3YvdMTyggb4MepQB+KbMnVJrslieln0xyEXTQgrWf66OMcXLlI1Ejr50QL5WTAxpMb2FZoZZtOOoppQfFVJ2DtbCI73DyrLtM95OzeFb7lM7/4kkf7r/33f43vfPN38te/9a9zbvUE3/XOt/ANb+343OVr/JP3/xt+9+JV3rb8Pbxv4y+hRH7pIz/O/zb5Od79lnfzw3/xh1m97R6UjsAUO6y58GDJhT9WEost4v/1C7RbisZZWnS/AH5+A+gSWTGcbfNHpo+wXk8Yb51nvHWOemWPnVueoRvOUkXeZEFLPq6LbAZIx3YRWm7CsfDwNqk7imkSxSyIieggVJ7de0I6bC4ynCcypE0cExVgukTKHZyEJrkrYrNahBgRjbgmBZ6Xk3QKYha6Lm3DEun8t2NobD7/X+SVMtak7vjmaVJavIj0yISHAOdOwbd8Y7KFWi1gNRfqL7QkZ8a81qtAbWDPQuVhuUlf378EP7oO28eWrYXqyAF/voP7DhIJUDTp+CswIhEoH9mAfzZOmSDkMX3zAfxXW3CyA04By1A4GHtwm8keq1iQCR3g07Gsh4mIqgxUkvI83j6BN88S4TF6hWqNBVyA8Sx9lkUGzxfCaZ/sxOYmfea1lyE93j2D+5r07/VXObYePXr06NGjR48ePXr0+ErHTUt6xBhSaDnpLzmVIzsHWXSap3LuYUE4/RF+45/5EUVQVCNKTB4/kkiHnIqRO9rbRHrk4kLUmN+tufKdQrA1Bx2nUOz0SDUSgx4GlCfrHo0FGkqULoVlZ5sjCEfB65rVBvkPW118rjQw0EjwnmgMMXS0bUPwLV3XJYJDNHXxR8X7iO88PkRsVVDERAIkY/GAMZHKwECyCkEMzihdPWOyv8t0uMS8bjBiGA1HrK9W7O5PuXhlh73dA+5YFm45eZbpvKaZ1jz71LPceft52qZNxz8XfcVItopaeBEFRAJVYVgeDvAuHNotzWNDW8+oyxJxgcGSRY3Flg5pHBGl9Q3atQy0oiArM6zFFBYxBWI1nStpUdK5TcSPYlJoBwv7MzGOxJuFG3iEI6sQQVAkp8Evwr0Xs0nQoxbbhe2ULEiJXHUQzRZM8bAwtMivRkA0+TJpng8a06uMMXnvMSkgOKp2fKHilZGXr/Irmov5SXkBSVERVY9CzF/4pvzZkopGcE6IPp1kzf8tBnf4+TjajjFwXG6hCFEMXVbWOAmYbOG2eL+1xz/Gy+deJEIqfa7Fzq2FV8l1HH1cSbkbL7e/w3mSO5JTR7bk5xWv6Z6Spt3iPnX0/6ONvcRGX3QGvtD3L43JZP6KXveHDWpArRKKlLvkSa3XNiRyQ3KnfHA3dvFHD/M2kR4tScmxsKdSSV/9wpEwR/AUAifdojjbEUJSVB0PFJfOYDpL1wmznFvgfOqADxbm+RawrBahwsWAzAKKodlYqKVSsdaTvkIee8hFeM3GQMak+42k9TLOakJXp89QAhYkGFxrMY1gRbI1lsIsoNNAGz2teEQ7inaG9QfYdp+16Q5R/iKz1YeYrT7E4z7y93ZKfuX5a2ye32J/vs/KcMi4qlgdn+XazoztvU2evvwU97fXOFW1qAbi9U02ty+yd/4ufNvm6yuixiMuUC457LrBL7XM7RQk4FxgkD5hshf7PN3028ywdoAV2HOePTvD2YaBHWDtCUwpsLKJjo6OYTohNZrv64tgcqNZ6ZHJjgX5sQi5l8XSkH8ugK8UP8zr0LFl4xByVOgPLpFeJnJ8SUlf84IiWfiqJo3p0HpNk02W4dgy9UXAagoiP/kFCumiUDk4OUyqiw0PJ3wiFIaL/d+w0B7dO022BetIhMf1l7hxFwq7kgLVIVtixRTa3UgiWjYjXAxp/5VJOSAS4dYOzntSZk5xtH9eaE+1uJcrN1i8YdNxWE5S2S8Koi+T/SEQYg6Af8FrVvODPNyO9NtAlBtfJ8BG/rfVZBm6+J3jleKlhicveL5uX8UGe/To0aNHjx49evTo0eMmwU1LeiSP/0jwqdUxqKQScFSky0SHBbEWxNB5JcRAVCFES8xF5HGRAqsdFUYtPlq6kP+CjgqhQWNIZIVYxDoMghihxePjPP01uWQwUVBjsNm+yVUtMTqKwRLV6CSoIYx2od6nLEc03jJtYrIcSf5bBBNywd1gYolBMDGRJSIGlQoVB9KgMkVFMZSYmCpo1g4QsbRtx/XNyxgRmnBAF2Y0c8/OtRltE1g5dZq1c+epBgNOnIHlNcWddvi77mB24hSb0+fYnBmiKelmlrYN1LuXuPTMNoOq4i1veSOvv+9eZv4Kjz75NM8+/yynR7cxWKsxo46NwYRT7LKqE1wMEEgkSmmxRbIYQkMqqPsSq0Pe8ZbbuO1uQ9MGtreV+Vy5ttvy9NUaFcvTjzzET/74ZdquYGdvRNtaltrLrBZjhuMV7rz7zZw9czsrJ5a55b5bGYwHSAyIBrr5hJ0nH2a2dSUV1DWAKlYMxhkwBSFa8IJGQxQHKCKCk0SG6cIuRKAwiShofUMMPhXksaQyXI3SJFKHEoxLREkmKYJCp5JVCg0iHsEjts32MmWyIUOJJhNsIWLapICJ3ZyuEKw4nKsQWyKL0IsvAiJQFCbZf4kckgzGOIoUXUIcCxqgqAzGptcMKnuosnBFso9yzhwW3qxJ2R4LpD72o8LLiFRriuRmWoWLteHpfcfIKvcuGU5UirOv3hbKOmEwtKgqrvgShoJrylWIHroOptP0/XwO9RxCUOq5x3eBtuuY13N8CFyZt2zVHZ1G5hrwi3ZnydW1WYRGoWtgcpA2yqLKmcncw+/bFzwHL13aSvtomp70eCk0ZzrMSibY9MjCyiw66mN6Tuyx7n0Pj3v4LQ+Nh7e28MYm5chITIRHlPT9Me4NOPLwdz6pN1TgYDllGlRjT1MeEFvDB9uGD12EDYXviHCvwhMH8IEt8NHwXfvLfAOnMQQsU5QO5wNlvUMoI8Gm0GoToarTuAY7huGWwcQKx60Y1mjG20w2niXahsGOYbBniaUyPxXwQ0WLmvmJHYhwsNwwG8Gg2mbjw79K8dDv8NFiyq8WE2xZ8rYzz3HX6hmWLiunOygZoaYgFsKKXee9S+/hjvJu7Db881/8F1RDx1vX7uOB1bt57pqn3h8CMJi1rF/dZaTCfzRf4au5kwvhHGfqCmYQraddm2NWa1w5xGIwukYV70QxvOGW5/m285dAleUa/tknXvrcD3/3X3Du/HcxHp7n6gT+2XU4KUO+5/6v5h1nvpZirWbljh3i8Ki6GyabuM/8As3Vz6YCsORCcCYbTEyCQNum58gZQ6FKBJSaFB6/eF70iNSI+ftqnuZMKODgRFY3BBgfHCM1SOd0MU/DAFqblEbtMP1svJlEOAYOVRX6aqvfrwKiKZjb+UTwFTnTaZjJDpOJt0VvwOI9S03OQNFk9yQR3jqD/waYfZ6x1gb+wQlYC/DtE3hTDY+W8AvLcNnAh7bAPw6nCvjOk/C6ETzQJJuoV4PF9aOSrv0vGTIPicClXfjI47A3OzYOEtlzaL9Fct68YmBzkZklx7Yl6Xje0sGJkEihUTjKOXkhVPJKIWm7L7WiLEiPQJqrs35J6dGjR48ePXr06NGjx5chbl7SwwESCcEf++NLwEfoAkTFlhbnHGDwQVMIOZEgSd9hjWFoU4C21ZA67L2l88mORmMu08ZUJRAsxlisODDQEYjRY42lHBfJBEkd4MB0ifQIlrJaYzg4DVj8wKIDQ1GUtMEwbSJFAaUxQCRoQCVg1KVcCxEkSurIFQt2CcyQyAHRpMD2RaVEEIwdYIyl7Tq2t68SNdD4Ldqwx2y/5epTe9RTz8nJnXgpGK+MOHuuYmPFMWgcxe0XqA881bbSbc1ovGFv4pi3gUvTLTZ3rlCUBWsnb+W+N5xi7nd58tmLPPLo7/LW+95GtdJQxcjaYMYG+6zoDBdiJj2EorQYJymjQUMK6fYFhgEPvuEWTty6Tl1Hnno2sLenPHWxY/jZhoNpzcXHH+Kh3/5JPOvM9U1ENrj/dM1XnR8yXlvhwoNv5d43fRWjlWVO3HqWclAdzpd6+zqzzU1m17cQjdicoWJsRKxBcSlsPkjKPhFLCrYHK5ryWjQVAAoBZ5Kap11YqKklBWoLqnOUOYjDsIHYEogYSVXOEIQukkmPNhEr1lMUKfzcYNCY5oMnpkwPH5E2WVkFP8eHiLgxxq0kgsx88aQHgCteXAFzznKDLuIFVduyspTVje23KT/jpbUUQirPH5ALN/kRgCb/7PlG+PS+Zb2EO1ZgNPjiPo8xMBh+CcmODAVCB6GF+RR2NpNP/N5uenStsr/TUc890/mU3b1d5l3HZ3amPL4/o9bITmyoNRxVLoPCtodJhNkUrl+BZk46Uoue3pbUv98Bs/wznx9wWDUDbixRBVS/lBW7L1+0pyLFUj5quTAcTTpyJnv4R5vIuYW1kO3gqQ5+3MOeh7/k4S1tUhSJQgxZ9RGOthdzZoE5lvtgfVKDTMawvwrVsqdbnuBb+ODj8GOX4A7gbSW83sIzHn6yhVqFe3WJb+AkQkCogBYXJpSt0JHyOupBsjNamiX7n+GmMHzOYsOQijspuMDuuafYPn8FXzYML1nGzznCUAnDiDhFXUu93hIN7JyF/Q0Yb24z+PgHqbbhYwL/BKUYC9//9g8jdwqnrt3NevdNlKwm0sPBEqt8/fibedvg6/nVvQ/wP//6jzJhyp85/18xOvUeLs8mNJN04ZfzhrV6n5M47tdlRtyGiaexTQF1CnHvVmvMSk1VlECBYYUyvh5DxevOdczfepkiKmf3Xob0eOQnuLD0dtaL8zwzhd/chFOjIW+49x28413/EW4VVm5TGB69p7v6GPrMZ7H7nz0kPNQkoqEbkALG51DUWTk0yEqhbId1CDkiL5RkaxVsUvQMcoB3PYD5cpqDo0kiU4IDn+2vDsPRNZMqRbJimi8lW6zBFpg6/Qqx2OeX0ktPFMom7WMIrBzb7SFeUHQXYNzAqD26BgHeWMP99UvvpxX4JxvwD06mgv69bSI9nizhX6zBYwbCExA/BScG8L574Js30t3x8yosPg9MgDI7VX6xCplXvjPAwpUJ/OJn4fmt9LSQxj3UG0mLVuDTDh7PhBnHHya9/sE53NUmwuNElyy8Xgoxkx0KdCYpZA55mIWiiKOfe8nZKD169OjRo0ePHj169OjxZYablvRIdlTJQCd1LNqkxsjVKRHFSEToQC0xpnDqRXfjwi5H8n+KQbPvhCCIanaPSn/lpcwBMDiEEtDcNRkQTYHLQkTFINnOSEXAGqJEQmwAg0oHNqDiCb7GtwEjHi00CQM0JZcqJttt5UqzJHssQ4diScXNxZ+iEVWfrD7U5zHlA6MREYMxFUikDjDzkU5BrGCswbkhhVuiLFoGhYeCZF+SK3TGgHOKlZCULz4SoycQEWMZjZZZXt5gsDRAxh0Ez7AKrFQwLjTZGAnp2EaPRJPlA+nzmXw+ZnNgS5nXge2tKbt7LQcHEd8FYmhoG09dB6J4MA3GzNHQphyJ0NHOZ9STfZpmzt50D+Mcq8tj1leX6KZ7xOCJYtJ5j8nWLKoiKslOTBemTIpmCyo95jGyKNioQvAxH284LDAvXmosIlWqMOV5k4oESQmCSLa0kqxgSI/F23VREUXTuRObbNmU9BySU0Y4nCPOOYaDMRoNTz99lU996onF1o5dNXLDF5OVGEq2scpz3+aXxHw8BDAqR/ZbJl88aVS5gHd4dI5sWY75p2i+6GYoE5O6VLdVGKYrlFqgjXBpS9neTvYtT08jYbw4esLRHl+Io58ffdpjn1uPvlvYkh35wMiLQ+D16LOk1+rR1nQxjvR/VfC1ELxQz5W9vUjXwf6ecLAvdF1kf6+maTx1XTOd7NN4TzOdEec1qhETOhzH/G+iQhsSgRvniDkA26AkQjQxhQtD/I6UFRNR6VDp8jGyx47WokSVLfk04nve40WINgeR20xMxFRgFE3Px5zjoPlSNG0qaq8EuKOEA5usZFwLJheuMUfkhr7E1BUF2w0oZyOMi5TNjLJtcdmKSAQ2Crh7COcVBjknZBTgdgeNKmOd07FLjAEJM4QONQ0SNOV0zAw0go0KGok2ZZPIqmJDQMIEjTuEcopoTGMtFD9KhEco0zGhOMqvEFIXfx3gSZ/sCJ8jq7hCQenOsTRaY1ieQKQDDjBBKZoxDY7r3TWuhydouuvcEQydlJwdlyydLRnuFZjL6f5WD/e5vvQkiKWqrzNup0hVIy6mKW5Sy3visC3EIq0veMBSdicZze6njDXLky0+8c01z4Rv5eHuL7Hdlfz6M/8jD13+KUK7x2z/MZwpmE2fp11kE+1ch8tPMTmIXPIdzSCyUcDJAuLWM4RmkqK14lHQuEm/HhzeL5FMluU8lcPshsVr8veLh4n5GB+zf1o8b/LtULMSxPijeXT4CEf/hkSo+CpleYQqj7Xj0EbtleLZ60fU6bGPdgP02FefVQIuF+mNZuWAgKhSRXBRiSKHmWyLaytKKraH/P5SIWrHdH6FebeNc2OGw1tQV7G3t0l75Sp1dOxPzrLdrLK3dUC9dZmOjvHF04z2TzGetVx9+hKfvXbw8h9UYFieYDw4i5EbfwXWo5cAEGLDZH6Jptt/yU05O2R5eJ7SjZm3O0zqy8T4EjdfEUblCZYHZ0EssUhz5vK1fbavX2Jnu6ManGIwOE0Qc6jtGygsBTAaiLMrtGELa4csjc9TuBF1t82kuUwTAnsNbHawbJZYcucxUjFrNpk2V1E9YkBsuUI1Og/GMZlfY9peT7+ncTSnFvCSHl03eflj2qNHjx49evTo0aNHjx43IW5a0sN3c4xzqBPEGAozxJoSYpOqURowNJjYoerwfp0QC8TlzAIxOI3YmDIgvBREXIp3iB6j2Xc/F+StMbn4O8LoSipR6x7EmhACbTsjqmKLUbJL0og6QywtnTTE+ioADTPioMELzKYTurkwXh4wKEeplC0VGh3QEXUKBHAl6qqUg6ERS0HKwUgZD1EDqtPkex7noB0OKEQwIgyqMZVdZ97ssR332e5aVqylXCoZLo8Zjm9lNL4DO9uC4aM0XUdFxDdCjMKwUgaDSOw6Dsw02TjFKY2f46qCe+5+M8vLp7jtvlspbttDuzlnztS87oRy6xpUFeBAtMM0M0wQpG3Ae4x6nIsYozz+eMtzO3PmswOef+4xJgfbNKFkFoa0Xpkc1BxMliicY2m8T2lT+Pd+E9ADz6UnPkcxr7m8uclDn/0sk/mMb3zXm/mmr34QjYHZwS6tKzEhoD5RXcksO2ezLALHrSZiCtAoBJVUnJTUou29p+l8ptwMSJkKNpm4sG4JUxapeBM0FxQkk2WClZByRsQgUmRyBGLuwFcXchuqpaBKQxKHZpLI4ShNCSoEX6MIy+MlSnc7sRvwz/+XD/Av/+VHeckSlUjanRHKoqQsByhK7Ru62FEgjDOl4mOg03QtVEFwEWxpsEObc1ksYkzuYE+V0FS3z1ZepgbpEj0oycdFXIQiEU2Fd9hoCJI6RgPKfq0c1EphI58btwyLkBRW6tIxFHkR8aFqk8JKBb2hipf+HWPKtUEU6zrEBDAOtRWIYDSm8SpIDmI4TqEE8UTSOUwKHMFisJJeG2NBzPlCSiIy5rVjPreEqMxaTxciJkZc9GhUZr5j6DsqhXHQbCGSSQ8FDZqumVHAuA5RJYgScpVUYiI3UXIOEHgbCManz5SM8TBCsuNDcgYSxCA89eQXeeP9CoYvwQ/hYJy+X57AsE4F//koqz5MWhNKD8UWDLfhrRZ+cCMVaS9ICo0OVe7Yd0eKEEjfB5s7/i2AMNy/hbWLryPajmA+zaC9fMhnO4U/ugxvvgAD4JYCphbuUfgrmu4Zd4dn2I3XsZ1STAKmi/iiwTUBVwvjvQozK2mXPdNb5tSjyMFtAX8hYsOE1YPPMqifxFc1LtaYFrq1wN4wEhzM1yJdlYPOh4BCEWBtB57Yh58K8DTwPDAHVtwat5z5T3jgrvdQNE9Rlr+M6lNUE49r7mQb+IX483yQf89bQuS/Dic4MRxz9k1nOfneZdqLI0aXLbqtPHfhYX7tq7Y5aYV3PbWNu3JAefoU45UGOwYOSRgDYQjdCngDuo3EAaPNd3Li8TdQddc5f/XnWJ0+xqf1Md4f/x5Xo7I5fwolMp08zWOf+fsUxQrz2fMEP0uhKR/+APrZp3jETvn/Da7yvGv5jhPwx09B4Wd0m4/hq0R+VZNUFPYOTFaoqUtzoRnBdBUQGMySCuKQoADEZTKCHIQumSxLUwQXQLLaQSXlxpgu75NklxUdiE/KEvHQ5eyZaOHgNMzW07ZHExh06XWvBv/ql1NOxiyrn8pjaoNFlsSCp/ECewJTk3I87m5hFNPcndgUfn7rzLPSKa01zJwlSjp1QZJl1dUi7WvNwykPvpnwO0/9a5648gHW1t/E6+77y4yW7uChS79C99yP0ZhlHj3zn/Phla/jcwefor76T7HdJnet/1lev/a9aHOFn7z0P/HjB7/98h9UDPee/y7edOd/Rlms3PCjF7YQHMw3+Z3H/znPb37wJTe1vnQ3b7/7L3Nm7S08ceUjfOKp/4W63XnxLsVy//nv5q23fz/OLTEtUtj8Yxc/wyc/8j+yc3CVC3f+aS7c+adpioqnS9i1cHsDD7bg2jmDZ34GLv0sK8v38FX3/GVOrj7AE5c/yCef+ud03T5PB7iqcH71QTbu+suUo9t48vov86lnfgwfjvypTp3+au697y9Rug2evPILPP3MTxG1OyLpjiEuSKqXInJ69OjRo0ePHj169OjR4ybHTUt6xJiyDpKyQsA4jClTFUFz4VU9EpukCokxBUJrIgKSb3uyjRIgikkZCpjDLkwW3fUmW3KLIDgMA4SI4JAoaFCC74hRERMw2TdhUQxWAjG0oEqQFnWeGJWuC6jCYADoMLcQF5CVJBoDSgcY1CYlS4xNIg84CkVXVaJ6FE+MKXDdmKQkMGIQu4wUS4jtqLFMA3Qiyf6rLCjKZZzbQF1D5QRxAYMSfEqhcFYRp5Qu4GixWEQ7gnYYa1hfPwU4Vk4sI8sNtHPGI8/6UFiucvC0kLqIQweS/V5iRDQpQQRleyfy5JMds1nNlUtbTA+uYKsRbrSCV6HrAl1bYNRQ0KTAdYXWQ90apjtb7JmCS08/w0O/9Vvs7O9x2yjw7jtXMdbStTVBUuE3kKyiFgqLlCOvh+21mgO0c1b8kTJDwUelDTnk2FqMJAXHQhWBLZBinALvYw2aMlpUk/JDhKSaQTLhkULdVeVQ5ZGmncGoxRoS4ZUlC0YMBocixOhRMoFRDJjVwsOfepKDqZBKUC+wOzKCcSmTpqoGDIcjFGXazmlCQ4VhBYNTaNXTxA6rMPJCGQVbGdxSkXI9zIL0EII9Ij1MWJAeUzBNJj0qEENRKFUZk11bVyDBpWK+zdRTyESUBC6VNWJ8uuY0Ze8ssj2O6UpSZTGW3CjYONSBEYMSAiARVzSJ9LAF6gYgBkPAEJEohxVpWZxLUTxdztkRNKb2fYulIJ27ZGtmMa6jrGaIiTSto20LgkIdA14jpRHGkq7aQKBYEC2LDKGFGiN3cqsBYyRl4CAEAb8Ifg8e0ZiIjGiT1YiLeBvzZzq6Z7nFEctG/iG8SjP7PyRQm0iJtsgF6ZhUGzETGH4RBE66skwNxQGcGcPGSpqGpk3PQ76V5K+H+QVZJRE1kSgguGaJ6uA80TaMJk8Sh6lQ3ZUpP+i2Eu5eTu+NRSoMrwPrAqhi/T5N2E9cv0/xUNEsQtENgz1HuVMwizC5RfBFtksaKDZ0uGILnXGYXyIRYg7WXqhCgsukjz3KNnBNCnD/nQgPHzuOxlQsjR7gxOp7YFyh5v3ANqYrMd0KgTlP8DgfZ5t7OMPbuZcLZh05NYZ7S1aloBila32yssnF2zeZWbjvAJoDkNEBWobkjbeQpUk+OKHMkpo5ouDm5xnsfDXD9jmWr3+MlcklOnZ4is9xOd8bBQjdPntbH79hPog3cOkpuLTPNnt8lGd5XObcewtMb4GhzWRDtoyyWT1hchbFIvheTTp+XZV2VjbH9qFHc+0w4FxunD+Hc+iYyiNKur5dl4mWrCZZqD8Wj8XvL90oWSDpBMZ7YJtEjLywc/+lsLb2Jt759h/lM89E5gL79khlUOqRhmyh0Iik8Vw3KWD8bAdhnjI09lx6DIMSDpSTTaR2sF8agiitSfN7auCZKqmnTndwawvtvOGjD3+WTz79y5w+45nbfVbXIlc/+wzh4V8juA127vsuLp2NbF+7jn/kQ0hzibX7v5rb7gvsTCZ8/NO/w1NXfoWXk7gIhp17XkelLYMyHltrjisG07O7BzM+/MmHeez5X3nBVtIrz6xuMQp/mumpyCefvsSvPfybTJurL9qnEcfs7gdY9R1FGdkrhLkVnn1+i+uXPsz+9FlOnXxnUnRoZNfAVZdsqooIpe9wu48hl36Fcm2HM+d3uGUY2dm7hL30m7TNFnsoe8AgKN1tBwQN7M6e4enNX6PzR0qNrlriXJwxlBW2pk9w8dqvEOPCv+ol5GrHPm+PHj169OjRo0ePHj16fDnhpiU9pLCoREKokWiJJKWGhkBoUoe+MWXKOhCLdQVWQU1H9G22h3CIpkqB04hKpNNIE5PtkUpIBWmv+C798etciym6VFKNISk6VDAyQAyJENESYpdUJ2FGqsw4VCFqINAkB34fkQBFEKJUiHG5VNulQnnubo/BEbtkRRRzWLEuWoZJ6gMRcgvoEI0Baw1lmTJIsEOgZHm4wl233MHJ9YbTa2fRrsTX0M72aWdXmc822ZlNqOdzZqFLIbyqdKEG7fC+JuZisBjBGUPpLEuDgjAqCfsNl3/3MqGds7/v6MrTeLeeKkOBFCIviSRQU4ItaTtld3Ofva0Ju5f32Lt0gETP7dUZynKZ0eqYlVNrBI18OjzKkzvblNGzUVsqX3CqGHJ+OGYYC05vzRm3W5xtWt566wmm7ZANV3P94qcxOOb7Dt9YvI8pdVgjaueobVAcyDJIibiIKSIiQmkLnHEYqxSlx5iIERgaTR31ziKmQI7/0W9Ac5HAZFJADlNnc9FeUiu3HhYRLEiFoMSsPAmqxNDgQyTG7rCuoJofLDanuZgqFE5YX1aGZZrDURf2WknpIQZsoYhRnOsoijmglK7B+w5L6ihPmRvJfkoQBsHhokUKxVSpJVkExCxUCkoUxRpJeQY5nlxpUxuzKYHcwaz5eBiL4FAiQf0h0aBpwxAdqgudQqKnJFvXpe9s/pqsnRYKByMG1UDQJh1NsWgOple1yc4sWjSkcatJVce031zRQ0GSmidqIGggaSZs/rRKyNZiQqouavR47xGTyAgxitGI0TZnBsnh+dBMriViJc+BxfzQbC0mSQ204DmipEyiNHNinnOJ2hEFfIf6JitwHElJlArnkgldVbK6qccLsbilLjI3gkuWRItCddFlC6xMgoeldBvxI2hW0+kb7Ocu/nCUA3JobXWsemo8DNqkQnq02eaX9VEcnjvlgJMCtjGUO44QhEc6z+e6wKiA+0/CySoVu4tcPO/KNIZimhQoMgfnHbYpQYRQKfWpGj8OFK0ik6QScG0ukmv6nEVdMdxbwnhDMC1RWtQYRkVJtBa1dbbAgsFBSTEvGM4Dpms4ijsG9VPqK7/O/uMN7tIzVO0eCjzMhN+l4zkaniMN/inm/CRXOUfHg3HK/QFOjE7wbW/+Nu5evZuz1WXueORplkLHheeE8Q64vVuQeXkYBCQ+PdDMIFAAa8AYoxU2RGxwiJ5FuJN72OZ7KdilITAlMofDJgLBUGEYsI7jbpJk46yDbx3AFQdvGAEVxGgZ7C3j6grXCOVEIGrK2mpm2FhQNevYMMDNPOU0mRJVc6FoheA6utE+wflkkZUvS/MC26lFFkxwaQot5pSJaZ5JdvqSBdmST4XzMJim5betMnHloBln8mye5+UXuB207Q7PX/4A09mztALz3AtScEzpcXys+ft9k2wLJcBn20SSzA3MLCzbFU4N38aouIVr9TM8cf0h6jglSFJ6NAJbRVJ8TALsduC7fbYnjwFKPb/Cc8/9HNvbn2Br6+No7BLxa4TaWrqsQFT1XN35BJ9+5n8nxI6TK29gPDjP7vQJrmx/HB9mL/q8irK9/wifefZfU9rx0Q/y5xaxrK29gbX1NxOqFW4980cZFusp28KA147d7U+yt/sZ5u02T1z5ALvTp7m4+Vs3KCpu2KdGru1/hk9d/FcMqpNsnHw74+U7KRfkmXp2tz/Js0/8GI0rmGfCb7eFR2qw3YzN/c8klWG7yZOX/wM7B48xb7d43S3vo+32ubLzcXYmjzOpr/C5S/+O5cHHuLTz8fS7xTFMZ8/y7LM/TVmssrPzMKqRolznxMl3Mhyeo8pB6JDOZW0hxpZnn/yXLz+RevTo0aNHjx49evTo0eMmw01LepiiQs2UrttHxOAoMDhC21HPFA2CrYbYQZUCy11BIUIXGuruIGU5yDJilhCUQgNCwGugjZEYUwFXJKI+4psu5XuMB7hBAygxdsTgUXVYMwC1ifSIFRIU/Ay6HVSGYFZQFSIdXuapA7yF6KEKcNqMMMaiNMkiBwVNio8YDEFtIhxswIhiokFjIm2MVaxNtczgS4hgy4LhsMQYk+13LBvjIQ/edwqvKSVTa0snQr2/yWzcsr+/x5X9XWaTKXu+TfYsMRD9BI2RppsSNGeeiOCsZVA41pcqSh3it2Y8/utP4tuGzesFzegOuvIsMZbQQQwWL0X6nG4AxZB5o1y5uMn2lV2uPHHA5uNT1oYFb7zrTi6sDzl5bpkL924QQsNvbG/yiaceoQjCyrSjEscZc4rbqlO42kI9QYoJo5Fy6r5bCGXEx22ee+Q3ka6g3DuHrZcJXumapBSKxT7RHqBSETiFyhDrlKIMWCMMx0uUgwGuCrA6x5aBclBRDSuMdUhRIG5w2H0LSqcBH2vAYEyJSAomjz519Bux2IUtBIvSd4FQkPQOLZEOYkTDlM77nAmTi/0xqU9S434iX4Rk81aVypkTAaLio9CGI9JjwSW4IiJGOYwQVyV6j4aYKZc0KmsrjB0gGGwcYCiItESZZ1VLUhXEFHICMeKsoXBJKaGhgViDlGAHiFiMCjamsr3YAnEFGjzSdahGxBiMSYSGhipZN0lEJGXmGPEpAwebivhJKpEydUSwUuKMIcRACJOcdTMkyjBbPKWkV40cWl6JC8lSDJOJJMlKrjYRMlHxMSJisabInf6ZgFDBohgsMXTpvEkEsRgTQQMu1AgNJqbrGBJZJAuBx2HzbAGxSvMiEy3GWMTYTHhGIk0qeJIempVeqiBdmyqZ4hBXIdZhRJNSKO8nINArPf7/7P13sGxZet0H/rY5Jt3N6553Va98ta1qb9AG3gOEkQAQHI5oxSE1IZGjkWakUQRjODEToRlS0EwgxBiQUgwIEoYg4QiQIAACjW60RXe1qWpT9r16r567Nu0x28wf386891VVA91ihFgt5qrIynw3M0+es88+52R+61trvSraXIrCLhWg25RhoT10Z7Jbm0KUDwZoN4Cu/Hs2SEqJBorDRHikgHJFUgMsitpBniumENrIJ2Y3+Jm4Q5/I/063fECDnRkGL3Rp55pPxTk/w5xTffgr29DvQjmBTjolTPow3oCOgn4DegxGFRgGxAymZ8ZUG3PJUagiRQWlBZ+JcqMpZTvLUYf1a2fJ5zkthzhGKDKsGqJVQdXfY7ZZEQl09nrkoz69UGP8PnCUZByaQ8bP/zy71a/SvVNiqyEew+9ywE9zmwmBcVJZfI4JzzNnnQP+VjjgIRc5v3aev/LBv0Izq7Gf+AjZv/p19GRC7jSZ16jTD6BGXZiCqpK6piVl80SgAE4CA5TvYVzAuBwT78WQ8Th3eJA+nhkNL9FyG9HVWSS1a52MExg0fTyKyL0Z/OUNqAtQQwgd8POM/p2T9Hc2JEckWCBgxy+S6wpNlzJexsZNopoR9BgI6GggGurBiP0LNT5zpN6LZbC99kJ0BCtb5K3MTxUlgFr7RKy18tgcC5JehKJntag6goU4PCI95uvgHDRjvnrj/jHM5zd5+umfwehiSWqQ3vrVOJPj6o894Fo8em0AtnqXOf/I32Zw4hIv7D7JHzz933I4vybvTdfGRZi2jnK8xRhonORxTCbP8+Uv/X/QyuLcDO9rgoLKGqaZobJCC/vQ8Pyt3+bazkfYGNzP2x/6m5zdehdfvvbL7I+fflXSAyLXdz/GncMvJIXl3dA654GH/hoPbT1C3t3i4Xv+HPm5H2VmYM9C5ad8+am/x+jwS0yqG3z6+Z/B6BznZjTHFBV3f2Lg6u5HuHn4WYadC7xP/9ecLu+l69N5PrTcvvG77N35GFEpXNpvtyMcRCAGWjchEhjPrvOZZ/8+Vhc8eP6HePuD/xk+Nnz0qf87+5Nn2Z8+yyee/u/RytL6KT40d63L4cEXeerJ/ydKGZyTa2inc5rLD/wFTpz6JtZbOFPJ/rxZwG4ObTtekR4rrLDCCiussMIKK6ywwjccXrOkxyKIWOypFp3SKZshin99ZBFevgiOPv4bf2F+kwol6Ue5ikcF4oUV0aKozLKoEpbvlBZ7JT+OlV6uV/oIWH5KPBaiLj//Q4z41NUdYkxLTX2ScfFORUy2NJBWgSiFzkVVQS8/Rv6hQGmLNgXaaEKriUG2wRqDjiljQeVYYwjeU9cVdV1TuZaqdTRBDH18jDjviF6Kyp1OjywvUFrTNDXOOWyWUZQdiI7p4Zy2qanbgFcWHzW+9bjG4ZqGuqkx0RCaFhqHChGT55iiQFETmgqMJguKMkIZI0UM+BjpEOkClkgZPBmRzDlM69Ah4mLAtwFvFFm0aAVN0zCZTVAuoxxPsZXBe2ibRHrYSm5EPHOiktB2n3m0ET8X7yPGeZydY1pP4WV9lM7QrgBr0dqgTYbSGpUFbC4+JZLPoolOivPLCpFSx6pFcallkEr4QteQ9vNy3i0n1aK//67ZrIgoFTFGlBwqJM/tCEqJckXrZFemEVu0pFbQOi5nn0/zVRuwOvVAa7UUlcgxFpbzeJFmIoH0Ea1SSLySOa+WfnFpO9Mxu+hsVolAUYlEWIzN0bYvxoylzCUuaYe05JhoGJX2a/T44AjByb34W6FCXLg8SdqJEs1GJJEeQQv5QoNCLOmcF0szsdETpcliDEhEisaLMiQ4sUZbvC5GvHd472V9F6RhSPvo2F5UUacubSWWaVqhdSJatMYmHxwN5FFhogIMCsmPyZyi8KLyyIs1jCmwGrJUtwsoglK07u7O3hWOoANHIeJJoaFiIjGSTZVx8hjhjsXCaKHGEbcxIUC8wrSKqBdqoqPXgZAoOkCMnpaAQ8i0xWsW6xAAF+W2bKMn5U3Bcj4vLNHQi7OE2OX5LOILURWahbojgBJeFZUv1kehnUK3Mrdiug6KlV0iFLM1AoF5LJg1igpFHwlwV1kJeZdhHmnaKTujQzqzAT6UBHJu03KThupYmTxYiyt6tL0eY9+yc7iLpURlaxRdQ1RD3NTAVNMkJUbmFD0PJh38MZ3j4hTYh1hn0BvA+pDYKQlaizVX+q8EOmgimgaDI+UFJSrRYshSJo6cGwI5kW00Ds08wMyBdgbdGExjZCIk0loHi+HoJmRKhsGmnScKTd0atLNob5cWV0SFdhnaG6JRRKUJRqEyhe4pIQBsmoOxJk5mhBiW31/uQtrPMRzNJTiaJ/EVb3h1xOhoXiWH4muFB15+xpmbHtP6DuN2l3Fzh3F9k0l9c/m8VobC9NAqw4WKmZ8tv3GBKAuaeheAXJf07ToDs06OqC5VPNJQihrXEaPkoGltsaZLXmzShgbnZwR/d8CJ87OvQogI6dG4segxlWRbaZ3JsaJBR5vIEkWILVWz9zWNU+tntH7GtL7Nz3/0zwDwo2//x6IoBoheumTw4KYQWhxHBpbLsUmfKTk3DWt2i4inn5+gm28tx9FHhzIFuSlQSKi8jsmiLEZidGBKsCWmu81weIoTm2fouqQSAwYZ6AyapscKK6ywwgorrLDCCiussMI3Gl6zpId3kdyWlGpbbIhijo1Bwr3LnqgylEI5KcKiVeqAzNB2IznKaOkQj+BajQpS2O0UqZBqDVEblA+UuUOFgNI5unGpgGXwRQGLYmUUm51IJBqHznrYmMq5Sn64GnLpxI4Oa2dIukRD1Y7wSHe41lL4kk5HhVGaLGU66EReEDzez1BRE9BCZGiFLhRaa0w/Rw1OgDLMxzNmVUVTzRnt3cE1NZfufz33P/omtNHMp3d47oU9pqMJtw/GVPOK/api4h1t2zI9HNNUDedOnectj7+fTreHznt8+onPUnZ6nDx9gRNn+oxvvsCVK1+knk+4Pdpj1BxyMN7n9os3yWLB7a98iVtPfYLCWMra07s5YlMXvPk7PsikhjkvcP1LV8ibQ/avfRGzs8OtlzKefbYkRM/1KzfwsYsn4GjROKbzXe7s1qA0lY60OhJ2wO9o8cV3UxpXQWiw9Q2034WgxR4MCLoiqAbUnIhYkelk3aWUwmYaYxXeROrCEUxAG4vJDEplGLOFVn3Wu6e4uPUove4aZ95+grNv3cZFx87OPrPZHDXdRe9fRflWClkISaZinoptUvVa5IIsCnCiZrCgDMqkHBJdgzagLJLkC8SW6KW0FJSW7vIgxX+x5JDtiWgpyniFix7nG0BhtMXYHLFrWlRVTVJ/ALZGaVEyhNAcIwDFLipbhLSHgG1TLgWWoHLJMnFiJ2bI0UrM7YNL9nA0mDiXozHm+JAJqRErwBGx+JijEJWIUeCiZ+4mQj4pjRLGhUrVgCG0Ne1sJnZ3weN9i9hgzYm06ZgUNkBpLzkfUY5QqQYuSnWKEDvEWABarKNQQAXMkGJpRyztjlcWlU/kjceHGTFWQEyk6kK9IlZphY4YIp2wTjcUWJNTbg/JBl0p0OUdUXvkHp07jFIMVEGpLEWvx9rWSWyeYTsG2xFbu83NLmUnW9pbLRBRzGYzPvyxX/63Pwn/rwx5DZ1dGNyWqaDkVI1JVlI6ddbnM9nNtk7F51oeBw0xg9EZMK2hs9PD1pZ6WDPfmhFslLD0DDIFuZFlvlMVrNPBqsj9dobLGqqhh0tzglM8Hhx/I0Bfw6MVrN+Srv/DTSleK2DtUAqRfhPmHYimIdoRwUaqYUPb4672+3IK5ZglYe4bscipy5dwykDdEFuHLxSzszVuoClO3U/v8ncy94p/9dFP8NHdpyhxfIdy/IDW2AfeTfam76EOFc9/5Z/z3z3/KWxdU7a3iWg+w4z2ZbqAN5x/Az/01h9i2Btyc/8mf/v/97cx3Yt0zv8otneZZnePeXiKyB4LMvjBUPAjbs75Vsah2hQ1QPlbGj5ioHsGvu/9RH2K6vktDl4Y0Ez2me0+RZcnkGN3CknFkbFFxBGoEdO6aVpPIUIUQOspDgZkpkM2UnRvg3YWO/V4xigyFAUAhg45J1FYAodE5onYFd+qBZGiq8DazROEbIuolNwoceF+QjxJVXQYr63jy4y1hzuceEtHiuqJgJtf/RSjz/4z/OxgmcVinKiATLJia8uU9YHYsxkH+Rz8wh7t1WQa/wtg1uzwxNWf5fmdD7E3fZaqPbjr+fXiLG85/UOc6N7Hs/t/xBO3f4Pav1IloTE8Mngnb9n4Vgb5CS7oy2yN57xUNZgQ0Drn3lPfyr0nv5UQHdfv/BHP3fhX6GKD+x/8q/jYcu3FX+f2rQ/x9QyGjWLx5OtdvnTllznY/xytEjsuHxr2dj9NjP7fcpTgias/y6zZQauMs6e/mfNnvp2q3uWFq7/M/uGTf+r7h/OWy7tjrOniNr+Xs4PXLbNTvEp2YxryELk4bdmoPdPMsNvJqIzihQyuZrC+ucUH3nkfj52DJwr4113JbfmWGby1gvkMfvYf/ltv7gorrLDCCiussMIKK6ywwv+ieO2SHj6idEGueigiJnp0Ij10nkkotGuJrpWihQ6pMzdDZyVBKWKsibFJDXQa5TTKKspcSfinzfDGYkIkz0RNEFpNaLxYGZXSCi8BpCF1pTsJTo8ebTpokwENnpkUOshRykJsMLYmRgkrb/yEqAw2k95Qj/yojCi0shjEMkjSbwOEQPDii66whGhRVmMzjc4iuszQ3XUihnrqmfia+bxi59Y12tmEe+5/mAv33ENE8aUn93np5pj5bMreZE7d1IzahnnwNK5lfzpjPplz+fIaj7/lXfQHQz73lWf44tPPsHniNGfufzPrZy4yOtjn5sGI+eSA/emIaTtlPBtxcHuXju5w6+oVrj73FD2bcUltwKFicPk+Bt/0OFXW5+lPrNPXFt28yOjO7+F5ihbx944oQuwRKQm0zKkJOPabFpoRHilBNzI6+BtH4peFJkIh3ZyaDIsUsQM+5SQEFC0Q0Fg0WZppLeCogX0lyz9aZoZljGaNc+sl+tKQzfWTnHnXQ2w/8gC1q9m3z+H29yUse/QshBlRWQIGhUldwCopDo7UEAt/eTDEFJiNTooI3YJKrZaJbIjBQZCwbaUzolISbh/bhW4jER+GEAwKjQ+BxjlQilxnaG2PxipG8JHQRpTyRCOSooiTDtBFi7UChcGSrNaiwyxKhsaCFuslnIfoiSpbdsHiPSEEUA3aSC6AjwofjRQGVQWqIcZStjPqZa+08555U9EGjzEGYyQkPkWSE6oWP6qJbSI9QkPA0XCQjkWNX6Yg+3SDuxU1HunKXgcG6e8Lk5YxsJ/+PQA6pGjhY/cF0odbAfPFmh9bdsCqSN8EMh3RPqPvN7G5ore9Rq+7hTYZJuuijCHvRLJeJNOaLd2jp3MG21ucvu8yRbdDb6tPd6NHt2s4dy5nMDDLubpYcwWMRyP4C1/93PrvK0wDgwrykZAJ8y1o+lIoNk2yEVrwWnERFA5GSwE5aJitw3wNipFm/UqH7l6BDtAM50QT8UZsswhSjDYaXq8y3k4fpwK7pmFiG0Iv4IsaIjzk4WEvhexyBNkIRlswPSWWRWuH0J3Ievk1CANwWUtbtgQtJIu3HLPgA1vJbTEpvAftatq8xinQXqNbLeTK6THzbdi6+DY2X/ftVK3hY1+5yj9Un+CtMfB3FDymDfmF11O+989zfT7m//TC5/mFG59CzpjS6X58Li5w36n7+PF3/zjDzpC/86t/h3/4O/8Qvfkmhu98L8Xpy0wPDzkMzxO4s3zPB+I5PuhqzjvZrnoNzAjCxxRxR6M+sAV/83E4dZ76dxzjPUcIkdo+R8Nn0rlVzr8ZG1jWCNRiTYcjUBGoEeo5R2HBKbJxF4DiLn2WxzNDk6W0H3mPZmNJoHgO0WRoxK7SUxNpUG1Bd3cdlc7hoAisUfF2Gh6g6Q1p9DkcHfKTQ7YeX0PnRwymW1tjduNf0Y4OMIkIySohNWwrc9jnKaMGmce2hWIOrpXH/65QtYd85da/RKGW173j6OdbvPHk93D/xrvRSvPk7u+8KumhlOae3uv4lpM/Qdf0AY2aVfTrFh0jRlnObLyVN9/7F9mfPsvvfPY/5/nbv8M99/44b3rkr2Fsh/H4Oe7c/vDXRVLYCEWAWTPihZu/zfPXfg3u2opXm+1fP56++S+BiDEdtjffwkP3/0XGkxe4s/uJr4H0iPSaljMHM7pFF7bew8nBt9JqmMmU5tDCvoVuG3hsr+LCtGWvzHh+WDLONNMOXCuhvwWPvVHzzefgpXV48hQ0Cn74NnzzHkxf3bVrhRVWWGGFFVZYYYUVVljhNY3XLOmhlQMsHsQSZ+E2w8KkZ1GcFHh1ZIgT8EKKRA/RIXZYQCIWxPt/4aSTjEJMjtYQgycaJz9pA0R/ZLdz1CkOS2NqFo+NhDerTMLVNRTGYKMmM2qZZUzQxGTKvVhENJqodSJTaglIJwMrhXupl3ii8rQeUbjMa/RBA1hCE8gNxMzS6fSxaPK8xCjw3lNPKiZ7E6bzKbujMVXbMHENro04J9Y+bYx4pcBKpW7eNByORwSTc+XKVcaTljs3bjCajqirKdP5nPmsom1bslzR6VjW1tfYPn2WHI2zhoNmTn3nJpPPfJo5BXvXnyPEKyhu4ZnjENOhEHXaKx5FK/fJdmyRZ7BwfVkM4/Fyw+Jx6tlNJS8hEMQsQhQQMt1jiogW66SGSIOUqtsIi4xZIQcCiprIjGm7y7XJs4z1AafuwMH1iI8Of3gLPZui6xl4TQxZUmmktUjWaTGKMkP2eziyUAJU9GKFFgIuRkLysIkxFdCiwjctrnV0yg5nz5xiMFij9TW1m4v9CQ2oFqML8mxTPMZDS+tqtNZ0euvkRZcYJMMmxoj2AR3EpksXOVjJrfBtQ1yEigAqWnTsSWFPOaxugUhrHF4nqzbx7sFQYGJnMdmT94oDXYEKND6n9plUk/VEPHgoUaqHQmNo0Dha5zicTWmcw2aWLLNEFK0zOK9Q3mPbGhUCPhh8MITomLsRrZ+jjEEbm+aQEBAxSvE3RLAmkGULCmgAdNM6yzaHOCUE8ZdXqosiT6TSgvToAz1kxoyQ1GXp8iZGvPf4IGTHoIjkGnphg7VwiswW9M5t09kcEjB4CiKGrBPIOkJ6bOcdeianuz5k61SPrCzJejk2N2ir8WjaoNAKjEnHQRQ7I/+1+tr8e4Y2h5dq2BfhGNstDBYWSkbOL1r834hKcjDC0rIwFZntwj4oErIWXyiidkfB5slqaOrg+hzaOZwznkubNWSiAMoqWdYiB8TOk7okER8AWW3p7+W0Bm5NGg5njp6Gi5koQqKWUHZQ5LMc5SzBetqyIajA7RqercW+7uQA+gX4dJwqBzqLqE6k6UPdidQ5zBrN6FbBvLGcm2W8DcujaIaxIIs5GV0MUCrDA5zgHdzDPnOusMf8FQZHAqUURhuxEkTOgdYH1p3kkygPh8n6cYEQWwiH4PYhzBMJFQmhwocJ6uAm6kufJ96+TeeqYvtAUU6eJ3cLu6KFgkMnhcecQCuELscL34vrQkyPF0aa6q7XsNTGVUeqPUjnb50IdEXE0xK5QsMtaoYY7kcxWBLckiWkOcByk6nf5+lqj6nOiLs91q73sValORQJN54hHzXoiShddEzzQ6W5o4SYI83LYCCkrJCvx95qgXc9fBnyMXT3CNEzPpBid17AcAOyHAmKcQWQQzgNDOXiWcs+orwBnRvyvLuIhI2QOOcA2Q3I7nC6V3LvxYwzfcuDQ8071xXTNpP3hJPLdTLKcuHUZfzZDl4XrLWR0sOl8TZvXXucA7fLo5cvcu4ey6AyvM4WDA9KLpzMeeiSweocO7/Mic67iMqLPZ2C2xquGbkeZLtgJzDI4dwa9IqcB++5yH33aGZ1yYF/kOGZdyzXKarUKqGgauH2Hsxf+Oirj+mb3wXAR5/4Ks8//k65buqS+++9yAPnLbN5D189yoWTh0wM7GTyWQuTtTzARgudoHlk7QG2NrsUWUY9tJQ9zcQqbhQyH2ojpMfMKa6MMqq5wlrD6dywZTRP94AezIbw1AZ0ezCy8IY6KUUMfLwH81VM1AorrLDCCiussMIKK6zwDYjXLOlh7Ry0ofZilaOjFPi0iljtkqVLXEYnzJUn6JQ/kH6gKV+Br4hB42JOQPIuVPKDiC6KR7/JMHkfqy3BjPB6SggR3yp8k7r0zaJYkkO0yZtqYfRuoelABFN0MVlJruZ0yin4SJkbjJVcENVacDlRB4LxUjzTlmByYmho3SGhOUDna9jeGcmVCA3K13gCdd3ias/hKOfWtS2MytnaaNgYQEOH7NQFXOtZX9skw+Prmv2rO1z//DV22wnPzm8yCzWFLSmyktbB1EVmeCoDobT4wnBncsDTLz6PuX6D568ckOd9jL+D9i8RXMXB7g7T0SHnL0xZG1pOnemyZh/k3GbE1RWHtyfsjHe4+dxX+OI/+seMx3P2b0QaF8mYU3NnGdQcyJLmoZWit4IsU2htwQdiKxZOFdJXbGChn7irJ1cjCodFuQsiKWKagKalQ0BRUTNlTiCwk4xVjvfwLyCkxwEw5sb8gKvXr2J3C9wfP8hg+AB5lhFjIT3AbQuNzA3JmRE7MoxBKU3wHnGnCijrJTwAsSxR0eN8y9x5XISeN+BzPA1NHBOC53DcMB41XLhwgXd/4D28/tFHqZsJs9kewdeE5gax3SUrhvQ3H8EWQyE1vMfYjPXTl+itbxMah5vNiT5gjMMaB9qgigHYAl87mllNDB7v5/hQoVSO0VsoVZLljrxoJTNEG6LWdzW9tq2mbYTky3OwRslGprJhXUfqBrF+snOUEaLGmF4qVAolVdUNu3v71HVDXuaU3ZIQNJNDQzXVdDuK7W1NnitCgOAVrQscHM6YVy1FYekPcozR+BAJURy4pjPZVYN+ZGN9QRjcvedjhLrxzGtxU8+tFI+11lhrUTqFPbBIr05pDRFCiIQA05lnVnnyTLE50BS5wsQMm8gTU2TozDKvYfcA6hZs7jGZJ7ea7UFBv7RYa8mKApRmXMOkBqU140Yxj9DNYa0jU61uoXWRafXvyNPmNY7DIXxqCr9+KKHgP9mHb0pcl0u5F7YG6+WUfrgJdVcO1SzlgLhMiso+89TDERiN73iyOqA9tFYK0M/O4OduwvUJfNuZih+87OgT6Uw9/R25XEw35HO6h9B7EbkmDSDm0N/rsn79BJOg+A2/w6/4A+7rwF88DY90hfBoc9CtYfOlTdZuDWl6M8anblHlNb+zB/9sFwYl/Idn4c1bSQmwsTgcI0RPm8P+FlQdRb2XM31ugK4yvvX6gA/EPgO63BPP0gkDtD8JvmHdK34yPsZ3kfFRnuen+AOu8FVyDeTEvoi5AKAf4I1zODuFz9cS1nxXbkGYQP0MVA7d3EQ7j/KONu5QcYB+eob5+zdRWY+zozW2R2vgD7HVTRQWhUVTJIphjkcCoONShRWXjRORFpWO47upF5IiL4N0RfFM099suhk0HVFi0hCYM8LxS4z5dWa8mcDf5ASPLFWFoGjJeYqMZ7jRzPjZvTvcGLf84GcNnWgoFRTJVk3t7jG8erC86MXEnUQLbVf2Yz5Nxe1CLj8BIScCiRj5OvBTf/FH4dTn4fIfUPspT3wcnn4Stk/DW98L2yeB6RDGp8Fvg/sR8G+DiYJbQFvDhV+Ei78A8QRM/mNo3iGEyASIM9j6RVj/TXK9waYtKbThDcrw3RpC6MPox2H2fSyu6lEpbm2d4KXtDWI0PLAPF2Zwr38Lb69P09Ji189g1y2NyngLW8w4x0azyZnKYH2X+Xt+hKp+H95A3ZFj9NcK+J86MJvC2u9D//PwxlPw5x+Di+uK3uA03bWchm3e0/4l9sOPLMcpAvsGDgy8tAO//mF47u++/dXH9L/4KQDe/uNf5fn/+qeEQYmabuc03U6G96eYfvNfpWl+jM/14V9vwdhAP0I3wskG3rMnYePrdovt7DRaWS5bQ2vgWgf+cFPmxK6CJ7XkPT3lMnJveU+l+GsHinUPV7fgQxvwUgY/3YdhBm+fw/9hV9Quvz6Av3Uasc9bYYUVVlhhhRVWWGGFFVb4BsNrlvRQyi/6pqUTN5VD7aK6Ghf/E/sEr8RJWxEw0ctP5pgsd2KU8OPUzakj8r4YiCGKb7q2KJOB0UQdpEgSNdFrlobaC6IlHl/PxLp4ab3U0aJVhtYOY6QInxnJW1CKVDFLhWIVloZHUUmZPoQWH+ZAh2gUymhwUWyyoqcNNS54fN3gJi1GKzYGgdwoVGZpOz1cFrE2J3pPaFvqyZzp/pSxn7BfT5jGhrVSYyjwKcTZkXgcrYlaUbcNk9mU6CvGBwoVc3qdKWu9CYSGeVVRVQ3OObJMU3Ys2XCNbjhNNZuxd1Az8mN29nZ44fOfZ7Q/IsYugS4h+auLqkKnblsAj0YyDTJtMVpLcY6lVf0iW5g8PT4iPo7+06mMBVKuWmhIpDilcan4FYjUiPu7RXr9726OjURaIi2Vr7gzP0C1hjs7msPr0ClKOp1NbNYhBiM3smQLpVFRfNxZKHpCTHZRMc3aFMYaAzGFuYuwSAlxgnQ9+9hStzXTqsbHwMlTJ7nnvnupqxHTaY/g5oSqJdQteWeTtZNnyMpNjI/YEMmygs3z99HfPEWoW9rJjOgcNnPYrAVtoVgHW+JqRzOpCc7j/RjnpyhdYOwJtO6QFZ6i00rGhs5A3V1ZqxuoaiEjO6Uie9kZppoH6sqjVMDkFdo4jCnITDfZYqXXVTU7d/aoqpq8U9DpCekx2rXMxpr+wHD2gqUsNTFIh3PbRvb2KmYzR6djGa6XGKPwAXwQsmM8gaaB4RBObIuw6dUwr2E6B2KksA5rAtpo8tymgPdXIkaWnzWaeCbTQJErttYNRf7q75nOI8WdQFVHjPWYzJFZxYlhQb+zMNSRZbuRZ56UOS6Ad5IbsTwlBgllD6uu3FdFk8Ft4KkGegoOfSIAdOqOP8ZjRyUN7XVHgs9pWQafgyg9fO7wi0yFcLfSY+bh2QqemcPDOjBaa1BAOROrLJeRVGgQG+k0x4Dryu60jaF3UOK8ZjdanpLVvKvjOohLI9m8oHPYRXtPvaZxEfYaeLKFDQt7RlQrPoOQcVfgdWuhKeWeRhFuK7K55vw856Qu0bGDiWvAGiHk4FuMj9wbN7iX87yLv/unD/xxZhq4vf/H/NK/ed+f8AYvxEcYQajk0hsiQdd4WxNnAf20A3I6bNFni8Cchgqfzv4qfbWJNMnKSv51dDVZkB7y97tJj8W/dVIPmqQPVCy0YSktKBEfWbpOBFo8L+L4LA19HHNYnOUXew3NodAxYZ8rzfNc9XNu7cH0errOJfuqfALFWNQw0SY1kpW5E43sR33E4xwpPPQRQfL14PEH70FduIV6uKDyFdUeNAdw+gK86U1w+rxCjTqwv4byW9A+BO5txEMlwremgvs/Dg90IK7B6GGo3ibOf4eg4hhOfRRO9CF0oDUQNCdLDX1DjJZwcJk4eas0L0SZ40+sw7UtUWV0dmB9DBtscZ4tooJpD6Yd8Jlms9fF5QP6hyUbtxTWWXS8hOISPoN5T84DT3Sg6EMzguIqlHdg6zw8+jA8sAmqAF1Aqw2d4gHGNu33KMN9y8IdA+oGdF8E859F/rcPwN95K5zqHleLJrL0C5EPbcBvnYAywvcfwmNJ3aUquJtv6wAPgoJ2DZ44BVkGaxEGEc7P4XW34dL87v03kK8XVF0oToEpRCEy0dCg2MMQFbxuBNs34bSD9RNgt8Ri9Nm0vo/W8LoK8gj/dA2eKMUubYUVVlhhhRVWWGGFFVZY4RsNr1nSw4UCExWxacVbJAvJcF2hlRS2vYJgpItbJ68QpRWLSIGgDKgi2ZFIZTQGCflEIRVPq/Ah0NaKqA3OtcTYEXsf5cEEUBZUKWVzrcm0FqLAi+1FiBGVOylW61qKn7EhaguUkjHhpPhtlcdksk3GaHQKQ27dFKJDZR3pqrc9go+p4x6UNwQUWhUYHcg7BVmnwJiCTj+gMrFbGmlNpTyfffEqz+zfpp3XvHD9K4zdHlNfUfuGNjqca3GuwXuHDgEbQLWeZl6Tm5xBv+T8hS1ms5ad2wdUVYvNpONVKbEackRcVLiY08YS1xraKhJixtY9l+hfukDsrHHthSndnQPa1tO6gPKOUOVUvpaqRiKBmtCiopStMm/RUeFDi6MhpvKVI2CwZJRoNA0VDRIibVMseEfnDLMeWin225pDX7OI745oGlpmqe83R7GeSJJsWeQS0kujyCkkzwJPSw1REfdmHD63Q1N2UJuWsuMht6hOIS33WrPwMwtu4clmUFoONxNElRJjxFsnRltG4QCHoomKLCiishjdBRxayYijMpTtofMhvbzD2voaREeotwntSJ4rz6JNl1xBoUFrQwgZs3ENMaJ0Bpll7mrc3IMGU7ZoC828Zj6aEpxD6RalIjaL5B3IcqGUXJ0qQFZJ8Q2O1FUR8kzIQH1cNgPEGJlMZ+ztT9AqUnYiWRYxNpLlGq01RZ6RWwkbD97gnaWeedp2SoyaaZ1TRUs9h8PrEW1hPS/ZKDtSVC4tWaHJMk2euvf3Dyv2D2qU0uRFh7yQ/VDNJXNhUcXUGjKbdiGIPVyMHE4cTesoC8v6wJAZhbZHtlLeHxEebZDHxmp6PVG66JQ07iMspoPVsvzMKtYHmrYTJcTYyHmibgONj+RW0SuMkEiFZj0RttrIea5I66sUWKsoVaTJ/61Pv/+rRGcOj7WWSEau4FLeUHc92kHWHBEWPgNQDG7k9DC4rqdebwgmSnSUlylTD8CVqchshPyYd6XDejiAbz8Lj81FVfKbV2Co4JsUPNCDqwE+/BJMAryzhbdvCffYrEMooe3UVIM9Kq94Q1Pxkw7O5nBSHPqwDXTHoH3AlSMmJz3BVujWkQd4tAs/eC90cjjfEbWK8bKdKnKUW2Khk4EOkRenz/DFg1/Cuj7fdc8mZzZ+kluH+/zRV77E7cmz4gf0h7v0W8N7bh3yALM/abhfia+1CK9LKM9B5x6y+iTdWz0wUH6gITvj4bkN+MM3wGGfBYGhMBjOotlELKfk+0CgIbK44C8yfhpIdIQgIoXmTeQr0TjdFoZXi/eKjZVKGVEsyRVRhBg69Mn5IJouXS7T5cTyK9bC40kBHSI5lzD8WWr2QsVb9mZsPz8lR5E1BhMUPnNMNxqilsYMEpkRMrnPZ2KNZjz0bkG+AzGD0BMiyy3kkF8jfuPe13Oh0+fR8UmMrzi/Bfr1kG/BbgFjB+vtGtvNBiYMgQtgwQ1gfh5CMOTDN5OHPw8M8dkFgpKvbXYOyudQvQV2AqiTYE/KibZ+FNRfYK4Uf5Q/wlObinMOvmkO2x5OtPD6Q/kKOGzuXmcPXLfwXAm5HnLWvY+Bu8jzPMqvDzvEAO+cwRuqoz0N8IiDPzuHvQBPPQAvduCLBn5uBKen8PgJeOtJGGn4gxy+lMF9FXzTIRQtvHAIHxmLjd2pizA4C+e2JfPnTgYvWrhlxIbq0RkMPGwFeKSRrzzXcxil5+/R0PFCrppWyKt5LpzQzQKe1bADlECh4NkMdtZgo3M0Dr0A757BIzWsOXjjCC5aOKfgDQr2NHy4C88WR+/JoozNf6yEHFngbXNRlNgI75/JfTWBv/+1T6UVVlhhhRVWWGGFFVZYYYXXBF6zpEfrC8lIEC8cohXVg0KCvzUKb8AtijeteGFHKxkC0rWbEZQlak9Uc6KSMOjgUhFE5SiT4V1D62Z4FI4uXvUl68PMUaoBMoh9FJrcOjqZx4VA7aVbV+uAUi4pUqIETBPwOiMqg46WrJEipc481kiRJqqCgCbElsbNhdvJ+th8IH93iNbFQwySE6GsxirodjsM10qsLSkzhbZCEBwYzcg13Hj2Ga5ceQrahmENXRcZB8/c1dQx0pgG11aE4DE+kC9Ij+mc1mQM1zrce/k0u3v73Ny5ykG1T1msoziJVhlB6VSk1zQUNLFD21qaacAUGScfukx5agPdP8X1pwP7N/eZz3aZz/dpm4bJfsm8qqUKXKccBCeh1ESF9haCook1NTMCAUeLx2MoydhEYRmxz2HKU8jxWGDDdrjYGWCV4Qa73PYSWmuFNsLjcKn8UaDoLNUmJt07Ii0aQ4cuGR3yZJJF8HBnyu5Tt+h2OxTnc8zQo4c5uhNkjiqFUqIkCm1LDAFtemgzRKGx0WJdJGiPziLRBJRVOCVF8zooTFAYnZNrg1ZeMm5UjdI5Kl9DFRsMepat9RyjwbtA8NLpP63Ae0UnV/QKDTEyqxrmhxU2s5TdEqUUs3ng8KBBKSg6DcY66tmU8d4BwTvywpLnhqIDa7mi6IGrNM00mYflUmTTMRWCI5gcyuJYhs0xxAiH4wnXbtzGaBgOcrF+yz1ZB4w1rPcVuTWSY+Isvo3UVUXr54QIczo0FMymjjt3KtoQeGBzk4e2Sopc0V3PyDtSS9MKvIscHM547vlDyk7GxYuWXs+iEGsTdcx+J7NCgmgj7800BAd7hy17o5phLyfTOZ0c8lJIjxhFceH9Yt/JtuaZotMRskJrKc22QTzgAbqZvD/PYGu4KKxKfk/rAndGLZO5Z9AxlJnkAnULRae4W5qShETymVZIlLb4Olu8/z1Bfw7vrjO+OfYIKjIuAvOeJ59DOUkFx0zCoU2t2XixQ35YMDpbcXutxRWRvJHiZFRS4IwqkQhIMXPWEdJj08IPG/AN/Op1+MdfgTUDp+6FC1vwzB78/AtwqwK9Da8/DdZC0xOrraDnOFtBVLxjEnjHTKZpRydisYJiBhBwvQNGvUN0E8nGgcLD46fg/BlAS/KMdXJbkDs6ZZDYTJQDNsDV8ZP84s6zKLPJA9/0n/Ked/4H3Hjhj/n/3v4Mnxk/Bc99BV78V5yLBcP2HA+x8bUN/MuUHn8qTBc690D3IbL6HL3ra6gTkez7AuZ7PeE3t3BPvgMOt4AXgesoSjIGaQEpmEUkmOnfBikbG4TQOEDI7TY9vw08guj9rqN4kZT0lJ7P03OayASYsVB6CMmSo9AMiHw/Pb6TgCWjy4KB9EQqIEPRA9Z5kC5/g4wQa9SdW6g9IUVMLFAYRmfn7J1vacu7tSJ6+Z1H+jJ0A4MDiUiqNmH/YVEo+eyoyP+14B899DbeP36Me3e/l3Ufue8U3HMG9gp4soRDB/e1mo1aY6KCogALbQkHJ6BVlrX4Hkx4KxFNVZS4Agr5KiV+bNNvgoN3yMl1WEoV378F2keZGvjVzQ4/N4B3V/BAgBM1nK3hVOKobLx7KgUFL2TwkS6shw02Zt/L6dbx5SLj720VVBH+z3fg9fXd2/qYg0c83FTw/3oDPPEYHFyDL34MykP4GwbecFJsrH4jh98q4ftm8P5dWJvCV56GX3oe1k/C+78Fzl+CywGmXmbXhzvwmQIenMHpBtY8nHLwWC1WVZ8u4IqF+xvJ6Nl2UM7F1sxrGHVgVsCLBTyp4CbLPgp0Dr+9cbcV5ykH/5fb8HAtRMrb95NaLc3iFzLYtfDsMUI8j/AtU3jPy7jLPEInXce+ZwzfOoHRivRYYYUVVlhhhRVWWGGFFb4B8ZolPeLLrCdICRAxBZXDwv1ffgkqpZY/hmMEpaJ0mxtNCAGlgpAe6e/pTUu/Ep+SzeMiYDqyXG7yv0q2GcnqSnyKjhV31XJdY0xmTEajo5IMACXWGhK0vrCzOtZyu4jpVskyKFl6LYLWpbophVF5qNFGyJbGBVzrmbtAiJ6oInXrGU8bYttSKEWuFH5pEhVTQHg8CnRfPKNkW7Isp1v2mBYVWunl632U9SzKLv0Iedmlbhqm0wnUTVqWwmQZtizIihKbl9isxJgcpQxaWVE9mAihlf0SA0GRSIdkRxWVBHwnK6qQ9vlCi6Eksn4ZTbu4dzHSJDszia6NaQ+F5Sxa4CiZYWFusph1ElmbtC3opWGKglDS+iE+dDHZOnk5RHczdL9EZYrQNkSXKqOp4qdQKJWMvKJahtmjkjfOy1mChQVNsrtiOc/BGENmLUobfJA/Kp1jtCaqiDGyn5VShKggioeP0j4poSRfJqIlND1C03i0CzSN2GzFqIiY5XxczpPFXIkcmz9H63a8CL+YMwsSCCIheJxzRC3bpLVBa53WSd11PMWo8EFJ0H0QokWppI5CiB7vQ1JEyTprldQbx8ZQAYuIFVlH2YgQZJ289wQCMdeEwoBRyxkipEbANY42szRVxAQwFihIy4l4HwlREby8tw6OtvFYo9EdS2YUwUfaVpbcprmlFJikBIkxRS2k+aK14riV1vGxXeF/HrIs0u1EgonMUyh50NIVHzmygIoeoo5yHUFyovRCtJXe463c6/Tc4jBVUTQBveTFt6aPYu8t8hoHTFoYt7Dr4SUPpRG7Mp3BLEYOvczTbQ0bIjIgqqQXSEJEgGgCMSmH9DwJIzPo5elzKrF2M4n0MEEKrX1xTuSwhomD/apl5CXj4nY75no95kYzZS/WHNBiKMjoM1OWOziuMflTx/sXPvoL/MJHf4GD//GQrh2yUZ7lzuzqK16ntWY4GNLtdDmxuU1mlSgfA2hnUNGgOwq1DqpviaZDpEukRAiJ5FMGQE2kgURyk3I5joJFjh1Ty/eodCXxHJlYHb8t8HIaYXHtlr9rRDPSSZrBxVUpLsmXxc1jiawh17yZXmOmjWhGvEUHTSwO0dtzTKclTiNxHpf7XaWPDFY+IgsG2xqMC+jgUXIi+brOF6UqaFXBDZ0sHwshxaqFsC+wtJwKx0dFJXWcUcRQ4kOJD5I/VDnJw5laOc8VsSSLJdpAlo4VKAgUkkeioKuEnlqMvA2Ss+OQHI25hjLAMMiozxTsaCAafOxiAuQeukkcnKVdFoBWQZOOowyZOSTSWgUgE1urkIFLoedWyaneK7hjxQpunsv45Dn0S1gvoXQQ6+RUlcak0XDbyvo3WgiFzEM7lZiTcQMHM1HrrHshiBZjGpXM2AL5e12JNWOmoZ/LucIpaJMCaG7hMBNFTCedkyYaZka2eejhnBNVyI6FThQFyrqX5RwYsbmKAcr0dbZWMNUwe5lqc4UVVlhhhRVWWGGFFVZY4RsBr1nSAxXk124pRQOvLMFFYmptVCrgKHApsLRQWixfVJQf/ICyBpUZvPNUfkIIM7TporMBYPDaJKUF1EGyOsQ95sgDHAxKG4yyKGUIChovnvpBBWkP9hC9JQYpQCnl0EaTFXmysJLSvCdSKUUTATxoTVQGpX1q39QQ+0CHGFsCc6Ly6GQhJL5dXUDCstv2kCZGbt6+xd7+HrroUGyepJsVGFXStGcJrqEqJlhb0bqIcYosilu5DwYfFRVKQsKNRpc5Wa9kc3iO4AcYd5N+do0DGry3HM5nlEXBpQffyPaJs5zYWufai88yObzFySxwyoJd5DxEKd8aU2BNh+gtbhYJXpPrHiYPuLhPbQ6JymFiF00JMRJCA0RMrCiokHwXQ8CiCRh9AAp6oUFFoTLUgrbwFQfzXTSK1lcUaV8KleKTIYlGIYkiakmiHS/lCNVhaZOxSUuJEwLAvJFZ8c101geceN15zl9ag82AOh8IquHwuWcYX7siNI0BdMRYjc1E0RKagiZmxOAhany0EHMMQubotJ4xBhrnCTHggyNGjzGR9TXLic2C6WzG1euHEGE43KDfG0BUFJkmWmiqlt1Ri1LQGxjW+h2U1hgrFQybZRjTxbWO/Z0xTdVgcrBlD10qsk6XouyQWY2rDZX3EtadImmInugiaI3NrRTpZVcQQqRqahrnyKylUxZSVPaepq0pi5y1wYCN4QBtNSazKK3IUwhIiFC1inmj0KaDLrpopbGJhMmp8FlDq1p6JkIq/Ao5ydJuKgBrw5wL53tYY+gUYk8TAwQXcd6zt3/AaDJmuFbSue8EeVbI+73Yk/lZjR/PmFVwa9ojyyInzynKrljb1VVN3Th8NLQxw/nIzZfusHN7n+Gw5PWvP8PmRpdq3rJzpyKESLdjKHJDkWuGgxxrFfMGZrVQct3C0O8YrBGSynN3uXZBUh4vybZIYbD6n3G6/fcBVQmHp1tm/YnkWQxadJC8izunF+d+IQ1sHcDPaddq2p6naCM2SrP6rCvHQJNJV3ZZQ3cu+6dIQejGQV5L5sK7Sjh5RoqVj+RyydBO9lsb4UMjeKmBk3344AbcM4Av3IHfuwrOwXduwXvWAQN1nuKjkDkOR3ypbaHsSVF8uiaKk70afu86PL3LkrgpNHzgDLz7JNxu4NevwjMTuD6FWQvKz/jnn/41PnftC+xMdnhx/zqg2Tr1Xs5c+iEK3/Cbz/06H77z6a957HNT8uYT38WP3n+Jn/7cf/SK5we9AT/yXT/C+97+Pk53upwdTGH6BVRzBx0zVCxkACKEaGjpEumjGWKZpqVYQOO5QsszQEPGGQzbCPlwAHgCYzwHSVuVI0lhe3ieQM77LRq5/hwpRioiU5kgy/55OCJaFuQHxyh6jRyNi7Spxev2UMwQw8YJQSlubL2TqyffjnGKzf2KTtViHv4s6z/yL6F3QPP7Fe0nG3QN2VRUHr6A6QaY1lCMtihZAzejN9qBtiE/7uD1NeA/ugXPWPh7W1KgP61h28CWhze2cLkWQqcZyLk1b1P2iIP1ZMvU5jDKYTyDz30KbrwEzSWYPi4CnocbuNxK4f1MCz0vJEJdCP//3Q4emcCZWp7HseSJ9g38kyF8vAuPV/ATB7Ae4ArwRwouAN/qhXx4h4P/aibr+cZayJVawY0MJoU8nivYqeDgCeAqnB7Auy/DiQ7c34fDQrbpmx3cC0wL+Onz4DyobfiOR2BYwOuHsN3CRiJZNPCAkwyOA+B/2oBJhLdHeH8EMwP/WahfhBc9/I4TgvRtl+Bt98gMy4OQD5cCfDDAHQdPfh6e/jJc6MNPPggPrsPNDrzQl/cc9uE3Sjhdw1sPYeDg93vwK2vy9fKxCr5rIrZb/2BdSJwfGMF3T+CGhX+0Dk8W8N4Z/NihqGp+ZQC/1xfl0AorrLDCCiussMIKK6ywwjcaXtukhwaUS2oOJaSCakFNAY8n4FMOQ5TqshQykoDCGIXODU5BrWtQU5TJsbYAsru61l16IO9vpUSx6EZXGm1MsrKIuBjxSVGxSMKVIGskBF0FlFZkhcFkViq4oZUw9WPd51r51HkeUmaDAspEfMyJ1MSkApDClibGAigIQRPCjNa13N65xpVrL9IfbnBxrUOn1CgynN/Ah4ZGOxrb4mOQTnhIagNDiNIT2wBeK3RusXlOv7tBbAfMJ1DYNazaI/jIrG1Qecb22Ys8/PDjmFixu3ubg73rZFsbnDyxJQWeCATRZRidobVUCH0NBIVRBcYoMIfUegaxRekcjRYyAE+IDkOLok1aHyGptApoLTkeReoWXQTdByIxOKbNGJD9m7Go/UhRSpzYF2WopcZl+WjREawAg0/3LVmySYnmEk32HkJ3yOD8OU48sAZbDZyf4+Oc5mDC5KWbECPGCENgjSOzLTFC3WpctCzSZmP6BDFvS53lLMLNPSEEsf3CY3SkWxrW+hmzmWNn7wDvI8Z2KMqB5EQY2bK5j4zHLdpAf5hRdo+8LWIEbQza5MQGpiPHdDynXMsZ9LqYwmLKPlmnh0asx3BBhsYuximlZmuNtkb2ZxrEECJ101K3DTFGyhSwEWLAewcxo9PpMBgMxE7qZYHiIULrhWDMTI61JUprMmUwKLSNVEbjoqLQxw76BRWQVBMhKjody9ZmyuQxCpWOQ+8jrnWMDsfcvrNDcAPaixtEhPRYBKSHxhGrhqbKOJgErIHB+kLtEmjblqZu8VgchqYJ3Lwx4tmnb3Lq1ID7L2+hNro0tWN0OMf7SNvmFIWh17X0exkWReukK99o2BoYusXdZdcFycGxfy/OJYvXtem2wivR5jDre+KGR8Xkoe/F3mncB2eSVVuAvIiUdYPK5TDNnCgkmlxuXicCQssyFPK+xeuMk4Kw8fBgDo9syDoEKyoSnTr1PfDFudwuBXhAwakSrjj4vZvQtPBQD96WrORm3aRKUdKFDkdT37pkzRWgTuHkowo+tQd/dP1oHLoWTm/Bmzuw6+ATO/CpO8cGKjR84oVP8YkXPrX8k1KG/vAhztzzI/h2zGduf5jrd46/6U+G0Rn3DN7Mu069jp/mlaRHWZS8483v4Cd+4CdQ4x24+lkY3UC5MRoLZKi4oA00npxAQUYX0dEAFKJeI+K4CVQY1o6RHlOgITIhLFUqfQyGyJTATSIOTYliUeUNy2tHXCo65HtB0rel18XlFSSmKn089rwiQ5Ol106Q67sjUuFVzv7gAa6c/kGyVhPcHmvMGZyD9Xf8EaZfMXvKUVUNeg7FAZgaZlsw3QLjNGQDMrYIPqOY7+OD5L58PfjAAVxdh3+xJVZIDwIXkRyKd1VwsREypCqFTLCJ+zFAr5U5eahhXsJBA08/B88+BaMMbr8P9Ba0DZQtbDSwtS/kh09kntLwmIe3eFn3zjHCgyBqkT/swj8dwljD941gLcAdBV9JL6uDKCnua+G+hmVAuCKpGSzsW1EvjDXsz2F2BfhjGD4Ab3ocLp6WkO95K3v7dQHub+EPMvj5LdhT8G3b8L4g4eEXWlFMdOIRBXbGw2aAJyz8fh+e0WArySnRFfinoX0C9pBbbuFcAeGiLCOLcn05EeXzd1q4dRWe+RRsbsG3rcG7gaeDBI1PDLxUwqc1PDCDRyfQc/DFAn5xDU56+K6b8GdG8Gtr8NObEsZ+fwPfORGVx+/15GYQMqQAPtkRosmvJIYrrLDCCiussMIKK6ywwjcgXrOkhw4ek+ynpMATCcqjVEAlckIcHJJZkXZCDCjpy49K4UJAtQ3eBbHB0AEhDISsUBiMMkQVUVrseHAe5ZJvSC5WN2Kc7ZN1iZeiabK4islzRqko9iZRiRVP0GjAEvExEnyyHEIf2VQt+rSDfHYgEpQD1RLxaI6MmBbEzyI/ZFZV7I0bGtdy+3DCqPY00wpze5diXDEZ1RSqAuPp2Yxe3seolsZpnJcu1MrXZLnhgVPn6XZzzm9vcrC/g2tqdBzQKft0ckumAia2hBComoDJMgiRDMW8qrl++xptM2UQL3LfRo/gbbI8yglB07QtddPgWk9sSRX3lKgbA8bnBG8gplBYpVNuiyYon0YRQtSoqNFGk3dzyUqoapqqQcyYIova+aID/nij61GhOC41HWo5ssc76TUScb6wv3JkStHVXYzJOTl0nD6zR9mf8NTzL/L8QcQOHNmJGqU9ZnyAyjdQvkHNRyjf4lUAF8SyKdapExi0j6ggcyoCSimMMVhrpF6T5mpyQCJGsUiq64D3CqszjIoYbcTeRqVMCqAoNL2BKDBspu8eiMQpWh2JuWJ9s6TbU2TdjM5agbGGIjMSrn28U1mDMjKySkswsEk5JqRdG5MtT2bscs5Ppi0xRAg5g84G3U5OpjN0hLb2VE4qdGWZUeQWrSDPNUWhUTriQ4MK4BELmNa3aG2wNiOgqBsZvxBkTUNMhEWQz8+MzEkJHZfCpbYSf1x2Mvr9grKTAxrnoW0jbRVpasekaThoa0xQZH6fzGTUTRdiF6UUNrNkQRROudJYHSWLxVt0WJBbyZasLNA+EIjUriV3RxZ2IURcK4oV5zTepnNL2nXORXwrhKrNNFoflVxfOYdXeDmMEwJ0Ubd2RlQeziSSPNnoWCen+7pMpEYUMoNkORNVst1J5IUJR+cZ0yYbIJ8UHR5MBXYm08ANJbNjQVxo4JKV0OGTJQyTemS7gHeuQdVIDsxHd6BXwhkjWr+gJCvmOFRMBEiALBWhi/rIlmsrg/tKGOZwsZDt6hl4dEMsfO5UcHUi2TMvR4ye5576KZ576qd41zf9PPfNSx7icXY55GmuMaN+5ZuO4fee/F10vIfT953jp9c+wk9/5D/nCzf/aPn8rZ1b/KX/8i/xl/7Lv/Sq76/iWXRboCoNTZLapBkfsSgccIiiRVFjGAJd1NIoaWEUZBCKXwZPLQlui6ZIy7IszA6PyA55fGxE7iI1Xg0LQ0shSHRaF4i0xKQUUWTomDGYvciZ3Q9ROXhudsC8rrj84rNs/n5G0V+nmF5G3TckTg7x6ku4yQFtKXMqmEA9mDHdOsTlU7m2JLumr+dccNCBnhXSYQzcF+BsFLKj14BqhZBd2FIt5pWKLIUvNodOA0Pg3pOSU/HcSXjBJtFGFNupMiYbwkV+0uKalNbbuIX11RHKAG+eSybGGxoh+EYash04fVNSWYrkYDY2sNuRz9uqYFjLcT4BDrTYPo0UHORQn0MiWs6CSkHfMyVWVjYISdMNcCHAY1o+81EP97qUf5FmwUjB7cRrdePS/XB5s1ECyxsD4/Nww0E+hv5NIUePz7K5lpsNcGEOaxU8U8G1Fk4ds8HaV/BUWqc9Jesw4Ij4HiIqlQ3EqmxWwFDBe+ewr4VUudURC7M3NrIf3lC9zGYr3a+wwgorrLDCCiussMIKK3yj4TVLeti2IcdilBH7KeMIJqCjx8aIjlG8/H0gGoi5kxa/WBJjhxg1ratwTS2WQmqIzobEAN4HwGFshtE5UUWx7ImRUM8Ik5kQGDoX835tpPVQG7T3WO9Tu64iYMX73UheRAiK6A0ajQ2RnEDtA20jyRI2s2htUMosFRHBQ/BSrYp5hTYKjcOkwriPYnikFVjboLXj+s4eX3jmBrOqYdI0zF2Lmjiu7M/RWpMHy5rOyIxlu7PBoLPN3DdoO6HxLYfzMYezEafWNvmud7+dN95/H3fGI5574Uu4oLj/0pu4dO4Uk1FJ1zYUTKkbz8R5qW+0jh6aO3sH/P7HPs7O/i2K5h08dm6TrLSEYIAurTNMpnPGkwnVpCHMEBKpnIBpUKEla9YkF0FnBC1dxdL7Dl4pnJYicWw10WuyomBtew2TG8LuLvN6B2LAssjnOMr3OE5+LIoK8vhI07EoFucsSmESNitEygxNQ0d32Mw3KPIO916ouOexZ7g9GfFLv/sRnrp2la6JDG2k1y155we/jTe9/V2YdkQ+u4Nu9vDeEr2QOoSU6BA12mVYH1BSjQelybKMsizxoaZ1c3RwQnYhlkuzmWM0anGNppP1AChtRqalkGRzKSStZZbeQGggm6mjjU+FJUukNJFOZjhxYhOTA1oRUzXVt4aQbHiMMpJxYiVzQCnQJi6t19Qil8JLYR6gzHNKkzOZtNy+PadpAjr0OLu1RpEbOiZHe5iOK17aPSDEyJlTQ05sDjBa0+tbtFXUdcO8muJjpHYaF6RMmWUZigwfDAfTltJr1rysewiRppFzhMHSySzORcaVp3WBLDcUHYvONRubXYrCU3ZLgjJULcxnnvnIMalqbk2nvDgbYdsxxXSPXBtOXTpHpIPWmrJTkOU5WiuMVTQ19GxO1nYxbZHs18AWOb11Q+M88+mYejbHmIAPHSIG5yLVPGCSiiBTGmMhyyRlYD5zjCct1mrWhzllcXfVe5Fa8Jo9qf87RllDtxYywlnY3YTJICk7vFhO5Q0Ujfj5H6zJfujNYesgkRuaRQwUeSuF2QUhQpRw8Wx+VBRWAewBZLsKn8NsEJn3oZkmBYmCb+7ATwzADKRLvrHw8ABefx7mc/j1ffi7N+HyGvz5DB4cHq3HQvER9ZGtlknETWcOhzMhQAAe7sJfPgtnS+gOxELnVAY/cg/MPPzBDfgnz0iX/p+Em5/9u/zF+bv4IH+Bj/IU/29+mSvc+hPf89/80n/FX/juv8aPfttPYJ/P6D+lJZ35a0QTDtGzbfRBH6bbEroARDIiHWCM4iqwi8GjOY+YGPYhpTNJCXhhczhKhLdNN4MiQ1K3WiJNsqlyiaBeXEkWWFSFF80LcHe0tLwmLm2wBiiGQMBzm8AYTQfLBjpazu18lPXDj/B8dPyim/Lx0PC9f9ThzV9ZY7N/kvz930v8tvdT7z7Fzkf/H1S3n5BMGQNBew5P7zDfOMA0nnzSYiqZz1+PvdVz63BSw19O/QhnW9hOdlHrM1lextH5RS0uqA6YA0HyOAolhfXN10NzP/zmCQkCP0QUItsO+gEy6U+R61aSs6lalrcU0R4b7k0Pf/4A/sxEdn/ThWsBeh+HN34KznVg7XXACXhpAz5yUtQd77wBb5hKrsUNBddsUnkoUXiN3g68AZQF3ZG9vGvhBmIR9fgYzs+g6EBfQW3ggRrubSRP43YOUwMvWXgil+8Zb2zgsrv7e0jHw2YDYws33gmffhdsfQUe+E3IDo5lkilRoxxkMKjgnRNoZzAfQajg3hoGaWye0fDPLOymfA+PnBMmaTbeE+EDQYiZsiPZJxcc/Be74CMc9ODzW3IO+7PjRFgFUdCMVjkeK6ywwgorrLDCCiussMI3OF6z9TEVIzqKtZRYQB15HSgQq4tk66FiIgy0qEDE90M6qL13SIhzhhKjHmKUX9hLkwql0DGZU6QwAMkmWFjmJMsqpdLnS8Dtq6x0UnosWoKP1u+4lRZ3FVDEx0DywSUEPUZHVD5tZ5Ruu5gKXIgqoGlqDidTZlVLAzgUMQRqNwdgzRb0s0huIDeG3BQEpSjzFuU1up7iokcbxYnNDe45e4bmmmc6fY6q9dT1PAWyB4zyWOVoYsB7j3ee4BzROdq65mA0YvfggOl8SkjZE7KxYknmvMM5J2oXH4k6QHRACzGiokUHCOroV7ZSEgIflEZpjYphOWZKa0yWY3OLMUe+SIvS1tErj0b6uOrj5VZBx7vkpX9YHi0yPzSBDEWpMjo6o9fxrA0n7Lf73Nx9ni8//xV6wCbQ7/W4/43voAqWLGps9OjYivIgdSeruAg0N/JZIS4mhqyH0hhtRCOh0zRkMQ8izgXa1uN9RCuDUgqtZLkL2xWlwFgpwt+FxP7EkAqzSgJoO92MvCv5Nj7IZzYemshyeelQEYWBEvs4pV+5+EXWgFYarRVET117mtrTyXPKvEueqWWAt/eRqmoJadtikD1ktMJaRdNGQnSEEHBBi+WV0uTWYpQowXwKE4/pQIsRgg+EAEYpjNYEHYnR4710ucd0DNvMUpa55IkoRQji2hV8IPiAi4FWBWKMmNCioyaEdqkYEaWLjIu1EL3Cao3BJNOyNB5aYazBsrDv8jgflj3jMRG5SQC1tNhazIsQIm0ilBbqkOM4PodXeCUW4+pbmeNOiQVU5kR4ZoIUXxdd194K6VG0y9O5IB0TJhwtswlJ9ZGWtTyXRAitoq0UPiKqPw3KQK4lMHg7KT2igWtKirN9C2dKmCWS8qWJom8i80ZyPrROlnBpp4flteZuwiV30rVdABsaLhdio1MZqKOsw3YpxdKtAjpasg4WqF/lMucnz7IZ380lTvMcN8i+yteI8E9+mV/46If5P/7cz/LlG19i5G6TD2uKQUuRv4qc5E9AUC2+1agqx7dZUhLC3Wf3OTBBkaPoJBXHghxZHB1AUosdIV1XlqoPl0jxBVUeiEmtsfismJa40HMcLe/YdX1pd7V4hVkqDRdkiqyLoWh30e42BY7DMOMGjr39U1T7Q9peAW8/AWuX8e0hrlviiiN7MwBXtETbkmnJ/Ph6yI4FZpkoFy4GsDGy7WHoEtnhQfm7R22ByHKYZN55UQ6VA6AH6325XoQAyoFpjqlEklpNHx9u9yofggR0n6xhu4H9Llw1Ql7oOWzdgfUeZDOghSrCTiakxFy+tuGDCDrGWu5rJeoPM4R8KCSgaWVdPJLGkkdQDeRzGGq42IrL42kPG15m3F4a61mEW0n1NUEsoWJSsZRRjsMsgNXgh0La+B3QZeqtOXbidsh5gAhdJ30SGxFOaFjXR5adFbCPWGQ5L0TGON0DFEHyVgols7+1Ynt1MUXWfL4Hz2ewBpxxcPZlgq3Fursg+qgVVlhhhRVWWGGFFVZYYYVvJLxmSQ/dX0OZDsSCGB3B38K7EZBh6KKRYm+eSS6GbrX4giiNMl4K1lGhY8oxSEoKoiamalEbFS44YvCEtiaGRKj0+iitUFlaXlSEuiKi0cYSTZZ+4Ee09wTvic5LoTSpEbxW1E1BVBbvSfYbEecjLjpxJVcOrUj5HCm3wwVRkSyLLZFoAuhIVUVeulFR1REfDI9cOEMkErQhaonkDimaO7qK6OZoDKV2KCo6eaQcdgiqJLMRnGG93MQWXXyRUcXI4XjGaDrnk5/7FE8+8yzVZB/X3mZ7GKhaTa+2ZEFx+9kv8pnpiCbWvPXyabhvmzfce4ZeV5EXDq1nwIjoJ/iqwc1bvG9wpgHliD5VB7ySCqAGol/+vSUVemNFCLWMQ5TeXF8Hqt2Itho3nWKOGYm8vNYTX3YPYDHYpb96C3g0UugIgKbBLD3fWyBSB8dOW5Ep2GrHVO4A70f0Vcu2BhMVMSrqxvOlz3+WeTVnu6957Jxmu5ejdIFSpRTLQgWhJWqL1xneKoKJ0r0dEesWb1AhQ8Vcim1KDlXvA5PJjIODEc5F2iaiFMzmc7RtMdpSVF20NmQ5ZAt3lwRRQDiCj1TOU4eA8Yqm0nJ4KEVQYg813m8YH7ZkmWJtmJMXBq2UqDsSAfKK41YryDQhwHSqaBxUFWDAFIq8gDKP2Ax0riCDopsz3Fgn+IBvYW93iguBqvG0PhBDg6UVuzdlscpgdCBTDUYreh3JxTBaEyrNYQshOlyYE4mYvMTmBVEr8sKA1lR1zf6+JP12uoaiHJDnliLTZBmorsIEQ+5yXlee4HzdRzuwTcSgOHV6gG9lvioteSYRySFpA5R9zeZpy3DbYnOV5l2kS6QKETePjA8kVDosDdMXFUAwVtZDazkvRCDLDb1ejjFCtLxi7NO9ecUzKwBMOvD0AXzhphxO9w3h9BrkFaztQNZA24GqK+O9NoLBYSr4JpY0ryWrIyrpso9KlvnHt6FuIaulqHu2hHdvw2YGT00iTygpqj5ewaUJ3B/gx7bgYABtCz8zhn6Eh6aw1RVLHQWUSvFBOpympK0dn70249N7jkfX4K2bUFiImZwyIsnuKCZbLQcbTvH9IeNNGO6vAidveTo5tGc9vh/ZbeDjt+Glmdhw/QdDKVovCPu/t/fKcXzn6+Y8ee2TXN2/w3O8xD7jVx/wYg/sFFSgbmr+zaf/DfN6jpve5A32On/wdey7vZOew9sHzJ+o6T1/ipN1S05AUaFSRoZ8neml+1x2mJSPjy0pIvkdcl5X1ByRE4EjdYZPVxX9KoTGy4v/EclkkmuKx3M8/0OSmuY47hAJBGbEZVKPJirDfNMz2qowDXz/nQGPTYUw/TleQrV78JlfhfmX2XAv8cbRdbaCzDUrPQ64jtg9uQLmQyHG2gbiAV8zAdKkwniMQhT867LhCo5zrebbfc45ZRIbePf7YgZuPRXhS7npAGtTmfMPNfBXxzACtp6GT16ROf7We6G7hiyz5W6J5nEowMBhDb/zEnzxAOZn4WAdYhfuuQzf0cBGBidOAR2xcbqlxUpq2gWGMOnCkxk8peARB++rZI6/TksuyOkgtlXDgLAJcwhTeOFpePoOrG3AqfOQlxDW4NpAVB/7Ruywbt+AZ16QTTh5LwzOyrnjPzyU68Jbg5A8JRIefs8M+hpOPgLdKTx8JllOOjgxg34LL2j47XWY92HrDfCeNdjqwNpQhuVNDfz1Edz28G+uwWd3EIZzTfbLS9fgk1+EgYU3n4CNfiJ503esL2n4LQtnAtyr4OyxYe9E+NYJDD1UY/hvv7ZptMIKK6ywwgorrLDCCius8JrBa5b0UP01lOqnX/M1vr2Bq8dE1cfoLbQq0FlDntcQFaox4DUqM+jSo1RER42JuagncKnQkBFVkQiCQAyO6BpcNSYGR56tkffXpHteB8nqCB7fSnHElH1ClqXidcQ4t1Q+BB+JzoIzBGWpmxxPkWgISdV03uOcxxIxSn7hB1UQVCFdwwvrrBiS0iJK5UB55pXnuasVu3uey+d7vOnBM3RKi7E5ylrRJKiMEGF/eoed0Ut4F4lTT6zndIqcjZM9jDUob2inOeudTWzZJRQ5VYwcjKbs7h/y1DPPsjsa0c8C9w49J9cj1cwy9yXBw+1nnuT2M5/l/PlTvPf9b+HkyU3uPbNJr6coco/WU4iHRDfBVzW+avChxduGGL3kPnhQIeVBqEgMLfgmuaiH1E1boajS3zQBRds0zHfniajwmKTSWZSRjuto4O6aj0Jos5JC7KIIqUh1RJpYGvTSFVveXUXHqK0xRM61Yyq/hw8jBqrlhIE2KObeULWeL372M3z5C09w+fw2933vOzg1PElM4bhC3lTEUIOKeBNwWh9Z1KNkTJxBJ5/5kLqBQeG9ZzyZsn8wAiwqZmgN02pG0AGrSpzKsRjiGtjibnLCh0DVtDgXqNpI7SMmKoqZQbUKtEJZgw+R8X7NnZszyo6lKPQyF0TrVyo8luNrRAESWhhPYTxKdkBGiVVTCUUhigidAxnk3Zx1MrwLVOMJu6MJUUWcSTY+UUiPqEArI53yOmC1Q2tY73Y4uSn5MYcHkdE8gm3R+QylA0VhsHkBBgpnUAZGozE3ru0QgXMXTzJYWyMvFEUGeQa2q8gySXQ5cebk0r5LAcSIaz2ucWijyEuNsQrnoWmF2CwHmu0zlsHQkC1JD+gQUCHgpjA+UPRyRVgW+qS6p5SMT5YfG1cgzw1KG7QC8yrMxkJd8Jo9qf87xrQLf3wH/tFNIQt+8pxkFuQVrN+GooLdMzDaELXHxg50plJMbjoyF4tKnA6DgborneLP7MM/eQH2Upe0ivDYBlw8B0UfPrYP/0BF1iJszeHhsYRE37sttlL/4y34B7tw1sNfn8KlPpTJYqhQim9VPb6HIZ+pav6baw2fVo4fPgeP9SQnwB0LMgqK5bGpPWx6xQ/GAkuGnnts3RBsZDKMeOPZcfAvr8MTd+AH1uA/3RbliXLSI/BqpMd7Xj/jl2cf55P7n8ITaL9aa36xB9lESI+25nc/9bt86DMf4sFB4K/f//X1je+d9Hzl1gG32kMuPHuBYd1SSJoPihFQI/3vPe4+CiZIX3+E1HgQmRKRVnfRbYqKNN51BVlAJ4XoQopw9Pfj/5bMjiw9rgl4WKpDIFARmHOk8jgiVVCa2bZn976KbGb5wekWnWmfX2HE/5WXuNE4+PRz8FnDo4PA37qv4cQA8il0d2V1xyeFsAsaXCbEazN62ab8KWiUjFoAZiryL4uGX8vnvK3OeENtOYdJwRx3D0XIoO1KIPlhsmXKWyjmojR4pIH7xhIM/q+/AB/+BJw7BQ9uwql15MKdlAevStCkC/qhg195Af75cxAbiG+CTgf+1v3w3SegTAHoeJjncMtAreW4jx7GOXw+g08qeNDBB6YSRH5oYGZE1dAPkqPRPYDeDuwewq8+AV+4Cm86LaTk+gBevB9e2hYlyUTL6t+6AU//AbRRSM/hRbGS+okDOFVDKCF2RDnxfRP4/iYpJx+VY90gCkTTwsmpXDc/vgb/w5ZklPzvu/B990nAe7+SY/TNNbzuEG7OYecJ+NyXgdPAWyEO4aWr8LEnJS+ofgw2zqchjWLh90UNv2HhAQ/f87K50gnw7RP45imMJivSY4UVVlhhhRVWWGGFFVb4xsNrtj4Wo5ciRPSEuCggSGpDFLOf5I0gmxDVIgGDZFW1+PUsv5hjSNZRSszbF2YXMXV4irWAQumYvBaScUUUW5sjC5pElCTfGbVcilquV+rfPPaXpekQi0hTKZ4utiNVqtTCOsOnz5LX+xBEAIKiKHK63SiFXB0wOmCtxWQdWh+YNi1tCEzrhlntiQGsUhhrCUpT1R7VBuqmxQUn1lNegpMVGUXWo1s4toeBXiejn8HFdRjkMNpr2Z03xKgo17bIeyVbJ9bJyg5KW8kpUQZUKtJHnexkHL5p8d4RFj4YsuFLO6KXFzwiizF/tSqI7Muj2otO98n6h1cnPdTycWodTe9VL3vd4tXHQ85V8t0QwysxP7HWsLUx4OzpTQ5njuqgwvuAd57oAr5pEuEmS9fJIikQj6QSSsz5l1MgSClO5uqiU3ixzkI45LmhKCzBK3y7ODYUSktYd+sCITpMq/Fe3xVuHSMswgC0UhgT0UrmodhaBUIIYhcVPEqJT05QSQkjh8SxsUy7Lsj+0kolSyvEkixGtI5iAaUhMzoda5G6aWl8oHWa4DUhxOVCFQqTqrfGZMQyJMuqjBgtSgWMUcnmR+NDwPuI8wHnI1oHNIlQi0L2LGyrok/LtxK0TkSISHN8XqS8nQh17QhRFB3WWJRSOKdwLWiv0BlHFkMKCTe3hrzMyHOLTr4lETmmY1Roo7GZEcWGSjPSQJHLvTZH+8uHuHyv1hwLtWf53uXyl0fBCi9HVFBa6ZTOLXRTloCJQmh4A6MWrk2EZ+54ySgg2dREjqyjQIqTBOgpsYYyOtlLAeul5N94C0UpHdZrCvJcPksj1lJBw7CAE13YLMXuyniYtYlEqaHvPB0ch3iGIXIOsdbJUrC0dbJ+2osKRXkYVzCZS0bJuSxQ9gLaaXQjXlajCl6ceG5MYdxA5UV0ZwuZfyMPUwf/w2n4qT34cgvf9CB85xtgfwYT55h/NbIjYb7bx063OKMvgF3DhEOMG3Mqg/Uq8tT7NcObF9i68hA2lKi1DqpbcGBv8mz5SaZmn14B/ULRtNDJFf2BotMBoz0alxSUIZ2fF1f1IxuqY3ufo6Pj1aUPi+uNXKHNsfctrgbHrySL+8Xf5Pop/zLHXvPyzz9+TQtEGqIKRJXa721Edxy21xKdY954qujZcoqhgxNFJA8xZY4heWaKZcaLQq4hKlmvfT3oOimol61YP3mrmCnNXGkaLQX+aBbXECHc9LFz0IJqylIB3xvJp4lGrm1GQ7eEzTUhA28WEK1YaG2Fo+MwvoxQX+R7GAWbBZzrIfxWI7k1m14Uc1qJmqQJUFvJpXCIsgItAogzDu4BTrVpe6OIgG36/CIm2zqgzaBNqgm9CXoNTAkmF4uqLI1DmdZtYGFrIKTH0EruRj9AL0oQeuvFMtIDMy25Qr6FupZct6WKxspnkosV17YXFdiaks/WCsk+4WVfHReKmWNZLkMLl0o5P/XT+Wmq4U4my47AhUbC0Z2B/Vzowwl3X0cmr9lfCiussMIKK6ywwgorrLDCCl8dr9mfMm5+SGMaiDkxBCDDmC20ypbZFpgcsuRFEqQCpQDv5Fd/jBa0JTpHU3m8c1jbYLOJZBLoDKUMUUdC1xIx0iWrKikCp3yBCIRUGNa+RjcNPkZpa7ddYivF8BAjQUWiAaMjloZi2dlp0/qJwkQBMWbyw1IX6KxEfrd6Ii3EDB0KQFE1gWnrQOXcf986WhV0zAjiLm2tsfkm1p5iv9rnM1efY3d6SDWrmU8rMptx8dQ2W5ubTOYVLz53QNO07M8mHMymxE5gf+Q4PMzI4jb3nXoEt9nw4L1D7j0/INeRnnZkeJ564vN8/EMfQdmct/zQD/Pgez/AaH+PF55+ipvTMduuIDIA1QX6QA/XaGaHIyb7+3gzxesWFQM2gA6a6D0+BGIIKQtCc/zn9uLRohy1IJlC6tH1ZASyVJCqWfhjvLzcdRwBQyBPJauGhTGQ4ojIknDbiMZjUzXCMkVTiwokaoZra3zz+9/Ku9/l+PRTV/iN3/8c88mMgkgXKbaEAE2IZLqhUB4UNDbiQobSGag8EQUWYyH6gNc1LVMhDBJBtPA8z3PLmdPrXL73JOPDCXu39wgxkuWb5J0hvvGMJzN8ExioDirroo0mE1cnghP1k1JgskiezMFDgCpA3dRMZuNE3kTKPthC46yi0hrlpds9JhLEAyEE6loIniLP6BQZ0UdsrCh1K7ZM/Y7YMimDVpq6bbl5Y5dpNceakjzrSgYIgaLIUEpjdYFWBtsPZB0Zu7ioiqlFrk6kriK3D+bLbBDnPaW1lKaPMRrvIrNphXdQzYSsyKzh5OlNYoyoGBjt7hP6GeuDPmQWnCLODFXT8uyNO9w+PKQsu2wMt8myDB0VBo3NFGtRQm6tgdxKnsfaWhffKjqdDGuTNVlQVF7ToOj0O2xry3BosVYKrIOufLRWUBYyVxsXGM0cIUS6paVbGCFxfBTHPqOWBMlif7zMln2FBK3gzdtw8nVSlL2nkyx4PNRD6UT/6Ah+40XYsPBj2/CmHgQrBVxAjsUUem5rKQA/nkPxkHR7Gy/PDzowHEomyOvOwl8eSj7AJS0FZViohuCdp+H0JpQGHsjFQuvzh7IeB3Ugm08w1GwT+A48fw7FqRo2R2ITlxXgsxTEPgPv4ENj+I0RrNnAD2/XvOlSQ29/yMaLZ2kby8duvMQ/Hd/isI28OJFzZFPCYepe/60r8PEd2PNw3Qmh98UbEozuI1zb/9PH++l/8RbWbt3Hn8sfo1kfMZz+NoP5hxlUjvuuBIZZxMQDqv7n0b0Nim/5CbI3f5ArL3yan/nN53nhpX2+S2t+0BjWT2nWvivHvdtQasvw96ZYCoykMyCVXoOUto+TCwr5muNZhEUk+phFe8KRkkMIEUUXQx+WVlQL1Z96xf+PaJAS2EgEeYuiWq6DrMXR58RkfxWY03Jb8kn8GNtGonHsX9zn8MyY/Z2W8KKn02h+gA2+m3W61Gzr20Rd0XSTxRopH8II6ZXPhJCzDa+8+P0JeGQPzBTsCDpa0btUQDfDa8U4N+wrqak3UQiCzUbyIbSS7JjoYd1DL2Xi1B2YdaDRUFmZQ/e+ES6dgZd68EsX4MoQvm0f/txISIq2B65c9kRAFBuvvILNHP43D8C3ngO6wB0w+/CAlgyRUQYfG8L1Qv793lZIjHu8kAKXPPwn+3AAXHSSdZFFeW1YEDdpvHYL2DknxF/nBFyq4IQRBZ4yMOyDbuV9C/FLexb8t8vjN23CAzNYa6CXvsQsCMmRgQ+vwZc6sH8NrnwJqkOOTuDrwLuA03BfA//JLqxFOJXBPFnZlUmVc5jBzR7cUjAuIGYsOTer4IOn4VwXCgOPDmUbnyzgH2zAjoU3z+H/dlu+G9Qd+MO+hKN/Qos+aoF29LXPoxVWWGGFFVZYYYUVVlhhhdcKXrOkh3e1mA7Fdtk9aXQPliqPQNSGYDoQgnQHqnZpR3Vk6ZNyIFzEt6k7VDdoDUZ5DBloTciM5BmA+H0vu94RWyUlQQY+JjsrlBAZ6e+iTJHA86AjUUUMDoOUPRZZGwbQqft8kVGhVIYy0nUuKhKXlBKGGDVtbJkDZW7Y3h7Q6/Tx84ZmVOG9tHlqPaBxE64fHHJ9/xa+AjeHTgEnT1lUt0szd9zZrZhN50zjhGkc02v6zKpANddoumz2T2FU4G0PX+Kdbz4rGoq2JjpH3D/kue5H0IXhjY+/kXd87/fx/DNPc+X6dcYHEypviBRI4SmHmBO8opnX1PMZsWiIuUfFiF0IPoIUzWM8ojXujog93hurlroHiZaNSXmREZdtjq8kPRZYlMDE2swsi19Hap2FqkOnW0yGWqAJaBr5d/SApiwL7j+xTV7k7M0adP4FPEG6uJGCSoxSnM5iwCopqjnNXYoYhagjtFZJpeRwNIl6ubtn2BjNYNBhc7NP9BWjnQYXIsYYTNbFu5qqmdJUDbY0dJou1oggymiIQQJ1jUrB20mhUDeB1geq1jGezvDekZuMLLeYXMKXHVLwDK0UuhY1GucjdeXwPqCjpjAZMUQ0DqsbCpPTLzpYa+R4Sp93OJqxPxrTKRxrPVFRlIXCZBqjLAUFRhnyEso1XtVSK0bYbedM5nNRRLmaEBxZ7KJVjlEW7yuCb/EOXAPOSbB5f9AlxEg9mVDP5uQ2EEI3nYAgtgo3j9y+M+H5W3v0e47WrVEUmtwYcq3JckXeVaiMRKQCSlGWOd2eoig02iwsbsAFhY+KvMjoa03ZSWHviK1Wnt29fd5H5rXHh0iRpYD7KKG1IYBWEWXUYpVxfNUc4H/voYCzXbiUS8ez9aDFZQ5fQpPBldvwsetwuoRvGwqZEBbd5wsVUuqkN40UMc+vw9oJ6Wi3rSgvWguzUgrRp4dwZihkSHcOPhWjF8f1PSVcTMs3Iijjzhw+fAC3ahA6peEtwE+geQcK5yNNLYVmHdIx2UqQc9vCtRH8/j5sduAdFx33nwIbNfqldVTMuTre54/GR2kXCtnWuiu2N58L8NvTu8+jt0dy+1qx+8XzFM0Z3mLux3bGnKyfZpNPoJwi7qfCf29OOzxErQWy152GD7yT/U/WfOxfdHnqAB5GkaHpdwxbGxn2/pz4tMFnDVChaWAZCi5nzLg8M8mWLVSWgqMridwvVCFH1xyhMzuI+WENifR4tRjvo79ZFJ30OEsEx3FViUZCy49o/EhLYCx/iTUmRLyJzNfneA1zB+E6ZGheT5fvZYNWTbmh9pgrsV0L6QLhMyGiiTIHdSMk2NeDk7MIY2BX5kB+ShYelATfz6PYRc2VqDwG6cKsF+qnyDIpq9EwzWFqhOSbGDnOLp6BM1tiwfXZdfjDHE5ZqNN3AW+gTXEsIe0unZQLHQNvOQFvVcjEXcgRCqCESsOVAr7ch8stvKUWtcVmUm6se3hvsr9aCE5lz92NqKAu4c5QtiM7BRsKeg3oqRzzpZbjeUmvKbi0JjZjAXiolrDw3AnxopD3aSd2YM8X8MmBkBWfvw2T29zNWitgAD92CO+difXdbh8OktJjMasqA3s57DkhlpZCJ+R6dN9Absdx08Lv9eX+rXP4rrFYf32oDy924dMafsuIauZoUL6+ubTCCiussMIKK6ywwgorrPBawGuW9DBKo1VGiB1UjCgt3ZxKKbTSKCWKAOUbCJ7YTCS50xiUlR/rorCIRBUwuUHpXKxmlJLCYbB4bVBRo5UV334vVgMRpJBsFN5D6yCGxS/89AswKGm1DA1K1cm+SC+9UGLQUj0wiP8BgeBqQqilqK4NCi3ZI06lH/oLqyxolSNGzXge2ZkpemVgqzOli8c3NS5Kfsdodx+38yyH1ZSeHnC6rxnHiv15hfeW/YMKrQ6wKO67fAEdI6Nqj1G9y+b6Nv1ekdZROByIuDChru9gjcJajbKRcthj6+R9BJ1x+NIBT3/sM4xnEy5cvIcTJ09yupRw+RgC0TfgK6Kv8b7BByfd8apI6oUWomyp1Z4Yg1gQJVWFphWCQVuUWRcjEF/jwiLxdPEr3BOXhuCvNPZ5ZZkKIg7PfNmV+/L3xeTvftSne3zpKW8kOmKwEmCvPMEFUkwJkEpc2pBlXYp8gAotTap2CoEmXu5RpQyT4AieIxIrkS5Bye14lVRyQYQa0lasOXILpZFw915ZkCtDkdlkAaPRxmCszMtgpMDknMc1PllWKbFlMoayLAneo1JhKLhAM61wjZcg8PKIilmMjjKi4IhK0yYCy5aWjoE8k2MrAq1zNI2nqhqCi+ClxFjoDGsMWi3N3QhGyEsXFHUtNlDOiQ1X8B7nGkIITGcNrZN5kRuLshlFlqONQpuI1gZ0hndpu1tQVqNzqTS3tsB1FWUnw9qk+rFgO1Bow5nTA0wnUhZd1oc5WWaxShQdaPDBMZ1GWhsJrczpuhXiMyCWW61L6+4VwUeIyZonGJrGYrTCmKOsjsW8NUbRLQ0hRLK0bjFGvPc4H7AYUYqoI2Ou1+xJ/d8xIvDiFK7tShf0A30400mkQbKJubQG7zsvocibXY7Xw4kamgJ8KnjmldyjoJglAdIxFYeKR3ZYxstlIyixzbFzKA4U2oHvgC8jOhjyWQ/TZNzb1rzvxIx9FyjGGfnUch+GU3SxGJ5vZnx2PIIscnkTTnVA5UK2eA8Xge8M0M/hHKIeudXWfC7eYaJKdtcuc9/gcWwYcaJ6gq67w8kIn7wlJf6XprIdQ73OA/kjDPSQa+4KzzdP447RaqfXTvL/Z+/Pg63LzvJO8PeutfZwpjt+c86jMjUiJRoSIWEmYWNjg2W7qjyU7cJdUW5BFyaqXQ1RUV2Ojgq6O9xhR3WBK8J24WoXdBubqcBYgBiEQUIgGaEhpZSUSuX4zXc8wx7W0H+865x7v1QmSCpbKMV5M05+dzhnn73XXnuvc5/nfZ7ndXe8il/8+K993nif/doB/mpH95lAbIXZToCdTkldqyvdoJswbjaxh7uY359Depyz+w3f+uq389Ad9/Hap56i+OxnCF1g/2lP/9FI9VTLpOuw9CjMvoHu9TSvBZ6UEXFZhYrrPR96EgWGC3lGLEh0nOR56PqwzN94sWTtE5ur0z9riRzmrxtOQtGXM29pc3jaFlPpdAGikVWGke2VVHDdaYsq3Yb0ifom0EAqNScCUZJjBYTXasvUHfDiC+BL1L/a2OMu2eM1/nlKEd7g7+Uv3LyNuxEueRhmUqMUJeeKZY/B6eV4aa1kwDol1QN6PLL86BTVnu0bWrVVekOj6kFJeuxFUALjZqEkS0x6zZURbmthy2cCPLsTktUNlYHbghKAt7WwM1fC4aqDpwaq6No2mjNi8qPz8OmrcPkAdsfw4AW14LpRwRW9rbLda8j5braAa7IY1angk5DP20YPd+bPjts91F4JUDn98UJ0nx5c6L3gIMF9F6AZsCJi5jvw6SHcRO8VHxvD5Qj7AzgqlVyVbIU1LGECDBzccQleFZRgPd5WNc3zBp4RzRF5bQO393DJK9FxYOGhVj+rLIAnBB4zIB6+bU5W3mr1R/CzX/hUWte61rWuda1rXeta17rWta6viPqKxcecs1gZQNogpYQxU5JdYMRQGM0pCBKIfk7yPdLskdoFUg4QuwViCalTEN0YikEJVNoi7XvVBSQFiJyxDE2JsYYYenzfIyLUgxJXOPom4Bc9yedWXJsgCSlYzRfwEStzMJ4Ua2IskSDZBNtpB2YJKXl8bPH9EdY6ClchxmKJuD6QxJCMIxqnJlfS4RGuHUQ+d9WwOYxcrPfYiIJPkYYBrY985plneO7apxnUIy6cvY2Lozt5Otzg6OgqvY88c/mIy9dmvOLuS3zL297Ame0JN28+w97eM1SDDXZ3RqQiWyMUQEq0/gbT+U3KqmC0tYWrSiYXdrjzwbfQLCJXHnue5z79M5y953a+5tu/gc3zu4RnP4v/3KdJIUI3h9YQu2O8b+j7lrqsqKSCpCRHChGTAs52kCIN4CMIAUeD4HFuB1edJxKJzRV8XNwyTxSgUuRFXgSMUljpVEcmEOno0VwXmzU4t24zcpLEoVtYmpQZIKRASD0hGELTYXrBt54+pRXmY4HCFAzrbUbDs7TNlPl8XztXywFiK5COyIxIiw8dfSf4KEgw2GjU6914ognErBJJKRFTIqQIJlGUQoowKGDkInVlcJMJvk7YImCkz1ZWFUXlVuBUSuAPe5p5bit1JWIsRVEwGW8QY6SbL+gWDbHr6feOAEO5VZOqMRhZebsjgi0KBXUNNEEzcupJReFqiIJEIUZYtB3T6Zym7fFtBG8oUsHEVThnaaWnI5AkEVwPxhOCo506YhRmC6Ftoe96ZrMDgu8xRcK6hLOWyXCDQVljC7WeMgaKylGUjhjUgsr3aglUDRQ8S9EpAWdkRXrYCkwBLjke3jzHA+EMYgzWqjJHRLu82y5w+WbDdOZxNlA5nztxSzAOT6LpPCEZ2lboOyFkuYylJYWSxaIiBg14rwYKnC8h0dIZtscFKbFShKSU6PqervfUFNSVWemVstX9ul6kYoLfvwk/+ZhaSf2nr4CzkxNLKiPwyEW4+5KO43mv10mOwCEamI+VWHAeRjP913UwUrybbqj2PCvCI+VQ51Yvla7UTvbRkTB+ylIshG430O8kXF8wuXqecrbBG8/tsXnvs/QmsfvEgM3ZkJoBZzlLSc3vL57n/9XOkNrz13fhGzfyMeZu/zcM4WtqPaZJgmoKH1wc8z/Fz3LNjLn30rfz1nv/OrvdZ3jz9f8bF+fX+bU5/PNPadf4ca/7e9Hdzl/a+OvcUzzAL0x/muf6p/HphPR4xYX7+a++7V0vSnrc/xc3OPjQnOeutHQR9s/33Dy7IFjPooBghDueOMPuR95AeThGfm4f3vPr3PfQDt/3n/wt+ksDBj/149TP/hO6xZRnfq/h5qzn7GemPDhbUDIgURGp0UBz1Tkp6XADReArhFLvsRwSaXHcheNB1EzyM0SuZKJ7ec/viBznrz+f9LgV5VdWTO/jammVMpF+Qngst3MqbCEr/ASjc8sKXanzpZ4poVYtTkiPJRFvF5HR04nKgN+B9jxKMLSqIliM4OZFmJew2M/qjy+w/u6Fp3jn+Pe5e/Aedr3hz7d/mW99+hKlE7aGUGayPGVVh30h4XEyHIiDolAiAqPB6pDzMiLc5uFvT5VAmBzBeKrbKYZQ1Ko8+GwJew72BnBdYMPDt92ArSknTmaQZZUwtPCaDu4BJgs4e6yf8T58Bj64oUqPV3dKuJRJyY+9Gfyzp+FXH4OvuQv+80twx6YqMT5ZwiTAwzMlKYLVa7+zMMx5IslCN1BS5lyjD0nZNuuUEmY1Nqjd1dsP4c3HSuB3D6liazldnh3AP9uEf4eqxd59VomSI6N5HMfAkyM4TvAtHv5yD1sFvO7VMHkl7Bq4YWEu8MsOfq6Acz384HW4rYdXtfBf31AyajPqfh4JvM/Cb1j40zP4P9+As6em/vF0TXqsa13rWte61rWuda1rXet6+dVXLOmhfztr17v+QEAUbDSSg5tRqySIpBQg+ZO/yCHbH2mOhpgMf5ukf5GnZVR2Uk9tJIce58fS6MgYRHLYs+Q9W/oZcOrfVZhqZBVnHrM6ZBVYnsGLpA9Z5hIsE5aXCH2G4WOGOjqfWLSR2kHM3tkhQZeE1gvzpuF4dgwYJBkKo7Y+oMB013v63pNiYmMyYndrgxQmJD/BVUNEoPMdMQWcU5WBqlYyzO8SOCjqitFkC2MDR01Ps5gRu8B4MmFrd4fZzStMZdnfmtGRZQj8Cr1ZjjFZvHCSzSCrtlYdQ32o4kd/tszeOG0r8kLU5Q+aT0pi6Lx4aRssXvCbk0j6Ww1LIBHjUvlxEr0OS1MVzeowVrNjYtR5IEmDclMyigBlJGlFIqSEJFUKLC1LbunYPXXIoui7qqGSHp01osoi8cTQ53lQrAZCZHk6Ug5aFyTp+AqqUFFg32TlTiIGJapiCPl85jOQzyFJ59rps2GswTrR+RoSMUZ8CPR9wPu4Ci4XwInBGUMnhpXKJh9/SnothaB5BT4/+i4SQqAw4EolBayzFM5hbO66z933sjwrRm29rFVQTpbX9IudfRWXUNvilF3erRXyhPBBxz9I1EBhk05uFUmPIaU8L/J1b+RkDvmQQbIXlAjYF7y5blPJr+V2k5wcxReBc/6xKskqn2mnob1dPLkVLZUZYwdlpc8tWp1v+caBpBPyI1i16BEgdmqbBpBqTu5tS+IjKqkSgTaoPVDqYdQK5QLo8m0gCF1riY3DBcP5SkgWzpTCljPYaCliQaKkTY79fBdsTFZvLZeuBOMCJqXOvUWEeQfHIXLTtDwRWp74xH8Pn/jvV2PzzGugnsONBVw/ZYtkxTEyEzbsFrUZ8EKLp0FZc9vWOeY/8iT/8D3/mH/4y/+YSxdu47/9z/9b+sGcUDQYemzydC7gq4gvE/0EQpGIVy1ChfiKdBCIBzPK23e5tH0BLm3Rb2zTi1GStoVunvBtumWdz6vI6honU9TQI0sJ48o7SK0JNYMjAnZ1116uL5xaH/7wteVk/VfV4XLlPr0SwMnqkE696pSMaPnslAm4cGIZdevvEzbz1HFpYWVVIWF6MJXOgWAyAfZF1J71TF1DLI6xCLtNx26XDy03Q5A8xE6bAZLKDlK+0a3eLqFWTlE/yYhffRRQcD9BkYTd/DObr5HlNUhUte2sh6MIx4VaZRVJlRarobMn9+mlymqUyZhhgCrPYw9MjX7YnVsYiO6PMWpfdRTgRgeHXq24vGTRRdLrsg4wDtCIPkL+HUn3f+mUVUZ9T/NCwempjzzLczKM+hABm13ROslWYKUGrJeNHtvCZh2TganAIXDN6L/TpDZ7JbAxhF2nr516tSO7XMBThTpmHThY5Cm+E/K6m+dXQMmUPXIQe4CdU/cBt/ZMXNe61rWuda1rXeta17rW9TKsr1jSI8x6bNlgTKl/LMaOiFfwOBUYMTjnMM4QYsnCd/TWYqXEBoNEcGJx4nLoclBFgDHgFACuklphWJMoAmq/lEx+T8F7R0zaQz3YKBXc7Fs634JSAxQIYWGIc5ttawLGLABP1xuid4gIUirhgTFYN8QYi6QSiQYfoQ/5r/BUkaRCCFjpNCNEjmmZ0eLozSbBVuwd9Xz2RkfbBRbznnEZkdTwzP5l5GiPw9kRMR4jRCoMDmFIR4mnlMh4tE2yFZ1PPPfcNRZPXufMZMJd53YZ1wUXzhlGE4utC8x4A+qSrUtHPPiqAX0HC9mhlQkbl3YYjNQ0OhGJ0YMxJDOAYgNTjynGA4pxRYot7ewISYLL46cWTxkCij2GHiHlzA1HHyC0c1KKEBKOEjVEKlCYqsXSvEjv7RJQihnaMowocVh6PItsibWExDTnw2RyQ+mmJYwFJ3CWIDkrYoSIw0dIqacPYWUHodsSohgwFjFq/WSTUZKh94TYgATEFAoQBYfLdl8mtZBHSHJSrdHQmmzvlsk4LCkUxBCZHwdS26zOA0Tm8yOmiz2MtWy15xiNN3CFZTAslCAoDFVtNGw9BHwXSV4tmlIEmwxVVWrQvPeEFDGVYGqLcYYiA1aLReD4YE7XRja2S7Z2at2+KOHRzDsO9o/pu0DbQttB3yeC96TYYyRSVIaisPgEMVlEIEa1inPOUBZCSmoBNaghBsfWcIMUI66GYgDGGAZlSWHNipdMwHTa07W9XrOmRMSqH3viFjIjRQi98o/La1JQmxZrlGx1VmeWjwkfI12XsLGgFsegjmxuqMpl3kDTkkkoi7OGQQ1OhBiFtq/oglN1mQh9jBRJiEm3H/L+nS5nc2YICrxHA22C1Omto3JQmi+EAvzjWdsH8GYDw0tKej00VJDV9VAfg/UKQNqgoPGs1s7uwQI2j/TnldXfpZw90A3h08fwwRu6rUcLeOUgKzw6BWOrhXbvHwZ47xw+3kI5S4zaQCXwtWXikREc2Z73ues8wxH3dwvedOAZFwk/aji8J+Cajsn1AttUPLgz5T+5EEkVPDjOOQ4hWyJFKDrNe9j38J59+FSjtkTftQP/j+c+f2x8BeGFAULANX+Znzv+CbbtGT7VfZwuvUBHZBoorlLUFW9/5eupB/81bez54Ic/yPs+8j4efO4Mb3vuLsZtoE036Y4S3AbyKMidMLLX6B7/d/RHW8zlW2l4mHq8y7atFWcXT7QL7KDn0sMb7LypYlSfwX1wQDp0wA2Em8udQdF5pwoKhMActbpKCCWWMlO7S/urmNeSEmGo91TmROYsKfKTWlIVqvxTWluDFFQHqNkfaQWDLz8hGM0JY5lPdusVKgnKhTDZZ0W0+vLW86HZTwUYR6qEmB0Si7ne50zQ8142sHVd7wWjY07ZY/3h9d9cv41XtZbxfDe7cD0MVWYAjtAb0uDjMPptkAIvX0+QB2+Zdxr8BDi9XooIh8/B5Y8mQgeT+4Wzdyr58FStod7nOrhzS5+LAXpY7MEzz8LlBdx5B7z+bhgLXGhWQ6tKDwNtoY+Egv+Vh8KrTZMDHmjAzfUlSxcpCwwinHXwpx+Eh7bhjjG8IsLOoQaWX3SqBjmXY11agf3sWOoH+m8wMK2URN3oYZdVpMbJlMzB4ocF3CiVuOlEh2qjhduPdazeO4Ff34CDBTz+YR2Ds2fhm++GUQ1PDeG5WknT24AGeFMHty30OPczYXND4FccHIiGkvdotsr7NqCrT3bNJXjNFF55OrEc+EgN//DMSQA7aMj5uta1rnWta13rWte61rWudb3c6iuW9EjznkSH1AvtlIs9MQZEMjAtFmsKyrLAx55ZaOittjgmL5i0zOSwRCLNMrvBlCAFApSpw0VVXNiYkCTYVCKmhGTwwUAQisIxHJcYI8zmQjNX9YizBiPQ9YYUHTEkRLw+kqfrhZAcxmVQQrR73rihmlskC1EIMdJFVTcoKDMEaXGmI8VAkCktN+mkJpgRwQw4mCeefL6h6QKbhYJji9Tw/ME1mmggtpCaHKrtqLHU9JR4ComMhpvY0VmOjudc+fTjPH/lBq+7/17ueMV97GyNObdbMRyXSO1gPIK6YPP8iI1YkKKjHz6Ar27DjizlqNRzliIxBu36txW4CVKOcKMaNyoJx8d08z2MWGyxoR5CaA4ERJAewxw1nRqQsKSQSGHprw6OQsEfhiioBIb2BSoMyb9Zwlrq4j6iZkDBlIaWboWd2NXzTrJgIhpIvtSDnDi+g0iBNUMEQ4g9IXl81GdkzcpKq6KyAlVM2CzqCckTQ9QuT+uQINhocGgHs9ABFkkFkhwki5zyKVkSH4IlRUfwkeY40tNiXaQceIyNzGY3uX7jOcQ4kIoYK+pBQVU5JSWsUNYW7xPNLND3Sb2RGoGUsJXBlQU+BnrxxJSQAkxpMM6uwJ2m8UwPG+aznsFAqMoB1ijhQYSm6bh585Cm6UnUpFQTgmaKpOiV9CgNZWnx3qj9E0oOBFEgv8pWJkWhXcASHWY80W7VwUm37JLECOpihw+J+axnf2+OdY7hyFKUVgG2F95zknbshwBtn1j0CREoS31fZ5QYNYAPkSYEfC+YVFBhGFewvQXGJOJ+R9N4JAnGWKwxuEo92GOCRWvovM7ZLiVCDrxfdk33OVvodKkKJ++rQBKhT0Lf6zQT0X1ckx4vXpsHcLGA155XZURTa1ez9Wr/VHS5O12gLeHmJhwPtSv6zAKqU3h/V8HeOVjU8LEAP7anRMfODjxMJh4UA6dsoJxr5NQHnodfONSfS4rUBmIJDw/hqnh+ytzkfQh/rkt87REMSujGLYszLdVRT3XkKJuKe7bm/Ln7E9HBqNF9dz1UGUCNVkmPgwDvOVLi4x2b8Hdve2nSIxafP3duhGv88uznEUQtBl+YmyQtuBvYasRbHnwVb7zvz/CpK5/hB37iB/jFj/4ifzG9hnfEd3CRmqbZp7kBdgzDV4B7IzRXbrDY2qNPZ9iXP8WxPMBkOGRsqhXpEaTBDDzn7p9QvHGbdLhDqmsiDsMBwhMo2XEJGKNh5koSRxYE5ggFjgmGMhMZM5aKQiUmhhjOAgWB6/n3J0T3C1UZ+pVBVqTG0tYq5dctlXMuP1R9IqtnnFJm5a7+0ZGes77OIeVZvcPqvZySHrWQskrNLk7tkEDRwOZNqAUGU27Nk/hD6r+8eRHjL2D71+oPSqvEQoPKALoEO4/Dxk+S7ABv78CbB7G9Kk10IrFSLtmo6oz+cuLaeyP9DO6wBm4XGlH7qislPNTDpQ0lKhCgh+YGXP4APHMTXvV6eOsIhoUqSCSxsrdKVgmPqVMQf8NDnfMuCPoB954Ozi9gbuBKoWoHm5T0GDn4pnvhG++BuoOtYyiO4IyBhzIBZdAT1hdK0rRLVZVTkuHQKokhVgPPb70+AF3COao1KLw1aj3VGrh0DOeONMfkAzX8jzsQrsHOYzB8DHYegLfWsLMBv4+OQQD6TOi/socLrb7NXgGdgytGA+I/l9eCiB77hyZw5dSu1REGAR56AenxyQo+Vb1AXFqwrnWta13rWte61rWuda1rXS+7+oolPYKoWZRJK7OolUHEss0xhkTvFXQmLWEO1I4n+70kSUSBZCQjoomlt7baDWjfp8noggZEa6dmivk5GViOYojBZ2+DvD+iXfFLvcASzIjJ4PtASAnnhSKpqkE7SV22vGF1ZGIiSE6OSD1CWNkFLf8XY6DpWuaNw3uv+SYWRsOarYHFdsLesaFLUBhH5UqMwJCKUhxVVYIkYtLMhJXvQhTEK9jnKihKsBIR3ysq2HeK6AWvFlQCKQkxmpUCQT0t1D5IBEU9JOTnG0SsHl/K5FPsEFE6IZrcOp0sakeilmIJVc5o0OzSckThpROjq5M6DSYtO3GXFUn0BCyCX/mtn1hT6PfZgHwVWQ4Rw9IQK+XXpZRIUVvxU+pZ5opkjB8rllIKClMo5ZK8UjIr7Ey3rCSY5PFazQQSJmtQRO3blpMgrXaKFJXaca6ApLoYS8S4pGH0BoqyZDSeIGIprFPLrBDxXa8ygaTB55aEcxBjhHJpcgWmjEip+SLBRmwMWOuIQTT4OT+MMdSDrJcxwmLhsdZQWIM1grGGoiyICboefN+TJDIYKrlY1iU+JQiRzid6r74fxllERINss+oiRbOcaliXh3PJvrwAcFoGtFtrlOixlrKULPRKdF3MnJTBGM1GWfFUVgG7hL53jInkDKURMJpPEkJ2pTOi+2KWdidKbtpMdgUf6Emau5GtemKMxKD2XYXTe5U1srpFnYZYV+HYcmqeJx2X5CMRjxEhWoMUhnW9eHWlWr7cWAAWhiPNHEg4XDvEtYZu0BBMQ8xOiC6qtYtt9ZHyLcI4JRkKB5sW7tzQW964zFY7sLK3SqKd+wicGcPdeX8k6ftv520NergjCQ8h3B4cg6agDDo3JArFwmFCgZCVY8rJc6WBZgabHu7qdJ+jU2IGgXNDuL+HS5WGUb9YRQtjt8m91Tm2jSD2GmIP8DJkZi4RGDJq95k0N/DJcxnPAXqPx84RN8MavT8MiyEX5TbuSfdxbrJLsdsh1iPHPWYKNNBdA/8s9IcQTSS6SG8NrSmoC7dS/yWXiIOEDCIyyE0QhSeKI+HQO3TLiUFPADrUvsoALZr3sVTwZVR+RWr0K6r6BOJeXn3LNeSFSPYtI/ci6g19jaozykx6hNV29Hs59dxEyhZlMdumPfTrp98j8H08yffxJJ15hFAKvuKWm8RyXiaj514/83Bij/gFVLmcuEbbAAgziI1mk/WlSgb6AXR3ga0xbowxaqslp0PN82cAm9epuhC2dwQ/gHqgzzFRSYdxVHVGsjqXl/kXdQUXtvS5w4laPgWnrQ6l1+Nbqt2OLVy3qsoYJLWj8gJtpbvUOCUJOqPg/8yotdTyjBdGr8XC6GcgBK47uFYokXKbh40XENA2qTLFoO9p889ap+qPIur35P1Motsa9UpM94XOQslTQAQ2E9wV9fUb21CdB9mBTw9go4I9q+NjRAkLbWhRxYmgtN84wDZwRya7DgT2RPdvK8LFpJes8VAFVae8cHaXwBjd34lXq7DQwMe+sGm0rnWta13rWte61rWuda1rXV8x9RVLeixKC8bhfAGSlAQx2eanLwFHGxcEP9euythRpghBO5+JiWQiySTEgC0tYhyCRzgCwFPQmwqLtuCbDKwLCyCSwpwYO/rgiL2CKNFbxCsgHUgEMcRegAFIzj2Ikdh7+umM2PeMbMlko8bgCKmCNCLFHolzTApQBGyRSY90TPSNdnwjhCgrm5ve91zbu05o9pkuhkzqTYyx3Ht7yW1nHdcPPEefWhDbwNlJ5MJmwFmD2Alia86cOYOYSB8aeiw9JaFPVL5gFGqGrqDehHorYpnBkdduT5mpr8u8g9CRIjTzwHwRqEQoQiacDBgnmCIhtgMzB9Mj4hApdUyZZ2vwVoPgpSKaEWovEjA2A1Ciwa0hdoRMPoVsO2UwLJ0/lnkbSlykFV3xwlDzQOSQBVMkG52lPAeUqFDLrFq7aVkQ6TMYUBJxBDyBFkiE2BPDnCACsgB6fJrTEOkQqmLEmWLMZjlGosf3M2LqSC5BXOpAFCw3zpGMgl4BJfu8VHgGmJRwKXA6PTYlCB34BRhKRqNNYowY8RgUwUhWkfud+gxnzp3X42+NKgcaz8x3iIFqVFON6uyzHildwlqhyAHgWBCbCBHGzQgfEs5ZusbQSybHLJSl49IdG4QQmc49zzw3wznh/NkhG5OCalCys7tN13tu7h1z3BxRlY7bbt9lMqnxvTDrAmERmDeBto24wjKc1BTO0vvAfJYD2U2BEYs49a+3Vs+fjydKCJGs1miVlBgMKoYDVbcUlcVYVafs3WwBGA8r6qpYESkAthJqLN5Hbuz1TKc944Gj2h1gRPC90C507tkiEzCFZjZIBDGOQW2JMTA97kgh4IqCqqhIQNf29H1PWVsm44qisCc5JJwoNgQ0AwS11wIlPIIX+s7Qd552scAYYWiGSF3faq+yrlXdOAO/fxXe/bSSFd82gdeehfJog+HeKxhMBzTDz7EYfA5fRMqgnfSjY6hvahd9HECs1L9/dKwWVo8MYeeVCmzeUyhwTVZ6SFLCo8lWWt+8C6+NCl7anONy/wI29mDQCv+HrmCK4fxiwu3XzlAZR7RKaBmfcIslLdoAwjTAz1+BDz0Pr3Pwtyq4y8JsDAfb+p7fUcA3zuF8D2fmLz42voJXjF/Hf7b7H9NHS7nxL3CjX2Pf3sMnyv8jR+YBXv3sr/DIkz/LoT/in7DPrzEHt4DRc5qW3l+ALrFT7vJdw7/I144f5d6vucrkz3xG/cPefQTvTXQ3YO/d0H8UiifVQSkMhWlVs1+OMZOS4JR8DmNoL4DZ8dS7Nyi2D4jjLTpbk9jAkjAcoFfLIWpkuIHlXFbxWSWes95TKYpm9RkAQl49QqYl7epxK/WobHPKK3Nubci2VcJSE3iSOyUIFYZNhDLTJyrLsAzyz7zukwRCIXRDwReJ+eil53B0E9ptRzvOpFomaoP2DOieGhVl9NMv4uJYHpJD0fPYw9GnYf6keiIdX1BPJ3c32L+NuALnbsdaJTxEPzKpMqRW1UMZNRfn0i5M3mZIATbOgnjN1binhXMRNoAw1IydpWXihXPwZ98EixamF+Bj5zXM+8FDVW0ECwunyoZPVfCxCrZ6GM40xPywhGfPKF+j65gGgT9VwHEmNC/0+XBjji3LhII38J4x/NgW7Ab423vwdfMTItMmGHrYznknWzmzpCng+lift9PCRqf3gs7pv5MeHphrBs/nNiDVOlxLhd6b83j1JfRvhvAauDyG/+euEllvEHgl2ZbL678DYK9WAmSUNGB9aHWs9gy818EvFWpV9WgDb+9VdTbYV2XN2Uzyn66LwOujkiSPHMFDxzA/hu/4IqfTuta1rnWta13rWte61rWudf1R1xeFj/3QD/0Qb3zjG5lMJpw7d47v/M7v5PHHH7/lOU3T8K53vYvd3V3G4zHvfOc7uXr16he9Y8GIEgrJEKNaWq3a4qKFYAk+0vUdvVd006SExEQMiRATfUh0PtKHZYe4yYHPHUJHFAhYApaYO6fVXigg9JAWEGZEP6Nvp/TtjNB32aMokkIk9iHb0ChakFJJSiUhWrrO07adhoinHHadHDGVpORIMXfXkzA2Ika7VFNsVEGwDCnOYxJjZL5YcDQ9pus7SmsZlCVbkyFndzfY2ZxQ25oiFYxcxZnhgN3hkK3xmMl4wrCudfhSUGImnmQ3FMlRGIOrErZOCqB3DbQLaOawmEHfQgbhg4/0bcL3cUXKiOSue4O2E0oPEpHVDxPqa97p2MZ5ti2zxORIySFo6LeGPQeS9ETa/OiJBA0Oz/DTUh0Bn9/Q+kLlR4dnQU+/ojyW8bNkGsKy9GgnbzdiiTgi9uT9UiDFPp+jjpg6YvLZUUNwpmBgB1S2RFIkxl5VKsthMAkxATEpP1DCS5Y2W5Yoy/dMrFJg80HFANErUVOUFWVVUpSCKyO2jBgHYoVqOGB7e5etzV3qssImIYVI33R0i5YUIs4ZbGEpCkvhLFVlGYwd9dgxGDnqYcFgWDAYVgwHNYUtCF4DnpdKB2uF0aRgY6tCrHA86zme9ppTI+CcpR5UDAYDjBN87MAExhs1O7sTBqOaPiYaH2j7QNN52j6seqhjjPQ+4PtICGk1FMaB5NOVUlZ2LM99ysHnAZwzDIcFg6GjroWqAiHRNJ7FwtO1keiXqo3cxV+opVZRQvCBxcLTduGU+gu8F0KOCbKFvtbnPBBEsM5gROi7QNN4ujbQ9Ym+T6oC8zqApYWq1MyO052/Zqk6kRP7qmXFKKRoCH2kazq6RUf04Q/sSf9Kqy/negKwGMAzCT54DL93DFeDevEnKopmh2JxDgljvBOC1U710qt1lF3ow3Q5ZDr/vOrgQgGv3YXXnoGdYe66F1ah1NFmL/0R3LUDrz8Prz8HbzgLr9+F20soW/X3f200vA3LK0PNeLFBOdukPtpiuL9FfbyBCRWKSivC3UV4cga/uw+fOoSm0c77gNp3yQDu24Q37cCDQwVKX6y8EbaKs7y6fgOvHz7CI5vneeOO8DW7m9x77hHuPPcNvHr8EG+XDR5lyHmKTMh5cDNScUyyLclC7WruLx7kDcWbuPfsXZRf0yNvmCrrAsQ5zD8HR49BcyWr7QroK0NbOfrSrpQesYA4hDhKpMECqmNS0RLFESgJpLw2zInsE7lBokUYAhOEWtcUrKoK6UgsiByTmGYV4S3mhZ/3kNX6klb/5wUrSLpl9VHFyInSQ/fhZHslhhpDyVJZkiyEQgmyvnzpOZxMSagNfqgcRKjB1/p1nx++gle+H/7+UzD/Iuyt0lIdYtHJHw5g8Sy0V6A/IPVTUrdBal4Hi9dimh1cI9gGpEXTspeBGUbVHDYIo4Fw4Q7h4p3CaCIQBRtVmXQmwAhITo8/OcDBaAT3XYCH74DJGbgxhBu1qjaW6glvVL2xZ+HZAq5YaBIkr9ZRBwPYG8JxqeqOmVHi49BkB8fVmVIiY6XMEHiqhN8YwQcGcONUa9Dy+S6pUqL2MGlho1GF1aKEWaVZQEvlTciPIsBmA1stDHwmeGClmLwY4WsCvM7Cgxfhnvsh3Qa/O4HfHMCzeT+KBJNMSpTomDRO7wobAc4HeFXQbd0W9ZNpCVzy8EAHr2jgVYfw8CGcaT9f6TFKmhlyT4Q3tPAn5vC2lyBLv9Lqy72mrGtd61rXur46a72erGtd61rXV099UUqP9773vbzrXe/ijW98I957fvAHf5B3vOMdPPbYY4xG2p74d/7O3+Ff/+t/zb/8l/+Szc1Nvud7voc//+f/PL/1W7/1xe1YbymswWVbkBDjCrTwMsVgiDKFNIfsiS8JovcE35AimHJAYSswiSiRhBASGg4NiNUOeTW+CKSUiMaQjCUlg/bhoX+xektKQpIuqwAMYiqWiRAp6euhBekJ9MxSoEvgkmEzOe0eTY0SIESSCCJOv/c5q0RR9UwaaN/oznjA3efOYFJAmDPvPSF4Qn+IjQXO19RxwNgK57eEwsJWJdioWRDBN3h6zO6E7fE5drY22V8IfQPWReqtEaMUKCeazhlbSKnQtnlLRlzJXj8CMVKEmwxioOzGSHMRTMli/5ibl5/DlY764g513ERiWj3UYgoclmSHiCmyn3qvxEUypFSTUk8UbaOUZHGUGaDoifhsFbIEq9SqTBBKUyFi1U4qdqe6crWWJAic/KF/0ssbSDRAj9Bh8jNVGXSiMxEEUiLGiMXgygprS6qyohahISGhoe+P6LsKH/psj+QVYMvzcAmfxWSIKRGS0RBvlp3cCnoLVi1KsodTBPoIbUyICGXlSFFzZtqmxTpHNRxgjSP2luOgJhriDPWkJIaAbxIpJYzJgBuJPkS6EOmayLzPZIWxOJvbh5dArjFYMQrU5KkaI6Rex7awwubEYqyChV0Hvk/0mSQZlAPObOzgCst84Yl7M4jCcGSpo81ZJYJ16ncSeiidoS4KJQCc0e5iAyEq0bG0KCNqeDhBz3yZwcOQYJq9REyr9FbfC1VZZrLEMO8SzgkDtxz3DIqJMBoVkISqdIRo6HuISW27EuCVrcJ30PQ602II+aGWXSHmeGWnEGoMlpQS1lrEnISX9345pkkJlqiWZABlZSkrQ4pQFTpWlpIUUyZI3IroeTnUl3M9ATj72ZLXtpE/fdFjC7h9pEBvN5izf/FZ5lsV0+09ukKVVy4ocJsKaHb1/OK0azwUSmT4SkHSMs+vZXB0FLUpEqsAbXYv1O0BbmEYHDiMB0NgvhUwPVQScE2ianrKqYcEi80F7bhlv4t85MCz1wV24oxzPjEWJU6cqL//5lywc2G4l9h2SW3u5GRO9y+hIviZ5xKh+Rz99OepcbzZ7/PKo9ugTjyw84scFR/hQvcELl1gzCbfwJghx7z6xu1MfnOTeHaI3Fkid8FxMeUD4X18uvkMr55FdvbupGzOYWdTCn8TH3uSLIgmQG8oDiwuRHaLD1I4y8bObRSzr4N2A+nyUpiDqfEgIWGSBoPrbWmpzhgBBYaKxD5L6YLhPJFFXmd8VmAMAUg0qMVVS+IIWJCYs7Q4NFR60unz715IfJyQIi8sVXLoNiOzvF5BpCGpTpSlueLptekPqsg+xB6JOq/6zKXkng5MUDLuS6kPbcJuA7fNofQW0kUoQ/a8PAOpJozHhA0BoyC/WapNXlDBwHGldk+xgKjOmmxkSyuDEoYu6McMZ06vxaxUJ5JgK8C9x7kVwcD+CLyDxqqN1fkevjYT8B+u4cMFbAmcn+t10Rc5FD4q8L8lcK6B8VzVKCXLT3Fqo9WIqjZW+2GBQj8NnlmoUuMTFt4zUpuseyvYDEqWD9SZkamD+UCJjtFcOaTHC/jopq5dtxu4vVMFRqo0l2ReKSmzMHDVwtTAjT3wz2ujw+FFeP4sTEX3eyF6/L0oCXMxqcVXGWC3V4uqR2o1fXPATQu/WsPZBA/uqFrFFkrwT0slgEED0T+BkkiXBnrOXiacx5d9TVnXuta1rnV9ddZ6PVnXuta1rq+e+qJIj3e/+923fP/P/tk/49y5c3zoQx/i7W9/O4eHh/zTf/pP+fEf/3G+6Zu+CYAf/dEf5eGHH+a3f/u3ectb3vIFv1fZOsraUgzUnKJvI/hATA296dUrnQWkhYKE3pKiIXY9vptDgkGxS2UrtXtYRrAGSN4hZOMi20FK+CXkIFZ9c+JSA1CAT9oyGRPBNXjbIMbiZIKRSsmSGIkpgsyBGV4iRykyi1Alg6fMYdQz4JBEAWZEoiSmROyWsEdQUN9ExAasCBe3Jmxv7rJoWy5fu8bhfIb0Haa7hi1Kiu4cYz8iOuHuc8LuZsK0DrMoiTHiuxmt77AXL3Jh+07OnbtAvHnIUXuILYTRhU3YKhjuTEi9JSwMqXRqcl1EbW9e+WgYTIjU/jlceBbbnsfOtkmx4PjqHpc/82mKYcnmvXewcfEC+IgJEZOVJR0QjWVYbIAdYlKPxEbPQawJcUCiITJFxR+0ygABAABJREFUrcYqHGMgYThGz1QgMkezL3qEiBFHbYc4W9OHBU3ypBRWnZmJpQHJS1UgMUMNSpaJGglDl2EthakU6I+EGHDJUNVDysoxrIeMROhISD+j8wu6tsD3rQZ2h56UGlWoiCNhNRcjGULUs+7zPgoJh5IaKymDZIIiJZoYmfvEoBBGVUGKhuPDwOH+groeMBzU1G7ArOmZzlvECDu7FaNxgW88XdIsCCeKcqQEXfAsek/fexZNS0qJoauobYkthHoDXAnGOoyUK8IjxWV2hn5fFYazuy6Po7CYKwjfdaoqGtUTJuUmffQcHh9zY3/G1uaQi+c2NezbGJwJpGSIweAD1NYyrA3WCqbQIYmBTD6wSqOPAZrDRL9I1CMY7wjGwv4cDhao5V0XIUbqwjCqa0A0tHyeqKpEPTAYyV3PgLHC1mbFxqjS9+wE7yFEJTBi0tDxZXB632aiQjptf05k+zDt+TZOc1xcKjBicE7zREQg9NDO9Zi6GAkpEnyibwIk2JgIkxyaM6wcVEp+WGchgXWO3itx8nKoL+d6AnD7x0acu9Ty4D0BXyX8hnK4i/ExV+//BM4bZiNPU0VMUsDSeYg1zC4poFy24NoTy6quVpC5XmRSIQOsyUKXQUTJVlaSNDTdRKj2LJufrTGd4eDuhsO7AyYmBuOeohPSzY560SHJc3TuOge33+QTx4kfbhOf6ODbY+Q/7SJbJXzLbfDobbB9Qzj7cYs9FiZ9YLCfSCV0OxCWBM/Gi4/N//ApSOljEJ9km4Lbb17kG+UBNicLhuF/phk27Mwfpkhfww6G/5h9vpMpxTM7DH/yLGEwwX5XjTwgHFR7/Hz/M/zy/Jf5rv1HefTKX2ZzMMIeHSHdFXo/J8l1gllgGkd1rcJ2gUrezXl+lXLzUarD+2B7A8nKFePJmRIgPmBTl+/NyyDyAsNFDBMSx8Qc2Wy4gHAJOCBwADQYBjjOoLTENSKLTIrcyIqQLq89DmGEYUBkTqBjaXN1ynzuJWbbUlt4M38X0DwR8ExZZoUs7bB0opAJ7peew5GrEFskath5M2QVdi4JXKeB3F9K/fIZePUNOHsdyr6AdC/UdypjVlmwBj80NGP13hvO9aPBaihOVS9wtYaDOmebiwL/98wzCZBg1GQBY6lWT3KKNFwGVkhSUmNnocqOvTFcyXM55ve8u4XXdfA5B//jBvxuBX/yGN51E3Yj7I3gaKjh7kN1QOXcHLYOlbhZZmAtStgfK2ExrU6diwKkglFQl7apwE/swD/ZgnMJvtPDAxFu7+EVrXIkT5dwtYCtGbziht4fPnAe/v4ZmAj84BQeXeRQ8qGOz2GtWSJTA09Ytad67ir4X4XYwvVvhE9fUNJG0AyQRjQUvUp6bNsBql7f1wSYjOB1CW5YeE8Nv1rAQyWkUsdmkPS1Bw76fL+6ihIfYwMbYzC1kjIvh/pyrynrWte61rWur85aryfrWte61vXVU/+7Mj0ODw8B2NnZAeBDH/oQfd/zLd/yLavnPPTQQ9x55528//3vf9EFoG1b2rZdfX90lL22T7Xkq41GhgmEDMAvWwwzGJ9gmdq5Mj2SpXVQ/ps8KRShioxsHZVOwIu0RB0SpLRs8VtmKUi2qDrdl5lYptVqMPgqal07wE89UlpuP0FKGfx+aXzj9M9FBIPDSNA8A9HO0xADIXpSjPl5UDhDGQ2pE0JQq6/oA6HvSTFijcO5ArMMEBDtWDfOIjaP49InaOWnc6qdM++/JI+JQTM+QtBA5d7jO49xRvdp6c11SxtrRhJEM1aIS6h/+aTluTDk6GdVyJAyHcGp58ZTG06nt/4F1MmxnbzmZEdPtvHSPbgaQq7HYcSe6vmNmQUIpBizsifd0gl+upbins//6RLNunWXT64DycSIrNQBJwqBSIqRmMAknWvKnQjGGLUwya9LUa+J5bWhQe1ZbWCynZSQ34t8ELIiPViSHqC5GVZ0vuc8mtPHZq2qR5JPBJ9ou0DwMQei6/W7nM9GEoio4Mhozoicsnla2muZ4vTZZGV1FfOpi6tjg2XWi4ggJke2CysruRiTvm55F0nL8U6rN0n5/rAifaLa6cWYVS9R7wdLpZExRuFNK2qflQE7MSbf1/KsSeg1myAmJVFjSISQTo4jnbos8zmxxuRLTfJ+fCE941959e9jPYGXXlOcB5eEM1btZw6MdjAnE+mrjrgkLE7f9vLcj4USGSGq8iDa/Ptw6taIdtwHc+oyQUkOk59nfba86uC4BToNV/dOgeBQgiERy0goe4iGY9txXTre+bsnx/hPP6ePD/0ZnQ9W9NpITv3/k2gXfszvnbzucyrgw18P//jZEf/r5QFt9HR+xs2uR/2JWvaA7w5X+W7g0H8tXbtHY4/x/m5As6k2adgkkqgI0ZJCXmgNBAkcpyP24k2m7THhwEMT9UDzmETlz1fAtaRIEeYUaYbtj5EQIIAEi/EF0jnCPNBNE6nJ9xdYkQdqJ1WgffuCMiTLNeJ0Vof6J+lzl4wp+Xk+r+Cn15UvrISlPg9O6PXT2zoth1jeG16E8MgT6d/+R/Cep+FHPgz9wvDfsMV/wYS4Il5ObS2vK6vXf4kVUUKgM9CJYKXCpAoxHlwDNhBdiXc1kjQlReV2ouHnSW7NgT91bAhq+3b6R/n+2aBAfxIYZhBe75uZKERJwz7pnF4S0qDfV0nVI1WA4w6uJjhWZ01cUjuoImbRquhx1kG3ubS0AiWL91s4DHqt75awGZVYuO6y4MNDS6IxLY1taZMlhpqEowMO8xDMjFps9XLyKSWIEjchL6Muv7d+PoRFD4cRZhbaoSovDEpm9FGJj+MZFMuhFiVL9kVn/VR0X2uUYCqivnYjQZtOrore6P2vizqmktQirMvjYMhjhp7a1urj5Vj/Qf9GWde61rWudf2xqfV6sq51rWtdL9/6kkmPGCPf933fx1vf+lZe/epXA3DlyhXKsmRra+uW554/f54rV6686HZ+6Id+iL/39/7e5/28NYEiRUwPiOCMQUqX8YMlMVEQY1IFhSsgGkSMgqWAHRSY2hCT4ILBRCGlDuSIRCQkFXGIlDgzQShIQYhd9upJBiMlwQjeZUCzEKQAxBDFkcQQjUdsTq2NA2BApKPhmDk9XUyk4BUUiRWkAdEI3iVE1K7J5B5//VPTIUb/eo5JuHkQuHYwRyQycEMmmyV70xlX2o55ShzScJyOmKdASDUpOdqmY3HYEEKgDQ19bGm7BV06opcRwTZEp7kkwUdCE4itR0KLxHSC3pkA0ilyhxIZKUIIji6WSC/46ZzUgW/ApAmGEokmBz9EbXnuHCYUuPyfxWAwhBTwYZFB+gx6E9CIzpJImafp0thKMhFygqtEIKVIE+b0sSUmzVABblF4ZNw/g19F/r7HcJKFIKdeI6woNXqgy69P1mKLAuMKklQESjwFfVZrWBR4qFJEfEvqFwqJ2ZGOX7ZjA0ii4JxIWClS/iDsyhhhODBMxoqct9k2CrEUZYGYyHxxg663YIcMhiPECCkGmoVHkuDG6okSk6GZ6eslQClQlAWDQn2hnNOHdUJVO1yRVSkxkKLge0PwghHNozCiagPj9Pr0vSEGpa4EBynhrMFZiA30bWBx7FkUkcUcrIkc7R2xf+OIalBx9uIZBsOKogBT5nGJqujoOjg6Bu9hPIFxqZeObAhhoIDO9X1NfxHTMbAdxhmqYYU17oTASWCTKFQqkcWip2sjxjqsc8SYmM/mdG2HNZaqKDFi6DvDtLHEFPFxQUweZwuGgwoQ2tbRdhoKv7VhqArBFgZXSJ5nQnRgC1mRGL0PzBtPJGJMr7kvGIwpIBm9J1i162ragI/atizB6hxtAr6NzGZfYqv3H2H9+1pP4KXXlPntcwZ1YLSf6EuYlSC13uraUgHUYPRfEzSIvOgyOIuCtoshpKGqD0Y3wHbQjWGxpYTJrIamgrKHyVyJlnIG9VRB2KXN1admgV+MDYcIrzOe11kFLn0m8BabC6JcpQnCLzVz/u2nX/xY2wbeewM+fAwPmMR3no9cvAjJJWKh71nPoTyAkLvXS1Px4Nl38M3b38ze4gofe/ZfcmP6+Itu/5NbT/NT+w3P3hC+dV7yXXHMEIdhhtAilwzm6z2c6ZGHA6voiuV5ffZpwr/5ebyt8E99gsA1WtMzqzqOBzDY8LRnIS4s9fEOxWKCxHNIV0ArlEcbyPU76eYHPP+BGxw3M0a/Z9mdDSgZUVDlsHLLMkxCzSoX6F38AItB8Di2SUzQvI8RZKurrMHi5O5P/j5mxaFaYJ2Q86dXnyWBUWApgURgQbzlubzgNcsymYQhf47QpxRZDVT0y7mXUKsstdaMNhKtztFqoec0Zhs1RAHzL6W+9brO/afPqQLiwgHsHgPmOshvgblOZ1/NsX0T4i3lwR7VjRmUAxjtqBRQP/5QCJxbwOZC9ys6PfqNBrUp06EjAR8s4GfG+rxv6uF1HsoEk5x7kW972JTDyjNpHHIG0jAp4RdmMP8oHB3AwTnYv1tzmVyCM/MTMjwlVcOY5YILEOHpm/Bjz8GzLdx1F/zAPXo9fqhSW6hzEe4PUNCzM/gQf40Ps+N3+Lqjt3GpvZ2PVfAzQyU2Hk5wN6oIO9yBzsPDA/g/NWqTdXdSRYnpoJgBPXzmOvzsNTATuPNr4NxFGJ+Hi9+g1/mVY/j9X4T7J/COB+GhLXhvCe8d6HnvSyVMzgCvyvZ8RxaeLtQy64EI5zvYiTpmvcDvOvg9CzcNPJOJjYcDfGsHWwl2BTbli8uG+Uqp/9B/o6xrXeta17r+eNR6PVnXuta1rpd3fcmkx7ve9S4+9rGP8Zu/+Zv/u3bgB37gB/j+7//+1fdHR0fccccd9CbhU8L5HOZrDdYaUhJCFhEQC+2VTIKkAjBYEQqrIHYqHakQTDSkoPkW6jUzJ+LpEPokWEkY2cJIQewDoVMvdecsIoZgDN5ZJVhcQJxX0BLt7o8maQsvAAOINZGGjjktPT5F4tJoP9aQqgzMdIgErPgMl2dPh+S0fddoJ+TR1PP81Z5BJdx7oWZzJMx8YCYGQ2JGx4I5LYZARUoVXReYTTti8PR0BHr6vqFPczwzgnQkG4mSiD4Su0jyAYk9EgWJoi2JLp6QHrJsZRdCdPjo1FR60YCH0CWEISaV2WQ8ar6C10wUiZblf0YUCidFfGhJMWQyYklNVMs+eRTISpkaUsIj55kCSy1GIsaGnhdCUie4hl39zpwiPZaEk9ZpIuU0RLVMDzFAMlkZ4xxJSmIqCbiVqmeZBlOkiIQOfItYh7WVwmChz/Mwb1mW8eW39vCmlC2uTpUxGno9rDUvY76A4IUklqJwQKBtj+i6SDUS6tEWIkJMC7q2wxUF5aDEGEszVzulFEFiwgHWWZyrNWei6MB5rDGUlVOFiI/0wautkxd8J1h1PtHwWmsoS7PKpglpmSegbb4ue4h3IeH7SDuPtMNI1ySMgdnxjMP9PTbSiLreYmOzOjUgEHvtWu9bmM20O7eqsye8gAyVKOymif39SO8jm+OWjeEC5wrGw4rCGfoATQ4vtzGf+Qhtp+emcFCWjhAis2nDfD6nrgrKDTBi8d6xWAgxhWxb1mLrmrpyiFh8b0nRYkXYGBlGQ80TWnb1qtIkYQtWzeYhBJquIxGpihYnAUOBkUJVPRn9iyHR9IG2jzgsFQZJmssSYs9i0fNyq39f6wm89Jqy2G2pPdRHis+6Xf19lJyNsOwwTzonbFAAOkm+nYmSI30J1VTtcQaHcHgBDs9CX8F0qMTHsIHRQrdVNPq8pUAR4Moi8tOx4zl0uw9bvT8Fp69pxy39oOWwh9/5HPzU8y9+rF0HH74GP/c8vOkMvOXhyGRywlkXLVRPg5vp+4caiqLgjs038cj4P+P5o0/y9M3feknS46nJNd79OXhsatjF8acYUOMyUWDhjGDeGuGOoIEGNt1yA07XrhGuv4+AwXNAkCO6bCU0r2AxinSbHVIVSDeiWJyDuJVb0cHNR7jD88R5wY3HpjzXzjjzpGHUVhhq7CrU3XB6rYi0gMdyzNL/zjBGV46lIqRHbbFOryZwevVILPI6tFRt6O9Pws1D/onJ+R9kNUb8vO3JitZm9b2w9EATDRGXrEDIj2VpIpYniSeapDkxCWyjr/HliUqpr198rvxh9bWH8OwYPrGj5MCogd0jgAPgAyBP4KVgbl+P8UI4PoIbN2FjE7Y2lfCodWhthO052i2QMzEQWHk4nqpPOvixoc7XrQZuE826KFNWa2TSwyQYZwFPNKqOSpIVEwbSAprHYPYkzF4Lx/fBpIatOWwsQ9ZPZ9afFvkkuHoIv/QYfPoQvj/AX9uAyyP4u0P4uTHcB3x9hB08D8jjvI5fZCPcyYOzV7E1v533bcG/qmBh4a/2cLdXsme2oUT13Qnub0+aL+ZWMzgGM9335z4Lv/kJDW6/cBdsnYezO1BtQ7uAf/Mr8JnfgclZ2N2F+2p4r4UPi6pzzhYwtEqw3C9K680MXM3T+46gZIdJehU0wEcd/GTJLfqhuwJ8RyZH9hwcLgXPL7P6D/03yrrWta51reuPR63Xk3Wta13rennXl0R6fM/3fA8///M/z2/8xm9w++23r35+4cIFuq7j4ODgFub76tWrXLhw4UW3VVUVVVV93s+NEYyJiJyyqUhGrWR6VRsolmCzzZDBGIPBQioVokhC6rO9UAy50y8SoyMhxGzmnJKGAaccZo5VkCKahBhlWEwGc0RS9mkQkGzBlAwkiyT1XkhJLbaWvaeSEin6nOFwOlxb0SFJSxAlgyvZSiehPil1LWxtwLCybG8N2RoXdE6YS0IEBpWj7Rt6r/4mgoB0RBoCHk9PwNOGwKzxHM97DqcH7B3sEwKUlaOwm4yGQ4y1J13wp906fGKVuxpl6YyFSMJIJElEnCGVFbEswFZAiUixsiZClrkYEe3BV7TBLN8rBhQlMaoWyVqLpeWIydSAQlhKZ5hsKnKa3HgxtcSt36cVWHXajuz0a+UFX9/yyMfue8/x89fpusj0yk02YqRwljvGE+4fjtk8t81wMECsQ4w9Ac9yorHOEskGLCe4kJPchYpauCzdxgBCTMy6yOEi0DeJ5jiSQiD2CWssxhhsYbLlTUHy8cRLhKXFiKzmshG1sBKnRIXJgekk9Jqyqp6KpwbYZFsoa3R79sWamLN1SQxq2dT2em0NjaUo9Vot6pJyEBFb0Hc6jxBLUVXYolCC02sXrzH69ose2k6BHSVZEk0b2NsPGCuUpcM6QwoJCZonk4KSdBIsXS+6X2QyxmQMLpHPj7YPh2To+kQMkHCIKUli6YJgk7q5jAZCSELvlRwpC0tZGowIYSiZoBJcIav9t3lcvPf43pOCIEltrkJIlIXN1lkO74FksTmF2ofIfJ7tr+ISNM3gqwhJNI0mLYHUl0n9+1xP4KXXlFBCV2SbmWxXZbPlVNkqGOiL/LvlDUBv6YRTgLQ0quDoa72sQqVd1XTq++9mULfC8MBQdgIhMh/H1baSKOnyQILtCJccDOZq01O0um3bW1xXMOqF+zvLo8nwb/l8GXyJcH8qeBTHQyGy0bW4VkFxa8D2epyhgpsCT85hYQOz8ml2hh9Aqud4/T2Oz15/ibGs4aEaBj5xZ2go+j16DE9wjZvcZJtL3MMOddrkaHHAYfPb7HU3uOf2i7z1tW/loYMF9eUjDeAp1CaMUsOWBx1UDdiFYBoBH0i0kDrEe8QH2JjAfXdi3YTJpZ7d3YqNm9sUJmGzSu/k7r8M/vDouhGIdAjzTHIv77AR6PMakBBcXmNO21ItFR/LiQDc8vVy7TghRJaZHacp8xNyhBfZRlrpRJZzTJJQzhy2M1yaJr42RnoMl6iwDPTalnn+fICC/aIEQJ8zMEyCD/5J+OdPwj/+DMz/4DCrVb1vANMG9j6n87lfLId2CNwFOFw4x6C1mE6wrobhGKrBcsHKIRX6sj6rTyx5TTv1XlMDT5ZqMXds4HULna+39zDyei0ktKfC5LVFTi3CwShpENF5NOhyI8w5/b05C6VRpUhv4TiTmiZn67ioc7AN8NQMrjXwKQ/uAmxtw14Jv3NDs6DcJtw1hrsj3B1gIxkad45P2IfYMRfYLobYEjaANzRqa3WOk/1vjK7hRX4sZyDAcQk3RnpfGu7Am8/DYAsuljCJMAiw6cF38OoBhLPw4DZsGs25udDCm5yqNh5McCnBltf5MEfX5jNBiV2XT4+I9rA4Ueurcyjp4fN+FaLnxIiGnx8YmJ8+eS+D+nL8jbKuda1rXev66q/1erKuda1rXS//+qJIj5QS3/u938tP//RP8+u//uvcc889t/z+kUceoSgKfuVXfoV3vvOdADz++OM8/fTTPProo1/UjlW14IoeMb2qKSJEMYQu0h57YkzY2qqFFYITg0tqE5FMQQJCGwmN2lIk0Q7q3ifafkhCsLbEGAdRiD6QUiDVDkZWgYSUwROjneQpAiGSfKFAhbEkUe8GE0oNSo4CKeBSpCJRAy56Yt9q+LUdKNiawESBpESN/mEvRLP0Frckoy1653Yjm2PDaFBx310X2dqYcG/X85pFhw+exewqB7M9YjCkVOOMIckhHXv0BFoinsRhO+e5GzMaOebTz32KTz/3cQb1Bq+89+2c372b3TpSFF5B/SVSIUmt3nu0NdAbiNnSyEWsixTOg/O4QUHY3CQMSlK5CbKFMUNKJ1QuMe0DDT0FCZ86ChwigSonRwc6YuxQ+N8ADhE10U9ksinVWAIFHZKJk2y8teJk4FbFhLzgZwpuNRk/OXnm8rVKqpzwPhkKP+knzuMzP57y7977ca587hrTpuW+4CmHFe946GHedu8riJOS+dkRvnY5jyHnybisG0mGEAwhCS5pZ2YQqJ1QFQYfE22I+EwRkaD1iWf3Oz51rSEd9sTrLSYltrdhYzLAOks5rDHWarD2vCOlhLERMaqEWmZsGJNwRQZjjaoJkhdip4iazQRFQvBR6D1YUasm8vwNywGWW8c8JfCd0Dew6DyH0zkxRc6aAcNhTVFaRttbhCriUmJ61CMpIrZmvLNLXRf0vmA+h7JUmxIf4doMbkwVmBkXkaJI7B3O+ezTU6rScvulTba2amIfsX0HPhJ7S9OPMN7gO73W6hqGI91XLzmrAYOYCiHR98KsI2cHDCiqikjiqNH8kfHQsLNj8EE4Oh7StBXjkWVrw2GtsDlRRZoxUBZZrZbnYPCRWbNgdrzIgKcFMQzqks1JTQyJg2ND03rKwjIaWoyBedOzf+QxxlDVFda5WwC0KI5gLMG8PD5QfznXE4DZBGKZsySMkhtVp/ZPWzeUIDjchYOsAFlyhdFAV+m5Gx5rZ3Y0MD2n3fU2wmABErQz3s7AdobB4QATDHt3dFy9p1FCxer7j1r4q8caaXRnC+cvZ1utbH9VTmvq/W22fMFfaQd8OzVv5N993jFtYPgrbPOX2KD0cyZH13F9twLDAVKlCpWPHMP/fAX2Q8u387/xzYMPUGzXfPPbdvnJ33nxMdvZhb81gziEO45vMDr4ODdT5H/lM/wi1/i69PX8nf7V3NHdzuOH/5J/d/CTFGabP/ctf4G/8e3/BVsfeD87P/H/RfavE0cWPwEZwWYD9QFs3jTUVx2uteAXePaQcICdz5FZC/ffBWf/JKU74p5LH+e2reex/hyujgjHWJZWbhFY6PGyINGT6PEcEphhqCkQhIpEn5UgS9p5gIaOT0n4rMhQQnGZK3VSSxLj1hUm4QmaEEPKJoynJS+SyfuT1yphIigp7a1arrnGsPHMmNHNird3ngd7T0K4g21qtmmZgZkSbZdZVJ2L8yEsBkqYDVpI/cn5/0Lr+y7AHb8Pr/wV2G7hvvsh3Q6SzgF/DqRl1G5SdSVEoRiegYtb2QcxJ11nH8hg4XAMTQlDD1ttdsjM9UwB/8MOfHgAb53B/+WGEoDnnAL60UDj1JZJ5CSpZTmkCwtXCgX7zx9DvadjwVuASgmPDadZH3slHA6y6ipne2wuYHcGRz382LPwC1fAnoWNr4ftMXz0Mfjg70E9gXu34Tu34f4evn4OLpX8+Ogt/PTgFdxuK+zkDK+q4b4O/rvrSjAcTFT1tUDVEvYU6QGan+EFbpbwxEQzNx4Ywv/9vF6vBxuqRDyzgLuO1erskXNw/GYYFXB7CXYBX9fC3cd6rjcNjIx+RJsNlLgYooRSJ/BMCftOBVnjpPt0X4K3Jv1odyT6UW9k4YlKlTZXsvVVV35xc+mPqr7ca8q61rWuda3rq7PW68m61rWudX311BdFerzrXe/ix3/8x/nZn/1ZJpPJyrNwc3OTwWDA5uYm3/3d3833f//3s7Ozw8bGBt/7vd/Lo48++pKhsy9VGloccx+8dluTrAb7eg3ollJU2SGsoIlojAa2JkipJ/lAkgimJ5lATA6f1CPfSIlIicRI6jtSTFBFxDqQtFJ/SFKQWyQTHzkVWsPOJbfPZ6UHsgpMtnmAVekRSMsWO7NsIV7+Ia/d3vlAswJCYXcRoa6EuhDGI8vmxoDNjTGjENkYR3rf8ZzfYzrrSFG9zTWkvFf/b0ImBBJ9jMzbQL3wHM2OODi6RoyBsrRsbGwwdC3WzBW9W6o94NYkznz8S5WHSMLmf8UaUlGQipJkNGRBxCngaxJIWvXfxvyVEDHZwimuOm8zGLTUQUhQiCipBkSImPy7JSnxYmKD03Xr73T80+qrk5++2OvMqX9NVkkg0Pc9N6/e5LnPXcY5w7i0jMuSixub3Hn+Iu1QeK6OzCxIDMQQV+8qovqOlNNajSxNVgQrSiqJrDROq32LKTHvI8dNgIWH4w5LYnNSYI3D2oKiGGCcI/qOFFolW0S3neIJOyGCKj0ExGooR4yrqYmIYIysfNBjUsLHmCUpknmo5TimWx8xgg/gfaTrPSFGfFBqSkRwZUERwXQ9vlt6TVlcWen+R8F7sMsonwRNgGkHQ5cYlwlrEm3vOTzqqCrLuS6qOiMmJEYkRoiWGJWg7JMgCc0JkZNzvAprz+qqEBNdr/ceYx3GpJzfocozY2FQCz7AYmHxXnDOUBYGu7RzeYn5lARSDPiuJyL4nE5elQWlM3gBMPhgKJzBWlWKhBhZNB7nLEUpFHKqDz2p2kPboV8ebblfzvUElKDoa+2qBr2f2KhAcdWA62B22hksrQRSam+FdoqXrdph+Rq6Wl9bzTTfYzCF6hBMJxTHVtHf6GlGQl8mOqekR1XBPU7BzMkN3YbkC0kA11iqaY3xJfcw5l6GfIA38F/xBB/gkL94O7zrPiiTcFFKNmRAlwLH3uA7TpYlgVBkEFrgMwu44SPf0D3HRnyOSXGGC5feRvi17+V/efcn+MF//D7m0znf/Vr40/cpgXN3BbWH8aLFyRF98nyWPT7Edc6mBU3aIsUzHM2PePbw99ga3slb7zvLQ+ceIT17jVBWRCOkQt0dKRR8poOiFUxjMJ0AgUiPiT10PakLMBzC5CLGjRnt3mA46onjCcEkEj2yymNKrGQGtwSSLxUdJhMaDuhImSBRmy5HylkgJ3ZVy6D0k1pebS+2TujPff7qheaIL7Y6pc/7KolONDtzuMOCMwhn8vuWlBiqrHxVZchyk8no+fUu72NveOO/+QLlHafq9ytVFNzxPNQN9BeW+zcA7tD7ZsznLgGuvsVZLAHLDoQg0FiY5qycF47ZwsATJXykgkcW8KoWzi7XnkKVBwvyR45TpHrM61CfVEHRk/ABaBNSg+wIsi1IAybn6DQWDgsF+eukdliDzBn1CZ5awIeP4OwuvPYcTLbh8Sfgk4dKxLyihTsS3B7gNg8mGfpwhifTGQJww6gF1LmkBGYS+PhQTcECuraYpER9mY9j2UeyZ+HZSr9/3Ra8PmoE2uMFXE8wCXCmhYGHCzVQ53EQzeI6E+Bsyrf9fC6OS5gO9Lgrr9korUlYIkEiSTRPzSRhnHQbjeh63oj2ukwzSb9vYM9o+PnLob7ca8q61rWuda3rq7PW68m61rWudX311BdFevyjf/SPAPgTf+JP3PLzH/3RH+Vv/I2/AcA/+Af/AGMM73znO2nblm/7tm/jR37kR77oHesXHRUOqVRnb8SqtZEFVzlijGqH07dEoIuGkCBZIdglGpAQA2IMqagRE1VDELW/0xYO40q1ByKSonZx0/eIRKzt1UMAA9EqqOgUCZPskZNSzH/zW81Xj0p6GBwjaxFnqASS98QUSfYYpAOxJCrAYKyjcEYDrr0nhKDgvomIsQxHNfXQMihHlHaCCWMIHSksIFpGo02SDZAcxBEpOnxbM90TvA8MnCfayGQ0wgjEGGhbOJ45nC1wdsC4HlGbhDFHCD0QlyxDThM1EAyxMBpi7Q0+6Hjb1iLRQVtgmwIrFukXEA5JaUYqPbGKSKukhUWzUhAFlkJUC7GQszGWPudCyAC6VQgrBZZGIj1qRrSEtJZqjxcCVctKnJAXSxDqpGf3xWGsJXysKg/LkAqXCsqFY7EfODqMPNfDZ4GtmLjYB5KLzIrE3gQ6F5g3M9rOrxBNQ2IinkoCMtxEzr6S3gyoP3qTufkQPgSGweN8T0wGkww2mZxkAlYSG9az6zq6sqcdebXYMZZFSJQOagu2gHJodX5zYqlmnSH1QgjgfaIPipgYq2RTSJ4+qMN3EZfEFVibubqowFgIiaPDOfN5q1ZVhUWMYBaCNWrVdHgcWSwSRQGbW6VOofaIy09dxseCxu+Q4kBpTaf+I5FWya8Ymc5bXOupWkvXGCJClYQzNVQFbAwFZ4TZyDEbFzhr6L1nOmsJPlDWigRVY0s9UmJiNk30XcIWwigKIommmzOdt/n6GSq5iiemjhg198R7GAwMW9uOsoBhrfei6COz9pjDaYe4mu04wdoThKj3iaNZoO8Tw9owGek4DcdVJpSEkNHpsi5JhYCN1AOP0FFVBYNBgYhQtIXajRlRKz/J8zMDaSFGQlqCv1/59eVcTwDqBVSixMWyC15QwHC+oVxvKKHq9Tk2W+FIUvAUgWRzfkKhJIq3CmSakMFdB2EAsYqEutUrftBTtwkXwQ+hU3GhEoUC8wm0hdpsDRdKhLhFicgmhhrYAjY4z5A/zxFvoODVsWHcz8BEjs4dM50ExLQY61c3QImsciKSgbsN/EdGff4fHMDhJsRg2Hn/kPpDE9InamiELsDvXYMuKsEzPoCygzcsdvn69BA9HZErwOUV1xA7eP5Z+L2PwvltePtF4Az4sqPZOSRwwHy7ZbGpNkzTkWaglKVeo4LDMMayQTqoaH73kPSZqzjZx5qbhPqAg3s+xfzMpxk8e5HNboijZmkOeGL1pteSZH2eYYJliOZFGdTEx2IYcULX6uqxfP1J1oZwOuD89DqxIhtXP1s+l/zc0yEI6QVfp9U9WSiwURjtDdl9InLUJX5p3nOVngcwPJqTSPryCF80dIMWpFvN4WT0PI+OoD6Gcnwb4zu/AfixL/r6+J5PwNkAd36tZmqM7tSsGpfUZsktOJE8LgfgBUvncaVWUvsOfmsIT5fw6h7+ZAvbnhX/c9bDdx3D6xp4Ywe2VJLjqIK5U5KxX87dAooaZh28/3n47BFc2IRXX4KdMjGaX0eaG5SLkosfusB9MqE7A79yBwwHGtB9xWpGxdcEOJOgLlQZIxbeeDf4bdjZhAcbGBzAbTuw+yZVBJ7dUQ67N3A9E3avbeFvtxAW8MQz8MRUyZLtC5BKuDKEmw7kEOynQY6hvg0Gd0MKMPsstNc1//3C/TCsdexNhKmF91v4eAFvtHAHGpeyrAMHHxnp9u9p4JULzQZZTrnSw3YHrYXHHXxsCIUc8aD7De4zT1D6exnN307vtzh8Fj52CDKEzXtgvAVbEc4FvZL25CTP7OVQX+41ZV3rWte61vXVWev1ZF3rWte6vnrqi7a3+sOqrmt++Id/mB/+4R/+kncKoJs1BFMhrlIVhLVgCqwT3CAQo0DotCM0KekhUUjWkJx2a7skWKstbFIWYAWHx4Qcd105KEp8CLQSSDGABKTrEROxVkGkSEHIUg9xkVR4zbVoEymIRnOLApMRSEmwKTC2lqowDIhEH5SUqXowQpKalHYQSqx1VHVNiIEmTAlBIX2XczLGk5rd82MKGVLJBhI2ED8j+hYwbEy2GW+N0BD0ieYBLAYcXTX40GPqFlN4NjcmGEnE4Gka4fDIUbqS0o7YGG5Qpg4TeoQWEQ/iddzLGpwlRUdsC6IH3yW6NuEMmNZiooOmwC0qHIJp59DvAUfEyhMHERaCFYfJOSwpKzxCUIslT0VkhP71romnCaNd+iw91+NKJwKJHu2YhBeLjj0NSb2Q9FjmHoTPA7NO15L0qHBsMKKgopwVTK9H9o8CT3aJTwJ3xsTZmEguMC0T1zaFEDzT2RHeLzBGsE4VHFsibAuYjQnunjfTD88wev/jTI2lC55R8Li+w4iG7KpaSPfMkdiyHeeKlmntORj3xAi9dcx8IhaJTZeDmiur1klJgZYU9d+Y/c/7CJ0ydMprASH1dGEKKVGlMeTA9yLjeX2AroW+j+wdHLN/cEjhLMNhjXOGFAwxGHxI3DjumTaB82cG3HbHNoNSeO6JZ7n85BMgA4rhg9jCQu2IY20J9r0nhJ7gA963mCSUrqAuSqwR6towHgpFCeORwVhoFo7FoiKlRN97jo4ihRPqocVZw2hsGY0ciyaxvx84niWKyhCiBYnMm2OOpwfEMCB0jhQriqqjGCwIIXFwaJhO4dzZkrvuGDIeqd2UCEQ8R/Mjbh4dU1ZbhDSkOKW06Hzi2l7PdBE4t10wHFicFUaTAcNxraReUKLUW8FbICSGw56BaylKYTgUEMtxY7AuYY0SSyZ35xZGz6f3kT55SC+PIPMv53oCWYWR1R3LbI1lSPnxtn5tEtTZiscFBZQlnnSrJwu+UqVHn0mPiBImJihAG4YQbSQUDckKaZAYNZpDM61z9/pS2CdwvAntGSg6OHsDhnMo5xVGtjM4fw7Y5jY2+Jsc46nowh5tt8BXgb1Lh8yHRwzmsHM9Uqpz0wlRIxAtPGDgFfm9Lw/h2jb0R5bb3jMmXd0m9UNSZ2gSvP85+N3LJ6SPS8LfSOd4bXodLQsiH8sHAHi9pzzzJLz/N+GOC7D3CHA/+Lpldm4fX91kupWYT3TcpkNVJoxKA2IV/GeC4wzdjZrFe/fwxlJzRM0BzeQ6zz/yUW7c+Xuc/dzDjNu7qFZrgjn1WJIPBsHh2MJxBr3Pz7Pao0Qy6ZGYkWhOqTOyanO1PpxWaaT8k9PfLwmMk9ecaAh5kX/hhKIXza5Klsl1GO45jlLPT4UDfp0F30nNqxkxFujrA/yowdeJJAET9JwmdK5uHEExh/Kee5jc97f5UkiP/+vvQX8eurdlG7hMXtQLKK6Ca9Cg8hf71Jh0nh0M4LkJPG3hJ2r4XQfftYC3NgrEU+rjooe/ua8WT5QgA82NeL6Ca4Veb1XK/EoFtYErAf5/n4NfeAL+5CV4fQm3jSJm+jwsPk51POHOx4e8cm9C+7XwM3eDH8PngMsC9wfY7KEIUJWaeSEDePsWvA6Y9HDbHMo53H0Wzt6rpNKGy9kgApdLqAO8+Ri+fQqP7cHf+yC8/yrIG8A8CIxPKVSOQX4HeB5Gb4WNeyH2cPQYLD4Cj9wPf/MM3LkDl7xes4cJftXBL5Vq8fUOgZ1TQ32jgHdvweMD+NYDuK+B6tS0KoHdThUj/6qEvz+GM7LPfxd/gm9IP4fEb0dmr2G+2GL/E/ChT8HwDLxxE85uwm7U8yPAU0bvcS8X0uPLvaasa13rWte6vjprvZ6sa13rWtdXT31JQeZfjkrRk1IJWREAIESFJcSonUI0qx52Wf0v3YIzLC1D0hLhEoPY5dcKUIhkf4ClpdOqC9hkMENOYRbqA54gB34LYgQxSd8rbzNJwljBJHPyu3Sye/rcbDyVoqoYkioelvuuj6T7IZaYhPmiZRGmJFqi5BBUowHGJG3DTFjEOIqyQDyI0zZkI2alsHCmYFAMqIs6A6hxZc8FolkGQYc/+yDlnT7VRS7QdB0HN/cIMuVodkwyAbFq2bQ8Fj03J324ZqW00E531crE/Nx06vQt/zuxhbpVz2FWA/VSH01OOnJfqAL5/Fe8mEJkWRbtEi9JdG3H3vGMw9kCEyJDEYbOMaoKhsMa44Q+tBB7XAQTLMZ7XNPjSBTG4EQwowXu+JAUHdIuVr3EtzxEdBzl1N5FJTBEBFc4YgLn1NZMEHofMV285aDM6uiE01+mJKtrRzIrpHZWib6LtIuAGMFag2RwffUIiegTQZISVwgpJFJIhAhWhNIJzgnOZgISQ4hG80WsUBRCNIkQs6onJj0+WFlqhRDxBKJR0tEYUXIl6vVnjKEqLTFFiBEfA1YcYhxidZ6lPGYp5RmVEiElJCWMCM5ZAiZbqSSd8tnGyzndz6LQYzA5nCNGSFHHpij0h22nhENhrY4ZrEgKkRO41Jh8ncU8o5OO/7L7PyS9Bk0SfNJTFmMiRj2v3ufUAKf3s6Uax0Ud63W9SJ1aD/7Aiz0/d3kuJKkKI5GDkOOJEmSpBokWQgLJK2oL7CfoQ8Kl7HYm+vxCI5A0vyML6uDkEk9AMoFQdsTkOA4L5rHiJKtC1wmJy5yEBCZpYLlTS7mlOmVpcSVJbWuGTo/p6QDX5zCfBbZnc+bTI1oCFxhjgcPQMAsn5JkFbtDxLMfMaJgvqeaTmzo+QNtA10DsIvQBMQ6zsY1JM6xd4LqWmNVIURKhSPhaFXDOR1IItLHhWnuDBYEtd8xOeUQv+5obVRYYp6T5S1PbSngs16p0iw4wr/mZ7E6E/Pu0UmrI6RvkS02Oz3vO6XSo0887XcvV6GS/U7biOo6Bwxi5ma0bJwi1qA1iskJ0nlB4khFsXyBiCCYQbEBiwjaCa8EuImY+f4n9/oOrchp43w71X5uyui+TZt4mQq+Z9CKateTc8nOQHlkQVRh4o9kRW3kuXnU6H6seikbvVdUQ6hzC3WYyTtCQcchZS8BBD/0Urk0BD5OcVVEEvS6nnWG2KDhoHeNkuCAwFzjIrx8mtaka9HB0DNd6GGQw34gqI5PRTK1K9EPxxGi+SDBKKLicBdKIPteKBpcPJSuXajAlOKui2FFUdUyMmh2UKhhY3ZZHSdNZrfZfh0at5+ZyEv4+TKq4ALiS7ymbQTNKloTQIGruxgtnaYuGj88MXDc6Dk6E6zLgKhNleqwwtzAvwFV6ProFzA81C2RfBda4CLse2pcL67Guda1rXeta17rWta51rWtdp+orl/To55AqxBUYYyB5UmyRZBBbkJIQRAjGIClhY8SkmJUBih6aEDHBk6whYLXrVgypKjLg3hN9VPA0CVAs87MV+KTEBsAnRbTiCRwtCMYUYAsigSJ4fNBg7S4GogtIZXFFhTM9NkVMAok1xCIjXAtSamh9S1xoUm5MCZtVJYlITIa+szTzksW843NPfITDg4YLuzvcc9tFisLRLKBPCuAEaYjJ4IGN3RHe97S9pw89YgzYCuMGXNy9AH1kczJhs04Q9iA1pFgTcfhFR9c4TG1wQwVZhAab5gqomSG4iicvP81P/fZ7uLw/5dV3b/H6+3epJ0NNEk0DJNZIKrDRUSSTDb3AJgPJElJBS0UiUBBwMiMh+GQyvdQR6TlNeAgm274IQkeie1EYilPfC6dhr7iCqE5os5MkhOVzWT1fqEzkrGsoTc9jl5/iE9OrEAK3zRbcU9ecv3CG+19xJ6Nhxc6Wo7v+JJWUXJJtKraRy88iT30OE3oGVaEg+WQfefYylBV87KPQ51BeY1RZg8lHfeLhHqJwvDDsHVtsUTHZKbDGUFlLaQwhJG5eb/AhKvrRgrHC+ExBPXFYa6gqBQ19b5BO8yIKJxQOvLW0FHgfmV3tSF1HWTk2d0eUA3cLg2SjUwus3tA0ivaYZPV8W+G2s0OqyjCoLaVYCGDcNm54D0VZcPb8BqNxyf6s4/L+FB8SlUlUJp8NozkcXefpQqug8VwQA1VV0DRjXGFxtuDSBaHreq5e3mN6PGc8GTOeDLC2oG2EbqGqiygBWwWiGNomYg1sjMdMRgO6Vjg6EvreU5SWshoBwngEMQmjgaEodeZ0LbQLCMlyfnuH3c0JTdfx5PNXQYRLZ7Y5t71JWRjO7xbsBkddGswLvdGXnK5yPZpIEAzHi5J2ZihKxzCoDdfBdM58NoME86lDxLC9WTI4O8BZgysMY4TCfMXe1v9IK7rcHW8UWAw2qzuiBpGTtLu9z5kfvsgAp4fxvj7P9vp94UD8SV7GdKL3japRxcZn5/AzV+ByB4/cAY+eg8rAZAabRwomln0mI3q1a7NeX2s99PUhB5c+ReMdv3Cz5jcPy3wfPEToeDS0fFsTNZTY6rYSsJioXZaJqmiRqHZZxoNYCFsKYH7oGvzcPkh7zNbh+6n5GHcw4b/kLfR4/gUf49d4cnW5RyLv55McMsMT+Cif0184YIwiwBU6CCHA4RSu7VOUF9l4w18mTvcYfeTD9I89xmzcsnjFPt12S7sVOLi/oWw8G5f3Ge0FnmCP/w9P8Yw43nKh5+13dgy2ha03DTh/7xspi4vYD24SDuv8hh1CQcIhVBhGODZR88MGz+W8ZhQIhsicyBEQSVlRKFgMQyVICaScL7U8+tOVTv1/Sd5rhVPPT9xys1yVEvyCIdHTs0dH4pfo+QV6KuBRLH+WEbcVkcFoTmcT/cTjh2B9xcbVC9h+gJdDOrkJBGxnsF6Q7ima9A+/uAsj1ydfB1fH8OSm3pMeOYZXzPR37SYsNuD6JxLPfzjhHDzwtYYL93Jy40KzOvYtlBH+6qEqgC5b+J8uQO/hvg/CXR+H7S145Rthd0uvn5BVK+cbtVY6KuCpgWZLfPJp+NiHoQzw+iF8x4NwaQhnPPRTw/uev53feHLMwBa86tImb7kPrtwNT4gSNGdaVXhc24P3fRR+bR+++W648DCMSj0jddSekRtjvSa3I3z9Tb1P+ErvHXtWA9iDhc0KLga1uktfr8c/3oUzFWxE+KYjeGQKM+D5N8GiA3dOrcKOHPzyG+DwPnhqAv9iB7ZK+NMjmIiSk3+ph288hqvAD+8qAfXOQ3jHDM728B17cGThUpetrU7VEwX88wk8WWo2SCdwk13+uflr/Fr6RhjcBmd2IcB8CI/cq0Tl80/AZz8CH7sLfvu1MC7gG6fwVxYwP4L/5UuaVeta17rWta51rWtd61rXutb1R1dfsehYii0pBQ0VN4L4FpKCG0YqklhkGcKcIi56TEqaqRGN/iEeAmTrpJU/SSFQOJIkYhdI3pOSVYJlCbS6rCihQKJBYoDQskp0RjvBpXCIKbAuYZzHSiT5nmACkYSUBhMLTIqaXx4FWaa5SgDTgES8D4QYEMnAzIr00I507wXfOY6PGz7z9NNcvnKT7q57ubh7DkmOzkMTlzGwfSYLYDCuCcHgjy19ADDaeWtLtkablGcTo2HNwCVIMw1bT46UrGY+xGzaEZedtR5JxwrxGAeu4NrhTX75A7/F489cIX3ra3jNa18PE6d/uccCkstAuFHn9pSyaEQgatx7nyO8C/FY+qz8KDPo71H0/gQ4EtT2SW1Iwi19vi+s0z87DUPJKbJj+bwXvn5JbyXASWLD9RTiubE/43ev9WwawzfXNfcWJbs7m9zx4N2Uowq7uI4/vsbAbrBVX2BiN+DwWXjiOvQtDCs1Fa+uw41PKTr5zAxi0HE1WVmTtU3xlMQ2Rli0wqwxjIqSjfGYwikFVALzRc+1oznzRQ+zBMdgC0EKkBLK2lI7i3VgkkCvKgGnPIuSIVi6KCwOW5r9jnpY4KoalqH0TkfMJIOLjpCErhftQsbiUFupnUnN9oZbdYLHCGLHmMpQ1JbJ1oDNDcvCR9rFgq4LFGWBKfQ1UfSF3if69tY50FVJM3oKy9aWZWvT0izgauxYzKZUVSbqrMW34JslMRgxhSqH+h6SFcbDmrqyNE0k+I62ixSFoyw1h6So9Zid1c5mUDBtsQBrLRvjEWUJz9/c49rlI3wIbAwHnN3axFnYHFteqgRWhFbM3GqfYNY5Zo1QBIs3eo7mTUvXTIkJfChJyVKVgNRYh4aeG4j+pd/vj3MtyY7TtlYxZyIUnRIFjYFU5t/l7ALXwWCWiYNMJCSrz49WSYbZxsl5xMLVBt57BJ+aKtj5mlIv6fEURstG/MzU2qhd6yaoAkQihGKBrxccBPjAHP7F4QmkblAA+Jv7rEBbKInSVTDdULWHiVmJ4sEe6zFgNLKmD/DkTXjfPvRpAXwGAf46r+fv8GYchg9xmV/ncysNXQI+w/N8hudvHVSLWh4NyHIW9EKfN8jxDOu2sHe/FRZT0kcXpGcvY7enuHuOgZZ+GJldiPSLQH04pd5LXKPlVzngMemxm/DA3bC7M+bcfW/i3H13E5/fxhdD4ip3I3CSqF0gVFiGJDoCxwTmqKXVRiYbOiLTU7o6MFTYHGoeaTnJ5DhBlG8NMr+V9DgJTueW7Z58ffK8lZoST2RBS+AjeH6SwN1YvoMR30JJcC39YIF3kTDQrBg7KxgcbVNON+lJOA5XRyAIsb1BP3/3F35RnKrn74KnLHy0VGu3V0QYN0oCHo5VwXFtCk98LFFWcPHhBLUsnShJUQH2mahS4S1zuH0GP7EJ/+8zcNnDm4/gdY/BxUtw/vWaZZFQKygblZwYdTqfPzuAKfDxG/C/PQbnHXzH6+AvXDw5NU0vfGp/h1+6vMMdE/im++DRi/DkGVVj+ACva+GBBn5nD/7F4/A7l+GOApoHdeqapDOnF5jXesbPHcP5Y71nzJJeWx1wUEFrYFpo/k8cQrodKHVbu2g2x9sW8GcP4aCGT94Hh2Xe5wTXLHzobp2yN4H3o3zhfRW8LcIowVuCqmL+VQ0/MlHy5NUNfMtMw83fMH3p83jVwL8ZaEj8sjwjfpOv16lX6KMA3rAFr01weAWe+Ag894TuF6+BXQt/qoWvO4TZ8Zc0pda1rnWta13rWte61rWuda3rj7S+YkmPmApCNHR9wBiTLUCWqQyJJJEQ1UZHECwFQkkyluQy+mIWOWxcAXYF2TOYhfroqxUViNGUCCNJAfkEXQhIzKC6VRWIEQ06JVlCVDufzgf61KoFT1YRGFhZpAhWLQXMEhjrSSIIAz2eJQKHZI8hPV61O4nMZw29P2I6W2DFMB5UlGVBwhJxVMOawjp8SMybiPeqNmm9J8aIK2BghKo2OpZiEesQp/4UYmAZ+hCjhrSLRIz1SjpJqb4tqdfg6ZDwwdIF2Nja5uve+ibu3j/m4fvPUMsEFyqMT+A7JAWMM9jSgrWajYKo3ZaNSEgYrJ6X5PESWUa8LsNoBceJgZWak0Q82qkbV6Yht8yf/O9yxrzkPOOE8Ph8w5Il0GUICZoQ8SLYZNikZssYdgc1ZyrHju/ZeeYyZeGw3QzTLRjYiBs+Da6Gm1egaei950kpuOYToY20saMzgf8/e/8ZbEuWnmdiz7dMZm53/LVV95Z3bQuNRncDDYBAAw1HkNDQgCBGImM4MaSC0g/FSJpRxHBCP/hDVIQiFBJFxVCcGWokDDGGFBp04JBAswkQAAG0q64u76tuXXfuPXabNMvox5f7nHOrqxuEIhRTCOy3Y/e5dc42mStXrsz9vd/7vgezyIezocGQstHw9j6FOC1dz7KSEt54ClNgYiQsDkkm04RMTpkYMs5lxkP14BBvMVbwXtvcczCEVvkVEhROR3SxCCwWibbLVIXDm4ydgE+GonQ4b04Hqd+WiCFgEWcYDgq1WsoGkwXvhCyZLiVSTIS2I6VMTAlfFFgrhJCom44YI96pF3858FRlQRZDFEfG4GyicBUpJebzhqbpsM7hvQbNphSYHnd0bWBQlmxtrjMcDiEbYoCY1YJLTGbgDKURSic4b9R2yki/5mTqLlC3EesM3veWURaM7cPbF5GUMl1j6ILR9WeRaUMmJ8PGeETOiarwall1dkItZ3CGRRNpuoSzwqCyGCM4UbsSY4S1gaHI4LyhLHXQO1+wcENV2Vir65p1dEkgZA5nkaaLHB8332HG/9GFW+ixjGeuekvFR1eckhgAEoXy0FIsDHebxLOzQEhw3xguTsBGQzUvKTpLSh2ta8k243qBwJqHj23D1hgeHcCo6UPUs37mXgtvTKFJGsp8odLg8BfnMJ3Bxlh/H9DC8Wcj0Al+anBB+EgoGM8qiiLTDue0ZcPdDC/c1SLtQ8DDaMd9MetJj96aR8TwmDnP59lmn4aXuME+MyIFDRtY53nyyiV+4vxV9qY1L7y5z+GsPRmzwsADE9gewFObMPBgrOHRK4/yY5/+Mc6P1zi3U4K/gxwcwY3b5Okx4fg2YXxM3oysX9zBX96hfGfB8O0ZrnUU5x7AbF1ix8H3l3DFZp62d7hw6zbjmYVX5yzaa8i1iGkvwYn9pJIVWpaeo6Pm+7V7wfIEPA0qdxjKM8SGZnKodVjsifazFPkSyytCuucv7zVXlJM7gHuJ9VOaRK9KSzWJAR5jgx9jzAUSOzRAQGJGauXBLQbpDLaBmI4JEojMyDmQscD9ZHa4mw55sXujH4c/GG5/M2M37vDEhXcQm7lh7+efjc8zScLVOQwjbFVw/6OC9zCcyOlOaZ8Gay1cPtR1LAscV7Bu4fs6OIjw1BY8+hiMd6Adw65TK6hJ1KyLF3bhzj60a5r7koewvQ1PPQHbBsrzMJv01k0WjoPw9kDtobYMhAoYaqZVhYp0W6PZJGkMjz8AeQIPXNC1vY7wxh24dQTrI7h6HoaFNgEsrepcByTdzp0CFlYVKC+U8LrVbUF09h2izQfLs2UKPG80SP2BDh5tlWz4dAsjq+910BMiizvwmze1Z+TBHdgcqo3VD8x0Px6MqtaSU9HrCRqBl0p416ka5WM1XL4n2ul0Jt528GLZ22DdgXf2YTaFehv9RnBRf7YJnjuC/+EG1LM/8HRaYYUVVlhhhRVWWGGFFVb4Hx0fWNIj5hFtZ5nPO4wVnAdjLYhBRL/xhZzoUsZkg5EBWTxiCigHWuDJB5APyR3kIwMt5NIQlx7U0rf5AuKCNqSLINGSc2Jet7RdwPuCajDBWIs1AWc7YoD6CNom0eaGRT4m5kDEYsWQRbBZDZqdVGA82SSyzMnMgSEim2j4eKtKEiCb5T4Ktt/PO7cPODw+IudIaSznt9YYD0dESqKUrG+OGG8a6nnD3Rv71LGjDR3HdYsQmYxgUDnW1i2Fcxom7itkEDGlQ0zGoOnWKWRt2Sw6nGsRbxAzBoakbIldIoZI3VnmEe5/6CH+V9//Q1ANaK69Q/PmmxQdmCZCfYykGjewuFFBPizoKDSnwkWMb7EpY6Ug50SkI+WIloUEgz2Je12ajiz92RMN9Fkf76fQWFpQqx5EsazXy5nnvVclomWxs2SJdhB3KbPfBhxQ5BFXGLHtLI9uljy+ZtmcL7jvt76ODxlJJeQS4xN+8qq2rR41cLRgGoV/OvN80RQsJHDHTIkEPtoZ/lTy1Nbzu8nzVnTkrFZtKWa1YAMMhoEdMnETUneXxd51Yu44mAWO68i4GnDl3EVG1QCRgqWhWETIQYgZFklOFAzDEtoucXt3xmzWMhqVbG6NsNbQVhXdWkasYEqjg5l7fiwKITsa8QwKz9b2kKKyxBCJIWIEkknMA7RtzWxxRIyJFCcMh2OMzSyali4G2jYwKIVcWNbWKibjISlDF4WUBCsOawZ0XWA23+XoeIEvLKNhYjSG6dGC/TvHGDFsrq9z6dw5QrI0sVd5pESwCedga+LxhbDM7xHU/gsgxMjRomY2D5QDYTQqcX1eBgJHi8i7NxY0TaKwJYUrgczRIoBEysLz4MVzWAuDotLQeKNuZWcnaUyZ3f2Gu4cNk6Hj/gtDBqWlpHeF87C26UjrWXNADKQkhHrIdF6RcsbYSJZELh2LJMwbePPaguu7C2bTVVvu+2FwRxUS2al1VVP0QeRLxceZxcG1hrV3hox3C55JDX8zzjhwiT+5CZ+/DybHnrXr20zuDig3jvDNHaKPhKFa3lwZwM8/Bgvpu7+nfShzVtLl5SP4L9+BOy389KPwU+dhN8Lf24Nv7sJ3PQg/fU5tdD41gE9vgz8W1l8vKY8dW/NNzrfnyWXi8NxbTNcbXtqD//drcGMKP+/hY4V23JtWrbjCGNpzYK3jx+3H+GN8Hy+zy/+JX+HLvE7LhCMeoKiG/MwPz/iJH17jq6/c5m/8wlc4fH3vZBwnBfzEA/B9l+DSw7A1BF94fvwzP84nP/JJPAsu2GsgL8GLt+AfvkY+OKYpn2d+8V3MlQ3u//jHsQ/ukI+vk994A0kl5ed+APf0J3hiuM7/+sJVGley9s9+i7Vf/hKZQxZ3X+HuuRcobzzFZPYwDt9bVq31ao95//AIQ7QyrMX/UwLdYqg4DSpPvUojEFmwpMGX+R6nEE6DyuGebKtvwfL1y6B14WyVWs4oVDIZj/DjPMBneQrHnA2+CdyGNmKjUirOFHpvkzMh3yC4rLlnsQPWyHwviU/zaniZ/9vsv+P/F9Lj+b8PH3ryJT73ff89YRz4u+M/zT9ZP8fHjoX/6DW4fAyjdeG+HxPEwnDrzDAUSuhdnsL2bQ2rP9qGd9fhPoH/sB/a9Udgck4zMF69CDdKeLCBSw1M5/BLL8IXXoL7r8IPXYDzY3jsMbh4WefymoXbBl538K8rPWe+9jq8a9WOqVkHdqCsYDNDG2Hq4A0L4QL81PfDDwW4VIAv4GgOv/wN+LUX4Luvwl/9ATi/peswlaqvqgXkDs6P4HEPM68WUv9moAHpd/qpcgzUKM22XIFvGvglD88XahP1o/uaxfGYaIbHjQE8swkHwDdfhv/zv4HNdfiRz8GjO7C9gP/4juaDnFN3Up1K7b1T8MjCf7MOX5jARxoNiX/wHtLjFF8cwf9xB94B3noJbn0F4gQWnwQu6X5TwryFf3ANvvgMxMUfeDqtsMIKK6ywwgorrLDCCiv8j44PLOmRMRpynVSJYbL0FktnntO7TaX++Tlbbc+zvq9w993ysW87TBocvEzMzCaqjZRkNMMjs1RZpNQHKMeIsZksS4VERmyClEk5EWMmSiISSScFDi1OL6Hh4U4rXr16o/faQkmPCFk/XXKf39C/U86ZtumYTiPGCIMKvHPa6Y1mHog1GG8wVrtQJWkoekwa0m69oSgtzhntto+qpjDWI3ZpXaWDmU8kBbqfYpZFGgfZ9fZXGkAeMwwHAy4+dJVifZ1bTc31N9/FpISkDDFASkgfDI0s7aL6EGZZ2n6Ye6yk7lVamDOmIqeduUvy4/2src6SGe/t1f3Wefb+/z77rsve3jZrCcsay8SUTLxlVBUMB5ZyusDuH2HbSGair3MdORyRfaeVkA66bNiNmTckMyNzK+u8edwY7nOeufMMRIMHcjZq15bzSb69iOCswVtLFyCEhhgbmiYwX0S8sRiTKbwgRu2d6G2sQm9BkqKeNz4ta/+Z0CWaJlBVHmcF74wWslJvB9S/zXKQMpkkohZUxuC9oywswUCQdNJVnrKqO7oQiDFqYLFXa7qU9HNTztjezst5g/X2xI0uiY63tflkHEJIpJSUrOtD0Ju6wzmLM5ZBVVJ3QhPPrg8qnXLOUHohwUlAOP15pkHhur2QcSpOOllnYsw0TaJuElJkbJ+K3YVIzFFtxooC5zRBIMSIZMGK6ef78pyGLiSaJlI6o/Z2fSCwKrHA9cnXGuaeiLlXmYnRc9oBxiBGFWcxJeZt4mgeWSxWqbPvB9uqRZUJPRHVXxZyvvfcXy7RrjH4uaXBcBO4gwb8NhVUtWCCxzYFUltS3QfbF0CpodCXB6oiKRsoav281JMsiww3W7jVwGFS8qUxcDvCOy1cTnBgdR5cquDcCMogbFlHicOnEt8OCSYCjmi14Lq7gJtTmJW9xVVWwoM+gD0rs8+GGVGyzZSOCk8GOgwzLB+f/in4L9HH2fHD4HAMBS6OMg9tZNZGQkoNTWjYmGyws7WDxEM43tVU824O+0ewf0TanhHGDb6KlMMBxWiNZA4IC1Vp2vEGcvkS48kW48uPkf0Qxm/DbI0utizutHTpEHcwU+vKewiKrDupFAFLhlavXUvrq+V6rjZYnFxTlteSyDLfg/chPb5VC/jtIO/5dz7zk5Ntlt6SygA7UnJZ1kjZ0GL1biJDG3Qv9NkGkYi4BpFw5lMMmTXgAnNu81Z0FMD/goL/iJLbJP4TGv4x33ldaHbBXVqw09ymqwLTPOc1ga2YqefAVCg2odrR4ZUlCd6v9TmrPZuZqTi0AQ69Zlw80Kn6oxiBL8F4SIUGg3f062uGGzW8OIU4hybqUZgMYW2oqiUCHEU4cLA7gN0A8+J0e2R5S9VfrxJquRVEf39Bo9MYJZCoVoJ7M7h+AFc3oG4gBGgz1FaJHJ/UJq4IGiQuSVUQNxPcFVWS0F9nAiduXyRRBca+6NrRJBgGWIswTLq/hcBegKGB5xZw80DHZC/q+X8uwX01jEOGQab2/UVLDBjBZvBZP++OhTcLuBJgJ95LekjWGW8zvNKToR4NL6/3VUHiR3psY39MYoZbLdxaoPcvK6ywwgorrLDCCiussMIKf8jwgSU9rBGM2N6KQrDSFxmzJUUNMpeUsDkiOZLSDHKtbbRxoVZSeUrODRIF6wotRFpLG70SHakBqftioxb/04niICMu48RgbCKGOTmZvgCZiCHRhI42JsTBuNgi58SiW9CkBsHgXdV3oiphI6Jh5lpITqS80G/eLEAWIIK1FcY4DdBMkZyh7RY0dY1YA26AFUcngqks0cJzb7zJ/vO72AhlK9godMnhTYnzhtHGJpMtR9MVfPPVF0m54P77LnP/5fuoCovJnnYueAFntLvcOK9FBOOg0+2UOMfaQM4JieaEPFpWX2KY0zS3tbAXHKSCuGiZ3T5kenOfMJ1hc4vFIdlBKpWkkYhIQvIYKDBK5yCE3vxj2ZWr3+K1dLQsSilV8u2IjmUp7OwrznbtypnA2rOvf6/lVYP6b1sjbF5d58KVK4wKQzUWZoXwVsj803d2aQgkGhKJnZT5VC2c7yx0ahu2D2ACE2nxNiGuJNuCq/ffxyNXr3AUYXRnBrOmVyFolUWMbp11MFqH9XOwqEvi8RbEwJZYJqWSD11TcBQzIS/o0hxrDWvrI4ZjNflO/Y4u6sjxsebPFFXJZuVxRphO2z7o3BKjxTphVAm+gK7NdE2kI2NLKMcOX1kltRI4MbhC7eWMBYxQmhJXrJNz7ruslXwMdUGKFu8yxShqHm6yTKedHiGxCELdNNRtTegCpMio0kD1W7s1+0eR0HUEo+TAnf0Zh4ctznuK4QDjDLkTcqf+K10UzUwIidBGckqk0JJCIGVhZ6Nka6NibVxgjBBiZnev4XjWYUTY3vS6TgQhdx1dCBzPZizajhQrjBtjLSwWuzTNAdaVVJPzOD9kUgmbQ83d2ForKLyhqWe89NI7hK5ha2eTnXM7OGcZlCXeOg6P5lx79y51E2hiQRs9ReHYHg8ZDBwhCU2TiAnObZSsDQ3T6XuSbVcAIJUaRF7tawB5a/VnMRVGtwy2hXorU28lsIl6u8bYwGUJ/KxkZhY+PIQygE2BrjigGc54Ni/4tf1MLOBjY3ikdy3UHCddJudD3YZotEC8sw1/4mGYBnjqnKpDBgl+9DJ8bACNg998UcmTH6pgpwLB49iiYIhmT0xJucN2HWUDD2X4uXU4KuBjEzhaUyLE9eHoudAxCAR+R17ieQI3OOYd7gLwEq/zX/GF9x07QfgoT/JpnmansHzP1X0uf2zGtfmQf/6rv8gsrfPZj3yW7/vI9+FzCe1D0G7B+R34UQvH+8itW9g7Qr47Z/r1l5HrN5B3DjCjPYwbIdUMY+dgRr3sJtOOdqkvPEdq94nusA+Sj5hcY1gAMyKznhZYQyjRcm7F0jrKMelVFQsSC/Qao2thpgaW6kLXv+IsUfGtRMdSNXJ63TilJfS/Y0/KL+l9OJvtcQqDoSJLplnbZbb+VcgN0tyF0PJCE/n1ReY4gdAhZC7mzOciXJaejSUhtBS8jmFEwVtIX6GW3spLTqQB3xmf/wysXXmQ6xs/Q2MTl775CD98HS7V8OpdmLVw7nG4dD9qbxWg6KD2sOf1GnlzD24+D9MxvHIO7lTwVIAfyrCW9ZxrS930S3O4kKGz8JWhvsetjwEXYbAO91fwSKt5N0XUrJAvF/BmBVsBvudAcy/ubMDdp2FnAA+O9HC+4VVhMTfwdITHo1pFbXRKEtRG1RGxgs8/Bh8a6rn5a6/Ar74OxVUoHoStDJ/P8IRXZch6AteAexXa69BOIH0E2IH7MjyRYTvBqIRra6oY+blj+PEpfGquoeNHHfzqTXjuEM5twYcErpYahP7RT+r0X1vT7X3tAJ55GVJI8Oht2NnTuT26hKQh31XD52ZK4vzkFC71vNY/ncCvTE6P7UaEz0/hqQYuZvjhCI8beOkBeNVoAPuPCTx0B75Rwa+NNLeER9C8nu+QIbLCCiussMIKK6ywwgorrPBBxQeW9DC273rGaY+jJJwkUnbE0JMeWXsiyYnctYSYwVjEqdIj0mpRCId3BdYpGdDFgkRS726ZY8VSuBIRS8qRri+TG2vxziA5kcJc+0H7rroQEm2saWJk4IaMiy0AYr1LnecgjsJXOKlIORBzOOn0NknIJIJZkKUjSU2Wuu/Md4i1arqRIcVE185p6iPEOnKh9lmdgJSOQOabr7/BM688y6QY8OjGBdbKAVW1zmg0pigKRpvnmFyYcOPGXZ595UXm84bR5Ad5+qMfobQWGzraeUSKRFVpsVqc74PagTCHtEBii7Wd6mGi9LWiU6ogxBlNc5tshRQ2IK0R5g3zW4fMbuwT0gxHq3202SG5QnJEpMOIKl8kZ4QOI8cIHRlPzEvSY9mpqp7pamwVe33IqX7mLOmx/N2y1GT6/z8lPU5pkeVzl32+Z12Jlm7xxggfvrrOh773CtYYUhOZhsSzxzV/3xr2gUBDoOHxZBguHB/C9QZTiSOykh6mZeChGhSY0vLAEw/yyPd9D3uLjtFvvgCv31IyyKh1kulVQtbBeAPWz4MclczDFhIy42JAkSpCDMzrmkUM1GHBrJtRFI7xlmO0XhIThE4bpY+PIgd3WqwXNi6VDCaWet4x3Z+rgomSjFBVwrq3DCrU9q2JhJwwlVBaS2HVjk0SWGtwVsmwZLTb1VlL6UvNZu9HNLbCNBa0QcPB/UBVIe28o553OGMYF5q5Uc9b7hweqlIkRcYDS0pw63ZNlpbBMFANIafEbG9GbDJrG0Mujgq8F1IrxE4VFF3sVVxtopu1pBhZzGbUzYLRsOLSpW0Gg6InKfU8v3lnwY3bNee2Sp58eI1hZZketUwPG1LqWCyOOZrWhLhOdhPEwJ292xwcvoYr11nbGVIOCi5tWNYGBm+EzbWCjbWCa9cOePGll9jb2+eRxx7GlAVVVeKsxVvH0dGc5198h+m0ZrIxZrI2orADdiZKzuwdZ969m0gZzm0WrI9Ljo9XpMf7IRWq8qhmSnYsxtANYXAkbL1u8TPh4NFAuw7YTLNdk8ZwWeDneo63G2knuEuBUB5QD+GZGv6LnvT49+6Di0Mt1Fa1hjM3JSwqTqKbsmg2wJ8cARmaoRaChwZ+7DIUm/AvbsH//UXtdn/gYfjk/WAocGzjWSMxI3JIyi2uaylrzfF4bAOYwGwbjs7p2VbW4IMSH76DOkT+lXmJX+AVGvLJ9e5FXudV3n7fsTMIH+NJ/hI/y5b37Fx9g8nHb/Pc197g//mrf4+3bs/IfybzqUc+hbcVtA9Dk+HCNlwQqO9gvvgc7l0Id2Ycf+0lwlAojhLlKGMHET+Y4u0CjFoXIplmfJvjC98k18fa5NCCOSE95kTmJI4RKiwjYB1O1B1gGGFIZI6JvEFijsEBy5Tnrn8IsvTv67OilhoL/du96g3pSY9lppQSDMXJ75a/76/43BvCsNQ1WgwDkiTqjdtM738TSZnyMOGazPNT+Ds13ASWGoKnEZ5KjvsxPbmihIjndQoWlOxjTqytTkmPb7Xr+lb82GfgxuRhXt28ynwBl79p+JEvQSDzqhNedvDkNrhSbRHdsZIeCws3CrV0emYPnnkO9rfgmU+ofdWPGngiqnLgroV9CxstfPQubDfw9TX48hrcHsPNDR2dQYArNTzSwKjTxzsW/rMKvlDBTxzDnztQUiRtQn5axQ9FhZIeAv/Aw7GFqoVHkxInFzsYR7hWwA0PMoDPPw4XHoAvvQN/7V/DC0cgJfAheMTCg1ltrbyoasW14J6H9rehuwzpMiekxw9HtdUalfCOg0kLP38Aww5cr8rY7eCXr8Hffxt+/DL8sTV4bA0+vg3xAhx5+MZElSTPHcL/52XYbyNcug2TV8FsAOuYPOTfO9DA+O0IP9WTK78xhL92AZ47E2T+UAsPtPBko0TT56LacsUH4fWH4FwLP7cLP3QHfnEdfmegtmA8ioYDHf2+02eFFVZYYYUVVlhhhRVWWOEDhw8s6eELj3NOiQDRfAfB9jZQkZTpCxPS+8YsZf+Zk2DRnNXPRyKn3tqBlLUMIktVgzE44zDG9k9PfTFB23K1EN+X07MhJwM5IWIxRq18UuoDtbNaOYmcljayCDlLr0lw5OxJ4k6C1EUymHxi95TzUhkiJ/tv+yKKNQZnLdYKxmiBJqVI23V04kkhkkwk+Y6YalJWe6DCDXCm6LuPM5IipKDWFDGrjVI6LcuoDZZ2qtq8zM1QG5BlwPq9FiCqzLGuxBhRSy/6ElCKpBTUQgiDXXphJPUNem9frZwUivqw5n6r5Mwz7n2VYmlyku757fvhbNft8v04UYycPmvZn5tPzE8AxBqct1hrSRiSy+A9AUuHElJBhCYLxxmO+v5hA8zQ4r7LkZwNRgymJ3BSzqTeS0nycp+BM7Zuy2FLGcQYfOGwJuOCUdueDNiIELECpfU4L3Rdy2w2IyVDjJachNC25FiTxZA7Q2ozqY2k0Aedm6znThS6JtOI0LW5t8dSxULhwVuD67MrhH7b+s22RkcyhkRCSRFjNadiiZQSsQ36upQwIqr06t/TO6GqHCkKuTMQMlEsqT981hnK0kPKdGUikjEGuqYhxUDbCm0QPXeSwyRD20RmRw0pREJoSaEjBkfXRqxNOtfE0DRLl7YEOWOkV6GZ/tw0Bucs3us5qWsEFN4zHAxxRUVVWAovLLPgl4dU0EDyshxSVh3eV1hj1caqf6YxhsKXFAU463W+iPQP9LGc/7k/ZCvO430Rfb+SGF1LfF1QTT2uTYRS8xWCB/q1O1lITo9VYU6zPwKq1ohlJgw0oPxc1vcfOE4OskmaCWA7LZhmEUgFkhxCwOWWTOZwoVZXVVb7nMrCmoOLBdQJhk6JkoUk3qFBqEnURBpi7jhsErMZTILaYpV9J3t0EBIcdNDVYKMWbNsABOE+LHMSt0ksyIwGBTtrE16/tfstY/cYOwwx7HKXQMnElqy7iwyYcrFdJzSWtbZEOshdJt3tyEcBGUXMpoVC8zdMVyAmkGLsrSF13MRG8tEUrt8lbw1gO4AHE0tsNyF3WfOwpOtXfyUrdOX2cA+JvbwCLK8RuddceOgzjk6tEnVCyMlz3htLnlheb5YEyL1Yvj+9omL5fvbM378Vp5/SEyo5QQ66fDglCAa24LIMMAh3WXBA0ydZwdlrl6IlM++VK2evl78/2bHEtZEwtRa/sAwXmQ0LfpxpbMPB4IDOt5SjCS5v4KJR27QOuqSWU4cpI4vMpss4K9zXCUUtbMygOYBZBNZgOIIq6jlhRX+WWY+M7c8fk5WgK7s+mcWojdRmhKstnI9qDWWM3sSafldzT7QPM9wfYZqVEBgkqBK4qOeBj0qsGKA0qlzxAyjW9VwfFTAOcCnp84j99QwlL8wA2AS7BiOnTRHVAvKBkurWQmmVbDR6KeGghsMZ3Gig89q8MBjp/rsMjYWuUlutPQu3DBwXYNeh7ISx9wy7IZiKpYHqZuyzgtAxJOu+j4GJqLKkyv1+9MfZAYMMowxbFi5aHc811HZrPcP5/r0qdPuSwGv/1jNphRVWWGGFFVZYYYUVVljhg4EPLOmxfW4Taz0hWUQMlgoXPTktSOwRpSXTZ3hksD4its8ZWPb+5wi5ZfnFP4slJkMXHRkofcb7AYUtGJcTnHXM65o8X6g/e/B9EnHG+KDFsFCSUgkpUHiLNQ2CULczLernFms50SAk0AwMRKsZaY0ga2rnJEHzLmxCXF9Sz4YUCoyzuEJ9IAZ2xgjBWMOwqvCjMWtDz7BqCSlhbf/alLVKFhOdOWRaHJGKMYV5iM3iAnUZuFCOmXVQhY7m6C7ZFVgGgMMbyFE1MG2TmHUZVwiDgdViREhgur7OI2r+HBPLwImi3GSy9jBOEq6YgKiiJdIQaeiAQAU4UswgLZISQsKI2j9JTzWkrPYkiUDuba0cBpGKSEeX4z3lpLPKjETvE37mAWfLVRpcu1SM0HfoGmJPP5wSZx2B0P9m+Yk5GyR7rHFUa17toyZ7TOxQS3FeCN4gMfJG29CkiCdToKWpJrWMc6A2nkUakbJjPq3Zu32XgzoQFwtc6jRPRYySBT1LkDLMGzieg4hja2NATpn2KBDmczAdvphiCEyqIYPBOjEG7t65xbvvHGGlwtktjDhsmOPCHBMMi9sjmv2CGB2p84DBFh2maMmtcOdmT0cZD65AjDAYZCYFeCMMrcEJ1AEWbUYMDL1QFNAsAntHc1JMTNYGTNYq1deIFpCb+YLp8T4pZ9Yma4yGY5wRSmeUuBlWbF2wxJiZHkI9z4ScqFNLIrO9VXJuS23k4mYmB5jNFuzevE3oIkGUsCqqip3xeYwZsHdzzpvP3ySGjs2txGQts4iRG7HEuBZjSqwMCAm6JlM6cJaTbBqsQ7zBG8/mDozWB4h4jO0QIzxw8SJVuYVYhy/WMNZROelJoFOMx+s8+tjTzBcdO1tDNgZjnDM4q0vzaDTmwQcepq4DMUViDhTOY0SLqs4IQ2+UiKoj8y5RH3+bBNs/4qjXoOnAOzDRs3nzCvadHeajQ3Yfe5umXECZyU4VGtH1ZXPhJLcg9pkcXQmzc9CuaRf5/zwqSXJ5Qwu2NmqOh+u08DhJYIKnOryPYr5JqA6p199hYRuen8I/mqn6489fhI0xPLUOf+UxLX5fmaj91duu5lfkHd7GQ78u5pBob7aEA/iohb9QwRWnNfTawd0Gfu1dePl23xeQoEjCZxab/B/yJm/T8p9zm28w53see5C/+MPfy1/4v/zdbxm7v8FP8gwH/C3+Lmts8Jf5Wc7zx3iCx/gPmTDPUx5ffBi/b0nThvpfXiO8cYB/ckH1wwlxDreYUB2eg1FNsIfUg5bUj61LLdWXX6D83Tny1EeQnafh8ibl0RXstR8gdneZbz1LM7pONi1ZjtA12yBso0RDotfjcXproxVrIWHYQa8ONYl5f5egagu9xpxaHZ5aV0WW9lWn7yn30CNKeETSScaI6+2zIon2TMOF9M8/S7joALhGKI8hWz3WeQAf6S7w18xHOcDy93iBf8JrLFUm9yo3hMis/7nor230SpISQ+Tfhvz46xfgu+/CT7wKkwa6ixA+LywGN9k9/wWa6hqXiu/nQvPj+MWQ8lCH+/AQnn0b7i7gcQLfe6Ujj4Sj44LmDcfiGtz5Btzt4LHvgiefUmJhYCEOYcPCU53aQv1On89hWxjtwXgB19bhrS09kn98Cj+1DxsCZQmHJQxrGDQ6j1qnJNrHIvynB5rlcQW4gBIdZaOHebOFYq6voYB9D+YiPPk5zdz47gI+dUcJgA/VIEGJDCn0uuU+DPYxGA3gyfOaDbL1Btz+DahbePJ+ePgchCHsnYd2BL95A/7519Xia+1J+JlPwkeBST8r3y3gjRHctPCPC3jJQnUFnvgcDILlU/4+PnZ7A4MHRgBc7dTa6izOZ/iRCB8K8FADjzawFnSMBSVY1vpMk8+ghMiFoLZXAA8k+BNRYzweaeC+FhbH8Od/3xm0wgorrLDCCiussMIKK6zwwcIHlvQYjgaAITcZ7WorkFRB7ki5IVEDFVkGvW0OqtzIvboiL60nevsrEXK2GsCdWrIIIgXWepwrKIoSbz1dlzH0HZfBk6NBbMI4gEzMWpGQHHC2xZhEjJGua1XRkONJSG7Sl7AM7waIlKRsMXRY5ghKfBibIFtyMORkIXuMLZEMzlgKwIow8J6iKKi8wbsIKfaKj95pKminawwtMdb4mHBiqOyIoR0ytgXiPD5FQj3HukhyBdm4k4DrlDIhZVoS2QglVou1J23kvYImnxIegmDdgLLcxkrA9EVbVd4EUg790fCYbPT4xNgrPZZWIsufkPpw3bMaCyMWgwXSSY+vfnZfh0ZLO8uI2+XjLJZlp9NOW7VCkf7zzcmROjU6WfblLvuH81IBJI6iLHGFpSwqSvGU4jHW4JwBCdztGoREgXZNRqDLkTJHQl/xy1no2sD8eM6iDeSuw2b9NNOH3Z5sU4YuaPG28obBwKv92qKjkw6kw/gWMYHRZMTG+oi2aXn3nTm3b97C2TFV4bGmZGynTOwUxNJNIUvofT08GMG4iCUQI8xnQgiCLw3FyOCcUFioKnCi3e4GaEKmi70zvmhRvs6J+bwhdImy8ieh7MsxjV1HczzVzI/hiMrrfPNGlSJ+6CjGjqjxJgjQpU5VTURGA8/aZKhKn4FynSE0zI5nLBY12Weyh2iGxG6THAYsjltuXz8mdh2lM4yHQpeEJjZg+vB0oxZzMYAz2pV8OpF046wYhsOKIqnlVugSxsDG2oTtjeJ9VrZ7URQVOzuXaDsYD6AqdJ+Xn1UUBZsbBW2Xmc3nzBdzrLEnSiojUBghZsgh07WJdh6/wyf+0UWoNDDcRjCNYXC8zuDgAuGyYbp9jdlGouygbPu1w/ZitL7T+SSwWVQB0o4hVbAjaDndQFv0ZklJ7aRcq0oP24DrDJNb61RH52nGcMQNom+4dQe+chfuG8LhBjCG85U+sug2Jwd3TeA35ZBvnN2pjPrtTyGXMN8A02cmRKt/evYIfuf26UvGCJ9jwE+wyQss+CX2EODKzhY/+vEPve/Y/RRP8Dq/xW/xZSbs8DP8PPAo56j4QQ7JTLHdBczCEA9bwqsHtM/eRgaZ3CTEGkwocfUIWwjJHBN8TxAloImkt26Tb3ZgN5G5NhO4ZhN3+BAxjKgnb/QLeARq1I7KIAzPDEbfDHGy8ge9xmIRhmhaVAIOezJjwDLUXM5cU5bvt7SqUqSTlfj0KrF85vI50hMNvifU1Trr3gN275VLEExU4iP6rPO0gIt+zEd4gGM8v831M++yVHDoncW6pmncsz268ph+v+Hfxt7q1yaweRfW7sCFTmAbuB/moyOqK89QD19ka+8yk9sB26JV8QXUd+HGy7B7DE9fSXz8/kAxEGg87MML78KvPadkwIcuwKUHQfog82RhYOBC1PuXYU80mgjFTB/zMVwrlTz89CE8NIW6hP2JWmv5TlUMGZ3zwcLFCA/W/fXa6nkrUckLoiodBkmff+hgZkAmcP6irvWfvAM/dQfK2B/CqNtsRO0YzUWQDb3ujehvjfZg9jyYWhUlW8B0E3YvwmGlQeW/8o4qSv7Ep+FDj8PVGRS7kDs4tPBOAdcsPGfhmwYeWYeH1uFcNHxmd50f3lunv937Fs3REiPgsQw7CT7WwSdrtfZaSlUtOpYxw5UEm8BGgkn/vpsZPpT06Z9o4Ykajuvfd/qssMIKK6ywwgorrLDCCit84PCBJT2sr0gxKrmRIbMgi+Y/OFdgEGLqCQwE6W1hcjJIXHpzd+Tc9V5TWiAxkil6CwUPuCRIiHRNTZSWrm1JMWg93yjhIiZhkpIT2fi+OKxZEiZDiqLf3nuvjhyjFmRkWUhf+oaD5FM9Ql52hyajVQ5cb/qeSTkRglpCtTHRAA4hYnuFS4G4CokR+q5vLdEkUo60baSdJiKRed3RdB1YYW17jWrkGIwGmKWFls0Yq4oT7RJN5JTIOZGj0X3D6hhKBZKx1uKdnHa/g+aumIAlYGIHXSaHBSm3JDoSGladRMjGkJ0jdw05z8lZu26XFiKupxjCGXoi5UwWHRshYXsdyLKMlM78hHsNTs4SGZz5byVa4qnC5Ew566yByMl7GsNo8xLnHn4ayZHp7nWme8c0B3PK2DKgI1MQxJIlo7RBwmEwWAKwR8c1ItEInTMYa7i1aHh2d595lzisI2Tfx6XIPVucY6KbL2iOptjKEaXQQlzS+WaMoTQZTKSdZnaP94gpMqiGXL7vMikWpHYAyeJkCH1kfJsdMWe8g8oZtXpjaXWVySlCyhgsXgJW1KbMRiFlmIZEzpkuqjdQCpn9o5aDaSSFjPcF3un8b+eRlAXvDGYEoVVVR44JlzM2RnLMzLOGrFdiGDglFZo20HaRJibmoVclLRu05XS0jAjOOrwtiCaQJCJZs0xCgNGk4qHHtomho6gCTQoYKfG2wFgPCVJoyGQKm3v1hdB1sDDQdZkYIcZM2wRCiOSciSmDCHf2FhzNOgpv2ByXlIVR+6/31B5DjExnNXWd8FIgg/KeYlYMkcWipWkSi/mMejHDUpDiEPA0dcve3oIQMpW3lM7QhJW/1fvhV2/DkwN9lEXEdvuEwlCvH2LpKLrT4HGA0NtK3VrAK4fazf3ABty3pkXNolZiI3hVfmTAN+AX4AJ6HljNEQFIJrJY36cbZEJxRCzCCYkCvXjO6ufenMOrh2qV84SxPGgMV2aWz7cDnsARiwXdYAZZ8PUath3whGmYVEeEKuASjKcwnvfbcgaBzDeY8/e5y7u03O6vTaQJdA98m9FbKiE4rblbkK0C89F18n0ec98ArCCVwz+2hZQWs/k24eWvI3IIt66frGmSRQn9uWVw12Ebi9QtgUMMM21WIKPKjTtk2SO5huAhugi9skG3a3lNLdCsp4bMEWqm6NDrytmrwnt1gEt6O5CWY3G6kiBnriS6zCyvKmdx+jt9H3qyPn3Lc5fPkuXrjMNd/DDy5H2kboG/8Tpxd4/yqCCn3V65Oj35HMH3+7X83LvfcrQS8BIdX2BGawZsDL6LH/Sb3O1u8triOeo0/5bX/PQ+PN1CNe4Pdc8HWdlgfPwpiuY+qvnjSPL6gp7TtaVaU5URZgfCOwjFmqG8pNZMchEefgJiB1s7ugYKSkCYpFZX670Y5rOd2kI91GjmzlsVtBXs9JkgXx3A71nYMfCwqMrB9sMgaMi4dD2R1s976edrK7BfQiOareGTnnO1h05gOoN3b8DtAPuxt3hcvs+y46HUz7u/g080aiO3Z6EW2N+B25+AQQvXLsGNbWjG0BT68lGGy30o+7mo1lTZwKsjKBLcLXVItxJ8JsNVNOdnYNVC7Ov7cOdt2C7gu7Zhp+L9OzvO/DpHOPFEWz4v96dwVlXLOKqVV9FP07v78PXbOiaTTZhMYPr78/crrLDCCiussMIKK6ywwgofOHxgSQ9TTMjdjMQhOSeitAgWjFC6IVmgaebEbgZikHKE2AITPCZWffZBVNuKrCqPjOAkMiy0IlWiXYJZIvP2iJwzIUDq+kK7afUbbk64GLVI4S3ZOO3sFNUBpGAgFvqtPGT9tii2tycKWGlxMoeeqEkZkI5kte0wBe1WFSxGLCIQY6RuGlJOzGLgGCgQRjgSBdlWiJ8gNqjlkEhfdA10YpjOOw5nHfOm4+C44biek71w8ep5curY2FjHGocxgi0y1keMDbpdJPVc71Kfc7I0wy90KyRTuI5hDhReTix/nCRK22FTg+kaWARye0hMcyILls2GVoRkHdl5cppDPoQUyQwB9TD3ZCxCe0ZloeHuWomwaE7Lsi4B9IZV7+2jPcX7lam0Czj2f9fPWmaDLNUjlqVJCoixbF55koc+9dPUhwc8+8YXuPnyW0xvHDIK6qkecCywquoQTwMUlAgVkcxbHPMMC4YiXPCWyltePZqy99o1YjLcXRR9yHuvqDljT5JCoD44ZH77DmYyZiCbGGNJsUDEYQ2Ubogxmdu39rh+7RrWGa48doEHH3mA+XHk7vWWts74OMQECDmyiHNqOta8sDnwOGOYh0DdaJ5FDg3EiM1CabzmxCSP6xx1SOxNO9qYKZ2j9I4QIzfvzjhaLNgYlVzZWafyltRFZocdxgrV0OMKQ+6EeWGIHZQkXOhoUmSvqWliZBwL1qnIOTNfzJkvGuokHLaWiLDTqSJjebCFZY5NRfKGYGoCSnqEAE0LW+fHXLkyIMXI29cOuHV7SmFKKj/Ee0+3CHT1HDGZwSTjBw5fWBZNr2ZpMl2biSFSHwe6tiWbTDJqcnN9N3G8SGyMCz7y0CbbayXWawjwWbRty927e0xnLZXdQNYLzQvp/951HYeHRyzmHfV8SrOYImFA6NaAitlszrvv3KRtExub60wmY2aL91S5VwDgb74Bf+J+2H4E1kygGV/Dtzdoi4TPLVIr6RBtr+wotCj73D78V2/ArIV/9wF42GnhspqpimM+hkUvNhgfwfBYyY5QqdWOCdrFnmzg6OJ1QnkTExOu7UhBO9GhV3V4DT7/5l34f72uWRz/SzyfpGAnDXiiu0BgwHx0i+n5GrJhcusSg/YS4vZg/ArdIFAmOHcHFnVv6XMGDZl/yj7/miM6MvvLlTPuQPtd7zt2wgI5IQvQRdGD3F/hfvIS1A1U6+AEs1ZQff/95PYS4bVXaH79C+SjG/j9IT4PkGyQrGNbHnrW3hxhW8hhTssBlj1sbyoIB8CbZNkjFFO6AcRZSzYHaJKCR69LlmWVPjElcA0IODaxrOn+sRyImtOg8aWST62oEi1qT7UMZ3kvwbEkSU7J6PcS6tqi0LznNWexvJoZBINYT/n4j2F+8ufhzh3yf/f34PVvqMQsvE6iI7OHEiUGQ4Wh0IwUCt6P9AjAv2LB12jYsffxk1v/Ez6/9oN85ehL7N68/r6kx39yrc+D2O5/0Yv+fLrE5p2fJecOm0cIpe7+UB92D8YZFh3sXReeedtSXhA2v1sYXITRED69rvZS1Vrfo5H19ooMY4GBwDngL0b42QRHJbyzAze92l493MGuwH8+gV938MMd/G9mSh4UoDk9CfxcP4esyo4lBJgP4KV12BsoWbIWT6YxFtjdh2d/F949hO+/COlS/8KzNxkDtYf6SAtXpkp4fHmg23njIXjmov79CdRSyxq1xcpZyYwPdVA4eKiD+4OqTH57SwmZrf45axmeikrKvOnhaxUcRvhH1+DtZ+CjG/CfjmFnrT/QZ07L5Wxb3jXkDuUNl6SN3KuM3QywETV7ZGmT9da78E++obSi+34YfBzmK8fEFVZYYYUVVlhhhRVWWOEPIT6wpIeYPhijL/ourY7AYqRQeyqkt1d6r97/tEtzWVHSDlAQ0/vqi2BSX4zKmZQSKacTi6dlN6a2pi6LzwBJ2+f638tS5rB8UUZJFpSEEOjzOyJk6QvsJ314/cOQs6ZSnHxuXpoaGRJCoO9oNBq8LtK3jcsZqQVaSklZ7amamPAh0aVEzBmM4CuPZA3iXn6+bp8ORiZDzmo/lRMnFEBe0gFGFSwSTgLbT8o/VnDeYpID6bRE4xzVeEg1qUlNS9tqpSOLPk6/oqflnp8cwWX0ez/AJ/9bdskundWFM0N/dhq8ZzZ8+9+9tyh1r77ipLFZNKzduRJfTuiKQKYkJTX6d736xLAshQlBhE4MHYaAocuZVoyas4g5sc1ZhMheasjZ0gZLTuYkcPlbsCRDzs65k63Ugr8xGZIQOq38WGspq4rYBrxP5JBUV5MNpm8HzUQwBms19NvE07m9tP8SSViTsaJWcno6ZLoQabuEFaFwplcqJdouEiN9ALclpkRoE9apfkZE+nOpH/OcT065lDMxJ0LU91FSUi3kcjaIWESEnDIxRt2WLpEjpJgQY7DWkURVYMaYk+PpnFANNQvDFw5jPcY4jNHnWQPRZIzJOAe+V3os7d9O1oyUyCnrg6xLToauSywWgcpZQlBVCAYIes4Yoz9zyrRdR9O2tF0kRD1PbW8RFmMihkSIkRjTyWcv52xKma7TsQ8haTh0/Nb5vAIcd1r/Cw6Cy5jcknuSw2RVb8Cp8gK0E7vLMO309bMW5q0qMMruDKHRq0OWtlaCkKJVQ6S+ZTxLJhQtXdU/J+mq562GIQ+dzoss0GaYBug6IWTVKtgs+OQAx8hZJhVIFta9Y2QdtXPsW6HrL52uD2weZWHSlzlzbxs4o+OA9mQ/9VrqIY3ed+w8f+Pk34e71/j5v/7z/Pxf/3nyPzuCjVJTpqUnFoxB1vSaJteF3LTkeU2OBdkmskmnBGUSTCeYFmJOJEKfQdHP4UJgZCF5ZDhChh0MxzCsyFJAZ7QNnqUeb0koLCn2s1eEs1rAs+HjZ9UY3+lq8d7z6v3OsyWJckbJ8W2fu1zfDeLWMeVl8J6UdqDbJOdj4AhoqYA1KiocDYZjpUt6u8f3R40h46ikwJoxY7tOZUYneUDvxf1L0UyvcFoy/pILXNhREqFX+AAnAhvrYOBh5MFGoY2q5GmtYD1MKpisQxlQhmI53P3hsfR2fhkG/e3RLQvX6KdV//vSqKLiwMJRq+R11/XvZ07VC6a/NKZ+yE2/XMasyoyZ1SiykJSg2DAwFP3dooFpDW3Laa9BP0VC1M9MCYyDda/i3nGCUcx4nwiDQMqZrnV0nWWZBkOEysBWoaHpzihX0aLb1Ihuj/RDtJNgEmFq9b9N1ri2vU4JkFYg9mtT2+kYlVYtIRNKudVoePxRoyHnVaGfG7LuZx1gGNQuMye1wrMGDjq4ewizDPszOGihXpEeK6ywwgorrLDCCiussMIfQnxgSQ9nM9lERFqgL8gbCwiEqF2S0WLSQP/WtKSuVVVCCpClz+8YaS5D7ogkbGEpx/o+cQF1E0nRENqClAQkkKXTonxKfSFTMJVDRGi6lnahYcW2VGsiMQFjl9vZkGnJ2ROT5pJ4AYx2riYEYntaoxYL1iBWq105RnKCcrDOZO0iWQy39hbM2EWcMFz3bG4WjEYGk4K2rqekRWLJhBzpcmQRW6axhlQRjID3SEpYKiSrPVeMRxhx6ldtSzLQ4YhknERMERCX1S9C0Iqc0+fHnOlCwsbUd9kL5c555MNCDoHQLDjuOjaffoAfW/8QR4fHfO2LX+QbX/oShqZXMXiEiJU19cmnIOG1aEAkkmkJdDR9iSpwUmmhAsDQ4mjfQ52cYhlwfoYauyf0XKEVl6XzkIXeLV7VNQ7BOI+rBvhqSDia8/ZLr5NTYnLlSfzGfcyqf0Px8vPYRY2PmaJNROCG9+w5S4UwpCUA2ZRclpLCW411j4EYMrMukbJQp46QDbZy+LIkmyVBBNZbNs5NOHf/FkVR4MteAdIk2pjwTpDK4gph6/IEO7oPyIgR9m8fQjJMJh5GpxYzMWdMZ2hSZFh6qpHDiBBmkOpECuCTI4thWBWM1gqMNcQW6jqyaBYsprs0XQvdCIljBMNWVbJRlhTOEeeGhcCsbpk3c6yFebB4bzjcn7E3b8gxU05gZBzGWtZLYSSZed3y7u0pOWWKnHE4ysqxvTbAOIMNC26+s08KkenhjKZuMWaIsZsUI0vpRuBbvC/YWCuoSpgtDnn9zk1SShR+g0cf3iBntcfLOTMqHW7TIQaKAdgCjLE4rzPnoG1Z1DU5KSnirIfesi0lCIMFNtQMvaVthKNppkuRJnQYCztbBWtjS5cC02bOwWLB9aMhebfDW2FoW0oTmc4yORZYPNXAUVQDhpMCcYVSwH7AcO0Cvk0440gNpPd09q+g+EsPauiw6Wv0SdQGxwQo56fF0px7smOgSo0nSviL98G0VfLj//EGXDLwx0t40GlY8rQCRDNuqhpcO2Lt5lVMGBD9LaK/rh/QoynheKiFz494+MsjGJVwdaCr0WMT+HcfUtXhY11gETO36sC/3HuXG43n8XLKd20mhpIh36QdTQllTShbdUv00BUwxPCn7YjPUtBylQWfoKbkt/gdfo+vqb3iEjnqtekPgkEJdluvEeVtKF7QwWvXIZTY+zYof+DfJ08P6N74N7TXvk496miGHW0B7aij3ZxjGzAzwTbDPgTcgLHw9Mfg3/8LWBomG0eUgwY/rbC312GeyV/5PdLXvwxJrfCWoeOOC2gW2BoqSQho73roVR16kugVuQEEy3p/rWjILPodNJyGli+1IcuK/SkpfapHXP5WONUO6ucss6mWV6Jl0DixJDx7SFO/RmgjR/XHaC5eZbh4ns3DL1KmwOd5kgts0XDMF3mZf8YBmtfx/rdwFsP38hg/zIfIseTawe/yC4uvc715g+N48P7HcukK2l9mQ6nzX/T24UTReQ+Pk2F7DT7zcVjMYJAMg+iRNWBLyFH1N0t1BwtObKfetztBxaSMO3j8bS30TyawNtHw8z/fwWcEBjfg1W/C2wtYfwLWHtU7ggs1jKJ+RNsTKaMOqgCm0qK/z/DKDXjhNd22P3kFPrUDmyNw340yEbHfzswJCfTaEfzLV2Ga4ZEPwYOP6WY/dgiPRKhG1zlefwnIfHT+OI/PrhIszCoIBj50Ga5+Rq2ivn4JvlTAAx189kAzNaYlHFc9r5SVqFhPcF/U3I2HrsCfAHYGMNiGGxU8uwu/+bLu00/dD5/cgbsCv2XhDQNfPYB/9gqcc/DHH4CPbMM7+/APvwG7tXKKhYAZg3sczHl4/iZMHcQa3noBfu8OdAtWWGGFFVZYYYUVVlhhhRX+0OEDS3pYm4kmIdJptoQIWaT/Ut4nzAaD5BJyJKc5mY6EIxPIWHIqSXkIOUCOCEmzKIZO7Q7aQJsiKQix9uRoEZ/V84pMzH0HtxWkcIgR2q6mrhuMMVR+pKSHRIyp1XrJtGTpdPOiGjFhwZqAkaRG0WJAHJgKMUbJBCuaI9BFCBlrCsbjS4j1SHmdOUJhhWriWd8qGAyNkhexO1GhZDIhJy2u5sAsNpjU0lnIPelhKJGshk0pTkniydFByuTs6FKFEci+RpySHmJ6+xNxYFQFoh342lW+JBOK7W2KrS1ilzi8vaA+7li76PiBHywJ3YLp0W2e/41/odt8ol0ZYGVMFu2KJAtJIqE/Xh2R0Jtc2T7zQ/BoIcv0jantey2rgXtVGmcaS0+sHeh1JMsS1FI1siQ91PrC4BBKWzAeTCgGQ8JxzY3X3qIYTVi7/ChbozG3Dg7wvtTXRu2nTgZ2C082GUfA02qGihly3lQYk3BEJEW6JtPOVJHTiqafeDPQrlyRE9LDecva9pjtSxsnAqQUIZlMm5J2/5YWNxDWByPWzg8JXWT/9iGHd48ZVBWb6wO89ydkSkxg65IuCIWHcqAjE3JvbWUgBc2SGVYFw4kW+Kf7gbqO1PWCen6Xup0haVPHwHk2RmsMygGhg3oBbcgcNx1HzQJjMnUjOCscH9ccLBrIwkaCaBziYDz0YGFaB27enZNT5vywZL30jErP+fMVRWW59c4Bt67fpq4bdm/tMT2asbFzH/c9cIlyMMRVAV9EfGFYH3vKAg4Pjnjr7TfJZJ56fMgDVy/TNpmD/ZauywwHjvHQqyLD9YIq9FRNCQ6lo2kWCMKwKPDWad6PVWu93CR8CDhn6VqYkpkuAvvTGmeFQWlYG6vyZdrWHDVz8nFN4zq8gU0WDKUlBE8KA6wYXFlifKIaGcQ5bUT2FcNJRdckbGhIbUv+A9at/6jgz90Pbg0WhZIeS4VHudB8Dt+C6dSyKnrtfG4FHi7hsYtKePztt+C/uQ5PFPCp8/DwUEmPeam1/rVSnQ59PWS8+xDFfJP5Bsx2bnGyQokSEgdrug2PF/CJUc8VVHppe3AED11VnmSwCCzawFvHDf/tdM4zDfzJMnNlDTYdYHbpRnfQ5TOf2GS1lRahf8KOGDNixuPs8zMcMuaQI77CM+8hPRKkP2BLd+XBbIAEKF6C8Vf6DKj7EJlgLmxRbvw5clPT+DvM2y/RFIGmgs5DOwi06wFXG4puiGnKnvQQTY3+0FPw5BMYMiOBEVkPygyYLUizW6Rnf5WUFkT0HsBxkYJHESq0FF7AieVU7KmIric8VN5gGGBZR/BE9gnM+kN1qimEJbmR+9eKNl98i5pjqUGEe9Ul6Qx1Iv21rEBiQfPilPrlt6nLMTcvPsV0Z8zOgWFt+q8pU80P8gjfz0f5Ktf43/EGv8PxdzwsFuG7eJD/gM9xOx7xvz/8B/wTvt5vefx2L2IpkMlZ53Xn++vhkrQ4i363NifwXU/2/220gaPzcLChpEWZdd3E9IfgmBNFyUmnwVJI6vUxbOChd1GS5DIwgInAn2y1p+XFt+FXfgf2pnBhA85/HNYMlF4zbGqj4eQAbgFVA1KAEyUU3rwN/+hr+pofKGBnAutDcJf7cXgHeKvfrv6G4O0p/NLzcKeFHzkH7im1hnryGDZryPkWtye/S5LME/U6Dx1dZV7Adae5IZfPw/kRXLfwD8/BPyjgJ1r4i0fwaAfPbaj1lsv9upRgkjSUPQCPXYKrW3pcDjzcFvjtY/jbL+ssf3AM372jhnBfEfiGgByBvAUPlfD4ZXiqhOtH8C++Am8e6PHtPHAReBxkS6N9olOV2LuvgrzwB+dCV1hhhRVWWGGFFVZYYYUVPgj4wJIeoD79KRq1dFn63KeMhD5oPGZy7IsKVshiOfkWnTNCRAiIxBMbppwzqdNCT8qJJL0PvwmknDAm6Rd00ayKrJty4iak4cUad52jfjuVLIjRqOqlTRTZnlhEafew7wO4TyHo3yQnTnyOxIOBREfbzSE6cmxxAk40/Nl5i3UWMVZts04stpbvIawNRviNEcPxGBcC0/07FFYYlg5nHSI1OYb+JdL7VFm1+BEQcUuNA2oRZvrOzqRVuajV9hyzerG0Z6y1msj8YM5sf0G7cOQ8IHQ13UIwjCA3pJjoJJJT7EPMe3uxvpJyEqjem1GftQrRbt7IqeWVvafT9mwz6tl/L50q7lF6iCGLQfp3EcDnhM1L5YfSJm44Yu3KA1TjCZOdbYaVxxcGLx0219gzxtohJ+oU+gmnBbBlX7BBba3UKstgJCPS26QZwYplMhwghQdvyNYQ+wJbX9UkR1ExU8qkqJZGQqbwgnPmNCxb+tKaMVjn8F7JikUXaFPGlwZfaIZMzkpgJSOkKBgBYwy+8OSeYyQJ4gxd1PMwJ90fayzee5KUWOv03MiaSxNCR+rt1IzTgpRFbW1S7O3SM0r+6QaTiQgGI4IYcEbnfU4Z4x3iPdmobRRNJIasvF8WXFFQDBPWe80CihETEtEmaBLHR5GFgaZJlIVa+aQoLOY1oevP6dRP86VrTtZTWtBm+JR0Nllj9XhkQ0rSf16ja0zqTmzjcoqkqMbuTtQ6K8TEounoQqI0BUOXKMQiKWjJ1KKd7iJaAcsJ5wRfWYrCYvv1sPAwHkLrhDDLxNBb2a3wLbBGC3mp7pfKU7e+E0u1e5rPT5dTrEApcKGEx4bwgFe7mNR3wBdB3y9ZaCqgCywmx5rRMVoQikx0+pyMqkuqhVrUlEFrvTkDrUY5HHew26jlTdEoIXOjtlxMQwKOQdPw5tGCPZd5uIVBT3ZEe7odyUBymTjqCGsNR+GQNxZvsp+H7HHAt1axlxTxvz1evfYa93M/VWnhKMLtPg1+EMg+waIj356RFw3mIOMWFSG32BAwMan4JdFfr3UbYp2J73ZQtvg1i9+w5JgJtwPxOJKTkDuBOiPTMZIvoRTVTb3enxzFhOZ3NGQ6hJZ7AtnvITSUCFmSE0qsn47PKbWfTx5KYCz/srxW6Sp/snCcwel79IrV4Rqy8zDixtj9Me7gEB8aBk0ku4qqu4NkVTze4pC73OA17nBMcyKW+HbIwF2OeYF3OZIOV53jkv8Ii+6Qg/pd4u/DjAp6GE0H5ozb2Lc8ycKxhXc9NAgXMlxIunQZOXudfZ9HP1cbC/PlkFglSaYW3h0rQbkxhC2rN6uF6LkyKuHcFhQVbJew0akLmkFVFfsG3nQnPAzrqKpr3EIXYcPDxjm1zLoxhq8XcNPBxf4+8Zxob0oj8O4ADgp4s9C13/V5G0VWhYVYfQxlwIV4nkTCyYC5h9bq8yTqtouD7PTcDGj8W+v0Fgqjz80B3t2DuzPoxjDeUjutYdY1LPdjkLLuUw4qTnnLwdcreCODvQXrWdeOcktDz2dDuOZhOobt81AP4MjDsYNiW/d51Oh2sKE/7QEctmoNtsIKK6ywwgorrLDCCius8IcNH2jSIwZDU3tysn1J2kAXyfMFxESXMiGCGIFhgfHFaYIjGSMNXmqtpRr9FptCYnGoX/jbrB2xSSJt0ZATOOfwXpUgkjM2R81GWBhyhqbOzLuEjVAuAi6AiMH7CSlD2y6ga/WbaYoQa5K1xLCOSMbkBtMbwafUgvQF/JS00GtHiPO06ZDdgzdI2RAW+6yRWXPCaOAZTUqqssQWBSZzmn8CSDaY7PjQ/Vd54qlHEGPYnx7x6pf/NdvnLvHoU08zHIwx9T6pDqTCkfBE7zFSUshQu8olYXLGZINQAlYZn7bTSlzXQtsii458oEXnNkaa1LGYLnjnmTe48/ZtbOnwo4IYA7uvdhTpYWKa0jQ3aNpjJVRS05MDCzRbgpMYW0PCcprLouX/BH0nbsIQKKHv2tVo62+tr8BpOc+hvb8CWFdgnMcAJZr8kkJH6prlM4g4xvc/xBP/zs+yfvESW5MxW+OxztG0R5oHbLMLWS1WjlLNrRyw2TKxJR5DEiEYj8kaRetFMKIEiBEhOe0QLwcjrjz+YTbPXeJgepd3dl9nXs97fxBPio5uBu2Rhlw3TaPF9KJkY81jvaonzsIYw2A0wtmKRdNx42BKSInz2yPOjUZIyLRdy2IeSd5hU4GzgncDqo2in1g6pdsgHM5UAeWCqMKhHLDhtulySwwFMXi6JEwXC+p6QTUsWN8eY60hZKGdGeXNWi36xGyxA68kh0uk3GCwFMZjjWEycGyvV6QM1XCEFCWdSewfdBgi8+NEDg5nLBsXBkwMWBkQYk2cd3RBu/dD13F0cEjbNIwnQy5tP4GxhmbR8PrrN3CmYOjXsbYgtkKzZMcKLVRJ7guACUieQTVUlU0HTQch1HTtMSmlM2tOJoYGUsJhWB+UYDLTWUMdjqnnmXPVOdYlazEszHFWsJWe39FmiB05w2BSsbZeUhZC6fWsWB9BeUU96K9fS+zOA3X8Np3cf8SRDFRzGN/VYut8DdqhFg4BneNLwsCeIQ7606k08KNb8NEhDA1cLKFx2j2+daTP7QrY3QG/fszx+nO44DB5rtcR0Q5qUMJjfAfN9Sj1IQmqYxVNPDeFX9iHu0GLz5LgShzxp+onuMo6v3XnGr+weI3Sd/zPtuHCWAmYdqDER+c1uyQNEnsPHDO9MOP37n6VX3zzXW42lne5QXyvGaBYbYf/A+DvfOHv8Fd/+q/ywM5l+NUAv7aAiYPPRXgkk9/ZI/6LXdivKY5r3OwifrJgsXYXbE1Rg63BNoJEg2BZ3Ijc/cIR3dYe258Zce4Hx6TjyP4X9pl9ZUYsLe3YA5H1Vx9gkn4Kwy6WX0d4uyfrlcCIHBA57ukc01MRHaqFyEivHoRIZK+fBh7HpH993T8/8/7Ex9K+KvZkLaglVl/FPyHmU/93QfoQcnngCczP/EVk4wLFF1/GffFlBl3D4O4R8aDBhdu4OGNGxxf4Bv+IZzmg5s1+O78TAol/yfO8xi2GxQXuv/Lv8Gc3P86r+7/Jr7/1n3HY3PjWFy13b6mQaMD28WXm/fixPgH8xQL+1hhuWPi5I/j5Q7WRWto02bOvWSo8LCpP8LA7hJfX9CmPz+H+Gl4bwN96Al538EMGftKcqh7WEly8AD/6Wc2jKHbAH+h7hgoWDr7q4RcqJRb+ygIeiJpf8ehCxSZ7m/DOjyi58i/W4J8O4VKGH+80OP2jGXwFtxz8FxfhNydKAHiBSxHOR9iJqjdlAE0B591VfnA2JkpG/Bavb8IgwXbU/J8sUFewsCpWBmg83J6oJVf0+ty7h/CF34M334JPPQR/9rtga6T7F/vXrUUlPTY6GDe6H//9GL54EeQarP0GfGIPLj0K939W9+XGBvzSELqH4QfX9FbuRQevOLgk8KcFnrjZH9ePw/ECfvF5+B/e5Ntpg1ZYYYUVVlhhhRVWWGGFFT7Q+ACTHpCTkIIhJQ3ITBZIiRw6cogaZZEAa8iUIPZMOHav9FgqIYy25OaciY1aXERnyMaQTCTZjiQZYwWsB0CiSj0yaqmQskZodDFDzqSg4bRYwbhCC+wmnmkLXyZqqtWWVg4iSOTUFzyRUwBC39ldgrHE3NDUh6QkpNDgBQoRvLf4wmG9xVjbEx5nitxZbTO2J+s8cf9VYkp8/YXnOLh9nUExQLA4NwBm5GBIVkgI6UTp4bEYjHgEj2RRYiIbbXOPEWJCYkRSUsVHk8kLVcC0IdIctxzvHnJwfRdxDhkUpBhZHCZs30LYxdsk/WSWCg1Di2FBQoi4k37bZfx0RE5KTEvD7UxBPikwhROS42xmx/uRHg4wRnDWYrzHAVVPeoSc6KKSXAlDxuAn62w+8jibV6+wkTrWUkuKLfPZgq5bYOJClTtAS2SeEz47htnj+mB7stH20V6KYU7UHtoVKxZc4dncOseFS1fgrnBj/53+8PZ7lYXUCanNhCbRLjRvpSgKysJg3L3TYTkAzjmkdCxCYta0NCGwHkvdFKPHLoSo4epBOzt9YSlKe48VSTfLNItIjmCy4NExLH2FxdLUltirs7oQCCniB4KvMt5D4fU1IWugqjYRG4yzmJ4kyDn2x8thBbwVqtKSsuAKB4UnxUDTtJAiXZshqcKlHJZQOXJrSHPNu8mi41/XLXt3j5nP5jg7YHh5E+ss+4c3OZrOKH2iHK/hRMhJCH2Hc45asDJ9/oMqAizOehKZplW1TegCbT0n54D1BdZrYTYnzSAyRnDOgSS6EKhTQ24dQztgUBgaapq8wGaDMZXm56RINp0SWx6qylF47fhdKj0Kr4G+t73O3Zjfm2yzwhK2g2qqhEY76MODz5IefYf3UjS3fICqPa5W8EDZX2GsWs2IQNloQbIpYDGAruyIxV0lx1so615NIqfbMTzW+dSs6etMAl9rsfnoGJ7dgxvhZNMQPI+xxafZ4YX6iJdqg/WwPwLGnCg9ojslbLJkmklLN4Jbbc0z9jbv8v6N+4r3V3q0/E0MxxjZ5xqH/Mf5N/hFXuTZV7/JjDm5AvYTPBeQLYHv0WtfPqrJbxyT78x7+nhIshnXGVzU/Zdl5nh/HOIsM3utpb7ZMH6oVLulOtG8WjP78pQwcjQ7JVgo99cYpQeBEsu4JzyE07DyGYn9ntyo0IXsLDmhC6DmfNSA2igaCpZ5H0tLq9PHWaQzPyOZU2OrkwP33tdmA1hkbROe+Aicuw/7zVtYswfhmLJ+l8wRmZZIIBB5jX1+nUPiyVz4TsdQ9/wae1xjjx0beXh8hUe3foBZt4e3g2/3opNtlqyEB0u1m3nP5/W3BVi4W8CXx6qs+N5G5x096WH6W6GTa1L/t9xfU7KHeaWFf8hcaYGUOXTCVzfh2Uq42MJnGp0nbX9uDgZw5fKZc6pRxcReAXNg18AzDloyt0WVjC7CeqNr+4VzcPky7Fr4XYGXgc8E+NMdPBbhPHo7tvDw3BB+fQL3DeBjApMMo6SERiHK6gQDA8Zc7sYEEW57OHBAgKJTUqO2SsiE/nZFUKXXooB51DGpMuQWXrsFX30L7h/C2gLOec38mPf9LUXuSdIIRdLXvlrAcyNV2jz9NmzdgAevwGOXoav0+Nw1aon3wEgJqUMHty2cb+ATN+F7Zv2t3jm4W8OvvK37kX4/adEKK6ywwgorrLDCCiussMIHEB9Y0sNmhzUe4wtyDBDn5LrVb95etJge+6K7ASsB2zsvnZYhTu2RkKQ+B3nZ5w9CwOaoGRdSko1gckeOUyCT+2pXzn0/pwiugMoUWDGIt2QjJAyx6V2fQkRyq5ZXfQHGkDHS6xQk9F2oQs5eSQoTVf2BaLU5dWQRRGokCdkEYpFJhcGYAZaxKjDiMRJqJDV8i5WG9zAakWNkbksOo0eOFlSvvMZweIvzo8S5YdL8jiaQpCP5hlQtSCJkacgStOATW+UYUk9QSCZLJEkfsO0Al6mPD9i7e5N6tiCnKeUIbCH4kSdnx/2Pb1PJFfVflyFZpoTO0rWWFDPt4piumdO1kdlhQ9dGTGogL/pOWekf+YQIEcD1BS7T21MVCAMxGDHgx4gb4QrLeKvEV5ZhaRlXDucM5WSCHw4wxuOLESKWlFu1KUqRbjojNQ2DCzscv32DZq9mXrYcFw3kROhaUozEnNi+/zwyKbm5d4w/mlOaxLiIVA5CcrTJ9rNOK6ARh8mVdiBboSyFokgY5hAPIc0RkuaA9CSZmISrMm4oZG/1OANuYLAldCFyeHdOCKHPirH9XNNKU8iZzY2BFoFEONyfqU1VhspbSmtwosWq+bTm+LjFOEsxrrDeEjqwfcZI180IoaFLkWnbEHKmKis21kpSzEyPM3WXqIKchN0PxgUb50caVp+WpcJIoNJztWvYO55SliVusEVlC1IKSFQrtenigBiVCBlXSop0XWTRRIwzTFxFUQ1IEum6AClivMN6g02e7fGYsfV4sezvzTBWMNayMVnH2QLnPGKWNnVKToaFEjRWDM70RVURfKEWdsYoyUMakie65sRsSdnirGU4KHHOImJ79YclSEUSQw6WPPTkYJjWiaN50gJhgthluibQLFpSytTTgoXvSKVhVBrwwmweOTgItG3keHpMylNSnv7/YUX+w4/BdcNbHTw/TxgPj0zgQp+l0QygXcYv5F7xYU473WNPIsApERKcqkDensELu/q7R8/BfetQ1AWT/Q1c62lHU5rx0UkuD/SWbsp/U4+hGaqKKCdw/lQs6AU+MoJHB/BYgO1pQrrIkzh+jjEingdcQ1d2mGAY3fJIMjTjjnailUrT23ddtfDTm7A7gOfm8PLi9FoJmWb6Cofv/OK3GT2B+y/AQw/jpOHCwXkemd9gY/Rh7rw45O0bLeuFZ+0HNxCT4foUDlrk2GGersi1kK4F0o192qKm9YHWgxtCsw62zUjqkAR2O7D1iYqwPWZ83iAHNWa/YdjsAXdJ6+vED6/DwDB6fhd3+DWQXbrRLbKf4hohzxwmqzrOchHBYRgCjswBmTuchpHr/stJkncm0aJ3EB2aEbYkLQTDDobNXgGyR6YmFZGuakgmEwaBWFj8aMDw8g52WEBxlzy4TWwy8zfmtLsNhdxl+NtvYasWefUNiG8gtBgCQkX0LW01paUjNi20WrD+xAS2Pby2gGenvTXSd0Adjnnx7heZdXu8c/R16vBt8kDkPf8+S1T0pPeug5seFqKWVnsWDhJ8bk8JxE90ytWKaLHfJI1Ik2U4uAEGeu4cj6DtLeIuBzCpYxxeh3STC2GdP14/ysfzhE/N4PIMcgO/dQN2D+HqCD69Dev+ZPpiAgymSk5+pIQ/30AwHQ+aFzlcf4Niscng6COYeovzQ3h6odZOlzPcyfBwhAc72EowEO0/mTj4YwEmNWwX8OCDMJ7D42uw0UCeZw5fCYT9zG5peGfgyAVcuQ8unFNixNOrPCwc9ATJ9zWwGeChBJsqDGQh+vd6BA8+BXYTHjkPxUAJps7A3Ki1VtWqVd+TE/gzj2t+Seuh24e1DFcfhuEWbJzX/Wl7C6zKwnwPvvoGtDXc7C28goU81NvjVw/h93bhdoAXNiF/GmWS/vZ3nmcrrLDCCiussMIKK6ywwgofNHxgSQ+fC5wNmHJADjXUc1J7gPgSU62DdSq7COqbb+nwMRIQElbVGZIIsgwOT9qtLQOMGQOCSVNMqsnZ4Y1Wv2LeJXb7mvUhFVlUa6AFUMGXFjMY9DYVaqbUtUI7h5QyMXYYasBietN4I1qYF1kGpzZAQU4jwGEk4iRp/kfoyLkFSYjJSIZkW8IAYmUxdoKTTVxaYLq7SLdAUr2sx5z2kxYFrK0RY+TYDrkTSw7vzri9/3UKa/nupy5y7skLiIU0bwm14IaJ5DLJCYmGLH3BJ9TQBP223k+ZJJCkV994EJ+ZHt3mxuvPEpqOlBPD9YyvDMP1AmMNm2uXeORJj6paHidLZDFvODpc0LWRg90jjvZn1Ic18tou9dGCFPdJYYZ20aq91Vkth/6/6jGcGqAxEsOW8TjxyOAiMrzEYL3k/g9tMN4uWV8rOXduQFE6Ruc2GGyOkWIM48uIG5BtANeR2gX19dcJ+7fZvWV56dnXmc+F8WbNeHOBMRbnRoh4Qopcfvwq4/mUd154i+p4xsAkNqrAqEzMGsth7bTYz5RO5nhKbDY4PM5ZDaovE5YjCHeQeKSWaCJahCcgNuCGUEzARoMNSuB5b7EW5sctN6/fZTqtwXmkKBBj8GWB9Y5R5bh4bkLhDAf7M+7cOkLEMC5HjMsCZwzeCDlljvfn7B8e4sqCtfPblEPNsHAYsgTm4YBmsUfTCAdHlhAM999fcX5rSIiZ2SwyayJVZ8hZM3JGmyXDtUJJkL7Iq7ExmRA73nrzda7fepfxaMRwzWH8hBRbJT2awOHtfY4PZ4zHQ8rL5zClp20C00WgKD3n/JiN8TqdnVN3+6QYsd5hvSMZy3DTEEeR4zZx6+Y+Yg33XR5zbmsNsiHFgpwNYhswNTllmmmmrcF5TzG0PVFiKIs+9WUIkHHGU/oRkJnPhUUNRSGsrQtlASftvUBmBAz7E1ZJod3bEG9BTJkchS5H2kVgfrwghkRpHD574tCyMSmgEo6OAq++PqNpOkLcJ6YDYm/9tsK9WH/V869I/F9TwlfwH2zB5Q0lM+aTfk3ryQ6TNPzY9R3O0aGcdE9+LFUdnYEv78N//Ya+5q8E+HCC4dGAndev4hdjbj/0DkdbU6I7LbK3hWZ/CFCXantjgxYdiwbapu/8NvAjm/BnzsPaLHNfG5Eu8ikKnmSTIA11sUc76Kj2LRtvDvFzx/zCnPmloO6BetryIQuPXIBZgL9zE16t+6wedBrW+19l96WX33/wjMATD8JPfxxvPA+82vH0rcC5YHjndzxzaXj4yYLJn92BOzX88j48v0A+toP9yYfI1YDuix3N4S3qKtKUkaYEM+lzotusBH5o8Pd1XPiRMfaBDUxdI7szzO6MSX2DITeQ81exn31Ugxnqa+RXfpVoj6m33qUdH1Mc1EjdYEKB4yqei2ijwwQlPd4gc5tMd0bXIhj6gwwkajKJREum7cdItYfCRRxPkpmSeIHMHl1V02zPiUXkeBvm68Lo8nkGP3Af/vwmbLwC2zdpD1uOfnnB/tcTo/13OfePXsDPd5HmWSQ+i8HiuYxlQiyPqTcPqU1N2MvQwqUC/vwF+OgIfmkXXl1oQfs7Ydbu8Xvv/iJfu/EPCKmlDt+GFD1LdJyFBUotvF8bwm+N4I6BLxl4wcBnD+B/+y48UsNwAn6iE2rQqEpOYk96gDIAlRbob67BcQHjBI+04GPNpPsyhN/mgfZR/vJ8h7adMDmAtT14dwq//E34J9fhx67AI5/sSY9+DtsI4yMgwGdLeHoE0TXU27/Bna1/TLX3OOff2KHa3+JKCZMNPd9cVIs7n9WuyvbTXYawZeDPBvjJKVQDmHwYXAfFJvg5HF9PvPPPG/ZeCTyzXvClcxY3Fv7S98KnBmf6DvrcklteCcifqeF/2kFnYdavI1MD7zpIG/DhT8OHAzweoeqPb23VxqpKsNko8fE9G/Dh7+6J2BLybSU53Uf1c+p1WESoW92/gwRfvw6/+iW4s6cEySRBuwnpU8Bl+Npd+BtfhxvA7I9B/gQambPCCiussMIKK6ywwgorrPCHDB9Y0oM+jNeIaNC20hj68yR4mzNm06l/iVm+tP8uvOzjzGf+3/SuE1rcVbsaQ176ey+/+J90UOZ7PtaYXmOQesuivmiZ3+uCcY+1haoksuS+az+fef++eIqQCCfbL324qxgtsmoHukGk795PGXLqg8CXw5bIOfZBvQYSWOfxvoLQsZjP6AS6dhMNa+/Hdhm6TlSFy9mdSbF/nKmI5Kyfu7TSEWjajqPjObELmOQwYsjS+55LxhYOR6Xkj/VaDTEFXTBYHyjnkbIVcrAUwxkpCCnUxK4kEzWvZHk8k+mpD9OblCjVZXLEGO2qN8Yi3mIKhys9rirxVUUxKCkGFUXpKIcV5aDSRNThELySHtkGsjek0QBpB9giEUNH1yRmsxmtmWGMhnMbKViERDkaMLKwtjZiczLCm6z5Gnk5D43OgZMZmUk5EekTa0SJgRg7QtdoCHiMpLQ8xlktt7KGVWcBYw2QSRlySMSQtJDZz4ncd3mfzDQRnLE4I5AyXRuxKo/RcGw5e+w5IdJSUo5RyJicdJv67TqZBqnPKXF6jPS9hJQybRexDp2zSee1Mw6xctJJbELGWtPbXOk5lWImJtTmLQmSz8QEL8850bB2Y8zJKSeioe7JZFV5OLW+M6UjG8s8tcSo64mI4J0jZ0MUIaeeJz3lKKAPNk9JB1Sshr33+fP6eUYw/XpkreCsrhVG4CQp+8xxkDM+ZDmBs4Lr92HpKOechrgb0b+rFVo+2a6YMm0babuIMeCswdn3tyj6ow4JerwynByKzKmqI4sSBPGMvdXJU997TTjbXZ/0vU1StYZNagdz3AqmhkU4NTxahqaf2PKcUZUYI5AcJhqqlNgmMSQz6PVtQRL7tMxp8KZj3WoO0B0P8z4cmayiRhsE11iCTcxtpjZaLF23aqEzPHOZW2LR1dw5rt937HaZMioTk40RRkrGRWKLRNktODzaI+aGCymQJyOoDbgjvc55gYmQB6KePMug8H47lw8VZGayyeAzbmywE0vbCU0NudZrtHiLKw1ubJGRJXpDwJCtg+EEWfNILGE2gq5AmiF0FWJKqCZk66Etyc3Z81F6+nxpk7hcYWJ/X4Bex0wii2Z3JJbWlQbJet9wEqC+PNcFwCLioBzCZAvJDWzMkc0W5hmmUzguiCYR3RDEMzMbZFknVcfEKhMlMSxg2+nx8/3HFKZizQ1JZOo4p8vN+x67TGQRDt/3b2cRzKkqiKw5RV1Qt8+yQGOl+kPYc7XkrId1K8K5mAmNKgcQ5TdMltN7oeVPo8LRgxb2VKjLOaM2Tba/9izfM4kqGoqg5IT0t01RNAB9YTLSgNTaIOKiYLIw7DM8osCdlGlyJqXMooYwh9kM6pkGhK8LrAl0Caadim0HAiOj5/JGhBE67oNB736qMTDkCEfAHYFDgRooRbfTnxnL5SXVZLWVGmfYyJpMNgU6YCZwIEqS7JQwLDR43fQ2rsvbXZ2Zum+lh0GvdknoNcoYMIPlsYfZsU7tagSTAkZBbbGqqITTZtKMENefDrXAHQt3BcoBrI31fb6NPmiFFVZYYYUVVlhhhRVWWOEDiw8s6dG2CyR2DKwhYgmFJ4oH40ksDcsTktUqqssQs5pZxaxWSGSLweo3tgBaiAgY05Bzpu0WhFj39lMaMoqpMG6bnBN0mRQzgsEYDTePOZNSB9kiXQHRY1LGiloPxWAJoSJloUM0J0RaogTt1jeRbGxvfxUg92GqyZPJRDFEqwVwbwTJUPmKUbYMy1HvVtQSk9CkIU0rxKSHMedASFM6qWm7BU2TEON44NxFhhTs373Fm688Q9ssiO15xEz0G3zhwUL2mZgCghAlEUWwQdR3oQXEk0WtiUJ3TLeYE9oFOWuh/e3dht949oicIld21tgce2wMHId9jEAhCc8AK5nSd1ibyMkhBqxPjNdLiqKj3eyo1tfpmpbcHpAW58gp0SUhJCGERF0HYspYHE4c5EiKx5BqIHGYAyJCMcwU1ZQ0DOylIfXcMEuR467FOcPgqKUcHSGuwlQzMAVtjjQpaNZKswexZj4XzJahGAhv3prx1iu3aFNmlhxtFh65MuJTH7vEhVIYnb/A0x+dsXdwzLPPvcbd/SO6XBDwIKg9GZ6chEWMCA3CgNJ6Yifc3Tti2kYOjmcc789YNA1d3UGGGBIH+w27t+dUlWU89mTg4E7D9LDFWNjeWefchXVYEmQiSpgZgxVDaIRYQ3Oc6Y4iyQl5ZMA7YoTQu8gNN4cMdxwxGerOUS8yKTaksFDbqFRQyBamf31KQlVUJ9ViZ4TCCs2i4+1rOgfC0Zx4rOHm9z92icn26KT6aoxhZ+sCpRthxGHihObYM59ZDhdqJbV9ruS+i5Eshmg9bRKGoyHjUjM9Yjfj4O6CsvSMtyZKoojFiqps4npJSplmf0YRFmTAl0YzcoxgbE88JUcKA6LJFKVWq1KGumvJHVTGUxUOY7Qg6C3Ui/j/Ze/Pg21Lz/M+7PcNa9jTGe+5U997uy+6Gz0A3QAaDZAgSJCERJBUZDmiKBWpyVLJiRUnTlXipFL5I4mqbKcS2wlVjuzIiiPLtlyyRFlDkRQpMqREiiAxAw2AAHoe73zvmfa01vqGN3+8a59zG2hKoBTHgLUf1Ma5fc7ea6/9fd/69t7v8z7Pw8FB0AwiV+CdgyQcHwWwgiTRArmBsi4oSk2lNbknEKNj5CuwUG8afA0xFrTnK0SEqiyoygLvLWW9IpYipljgyGyMNxkPd5jN1m2574S8FXjGwv9KgAoeHGv+hs1aUAVdurFXRsT+3dEmVXwYgaLPoBALdamKj+8LcH6o9320hljA637Jr5vXuUfBU3HGs8vM0IHvVNFhk+Z6CMC2Pme5rNh58zKTgw1+YDFjIx5wnAOvHyz5i22DCUvq7hU813hmq+EHzy8o68T+uY75BAKJ8vKCamFxrWN0bcJdMr9gljxnAk/V8K+MoTac5pjch68fw//7lXceu7/Az/PxsuIPjb+HKnieuHbI8IsL3oov8I/aX2JhD+Dhj/Bk8734OsBHX4HH9+FsDeOMkQ4bLa4ZUprA5KClTJnqEAZ3lTRyQB5oxzpWVShfOy75/JsWc1xyafww2w+dZev8JlcGJVVhad2TLPhXMYNM9XjJ4EGHaxx+4TBNxn7pFrywD7sb8OGHYXeMPH+IfDFDFzAMsdS9gkOVlzAGxggN8AqwTxi0NDtLsgcnz2PlNq6zDA4cvh3gm0h9L5BdxB0HhmWkesPgXz+CkcD7Hofv+XGc7di98FVGk7covrrJ4GuvwuwmtzffxZ3tD7JfVHxmc4dr9YBH7K/zEfcCVVryUQ9XCpgJ/MY+/OI9Q+0/wB869+Msc+K3Dn6Bb8w+9y90fdybQB1g3EBo4LkX4cU34cwOPPte2N2CS0v4gXv6keCpGvY9XA5wdgRSwI2XMm+9mKlGhgc/YNm+aJTY6rOQ9EKEO1P4uTfgazP4+ANw5VGofY2zHwJ/CWO3KPIW0q8LCtiewE89BR9+TFUaNy/AgYPy0x3VZwP1yHDh/RWT8/6EvzK5YjL7AcpwiaOb23zupfMc3oTXb8Dzb8JoAH/0IfjoHrx0AH/rJbi9hE/swY+fg8JrP4T3qiSxQ1aejDCFg9ryKz9e8eW24Ezh+N7CsOXh8hkwK7e0TveOzajHiEZtte4Vald1z+vPz3r4lIO9CD89g6cbGBvNbxIDkwhV0o+yB0O4g5IVu0GH9cjD3EGVNeDcJ7j9Cnz9BXAVXH5Kc1B2C7jyFCwbJUBrgc0aLm/183MJOAOlg2cvwpNRM6P+83+h1bXGGmusscYaa6yxxhprrPH/f3zHkh4xtBgRKmNI1iHekSn6dkOrGQVoWDkCSYyGIosha/t3333Ztydm/dZtTALpQIQQO7rYYY3Fu9QXR0us38DkhIQGkwLWOHyvrkA6jETtbA8OUqHZIEaNtRBLyiVJRLNZrZBMJLPUNAqnCgwjBicJKwL0HiQGsvUaVmpEFRFGKH3FgIKqqPpO8kQWQ44VIQl5RXqQibIkZEtILSEIZWE5v7XDTjnkzTTnjXBEmB+QQ4uxA4wrMKWAF8QJWRIpG1IWta/CIC3aru61AiBkcjwkdUtS0GwLAW4fBr786lytpooRvjLYEHFNgzXCoKgZ+BrvBGscrFQlNmPJDEYD6oGQJFHvbRAlwnITZmMkZ9poiMnQdpHjaUOICU+FNyUikRDukdKCLnfM8gIhM6wFqRZQCNPcEdqCZQzMG+2srmYdZVVibIEr5hjjmXeZeZcQI5SDgCsSJIuZlPjKcPOVJZ97cZ95l7jTJeYp8/vrK3z8zMPsbQ+4dNFgo+HlN27zjZfucbxswJXgfd9DPMBKgUiiSy1IpPY1Rhw5GY6mC0zbMZs3LKdL2hCIQfMlUhJms8DhQcvmVsV4UmFEmB8Hbt9YMN4oefDcJuONYtVUDWgHqAjEAO0SYhDCQoiLDGVPEjqr2SpJq1OTrYrxVk3TQnMr0zWZ2AVCO8eIMCpqSjfAOTC1Xo1VWWpfuoiGkFsIXeTodkNMke7WId3tIzZ2Ruw+sM1kb3RyzVtr2dzYZjLYJnQwOxC6VmiWlnlncRYe2J1wbsszbyO3j1q6mNgY1GyUnpQix4sZ82WH9xsMNrYoyxIrfbesURuRbKDOAX+AnmdhcN7h+gKXdRAaR5edKlLKTHaZEBLdsiWL4JMFo4RdWULpoZlnZseBGGAysZRDR0rCfJmIOSF9ers1huGmoxank5Jyz8caalvgCsPGhqHeWI3M7xI8DGATxrVYEcaTTc5s7VCVx//C++//EJEnmUcNPCIQKrhTw3GphEbRKzViz5Fnq4oP47VguVJxFK0GjYvRec9WbWie6Qv101LDiq+7jr9rbvMy8CcSfKjTDvBqocSHjWD7YmVXw3IMZVuwceccWzfPscE+j5M5oOHfnUV+dtaQaIHrOOBoAk88AOMaphNYDDSBYrTXkpYwvjZmcG9ATJlP0fHzBGYb8PtKGPh3Jj1en2s+yTvhr/HbjPwH+bFBYiSZh+7M2H7xgBnf4Iv8Xa4XN/nw8RVS9y4oE7y3A1PqE9kIy4BJFtdW2jE/CxSSKe9BdQN9D9+GPNaMh5XK5rW55x/d9rhlyfsHnssXImHHc7EsKD109iEWeIqqZHTlHPUTY042vnkDt34TXngONjbh/VfgoW1Iv4N8JUOnIROWEg0530RtsHaBXQxzMncwHJOrlnanI1URk9/AyBsUizHV7Cqm3cR3CbqAkChYkmlxGNzX+pCJxYOw+xPYjY7JuTGTq1+FWQvlTZKxLMbv5cbZH+f1Qc3PnR/y3KTgh7sD3tVUnIvwVISPZnhuCb9wC76wNPzo2Uf5E+d+kiiB15Zf/xcmPY6GIEsYtRATvHwNPvlluHoRHrsMu0PYa2BvofPz4VE/XF73/+Th3i3hpd/ODLdh91HDZqXXzv0EAAGO5vDb34DfvAnnAsiDULgCax4D+25Vzq0ydtDnGJfww+fgB2t4q4TPj2AaYHwjMvxkw8aeY/vRgkl9+pqMFAwWTzNYPsXxPXj+LcNr1+DLd+CTN2FnDM+O4aPbcO0I/s4L8OIh7DwKPzLQa7xIqGzFA1V/4CmwhOnI8PknCn59Cz4e4RMBzmYdJ1qUoQhA0vDzUVabqhdKuFkpeXTgYGHgGw4+beFhYLiER6eQS8hDwMIwqzJj5uD2AKYOTIDtXtg3K5WEGieYGCVVD27Ay78NoyG8exsenMCDHj549Vvn/0R4uAecVcLn8Qi/L8IyrkmPNdZYY4011lhjjTXWWOO7D9+xpIcxkHMmpUjKkZwckgswhdoK4ZDeA0a/F3sQx0mctRi1hTKndkirQHLTB5g6W+CdwRiPMdJbO0Vy0rCBLKu0CEFyp18KrcFa9f3PhN5eSh93Yg/VV5o1gFptemJvzWBsb6ElIJLIktXCiz6eW3oLKxFtKQacEUorFCYrGRMDZlUV0oRxfY333TBGLXicxVcFCJR1SVUaQmmwRkgpEqMldKg1UaHFCbXr6f1PrNNvv0767klVrFhnca7AWa8VkCT4FKlzS4qJozszbNMXvGyHMcKoygwrfT3etjgTiSHQtaq8sb2dV5ZEl5eknDBdxLQWyRomnYAQLfNUkLLHZKcFPDGkXJBzRZcdy2jIkumSZ7a0FM7QNB2lt1gnWqi3Bl8FXOEx1mNdgzGOJmaWIYEBXxpcYdRLInakKOwfdthoKAU2y8DARCZVwPW2Q2qUIhgyXY40ucMZg88e6W2btKqnCiIl4zT3QrMuAsSEQxhWA7wrmXWzE/sUIw4jHkmWFJTeKwrHeFRQlY6uzcxnkdg2hHaJAYpyiPMlKUDbWFIErKUaVbhCfZiSAM5Q1L2tmoEUIXaZrgk0TYKUsPTXS08wxpxpYyBJxs0i2akKZ7Zc0qQOQfCFw3mLGQ6wG5lyPMB6VTrkDCmpPV0OhpwMMQlJNEDYexjWavsUYmI6TTQxk1JCJJPIRJLaQVUVtfdYV9I2Qoqptz/rl6kVtaoRQ10MkCzEkJlNF5SVwxcF1tqT6ymJ0LYdTRsR1D4KYygLo5dFbymUM4Dp7cxUFdIG9TcpSqthtkmQqHZa3oERDS23heltw3S/MlZtq5oG3YdSVPKl8BSFI2VhueyIMRG7xMa4RgTGw4Kq1LyINb4V0is4jOg1Wi1geAg+GOqlw2aDbCSCz1iBotMQZruyYZJTCyzobaT6TJo81EDp11q4dgA3FnC1gK0RXC7A597mDMBogTg5JeCMQLWEIiRifcxy0yP5GMlLjHQ8GBPfE+EIeC2rJc7tBp47VAucWaP5ImcyjAzYCtpxwu10SMpcDZkPZXjXAHwF4uHcBjxttGh8fa62PvB21677kVnZFIIpDdWVitHTI84uap6+AxfJXPSaqSQdyL0EywBmBmYfmjnmYIGlAivEsqEdgIyBrd7p0BpsCzbYfk+HjXng8u0ArVBG6JzjODrePDBUC5iZmtneJn6z4DgMqA4LvZYQWIL1ZzE7D2EHE/zxBHt7QGwvEcbPgGsp2MQxRExFcpsIBUY2MGyALBHpEM7Sjhpm5bHmsogqMIuqJo8vUNohS9cx80uSyTSmpSMgpiZzRr2GqkuwGOBMwZZ9gMG8hVmHbM7IrWHqdyjmiY085dHlK1i/4Gp6nip3SrjJ6U1E52O/u80L8y+QJHIU7r5tvgxwkS0us00g8Sr32GfOptnior/E18NXv2WOX38VLnrYLvRtf28THr4A5/fAD1TBZBuwXb+WB/pEswbu3NPciLkzbL7LUG0Z2olh32smxTj21wqcuIet7JiOjuHVN2A+MJwZwEZlOHLwaqk5FxwBdwGvpJjUShxEA6UBd9biniwwmxYzViu54KDxkDHqQmoM7Rj2LmjfzGIIhxO9fhYtfOMtuDODnbNwaQum5+G3tzTI/GwJEwfNEqb7es6bJUxGkAeGqwaOEpw/gvlt/Xc7BKre3iqqDVbjYVmoq9md23C7BTuC4Z6qBd+dYCoa6j4ysCx1HlyGlOD1Y7g50+t7cAYmA7UEi/2+UkQYJRhEsC0Q9D4PXNIwdDZgWuleVMfeGba/zrKB4HVv2wE+3MDSwaMR9hIs3tn1bo011lhjjTXWWGONNdZY4zsa37mkhzXkLtI1C1JKxOhJeQNnPYWvtUicO6IUgEFkABRk0ZwEAGct3ivZEaPpvagzklvAUBYjqrIm5URILSJLUg7kNmhXvRiy9ZBbJE6BTO22qdwGQqIzU5K0pKzF4SyQs9UMEmPRUqclZcu8VQ//WmoKXyJ0ZJmhpIXVEAGxWBlQUGJPjJyFyhmcN4x9wHdLWMwRazDeAk3vHdEXafsjirO4osDXJdZ5ZCxsTCfsbBaUxlL4SNMuSSmRuwJvtGBgBwbvLNY6/cbtkyZdVh4imLjAGsGXjnIwoSiGmGQxAQahYTccMpt1vHR9zqLxRJdpigTOsDHaZDLaIOfEYnlMiB0uC0UWrIG60KchBwhzyBFn1SYJ6zCVYApB8GRbIRhCE9X6CYO1I4wZEKLQdpmUhOWiZblssRgqd4wzMzoyC5P74GJDMlp0XgW55pzIkgCHsZsYM2RV2TaSGSwXDJeWUQEP7Cwohkuubi0oTcLkjEtCkQRiyyzO2Q8zhjkxFl0X2VoyFussZekx1uBMiWRDJmNCg+REbceMt8+RxLKMC+7MbgMWJzVORkhnaI8N1sJkVDGqPSEJRwcd4U5mun+dg9uvYa3l7PkHmWydISdHCEralVXB9gNbagLuC9qkxZfJpmZIpADNFBaLxOHBMdNZx6AsmNQDJepyosuZJjbsN/t0qePWtIRrpRae6MhEhvWA3fEWhfN01ZCwmxgOC4qhKhhCSCwWkZSEnAuyOCRmQmrIEhnUFeeGFTkJ84MZ+zeX4A1mYMFBKxFvAs45RpMtiqIitMLBvUTOCest1hmwgnNBbeaCY2d0hpwyzfGU6f4h40lNVZ7B25IsynOFlDm8N+XoYM5oUnPm3DZl7RkMLINegJGTNo0bDMPaEZPQRmE+j1SV4cyep67NSTSOiCApIbnTQPTaY51DxnrJpyTMFplmlsmxJS5nGDJbOxO2tia0TeDNN/c5Ol6yuT3k4cu7Soh4r2TKqri+xtuQyp5kSFrw27oJGzfBdY5yPgRxHDzYEOslNsP4UMmI7LTjWmz/b9dbXjX6M3tY7MFhgp+/Bb/yqhIePzGBSzuwOdJipFvtLw5CCcuhKkWqJezcBqRhvvcKizNv4LqIbwISMz82TXzPHL6e4D8O8DsZvnQA1xZ66aY+E+SpLdi+Cm4CTdVyfDYSo/CHjxI/tlQrn8GW2nZ97w48aOD1Gfw3z8PXD76NAexjL9zQsfHjO4y/f5MPv3SG3V8taA7h6lhzDOQok35tSX5xhuEVMJ/F5CnmYEmRtwh+yXRrwXy3oxxDvQOuhck1R33X4o4dJimx8PCNGfZz92jEcffyDtOdEUcLw0u/YxAHrdmme98YWxjK4wL3oqXIUGbBpiHF4Bnce5+gdLD5sqN8DWT2g+QH3ovJGSMei6VzBbN6QLIOny0+WawkfJricktXaqE8O1W0iQE/MIxLSxEMt4aO1yaepTPc9plDKyyM5a4taI1VpcntLUZG+FD8fh5Kz5IXmXg1YS4IV24Il68vmFRv8SfsX6dpnmPo9tkoDvFZLdFMOlXoCMLXZp/hZvsGINzrbr5tqjyW38dj/Fk+wj4L/iP+Eb/OizxSvJufHv8Z/jf7/+a3TO8v/j149mG4/IyulQ8+Bo+d18J8fQ5mQ6imUB/3e8xI18P1m/APPgv3ZvDUo5an/5hBBrB/1nB9AGeX8PBcrZ2wnKomUALnldfh527C2SH80LPwvkfh5Qr+b5vwvAdeBr4EDEDOAhvwmMAnEuxaKD9cUjxSUAKmzzOalXBtAp3TjJHOQF3Ds17JzvcP4UMTtXi6/Tn4a5+DdAne9xF47y68MYD//QC2gT+Y4UmB6y/AV38bwhI+8CF4+v1KBP1hA59Ywt3n4a3fgNsJHvoQyOOqxGAJEuBeDa+NYDqHr34ern0DHngXfOgHYXMHHl/CTy+VSB+VcGcThgG2Wuha+Htfh7/1Ijy6Bf+LD8BTZ3RPW9aAwHgBm42Oc9HoennwPJz5EYglTB+AV7dgo4WLM6gi+oGxg1SoYqyt4YkIf+GuHnNbNOz8eO2YuMYaa6yxxhprrLHGGmt8F+I7l/QwaFZEiuSUkdz70qDd/daswkd7w2Ncf9Oe1NUxtADYV5tO+lh7WwvjsbYGOmJuEFGFh+TUKyYcYmzf8a3teoJgTaGnIhGRRlUfokHLImq/tXpOg1Hrrd7LPyerZIKxmhvSB6MKprfiKrEkVXqcKFK0WO6MYLJ22+vxV+bS9/Xnniata2+uQZUM3lBUBWVpKQuDMUJKCWsSKev5aH7Jatz6sbWigQVF3xaYI2S1InLOqHIlG0jgcqbIHSa0TA8y944swQvLKpOdYdFULNqalCJHsyVt11KIoe5f+bAS6gJMDtiuxeSAKxy+8BgHLooSH9ZiCg/G0MZE2/Wz5R3WWmI0dAFSFI4XmdlUrcc8AYuwJDNFA8QDWtw+DX7RcVdzsgL173C9hVfEkrlIZIzBF4ZxkRjUkWGRVGMkoh38IiCJkCOdRMocNfi7lxyI6PqwVrMkDK5XgIgyaAScg0E1IOMofNGvJlWIGLFIMqSgp+cLh6sMNIlwJCybxPR4weH+Ac5aRpOzVHUkZwhRK2fl0FEMtEoexWoAugVf9sXUoNOdghC6SNd1lNZpBg1GlU0iJ6RhG1tClwidXj+2ihifqCnx3lEWHmMKXGkoK/s2pUcImZxFbdVEVRFKPkWsLagrSwyZ4xiZzVtcZamqAussuZ9La8GXBWVVE2Ok61piEGwJtrAYk9XGzmbInsKVZDLLmFkuWorCnihORHqbI4QQIl3TUteqDCu9o/Dge3eqHJWsAA0wB2iiEKNQlOC9o6qU9FARmRDbSEwZa8B53RJOcpCjIc2ErhNSl4jLDiQTR4mcVJmymHdMjxvG45rRsKKqvKrH0PNa41shvXWV6beyogHTgesMfuYx4igai019zkdQO6tUQleg49u/lfR8NDbp32MFbYQbAV6cwtYQLm/De2pD9EI8keCtFEfQlPrTz8EuQVwmjGbkQi20MCqUu9jAFasByxvom/ZRBwfd21/fjoWlqIoku0ysMz7A5ajWWqHSbvPkYbuCQaXnMi4d3qoybtUw8E7IORNSINqEv1BgL1TshAo/MaQWxl4VFhIycjuR34gYmWPkFjDFUmIpwURiaejq/jUq50q2RlUewagiKmZGi8C5g4aFcRxdzARnaaLh+FCDt4MpiVulhli3gm21+73uia3SbOEnW1QxIbOl/uQsMjzbT4ZOS+stR3VBdJYiC2UGmzNl2MWnRHCOpfdkY8lWPxd4m2nzkqJM3B5XXN8aMveW616452Bm4JqFpREl2BfCRobdxRnKziipOgI7EHbu3MU196jznK3mFWzzZVIhtDadBt/ft4YAjuM+x3H/HefKYNhjwpNc5DZTNlDPp7Hb4OHq3e/4mFs34HhX15l1sL2h6yRWMKuVLPOARCXZVp8VmgA37sHtI8O7n4CNy4ZYwZ0Kjp3mUuTVR5X+Y4Wx4Ptbs4SbR5AGMF2qBeGRgxcKeM73PR3HnIpaCxj0BHJhDH7H4bd7u7hDkEaPsShUEbJAw7m3a9jc07wLGapq5GgKNyK8dgcmu3BxG4rz8JKDrzkt+r+/g3MRbkZ4bR+6ueaYzAf60ehyL2j92gyev6F7QtvbxInoXpGThpwfe30pR4dweA32NmDYwWaCzaCERHRwr4KFV6c4RB//1gy+eLf/iLCEUVA1Rtcv5DpA3eg4mxaMGMYDGO9AU8BsDPNCc0FWSyn3KsVO9FhNAZMED7Y9SWX6PfOb9po11lhjjTXWWGONNdZYY43vBnzHkh4RR8qJGNTmSGxfZTSBTNRuaRuwVo2EJAkiCWPVVghAxJFCTw6IfmM29xEFIktyFiT3+v7sMZL6+6G5E8aSKCFv6nPKgBiNFpxzJkvS3AtXINaQ275mLZlMi4gh5JY2Raw11IVa2vRlfpCE7T3IBSU39NwNqU/SDd4SnaOiwpZDynpEIpEkaKG6FymMhiOuXnyAreGQLMLnP/dpBsMxD199jHNnL2J9QQe0koi5g7zAIlSDiqosKCtLTpaIVjScA4sGkapHxKpNUxCilppzREJHth13p/D83ZrjKey3iTmRceW4cmZAVTomGwWTiShJ0laY6LAx49oMSWjnS8KsIebEPC0JEmk7CE7IFuIykn3urbv6dRIiMeicWRsxJulriBqs3XSZFiUkPB2WTGkdF3yBc5bRoKKuCg2a9hmxQpMiyxQQvLa5MmLWBG4fao7ITAw3cfhYMJ3uUYaO3cUOxpZ47yEFUk++eYSSjLOC+L74JYJJ/aQlwQp4IokEWUgxImSKqmTj7BmML6mPXgMDMQYOju9x694NxsOSLAMttNusr10MVW0pypIUJ3RhD2sdo8km9XCo68sUYAzWRHITMNZSDWts4XAm0y4CRqBr+tDzmPAeqsrgi4jYBdlAGzMhZYyz7OycAZNZzDKz44ixhsGGp6wdzjhi0IL9cFCxtVXinCqgZnOQZKi8RzIsl5bYQBsiR9MZITQMRsLYVWTJRJYkMwOpye0IkwvqUcX2lvoMxa6gW0KKlqIo8IVQVIai1PWbk+aNLGPgeH4XEWEwspzb2sEXnnkLTY4UhaUsLc5adnZHVIWjHlR4r5Xz+SJxtIg4axgWnsJZxFqk9OQsUBoqMehyMCxnELtI13a636yKWYUqAJy/z55OoK4s3hskVaTRhJwz05S5ff2AlDKhKBhsT7BFTTuzxIUwb2YsuyXH0+l/t5vzdylcA1QQ6p68GGhB0qaMaxrA0GwFta8yWuztRFUZzUjnZnjPMDhUlUEcZ8JYu6Szh9LC9+zC0MHDUvLAYoPRomCxPacbTgHBB/Xav9nCbxzAgWjnebVUy5xnSjhfKkETSyW8K8aUYcClbPijAh9G+ApLfosZzX1V8GLp2HqzYveuJQ0CadCeFMyzB9daxtOCTuBLLvJ5n8h+h48+/n189KmLfO368/zmS59h0S2/ZexEhOdeeo6/8vf/Cme3z/IDz/wAjz30GFJCGEAcCKk6QPwrmA2LfcZjzp2Bm2cxL1yE5hhDg9BhRDRHJfS3Ptxd6kTYFmKzJP76HWTzJjevwWtXdmis42BS0ziDzYmzs6iquibimojPHZN8SJkbnBi8GIwYjCiZhXGIq8E4FnXJbFDROMMrJdz2EBdvsrz1W+RwhDvzDO7shzDdHP/mP8YevkSyluAs4irk3Pcie89gl/uUN38NN32Di9WDfOD2e/C2ZOYWLE1DaxJHZklL4ovmgE+Zezg7YrP+COeLR1h6y37tScawvz3gpYe28f4qfuuPYAfPMLDfYNP8EwpRIiwNlJAQ+89e6wnhC7zB/4vfZErDK6j9VXWxYPdjG+8Y0PA93w8PnQeGapFnDFAqSWatOlwuN+DoQd2zNscwKGDzDDz1LBw3+vjhXIOvK6vXhF8Fmat4EoDdEfzYe+DhS/BAhEdbJdu/9hB8dktzKz6Y4ckO6l0Yvg8olCRKSzgvMOnPe6OF7T4sfL+C/VLfWs/MIER44Qa8dQdujOGNq+C3dL8tvK7dzSfhwbGqNu59DdKL8Oh5ePKCik4P34BfOoSNBp55DwwNPH4WLjSqyvBGny+cgxc/pvv33ctKXsxqeH0P5hmqAi7PdGzGV+GggjPnYKfS8PFXa7hRQZ3hwQBbjf7b9mJg3gVs6b6Vz0CudB7qFlILN18Qpm/CeAIXrxgGQ04yV5yF7VZJlGEDbgkhwWcG8Plt6DwsxrrnvD/DJzwMLRwUGro+XasH11hjjTXWWGONNdZYY43vQnznkh5iCCkRupnmXtQDKKo+c6Pt7Yg81mumRBJth7NWEKstajmIdgca0VY1E080H5DJsiBLi2QHqdYCCR2Q1HffGlUOUCNuqB3ouSAF23dtJ1JOZOMR75FslQTpMkIm5wAihBRYpICzlvFAw8mNOKyMAcFI6H0QAGuQ3jw+JyV0OjydcdTUuHJEVU/oUkMISUmP/jWNx2Pe/cSTnN89w4uvvMEnf/MfMxxusLWxx+XLj2CKis4IS8nE3CJpgQEGo01GoxIvhhQtJIM4gy/6GI9eyaHVQAtGEBMR05MebUfOLbcPDV+9PWA6h5znCB2TesAj54ZsjjzjjYLRRCiNYSfX1CLIMpKPA7GNXH+t5c7xMXNJNBJoUOLkgI5IZm4iDanPOuno/cr6sl8GWgwBwYGotZhIhVBiyXiWOCLn/YArtWdYeC7vDtnbHCFeffnFCQeh427XkcRh3AbYETf2G44WkZDgGM9UDDZBdTTGT+HybA9jK4rCk0Iimkg2gidT9aRHLrQCmbJgUlbneS/apUwgosqJLiRiEia7JVsXz1PUNcPrGxgMIQXuHdzmxu032dycgNvBO3eyFquqYHt3Qll6xG4SzQWssYy3thiMxjhv8LUqfZrjQHu0xBWOerOgGjtCk2imLSllUvCk5IkxUXgY1AbvI2JbEjDPhkWE8bDm/N45BlXBwd0ZPh1jreXMmQnjSc1s2XJ3f0ZKkZ3tmvPnKnI2TOewnEHlLaPSQobuGOIMlm3i1sEx83bGGbGUozHkTGROMEcqOmpLbBwwKAy72xpyf+uGYXoMZWGp6xLnYDhQa5OcoFloiPthXHJ7dguM8MiZCzxwdpcmZO4eRbppx+5WwWRsMZXFnpuwtTVmpd4SYDqPHMwbqsLywK5l4K1m6JQeEagqoNDnDAu1RGkXgeV0johQ2gpnPbnUolkutOtWUF5qOLK4EsBBrogp8zuv7/P8W4d47zi3s8Foo8KZguWRQXLm5sER96b3mM/XXiTvBLcEqbRwurKYSg6MJEzWQn9XC6nP/gg14KCpYN7nY49eN4xec8SRcPiY0G4oeSkGSoEf3oOPbcP4qOLSq+cYzIfE8iazvTliEjaqiuPaHH72NrzaF2uNwNUR7OzAOauFZioQa7GyQd3tcVXgz6E731/jLl9kofthj3Lu2X1lwjnrac5MWZ7tECdkp8RMOXOM3qpYtpavsOS/MIlHLuzxf/q+n+T7Hvle/san/y5fevN33pH0yJL51O98ii+98CUunbvE9pltHnv3Y+RaxzM0mVTfgfJ5qIa4j4y1Cvz5Kbx5BZojhFsIdzAiFBHKDsoWyt4mTIaZzmWkmZN+8QYpbvDWlXN84+GLdN6RnSEbw9Yyc+F4SR0i47tLhveW1HnOufAyw3yAqj8tgiUyIFHRVCNu7zzAshqxKAqmdcV+afknE8MXB8C1a8i1v4JMX8GM/i3YeRbmU8zR34E3fqnPyQKKCWz9b2HzGch3Yf9vYG98kj9qPsqfMn+YPYY47uA4BBqyOSDQ8Fd4hS/xdVx5jp0rAx7YeYDDumBWOhpvuLM74mhriGEXZx7CmMjF/N8yys9RmBlpRS7lb5f0yHySV/g8b5ARGvTzxeDBknM/ufmOpMcPfUJVGZhePVDRb0j60j1wuAW3zoAXXceDCDvn4EMXlCDcm8FkqoqBuoa6hGJFekROPnGencBPfkADvDci7HSwb+H/vAt/cwPem+B/0sIjSXM2did6HstKlRYzB7cL/Viy2cKDxzD38PVtuFvDxSk8vg95Dl/5HLz6FZg9BNevwHIHHs3wdIZqCNvvh62n4NbL8KVfhMVd+Fc+AD9hNJvn3/k0/PJr8PsehZ/4Qbi8qcqMjWWvivU6J90l+Oqjqhy91UDo4J6HzwzhtoMPHsPH9nWfePe7IT2h+4spIAi8MIBfHsJeC3/8Gjx8rPkjptD78TiwofkgeaHNNS7AqIHlFN76ivDSFzIXrhq2LzolPbzePLC7hJ2sH4XtXLNFfm0X/tJFaO3puvqpBB9dKBFzZwRvDXS811hjjTXWWGONNdZYY401vtvwHUt6rOxlxJz+W8kK01tOadFYv6lpJoP0FXAjpreLWh3MICtpQK/00HDy3sYq05vtq52TsaYPLefUGevkDO7zmVjZ0Vh6q6c+OP0+CwoxchLYidGOWb7FQkRtsdSK6/4nXb2C1WNOi/xZhJwyKWuh3ADOOQaDIcPRmLIoQBI5dSzmC44OZixnDZIt1jiM6St7YiAbJKOKGdR6aWWDZFzurZistnue+B1okHwWS0oJY9Wup0tCyGCM0ftYq/oaMaQsaukDBDF4IGVLErVXarF0xtEBnSSCCAFLMo7YE1upn+1V0q2G06/mxvVzs7I6syf/zr3BFRiieIJ4Qna02dEkVbbkmMkZ2mjoouZuGAGsqC3Ranz6OVopc0xf+ZCT51TVkTPCeODZHJWIdRqi3K+d3K9ZetszAbKRfrZ7Wi4LXduSMcSYENRaqvCOorAU3uILi7MaKE7qU0lFeqssjzF1r+44rVqc2L4JaskWYbmMBAw5xv56M6oo6AIxJlU+WYcxkSxZR9l5CjQ3x/RzYS0UheaVmH69G8BbDSJ3VrNtQC2zmjYjUXA5Y7IhRE/ODslqd5UFckpICEDGGosvyl6FtVJteYzRHBLnVBBm7craDlLOhCjkDFnuW8P9JeyswXuLS71dVR8cG2N/xZ9uPifWVyllUsyk1WvsLVtWl63th9yIWhhpnIsOvK7fXtXVT4Yxp7uL7hMZyRp6bo3FGtsTYkqk5hiR5MjGkmzqxwvNhfndHYr+pYbp3euSU+WDrNwRZXVdald1sTS9nZAqzFa/N73tlRHd4+52MG1h6DXw2AJ17144sILrvWNEhGQF6ckMU2ihdOg1LslkPe7IaOe2GLUPUi8hwBYYqchk5gSWJBr0GrTAhoeBgx0EZzPJZKYi3G3BOMOm99TWYZNFrEG84A0MLBQ+04Qlx8tjFmHJyhpyhdKXbI+2KV3JtJlytDziaHbM/KhleZDpjgXTeFxbYlKhZLN46AzSZExnlWmiRqvoFRBYhYGLVdskawyeCpsLchjAQpAQyFFU6eidquSAYA2dM9hk6LylKCwuOVoKfKrIxpBR0iNRkChoyoKmcLSFo3OW0Gc5WWMoAbEFUoyh2ATX+27hoBhDuXk6IMUYbP9348CPMdUWhjFRKjpKCvrXawyZhoTFM2bCJqWf4GxJskrgGPTzSnaGYMGII0uhNmHFJoXfoJApNrTktsN52KnhXIJF1AD6t8/YKToiHfFtv5MoxOU7P2LsoRZdi8CppVa/VYmoldW9RvWeF/rHOQvDQn+XowaTLzzcreBuBNepzVUAcge51YycwRaUlSqjaqu3se2tnhJs9zfrYDrUtV4BA9FrZpaVRymlNzY1cGDhhhPGJmBigwuQ24q2KYmdwYuKH+qstlKl9Dk9BVS13lINA6/X49jAtoMzHrZKGNRQ1pA6mNErLUz/SSNCuewFLaHfb/prOTmdq5vHffj6jopIV59QYv++4fqbpQ+tRx8vDrYcXPZwvh+H/uODHt+CqcGPDK6+781k1RQjfZB86m/6UZLGwpH2DbGddVwArjtY2p7suP+j6BprrLHGGmusscYaa6yxxncRvnNJjyRkY0hFqT7j1uPEIBREbYHWInPsCZCsaZEGj8slp1kfGTEWzCYYqwqEdKi/z1rQz8mSQkLE4OqMqzTnIGFICJmESQErgrU1xlRYG3FOFRmudBTDQgmAhaFNBrEZKTJYSGJp2gKLIcaOHBPG9N/cDZCrPojd4NG8EjEZW0QwGWc6PAmbHSG0NG2g6TpmTcO8adV+CBgUJbvbZzh39iKz40OOj7ZJwfDaV1/m+tdmdN0NTFsyqXap/AbGDJBc0SxAQqIuLUVdIAZmi475PDAcGupNT+HVAgqnlYZ0NCSEIaarmS2WiLc03QyRBmMCxaDGFQOC97w5hztdop5nqjLgxFCLw4ulC7BsHSkZprLJYlzTpcBRu6BLkWggGktG8CkyyElJKeUv6FJHF1veRkZxP2O1IhLkJKnjXnJ0TYk3hpdTSX0A2IQ4Tf/ssqPJHsFiTADmLLtM2xqtlvYVAG8d26OaceXZGIzIVHTJQzpG4pxJnXj2sT0e2C24sd/x2o2WkDLZOKLpSYCUsBmiN3TO9WfucA7m0ynfeO7LiHXcvr6PyIiq2uTKxbM88fBF6lHFeGuEAaZHM5bzgLGZdpnoWsNyXhOWZzEGQu0ItiUXFms9xhhC52i7iiYkbr51wLQNnN0d8K6HNihLy+zgmMM7c4y1FHVN7UuSLAmhwVjYHY8ZDEeklFhMD5nljHWOjb1SLaTaKfPFEd6X7G6NcM5RF2o/tWwDt27f4mg6x0mLzwsslsKfx9tdknRUvgCp8SESD+5grWVcjRkMd4gx0y4XJFkQZUwXxlhj2NqCyQTaTljMM10nHC2WdLGhcI5JPaFwBYUtmNgxxgq1LfFWyQ9nLNYYFnPDrVaL4dk0iOmwpsC7GrBq19W1iPEYm3U9ol24Iqfki1gtCkoGXxVYP1F7s6z7ky8txUhtsFZ5ETllmsWSEDrKomQ0HChBE1psnCPR0NzrMN4jwwF+c4IxFl8VTGQHS/Hf5db8XQs3rchbiWYQyV4zO3zQbXgVFD08dvhjTyqExYVI2Mj4FnYOtJBZd0KaJG4a+FvXhedvwod24McuKPFhsqoWyB2BuwieZTlnNhLEq2rERdjbhj+5rYXreqYB0cMaHhooCZCt2uO4YJmUIzBneFNm/Fe8xvMc8xItCzJjB/+jPfjQBpzxEVtNuW4sv34Y+NVbwpaU/ElzgQ+aDbp6xvzSbRrf8fQg8WdrWMotfv6L/xU/+/lf5NW7bzJt3q4SeujMQ/zp7//TPHTmIX75K7/M3/7s3yYuhWufafn64ZzRDdj9nTOUy4bqysOY5j3IHOJvXSO/fhd7r8UvNjGUfe20wnCAlZsYmbGoodkA15Vc3n+cjVuXCfEyi1iDUt6AFrSXDoKBZuA49ENcFoYbA4bnN/ASmaQtytzRWUNrVyaXym6J9aRyiFhPUxYsSkuyhidbtVfK/lHCI/82Emew/RhmXkI8g7n0Z2DrR04HxBbkrfeQlw5jHsBc/fOY8z/BFmf5rFymxmNpMHREm1jYjmAS+zLlI+kY52r88L1cq4Z0Tnf7XgB4Ulv2olZSk7PnOP/o9zO0N5l97essXnmF7Ur4iSF8LMFnb8OvvqVr6NvF4vXA9b959I5/O3NL9yxf9O9wvSWVFJBHWlh//VX4h1+HysHWY/DABbVM2klql/TCK/D8l+EA+OwmXKvh8YvwQ+/R62PxBVh+DTa34b3fAzvntegfnBby/8gRPHug+TSPO7WS+rUKfmEEI4E/3MIzATYSDPu9dohaf90r4Fcq+FwBn5CbPLX8KoNFYpme5NhdZYzhBzoN+37gCK7u64Df2oXDCbgzwMeha2B3E/Y3wQ7hp56CH7mkNl7VEA4d3BrBbaMh3+/pYDfB1mvwwa9q/8zFK1Ccg8EIdmvlGZ67Bj/3aXAlXP4I7FzUxz0cYYCGpv9ACxsd7BqgVLupxVAzSn60gScaJSceDvpRbF7A0Uit+Ha/zzJ5tzAuNK+HOadqHVDWaUV63N/DA5xP8Ken8N4O3vTwH23pn38gwwciDMK3v8bWWGONNdZYY4011lhjjTW+U/AdS3poJ5olOa/2VlhVHFiH2J7U6LMmRLSF1xBBLEY8am3UVxOwiBkiptAsiiwaIp565UQy5JARsdjaYrx2YCcxfY6HJkMaMsZYDFrdshZwhqIw1LUqH2ZWMFkQIxin3u/ZWkI2uD70OaeItRlxfbYIBVk8BotkD9ZgTOwrcYKTQKbFyIAUAyEkupBoukDbBaRXTxTOMx5N2JxssbO9wdndEYtZ4MZLtzi8dcBguGB7zzMYjPG2xpgCEU9swUTBC2rEbTQLI3YdYh1JSjXB9gkqQQJkW5KzI8aSpgtIWhBiCwQwCV9U+KokWe0M9SFTGqHsNTg2a6fvMsMsqdojyIBUV8TQ0UZIBIzxWFMoGZAjloQ1Dut0nLIs6OhTQ98uzekRoO92zWrWxTzr7dTHo19wJ/ct0b5Vw2l6Kt9ybGcto6pkc1hRlxVZClK2mJwhN9RF5qHzG2xPHJZjbtxqyVFzPZJRiymTlfhKOJK1WAwFqhRom4bDN98iZjhezEEqCj9kd3uTC+e2KOqCclJoJ3lYkjpVHYQuIWIJbUHsRlgrxNAQQwQcuXBYo7kXMRUslpk33pxz62BOeJfw4EPbUHjaLnJ8PMUXJVvVAO9KcmyJMeGcYTwo2d0cMV8suH60oGlaRlsjJpMJOWUOFg2LWcNkPGG8s0NZqdl67KBtIkfHR+wf7qv/U3espMVmpY+XRGG1AudSIs8b8AXV9hZuvEPbLujCbVIK2s0dxxivRSbnYDaF+TwTYmY6bzhezKjLktIN8a7AGUdtK6yBwuh46E1VK6E1dDPACLbsML7FWaEqKowRDTyPsV8mciIykpVyYCWMQs9Hl6cj41RxEkXzJAotgrnidHmlIISjTpVZNQzLvrM8RUxsQCDEgDUOR6KbeKxTq79BVRK7U8ujNU7hGk/K0JUR8eBXW2wG3ynpUR9YBjc8YSA0u4nkoIwwPtSOdZsEGcBRgE8fwKc6VVl8/By9yrDvlM+RJFPAElygrYRcgC2VO54k+OhECZLxPRijBc5pAa2DUEBbgisM0dcYxuwT+FXm/BYHJ69p08L7J0p8xCKzHDUcGvjqEn7hCC4mxx9kixFnkb3btDs36YaBKxuwNYZXDo75Tz/7Wzx3453HbG+yxyfe+wne/+D7uX18m7//xb9P6oSDVyLXjzr2juDCW2PGaRtzfBbCJZi1pG+8RfrKMY6AY6DvmWg4gSFjpMCIWowdbUDROiRdoD5+Ass2HQXJpBMFjtATHg6Ss4R+LxmMKwZZSYIy7+BEu9fnXndth86JF+1id3JaAzYo4fFgMCR7nvb8j53u9B3AGLv9/VqN5rRGnIzm9BizhT3zwyfvCq/0z7VCa+Go0PMeJng4nXbwn86gntMKtic8nEA13mTz6rsZ+k3a27cI115hWMGzW6oMmAX4jevf9vLXc7obOfj04h3/NjlC3/oG/QvqdMqkVPVDNnD3NnzlK6qE+P1ngLOqTBj2yrj92/Dci3A7w28O4bUSDg2c+yBsDeBoH6ZfhYvn4d3vgUHux9PqHD27hO9dop9MBxA8vD6Av1vDlsCHAnyQXqkRdbyihVTCrIDf8fBJB1flkK59gUEbCPk8S3uVLQOPRbjcwe4czt/Tx8YRdGPwE/BP6PmMAswj1BV87yUYnYGjAVwrYWHhzUqD1s8kuJhhLDC8Cw99AQgaveGGOpyTCMsCPr0Pf+9lYAhPPwOXa7icYNTCVlZS591Rx3LUC41iAW2lY//UvB+b+9ZLKOC4AhnAxiMwepehWEBxC2jRBbf6lH+fyuObsZXghxr4+BL++hh+ZqBKj6tL+IFGx3mNNdZYY4011lhjjTXWWOO7Dd+xpIexS0Q6ckoaDOylLyJmRKJaAPX2TELSDnoRrBGcUSWFOen8ByNLDB2ZoNZOgPS2MFiHWbVliyMFrx3X/aMlof4CYtV4nwASyDmTsmATxGDUGocIrsVYwfbtdE6yKjUQbBaM9L4E1qrJkWSQFoxad2UDkJCsbciCYIwni2XWdpjFguP5EfuHd1k2S6aL5cn32SR6ikU5YGNrB2tbYjnlmCOa1BGXM6osXEgR8QZXOYYbQwbVkNI7fOmxCCFCsolsHGIrxFYYAsQOEwVrDNYLvjJUkwEUA4qBR7NJIil7TIaYLDl5jYa3qwBytfYAnUJre0smKxjJGAe50DwVtf/Qb+nG9e2JDqwHjGDi6tv4fV4Oeu/7fuo4m/5nPrnnN99fc0C+9bJY3c/e999qqxUk0UogSjq1hhH1y/C2ZmOyjSuG1AMhyDFdjogTrMlqkGX0teVsCNHoMxiDwxAlEbMQk/Qqpq4n9gDpM2SC2hlJ8EhYUUo6B2UF4+0CZ2EwclQ1GCPk1JL1aXT+smE8NiyToS4gLTIhJto204hQIdjCUlYWX1XUo4kSBGSaxZy2bYkiPZHjKExBMhlrCjCRrovcu3sP7x2D4YB6OCCGQBc62tAxKks2N8/irIdcs1wGQgrMu46QA845xA8Ap5KJvMQSqcuSnD1OHKkNSDDEkDBWaBu1abNWGA0LynpI4Tx1afFW104UzfhpQ6ZptWhXFgZjIUdD8moj14VA6BpKD95EjHXEnOkAJ3JSQ7JGuUHklPAQgS7oHhY67YZGwHmLM6rwWN23azNNl5Ck5dqqrshY7h01JAHvCy6e28FkKKLDiaUe1pSuxliH85aEpSzXSo93wvH5RDHO+L5D3OReXWO1uGgcxJHQbSViLeRS7a1WmRjQC70y1BHeZ6GK8PiwDxzOqtAIhZJZ2SesE6rFgO2bW+Qik8op2be4pCoT2z8ulWqxI6Yv0gewAWzMGHtEO7zBME95tusYZnhL4OX+dZmk9lsezcjAwFUPP7ANOzlRF8ccWEuzeUxXJaLX56gCFPHUzuid8MkXP8mH/8KHiX89cPX8WT7x9Pv42U/9Bv/hS/8G/+FL/8bb7/xzn4Wf+zdJ/8FbuKsVsINjhGEIBB0U63Fjy/DBh7GTLczykHx8B7fMlO0xwh3MRkXx4BhGZ3CTIdkbsrl/FzYU/XZ/v2llsBBFfwqcsBSrXTv27+mGU6JB+t8lY/TvRgu8tldeSO8UdGIT9LbH635t7juW3Me3W6DMSgoU8nYqftVo/7bHogX3xvacgxPE9MaMS2Gwr+SAHen7nw9vJ1m+HezHu3xh+Sn+3fP/Mb86/Xl+Y/7LPPnwk/zM//pnMBX0DpCkJBzcgeN9VTdsBXADQxjC8eOqRgobOvCriC0TYW8CT7wb9oDDIWyUwoNDjXoxVhBvyE9D2jbEsRJCprfAMgnMAmhgv4avbcJhpdzL71tocPm2wMyqxVWd+7kyej3b+z4C5GKDOH6ISELKTQwwM/Ccg9c8XJ7DI2+BtyCbcGYTWgOF0znY6DQro0z9XDslsgvUEut8q8TYRtb7llFd0AZP6OdFcxHCWBUohVXbsGIX5EkNbN+ZwKUEZxOMsh7zuoXrRgmQTdsTJ1mzb8RA3yNDZ+GgVALwjRq+UYDD8EwHW532phinZFVXQlvrOqlF1+GtJXztHhxlcBP40S24JDARaDycBT7e6vM8FPX1r0mPNdZYY4011lhjjTXWWOO7Ed+5pIc7RmRBaCOShcp6nBc1m8qxN9dXU/aUM4uQ6JLgbab2QW1qEJwBCJjcnJAgYlVVkVgZqjus1cRHkYK4KBEjiG3JJmLEYHKpj08JyQskRw2PTigHstQu+yQtpphhjAVKnFhKMjVBzyerqsJYh7FFb5adgCmCkE1WayxRf2wBrKtwriImx43jGXc6x93bt7j2xqs0bcthu+hzMISQhSDCYLLFxUuPcHh8zJde+QzXeRnTCW4/URaOi90SqQ1+XLJ7aYftzW0kBKRpySnS5EyMgegLkh+T3QSTG2yzgJhwtqOoA/WGZ+OBHUw9od6qMEbJqpAyKZRYKYl2hHEWKZ2qaNAOywyIFYqseRBOEkkS2Qh24MnZQBIk5tOqRqZv6xUtSCXBtPmbvOh7s/77iA6DwRtVUkQy4SRXZVUpsahRBvQSovv+vbLLWhlcq+9HFlhKh02ZJoeevLJaGc0DKj/ggXNbRODlW45lvsM8CLXNFLbPyehPO8Y+78QYkrd4awhJaGNWVUFe4FngpAEsQklS5y0kQ1pWSGOUdPJTjI2MJrC5McBZy8AWVMbTdS2L+TEpRnADhpMBtoKzjaUaOTZr6PY7orHMZpHjnBlboRhYRhueshoz6EPFZ/eOONq/S5MybU4EZzDOU/uaZDLOtWAz09mCm29eR3LiwqWLnL94nmXTMG/mzNo5OzvnePTRRyhcwesvL7l5bUmbA0csCBJw9QZbfguMRXJE4gHeeDaGYzCWEqE7asBkWmmJEhFKJA/xzrK1PWA0HkE2pKUjB8AklrRIhukyUR6B9YbR0GEsxARdgq7LHN9ccHx0xLAOFLbGOU8TI/N+vtMqD8JBqZEumu8BxJiZTjvaLmkWiKiN1sakYlR7jFHSQ4DpLHD7zhJnDbtbFRubQ+4dtbx27ZguZC6cH/KBKztIMiynhtCBtRbXZ4NkC7ky5Px78Lv5lwg3nm7YMYaqPS1A514clkvUI38vEseJ5KEbK+kRyz78PJ0WtreAnxJYopkam1lJiq7SgjBdJpYB11o27p5j++AquYxMz75As3Ebm/pCb9bn7sZKrmD1d3UL1RxsjGDfZLZ3i50u8ecOWxYt/F2B/zT3IqMARdNbqQXNGPihGt73IBgXGI2v81p1C7HKtIgBn2G0gGHTF1P/GbC15WNPPcmTV36an/3Ub/xT72u2b+A/NsZ/aEv/G9GKdvkmFNcpiobd0TmyX7D4ynNMPvlPMNPIcHoDIWEvVoz+2HnS5YcpXilIL1piOiWEHPoWsNo/DUpWtEYL1isCAU6tooQ+rJmeiOjvkHqiI/RkQzYavF2uXkz/2FUGEnyrMmP1/On0ISf3m8T7CJhv+ru577Z6x0kGll7PZ+qF7CKGyGA/w6tKji3PQqihau472LeJV7rn+S8P/hOccRylQxJJB3SAsgqiJxICvPA8PP8VtWL78FOwvQ2Ls3D9D6kSYbFAGYkFsK+qqcfOweWH4dDDA2N4s4Ti60L1CwIN5I9B/ClDcKpoaowSdYN9vX7MEmjh5W34mSG8MIE/OIf/4746NXUDDTDfElVL+dTPgVeCYDXMaXCe9tzHaEdCHg6xGG4Z+GwFixredw8++lm10frgFrz7jNqn7Xt9d9+ewvZx3wJRAYXaFNaiz7m7hGca/QA9NOANbFyG7Yf6dWDUXSp6GFrd9+uHgStQGHi4gg91mumz15MZX/Lwtyu4YuEhCw8BRdDXuVproIqWr27B7Qo+6+GXCxgl+LdnqgYxGWwfnzMbwZ2JXu9n0evhqwv4v74Mt1v4SQf/Xg1VAfUADmt4QuD/MNXXUBo933ZNeqyxxhprrLHGGmusscYa34X4ziU9TEQkkVPuQ5nv6+iXdN+Xfa1GZBGigBUtoGcEY/rCuPTWV31x2/QhpydJx9C3C1r1/85W+/hP2jxPVQNCgpw0aFjUVCuL0aBrUeJj1TqrHaJGuxFR5cf9XaMnJv4nJQ9BjNoprY7bl4x66ytoQgBaposlx9M5bdfSEU9K91k0/Nk6Tz0YUnUd2SdaFnqHCB2eZQyamSGRbEWtz5OQSGRJxJwIORJyoovQRQ2OtcGQoiHETMyRIJEo2o2KzXgv95FTibwKWO5fr8H2RSmdJ53r+6agHyDbhz7rlPU2ZFlFFPfl17+te/a0f1be9t99dPR9P++//zeTJSfl0G9ekffdVo8WsmQiiXyqC+qrbg7rDFVVUFqD91Uf2K6PM6u1sDqWiNquWUh9gHVG+twZPbbaL5meUDOnxFgGSfqcmIjt2299kakGWqwpxGDFYCN6XWW1WDNOsB7KEqpK8E7IQV9HFlaeTxivRX1fOMrSIVmVLaHriKLqIlmpakTJJWuUTMxZWDZLcox0bUtKkZT6QHTJOOcZDEcUrsTajhASURLJZpIRDZS3hb5uaZAcNLjcWazxIJEcI5l+zYqqMawVjIHCOwa1JydoOyCp4kVXKcQkhKDFHWfV03516Rsr5JyJIZGK07lYdYjfd6WfrmXz9nmNKROjVuR0ZFWB4vz999Pz6NqMcxYRi3EeoaPp1M7OOcfGeEjuZV2uD0pfLb3UEy52xbis8TZ0E+hawS77DvFeZXMSHA50BYQsqu6wpySHuBVJq7fCwAV3Wog3/R4npg9Gvs9pz8eCuhmSukA3KciV6dUZWlHPJcgqWL0/nk1Q9N3vUVo63+KS4aJxGFOyJ+kk78Lm/rruZQfWwoZVa57sheWoZTnorZNWBdSsRWKbv3kPfWcYCzuTITvDs//M+9p//UPf8rv5f/INqD2UXj2+ig2wFdZuULUDWLakGFgwxZQL7E4mn7XkewZbKZmzUlWslBbfrJzIPelxcs733VZ/X83Rt7xT9ORHXr0Hyelx32l8Vu/j/6yxW53nitD4Z0FQwqOzEMlIDIgEbJvxyuviO11j3+7c3Y9WltyLN1XxaAzeDvCuwjqnA9y/7YlA0wSm08iosORliRkaTAH2TL/P3QZpOXWGDH04+ZaKei5sgFSqkuoOhLQA7w3+rD5VWiq54vrPJSe3pLaXbwi8JHqfSwt13rxeqsqhfzptJBG1nXPOUGUYiKGwNVLWSKX2gaXXa2zfwb6FiwkO56rsIKhqJIteEwnIAdIqiBxV6xjTX0MoyTAO+vfk+vmqQCao82qvHMxG1RVlBlcBY52zYVRFxzBDlfU5lsBNCwOjzlSG071gtS6SVaXLvQJul3Dbwi2r5EmbVfElRgmlZJQgOS6UqBmh5MdhhLcauNMocfbuTp/rsFYSapzhUs+bHxg4NtCuMz3WWGONNdZYY4011lhjje9CfMeSHmKGtKHj6LhFgKIo8CWAUaskA9ZWOFtjcqLMCTFCYbVL3hr9lpqNwVg5adVMWQgpISKr/n9E3Ik9lXEJ4zTowWQw4jEmaQe9EZKkvpPPgR9iRBAcMUYtXIoj2QEiHmQA2ZFljqXrizYlgtdiV182zZQkU6gllzSYHN5WnIGESENoheP5Lbp0xHJ2TMpvb9HNIoQcaVMAZ6iGFVXQznQtM0g/BpkX33gDgLqq2Nl+jsFgyEZVsTca462laTraLlBVFa/enFHXNaWxVHhSSlw/uMX+9BBTVJjf+gLiCl57Y877nz7HbJF47VrDvaNIypkmtyTrqAqHcQUgmBghi+owRPNXsrFgBclKAKQsmltQliBCjKquEWOQbPSnFDhqJQj6//WjoXOI601IhCTSB9Pfr+Q4WXH3/W5V6jKcqkaAE+LslFRJEkg5knOLyaG3zBHEqUeJSUJOmRgbujQj5JaYB3ipdO5XCpH+bG0CZww2W0wyVAIZj622qOoBW+NHGNQjygq6NjJfdOSckSJRb2esE4p6A+sEVw3whZbFwiLRdBnJhrIcU3ph2Rpm00TXdbTzGXFxjIw8Re3wvuCBjU12TYVzlqLwNCHRhMjhkdrCNceR0FmScZS2ojCW1BYcHnYYA1VVcaYsWNQW7xMpBnwFi9k9QgxslCV+Y5vKFBzcnWGNY9kcY+yUqnCcn2xjS892NWRzMMAYWIaOZQsigZxnIJaq6KiKgLWWajBg6EeAI4sDY5gvI02IWIOqfTyYwlKVY11nyTBfNNRiGW0UeGc4nAZu3uuIMZFSwXAwYTSq2doqKcqCdCxEsdSlw9uVyc7bV5MAWEtZeSVorME53ZvKQh+TBM2vySDeM9ocIAJHTea4aRCBSxcnGCPsbFUnypCyykp6oMfLGQ4PO6azyGz2zp79/7KjXMLzR/DcDSUtPnIGHp2cEhsJ+PIUnrsLwxKeLeCBUguPJ+SHPSU1YqE/71cWGLQ7uwglVdyiigVpkJiOXkaM4FrH+OZ5umHDYvuYVCYVhvXvxC7ozUd9ng74VANfmcL5uM3vD89wIZ9B5CXgy5gcqY43GYcBcdAy3z0iuMgXZvDZKdQFfEjgiujxQk/oBX0Loml7suyfBQNUx1C89s819v/+L/1lcIfgj5XJcR2GxNV727yn+xOIiXzFfInXeAVufwXzS/8Z5sw5zl36Xp7+/o/RdRUvPw93bnGS0QFqZRX68V9lYdyPVbEYTjvlM2oNZPr7O9T6avUAJ1ocvp8U4YSQ74mX1bHM6THfqRl+tTaE08es+DC57/H3ky8r1cni9j2mv/UlbLpBunuLuCGI6wmxBmz3uzzpPwUPc5Ef4gNs2A2undnlxu42V6+cZ9NcgRn6ibAAP1zy0DO/xuDBzzMuLjGa/Ci2uMQHBf6X19UW6gqwP4bSaRHftPD8HfjGy2AHsPcIPLUDeWhIH7HkAIsNQ3NdSZHFEF6uYGMMOwJFgvESBh3UAS58RrNzbjbwd5YwGcCD74HdizBz8JsbkDM8eqfl4bstZ0rLH2trPjgueE+G3axEyfsfhq0K9nfgkQEcRHj8AnzgB1WxUl1SAuG1A/jVl+HuEqqLUD+gSpCPC7xb9JpJ/Xp7YwiLCqYGvtETKbduw+tfUTXI3mW4claX+t4xbEdVj9gjVaVUV2C0q9kh20v9rPkU8KMFnMuw903z2hr4xyP4zEBzf96sdAz2WvjzC83keKrRdfVaAf9wDDc9LEqYVWAXMLkO9TU93h+7qqrE793rCZ2sqq8yqNWWSbCM8Os34FN3YTlnjTXWWGONNdZYY4011ljjuw7fsaRHZkDTHXM07RCE0XjIYPj2+1hX4ssRJiXK1AARbxyFVTojGUs2RosVTru+Y+zoelmGF3A4JDtiNOSseSC+SEqIZItJfUulT4hJJNHSt8FiXI01lpwSKXSkLH0g9RDJHklDNHsh4pj2OoMKkQFCwEgDJpFNQTYbGJP7wozRwnnfjZ7IGIk0XeDWncB04bEScN9UuBeELke6HKgKqIqKqqtwfpVVIYCqL1584w1eeestfZ1Wz+zS3h5PXX2IYVWTpUJyiTUW765hjGVYTBiXO8QceePey9yeXqdplhwe7pNS4pEnP8j7nv4I84XhaHaTu3ePiCbThI5oLePRAFyhyhvJmLxSO6iaJfavOaNZKSkJ1ltcWffKkIaUM4Ily6raWPSmU6pS0d79VcKJ9KSHQxAiof/7O5WoVv249/+3QS8R1x9v1dZqTs45SyBJRqTD5IAVo+oE1493ykgWUmoJeUqXOqLUZCpy1uwKJeA038NiKaJaFtkslKKkUFVeINcPsDm+wmAwoqqgbSOz+ZIsicFGph4J3pcMR5N+zjUsPiZh3iUW80jpHZN6gsWwWDTMjpenpMfyCKmH+NpR1xU7WyWDySZtyNzdb1m2mWbRMZ825JxxOWLF4FxBUY2xxpPazGHT4b1la6dmOCoYjUvKoVW7tOUxi9ldRAwbVcWkHGIpObg3QzIsl1NwM6pqxN6ZHerhmGFpGdeOlDKLewuWx5CSqkZyFqpBR1W3lGXFYLLJaLRJSkIXNUtjvuhYtoGiMGxtOerKYgtDVY5IUYgRZqkB67HGUXjHchm4fnOB5MzGwDOsx4xHFVvbFVXliGIJXUlZGrz71m30hEKzhrLy+EIovKUqLOY+hVLKsAgQMuA9o01PCJm7+w3zeWBn03P10pi6shhjeuGZUNWZnEXtrZwjReHuQeB4umQ+X/5TdtZ/eVG18MIB/JfXYGDhzBAe2ThVWESBL8zgv7gOezWc24Erk75Y3m8H2XKS8xFKta+RvtvbCNQNFC0UsaQKZ6jigOngDtNzr2CSY/PaBQYHO0zPHnNwaUE7SidFdJuVmPF9V7U4WAj8RgN/4wCekh2elB/mPI8Cvwx8A5OFerrJeLpLszVlvrOgc5EvzOGvXoPdEi4P4XGvgchtqecavVoMNstTlcs/FUagPoLxa/9cY//v/+JfRgMgTvddg+HHN3+S7d0/STaJv89dfplPw6278Etfw5cV//qf/bf40T/+vaS2YnYPptc5sbWCnvSwetgyn2Z8wCnhEUxvUyT6uGSg66/Bore6OiE0+mP7+xQaYlT5sCIoVveT+//O299R7uNQ3va71fFXx472lGK3KvyhM9pxv7h9j+nvfAkX3oKQMZv6INf3YLh/ju77d3GRf40f5aJ5gM/tPcKXHr3K3p5nwxRKegyBCny14MFnfpnL47+KWX4Yd+dpWF7i2Q7edx2ig6NzcLAJw0LVCqaB51+Gn/8C7Izgpx28NxkN4PiIDrjMQa7BwRC+cAXulLDr1K6rzuAbJT2qN+DCp2F+C24B/y1wZgt++iw8clZJik8OYSqCfaPl6utTzlSeP2YLUlfgPBSl9qZ84F3w9ENwWMBjQziK8MBFeHhLx32/Ususr07hb3wRXr4H5ofBvB+uOrgwgwe7Xs3Rr6c3h0ouXDPwcw5eMZBfhPxJJSA+8MOwOA/DFs7ug1vA1htgXgI7hKqC4TZMAuzMdU6fLiAPYCNpJsr9aCz82hj+8rY+f+7X77/WwZ/fh92kihKANwr4a1vwlfpU2cQCzHUwX4cfvwj/zvvg6lhtuVy/GEfN25VNTQO/8QL8Z1+D1P7e19oaa6yxxhprrLHGGmusscZ/3/iOJT1AbTpcoQUHc19xYFWhkCzkmJFe8WCMFgZPSxJ9378IsqpVZ6H3yzr9dmfVCguDPr4/hv6zt6Ux9sRvwIgqR/p76U9jsObUkoD+2UVO8yYM9NZbubfc0jBrPTm1tcKszllVBgbUIspkUoaUMzEHHILFYqxlXNdMKsdkOCA1SxbHhzDw+HGhlklyf+lFobZTmbIo2DtzhtFwyM5whLd9C3A+tQnLOfdhoYIGq2eWXcvRfEHbLpktFqQUiV2Hz5kCDWk21mvgubFYq3Ziq6FfzQunI6PjejKmFtOTEJJPdRwYo7ZEOZ+QDkKHWoIFOCE9Qj8Dsf+99L/7ZjWHve+n43TtfOt6fPtNxyOlRIxZFSj36UxOXo/o6zQiOBEcArnP6RDpLdHebryVJRPF4PrQeyMQc0tKc0JaElPScHPAe0sWXX9Z1AqKPsdkdTJGIAchNILxic6qTVZMgSyJTOrPRRUDKen55aSKm5xzv+6SBqoWDpMMxI4cE5KjBtwbUessSaTsiLEgJU9KgqRenSOOjCcLhCDkFDHeYrIqpQKG7EvwJdY5nLUYa04Cp523FJXHhExKgkkZ7z1FCc4XhATLpp+L3I9vghw1aD1lQ8wGweKdXuPeCc4K1hnaLiNGMz28s2ANVWGoSoN3lhiz7kUiatXSH+N3w8reKqVMionQ9HNi9XGpX3fOGJoQaRahtzfLVJWlLC2uV4mcHhNChBRFx1oiKQkhZVzhsH5tb/VOMAKDAnbH2gFerfLeRbvnXYbNZLiULLtZGOaMTb3i7756/YpvNaLFyuRODqOd4AUUhWimR+nYN4E3Q8IleMgF/KBjagNvtsLSwJbX2+o8TFTCQ/rw5G08V7JjG8MdjniRO9xm1mfJrN5j1A5S+vexiYcLFWyXUPU2XDZ56llNtIZD13LHdvzPfu7bGzu59jqcWWoa8z8HlquFf/98YMjOUm2OyCTyoWO5ej8MCULLz/ylf4+f+Uv/Hi/9gyWyLMjGfaul02qf43SOTkjF1Xvyfb/reyBOiQnzdm1fMGohJLmja26T4uxtqgwrpzkhKzusEzWHcfh6D19u4jAnRMyJkoPT57ofCSVvWqPF9c5Aqh12u8bFAfm4RWZBzzH06yS9jUP6trCk4yb7CAV3wpCjhaNuB3T2LKkYYfpMGbIj2B1icQUbzlFRnShgfIZOIBzCcc+vZsB5KEcw2YbREIpKSYcuGhat7lsFah+4LOCOhWsW5qIB2oMMRoWgdAPY2oRz3em4bW2oDaOgBf7NrOSULyzLocNYRzszxKBWds1un5PTAg00VR8s7pW0Oaz1vK/1tlf3KphswLkEYaCElBe4PYMXZlBWMBqrrWCYwizArITFFiwrGFZ6zpsZZjW84jTvx1RK6LiRWn4Naw0qr/sg+mOv13ln+/HhW+fVCmwnuBJ0bd72SowdNvDmAcxWMU4GbmfY3oLLFg46uNupwGrPwGQE5wcw9jC4jyHMBjqnP+ctHC5gv1V7rGoHUqPDuMYaa6yxxhprrLHGGmus8d2E71jSw+RIVcPWnieLUFZ9mUDAijIgqemI+VgLnBasKbTku/KlNpq2YAAT+2+ROWnuB2oVkR1IFEzWopRxFcbUGATrFlgXyFjEqhmzpcWY7oQYQJQQsIUji+C7jBXp8wqa/tn1m7uIEHNHGzPeZ2oiFgGZIVmLQtlLb4VR4vMQwRFtojWZJkVaWdARKCgxDKiKkicfvcKDD57FiTC7/jqvXnud3QsXOXflCotZIsaV8uFbcXZvjz/3p/4kH/rAB7j52hs8//nnWM4WNAm6bHDWMqxKvPeMBgWbE8+yTczfmPHGrTukFAhhjkHoZnPs/hQXPB5PMRxRGhg4wRuDdZoFYkSzKlgVpldzYzK2Jw6c8Rhr1R4qNj3zldUvO2WarlXVR5wizHpyY96P9aoHF527nsiQFbGEQ5e+BWo0trbEsgF41ASrN+x+W0/vCh2gtlLzRaJpMvNmi2ggW22bdDn0HdwWyUKdhQlqQUYMtKLVolU+h+k1KQBNbsFo6H3ZJ/MuFm+yaG6webRg//iAw2nAGcvW5ghBWObMoslUyTH09m356zlAs5+Z3YrYMjEfN+AyXcgkm8mmI+GIUtN1jtlxS9cIgcgyR7oIx0uhDUJVlexsboAkDu/OmR9NycERFktErM6rJHzhse4MIWrux2KeSEnADBE7pOta7ty8y3w6x4xq7NYI4x3WDbEbu5RVgSlKnAOMECSCFQabNcWkJHSR5fGSHDPDccloUpKScHAYWS73GRQFG8NayZ2lkBshldA0joQnGxiOtSI6HGhBK4TEjXsNISRy9uxtj3HWsDWAUQlREvsHS03csRXDQUnREx/fjBWVFlLieLpg2UQW047j/SWSwVceVzgmk4pLlzapKs/N64d846U7FN7x+Lv2ePDChLIwFP7tx48RDg8yi2XmcLbgxsEUETi7vcHO7ghffRvJ1P8Swlh44jz8ifN69T/cV6Bd1JyEKsGPdiUfoMSLcK5tqJZR7aZavW8uoestr8o+YyFUqJOhhcUAgoPGNtTnblCMHb/etvzta5mhE35q+x4fvnDMF9vIf/1G5F6GHz0PP3KuLygv1boo1NBOoHCWP+Q2+RgTbgK/wj/kOp5r3GFJwxAhMaUjEUxLNhHr4CPb8EClmQWXN6GrYXC4xdnr7yK0Jb9uXufvmbf4dv2R5K/9RXj2PZgf+APAX/j/2ZxsXKh46CMbJMlMmhJz653PaPEXr7Mc77GoxkqJ96RF7FUcq/8GJSSK+w5iVlk3/X+XfeEetNCceqVI0f/ujtdbu7jD3Tf/Kovbn35HXSC8/VzFgCs32XvkT7N56RNMsuFKq8+XzGmmhzY/nKpLBJh6OHZKduw7WFroHtpm/K73sCk7LH7rddovXcdEcMdA+89nb/V1Xudn+FnqXHN4Y8TR8ZBH5lf5Pv8/5fK59+l10EAKI240f4Q7gw8zard4cHGF8ZyVgJKwhLe+DK/egosPwN6HYLIJ73ovfPwhJdo2NqGp4a1X4Suf1Tyl8x+EM++B1yv4+SE873WN1gJjgY8V8FRUJdL7Pg7vXerf6qwk5YWzOmd7CX5sBgmD3al5/WnP4tDw0hc9+zfh+pPwwg8p0cErwEtwbhu+7/1wroZXS/hSpWHjX7LwmoW9B+ATPwjjFu6egzsGwgx+5cvwc6/B91yCP/WUWmW1X4G3vg63z0D7Q8BleOQy/OAn1B7q1XPwqaESjx8t4UwEfxZ+6hHN1vhgCQ8cw50CPrulVlVdH2Cf719gPQYC/+oxvK+BF0r4K9vw9RJ++xbsf0YVYquPNA/swR8HNifw967Bf/M6bBn4M2P4vmfg3AB2q7cfv3NwY6wkxxfegF/8Okwj5Afhw89CnMOv/l9+b2ttjTXWWGONNdZYY4011ljjv298x5IeSMYXQj2yajvlTG8D1HfBiSHHROw044FKsG5V1tAOee2A1W/pkvT3q5tZFYQtan1le+WFNUABRkOejQSMqfR3OP29CScOSSIaMI2zGBGs0cByzWnow87ltAipIeGCzVpIN6ysnjpVmIhXVYkYXKoQHFkywWZi7kgyR6OzSxwF1tacPbPHY1cfYnF0xPUXXmA5m1HWA7bOPkDotGP/d6uOjIZDPvSBD/AHfuRHeO4zn+f2N15Fmkg2mZwy3lmqylF6z3DgGI4M4qBLHYezOapQCVgDKQTMosUkzepwRYk3gvcZ36toTs6lD5wnC6ReI2F1LIU+jNmgSd1BM05wBuNAJBNjIKUIsgSmqIrjGPjWjmI5+f9VJkeBEh2OlTLktBvYqvLhbaqOb84AiUCLiBCCmmZ1IepsGnM6p6Ihw5IFz4pagS4lYg6Y3prInJh89dSMRBIJL2qxhsAyz5lKYNZss2iXNG1iUBwbTC8AAQAASURBVHnqobarN4tMiBlnjIaar6JIjDZOx0WmOxYoAw2L3q6t/7tJ6KotiMnQtRHJBpqOVARCgjZYumSonWG4UUFOHB9BoiMmw7INpNg/mWR8KFg2E5yviCESGrVjMkUJRUEUy3QaOTpYYpNga48tCwajkqqakEuHca4PmpYT8rIYeEpr6BqLhEgKicFwwGg0ou0Sy3afg6MlcZAZ+JLCOXIQJGgXa4wWiRZrLEWl6qzBCAYDmM6E6TwwX0TGQ8/GqKRwhslALVzmXcfhdElIieHQMxpavOd3VXoYVI3WtJH5suXwYMnt61NygmJY4EtVwVx5YELloFk0XL95wHBQ8N5Hd9nZfOftOWdYNsJslrl7EHj9+lS7+8dj6lFJlPKdT2gNzk76DG2BnQNgrsSFD2ADPBodT1OSJHOcOtqo4cC2L/aKgeR7ZUhSi6FVqLQYDUJvKrAx0UxmJAOvtPAbxzAphY+eX/Ke3SU37sFnDuFmC09MdBs0os/l2j4vxIETwxOmYpMNPsuCv8qL/DanmS2CIdH2xn4BMapEujKAByt9f2trzSNwoWbz9jm6RcVd7vHZ31XVdorvY8T/nQdwn/1/wGeB/+e3P9b5v/45/uZv/xP+d3/jP+eNe3e+5e/GGKqJY/tKTZJEPf7dP450nzwmPLNFvNzv0+a0G/5+wgN6K6t+u05Gc3NATu7jRe2YxJxmZ6/UH6CEw60CFsy5dvg5jm/+g2/7Nft6j+7yD9F5ISf99GHl1AZLz+SbyBIMrYFpT3rMrXbxx+0B1RNnqU2me+EurTGYLNgWWJ6uyd8L7nDIHQ57pkVv5fZTTN0foRuDmQFzkFQyjU9xKz3FdoSLyvOfPF0OcPQm3HoehgHiB8AUws45eNdlHcs6QsyGwwZeeQXmS4hPgNmAmwU8X8CX7WpEYALsWph4w0YBV0Ya9D3KMEk6R6mfr1Eftm0xvDUouLZZcCDwwj248RK8dBY+7WBR9K/zGrw7whMdnEWJpZc9HBr4rIHngWc34H/8Lria4S0Pbxi408EXbsLXX4GRh/yYqsTiDTj+KkwfgPghHZPdLXhqpOvvuQL+iYMrHrYLuCSwuwlP9wHoDxzAxhzuOHirhnslDEVv93/yOFlXAk+0etsbwN/e0N+/OYU339Q5W8lEPp7gf34FHge+cQP8i6ou+eD74Q88cP+6UxhU1TItYb+GFyL8f27DLMOzT8Pj71FlyxprrLHGGmusscYaa6yxxncbvmNJD0EL/2ZFEBjtIL+/9JysI/veTJ2EkYSIIYnV8Fkyhv7bsl1VgaU3jaIvuvciApMQk7Eu4AvNbsixJeVWn9v1j5dETisLKO2olxwgt2TJpGzJGLIRzXawkGzurUigzYKkjFhDlQuMMQgObG+CIRFyAslkG6EnUjxCAQyMJ5uyF5o0JGMoyoLhcEJoMss84agVwu0p+/I1lm3DwfHh28bWGNjbGHN2Y8SlnTHHb73G85/7DPvXr7GxNcQXhkUXaLqAc55BNcA5z2g0YGM8oCgsV87ucHDpAiKRLC3GwNntXYrBhNBZCjunkBay0MSeBLGesvIgGaEBE4nZEIKqIYSAEClc5EyxoHARbzOF1dELMZFSpjGRg6alk0TDkoaWTCSQyN9UBbo/yLw3VMFjqQBLpqDFk3E2UFUdzjowCWv13I6bmiaWBBwtRV96d0CJNVBWBd5BXZXaSbwi20SJFPUhgYvnt/j+D72Hw1nD168d89bdVeFSmYkVtaLFDiXrMo64smuzNYUMkFRx9/Yxb71xi+2tIcX5DZx3WGcY1IbSG6w34GC2aDmeLYkBsnOMd3yv3hByl8iuI7sA1rK9O2RnZ4PSDRn4CmuVbFsuhSxCIYIzmUI6cjcjp0hctnSLhHMV21ubWOtplnMWiynOZZKIutSEzDK05BRxOeFSolsuWCymzGZHbG+WXNzZpKhrXFljvWVYWCYDy7C0NE3H9LDDWJhsVdRjh0me1lVIzuRs6LpAzpntzZJBbZAE824BAkYSrtJrbjEP0FjqwjMqSzBweBC5t58QgfHIMR56DA6RTMqGNqgSZ9HCrFXnHWzE2CXeWnLwFM5ivOA0SoWc0aJnhkFVap6HcdTOk1Ki6Tq62BE7x/UbC8oy0LSO3Z0dBpUHU7LsYN5E7k41u2Rvs+TMhsoMsklkG5lMHA9f3sRaOLtTMqwhdf8iO+//cOGSqjqq3lbGr8gMA12l1jp2M2JDSyqEMMxqVdVfmEZOyQ4j2o2+CjIvesuhgemzOaKqNZKBCxa+fwADr7YzTQ0bG9o5vt+pMuRXbsFudHxkusGltkR8Q5umdAhfZMkdDnmJjrvEt72mBvgckRLY6YRH9z2DufCSJJ6XTOHh0W0NRr4ZFnxJrnFMwdc5/pa98p3wkff/EQ6PduDVF37P451++3NcOrzHH/zAu7jXXYBcQSpACsgbGKl49urjVNUhi24JZvG7Hutod0yo/Imqw/fz0fW2QAYlN4yKLylMf7+sP+vuiLOH32AQDqHsoF4iAqlx5GBxFJQyQvCMNi5Sb1ziYB44jpnj+0/EeAbb76HefDepO2Jx74vE5g4Pscd7ucwobXPmzozN4tMMbcdZt09tOpLVwrLJFX5+FdfuMR3U3NjZIBYFlWiWQ2e0sO+tqhuMGDCG7CCWqMpiTz8mnAvw+wPcS/D8DN76PfgPGePZ3nySzY3HOLP9EDfeOstXvqTWR1fHYEq1cSpEcx9Mqc+5KDRIux3A9qPweA17l6CqlbBf2uscFDcopGQoVyhkm8k2PPYkzBu4E+GVr8JyAM+chSeGQqjeohu+yAB4tns3j3YPUGGYoM8/yHpbdPDcHXjjGB4YwwfOwrjU+T0TgKjXagYuZdhp1Wru7h4cPg4Pj9Qe6uI+3JrD3SkceGguA7uwP4NPvwqvLGH/Ity9CFLC0+fh6QYuXIBfH6tt1+evwmsdyDa8ZwhPR3imgasLfX8Yz4CFWl69axse7nssxOt6Pa6gErjWwddehjvw/2Xvz8MtO+/6TvTzDmva4xnr1Fyl0mzN8iQPYZANBEwgwSGhoTOQhM5zIWkuJDe5dDrP7dyHhnSem0AToB9CCOlAiAOhMR1sBo94km1ZsgZrKKlUqrnqzGePa3qH+8e7zqmSLEsW2MZ29lfP1j61h7XX8K717v37/r7fL0tL4TY0UF+E3jqYBagOh/0/D/SBVQVvLOBwTeiiOA5UYJNwai3H8Ml1eHwLHt0MVo1j4GMZVH0CCbQarn+v6cDNncCZfFbD6QimPfjzh4J92gkNB4dQjOA/fPHDa4YZZphhhhlmmGGGGWaY4asCfyrS45//83/OT/zET/CjP/qj/OzP/iwARVHwD/7BP+Bd73oXZVnybd/2bfziL/4iKysrr3LpCuEE0obsCZzBSxW6vpvWTqcSvIoAh3QVuArvFcbF4EO0tcCAFPhIgZQIL1EumCg57/AmsB5CmmApFEmiFJyzFGZCZaYopYm1QQqFMQnWJIEosY2NkK/wbhRID5NiRYLFY5TF4qhrRy0CyeKcpTSQEZHFCQINMkOoFniLd5vgJ3hhcbICqZBehEBroC9SEhkx9TUDP6bGkbQS5hf2UZQxA7PFlalmtHOZnScfxtiKvHyh+kEKyY37F3jjDUfIkpTVzz3MR599mrjbY+XAMkItkY9zirxACIXSGUJqWmlMp5NQ1zV3nTjKXCyxzu6FcS/0j5F2lzC5JdFDUj+kqgXDXOC9QEWCrC1BGJwY4X1FYSMm0xhnQdoc6Qrms5zj+9aZzwqytqDdleAdZqfATGvG0nB5VJJ7xzqKNRQ1njE1FU0Vc0+3EQpawF6GSgfPPI4I6JLTIieOavr9KVFsiZQnVlAaxbMbPdbGGRPabLCEIyacNhqlBL2OIMsE3XYrKH68CzkZrkYIj9Kh8/qWmw9w4y3XszXM+T/f+wAXtk4SyBPVrNmulmQ3kN1gASeCwkjIFqnI8HWbc8+tE/MsR48v0eoqsixGJwlJHKMkqCQUYjeHY549tYbwkkNLyywe6TGeGMbrjrKqsdEIGw1Jk4yjR25irrdEXQjKocRaGJYwHoGWjk5UESmHtFPMdIQxhmI0Id8x9ObaHDqwj3anzdraJa5cGYT1d56ihrIyjKZjrK1JVEysYvLxmJ3tDTa2Nth3aJ5bD++n021TGkdlPWkkWeqG4O9LY8vG5QlSCrptTTdN0E5SRBq8x7qKST5Fa8mB/RlZ2mV1fcTJ59YoKsN8VzHXVtTGMdw2lKVjvpfRWWzjEVxan7C2nbMw3+K2m1fo91J2BpatbUNtYOIjylowKmBr7Kmsp7Yl1pYIrxB1C2yEbnmiXlCNVSWYGtJEsH8xo5UK3JLHHvVUVc35c5dYXx9S5panTiqsj2h3Eo4dPEwch4O4M4ELmxUPn96iNJb7bpxjoROHa5eosbJiaSnm1rkukZZEWqH11ZDnrzV8eeeToOZQVQgXFh6SKjxmNeSdQGBYXWNbBqcg7znqFHChQClcY4VVg5eBKPEy/Dtpsg2iOpAbCCi64Htw0wr8jRAPw5yCsYB9bfirSzA18P7T8Aun4Dobc8Id4hY/B3Kd6WJOISv+qxvyfzMmx7P9IpvCEZ7fpub3qbkv1/yj8wlLQvBZKn6JkvkEfgQ4AjxYDvgl/xQXgQH1HhH/cvj+d/wkj51S8PzPvur9bf7Tb3P7PQf4ib/wBtxcG8q5UHW1XahOgO3TaRe021eY+k2QQ76QdGH16BJlK93LlUjdVdIjbwSee5ZTpnmeoOjQDvYNLnPfM+9i3+BppovbjPevgfekl1Pi7RhFl5hDeNHh1IG3cfxgn4tlyfnScvGa9ZAqpX/0HSzd9LcoBie5/Nn/L7ZY57Vcx4/zHSzVLdIzm8QX/jOmtUG+/3FsuoNTYXyJepHk4veit1/PmZUlNjs3MY0jWg4yG7ZHArmHjgPpRVDzRII6C5kU5b6QSXFDAX8vh40S/s35V0d6KBlz+NC3c/MNf4c0aXPyiXnOnYJ7XwMH3wppG7QO4z4KnDsI2O7AmV44Fw714Y4x6BiSTlAMDvWTXMw+QOLm6NjvJnHzLB2EA/cH0uNfPwW//n64oQc/dgfcs+SZLD7OTvLvkRIOTP8WC+ODVEowSgNR1LXQNzCewHsehfc+B2+4HpJvhMOdQHgczyEtgrWUFXC7gbdOIYrgM8fhyevgSAF3rcLhbXjqeTj7NGxmMPzzwCJc2ID//HFQm2DfAvYAHMngH9wI37wMH56DX1iESzHkr4f8Tjgm4L9X8Joi2FXdsAWjHBaeAc7B3BK8/k64ex7OdOGZPkwVrLWCIuzJ8/DhB+HiBG58Pdy4HELD/+gpmJ6E6V0weA3IPtwO3ORDzslf2YIDBQSmKHx3qFvBau/Ry/BLn4HTWzDyUDrYFPBrffgvK8AUeB7aE/iR6wIZtCnh9yL4aALfvg9+/LZgyRXHEK3BaAz/zy9+eH3V4Ms9p8wwwwwzzPDfBmbzyQwzzDDD1y7+xKTHgw8+yC/90i9x5513vuDxH/uxH+M973kPv/Vbv0W/3+fv/b2/x/d8z/fw8Y9//NV9gA/2F0ooRBMajguZDt435kNNaGsIxA7d9Xixl48dyt6Nj9UL4kzFXtBzeG3T8yqaypawCOGajv3m87xF4PE+JjhTiWt8CHZDk5twanxYN3+1d3+3JBOIj4YraQoaVzMmmrX2Itzt9f9LrkZd7/7lQ/aEsEgpUDJCqRihE4RKKWvPYDTCus9v+xZAHEV0Wxmx0tR5zjCv6GpNR0p0pEOmgnMgFFLHIaBVy709mMWaXivDOktlFM5DHMcIpaDpvA1B3j5kPexajMhd/4ZdNYREq92HgnmFwKAp0aIgEpJYKfAOKUuUqKiwxL7C4NA03b/4hjp4sdKDPWXP7jGQBLupYHLliYFEOBJZEauaRAuySKKlJ5YlEkEkItpaUCOpHVRNQq6UEiUFUkrEriqjSWtvYuBDcS2Lydp9pI5J03jv2F610bo68PfGULP/BB6ERAoNXlDkBZPRmOm4RTEtQxR2FAXCYzeLXYT8kNqEVBOkR0UeqWnWNYRjewlKC5I0otVKKbyjVg7bhIA7K4OtnGYvhB1n8c7irce7MCYjrYgihVbBMsr5EMhu7W7ofHN+uKBi8dbgnMU1qibVBL1L75DeIlEI4a4SScaHTlnnEc4jvAjXBRl2tzUOIUApQRIrlBJY7zDWhHNMqSAW8y6suwuf7wFTG6oqBNJLSdgGGV7rHBiCCsQ415yvITTe2ias3niwodiKDcHztfHUtSfSEiUlkZZ7p7jWEEUSGXz6qGuHcY42iiSJiaJwfJyH2nqmpaGoLZW5Or5lc6yTSNJtR2gVjpPzL7Zi+9rAl30+IXQuSxs6nPcu9f4a0Z4CG3ls4kOR+holBwAepJOoWoQCtrR7geaiOTR1DYUFoUDF4T6LYF8cjoqpYehACVhIoBOFqWS1gI4TVFIh0AgvEU1y9ra3nOOFKscYRUJIIh5h2MKx7j3GhvNx7OGyC6Z/dSXRlcAZz8gXDPBfdCjxvsUjiM1Xt5+fvlHRutJjZ3MDlfdpJxGynZJmfWK7hHA9KFfwtk/FZSbVJcbFNsrW9ImoceRYhIj4jiM/wl869o8okwinxN78s3vbnSERuzZX4RoSG4N2Hm8NtbPYagvyK4jpRXRnTGp3EA5aVUlcxmFOEHN4KYmrEbrYQVdDhHuhssaZMVce+SmuPPJT3PSdfwwinNQRii4ZfVJatSMxU3I1oCwvUYtNtNLEKua6z5wHHgkLOxNu/+SdI6yMcTLCeRHCuQHlJcLp5jMkXjTEXBKIuszDggFtoSV5dRACpVLiqIcgZjAoGFGyc0BT5SlRJJCJIHKgEcF5s8lAMzp8Y0k6Yfwiwji33gM1+BzvU/AWfCAeOn0QSZg+BjtQeljM4WgF47qm6yZ4D3PO0GrOj7IR6SrXaHRtCNi+PICtCVSOYERZgZyAKoL1VJYKuiIsP4pC1kjShlSGBK+shrSEaBqUIfG0ycTIAzFDCaYIt0UBnQT2d6HVCtkb2wrqNtg2GAdJCR0TVCnWBWVFUkI/h14OXQMdG7JdaMZsLUMweCWg3v08E1Q+JbDuYMvA1MOOBhUFW659HuYNLDah5kigHcbFpB1UZO0BFA4GdZNw1qiHNna/9DSi4paDNWCgYCgCF1L4kMdyMIN9BkoZ9rP82ptSviJzygwzzDDDDF//mM0nM8wwwwxf2/gTkR7j8Zgf+IEf4Jd/+Zf5yZ/8yb3HB4MBv/Irv8Jv/MZvcP/99wPwq7/6q9x666188pOf5L777vviP6SsyVTG8twhrDOUeY6pykBqONGQFAYh8kAu+DIoLpB4KQGFkmmwK8JjRUNIOIuzJhRKncL7KBSnBSAcogZBHQq+pg2ujRcOayxOQG0dlQ22U7oJRQcDMgE8wimEd0jvUM4ifENayCwUuEWwcBLe40SFEwbngx2P8B7lIqTvBELEuUbZIqmlpBSOkS+ZulD494SKnTMSW0myqMVNJw6zf3mRJ58fsz48i3WSUPq62iHsgcJptmxKKmO6aYtEx4x8TL66g1SabhrTzjKUVMRxsDsajYZcWduirmrGwyHa+oa8MDgclc8Zmwlj65laTeHaSC3o90Mg+ny/w1y3g6krhtMJJq842NXccChFSs+5wYQr4xrlK87mFRfzinioyTYDkeArgTOKopTsOEWFZ0jNiLzRRuwSCA6oA7mj2mRSYT0U1mK8pxZQCYETAiFbVCJByZJRFaFczUKvy3KnT1FbBtE6Gww43E/5tuMdWkmbT1+c8OmLY6yF0VhQFILx1OFkC6FjhBgibHDZL+twnKTytFoagcY4QWVdM16KUNgRoRMcQmHIe40HrM9BSFKtiCOFEmPK4XnG64Yr9Q5qJ6fVaXPdXcc5eMOB4HVPsDBbmG9z800ruKYSszPZBmBxqQ/0EPEcIq6IIk233UVpcL5mXI6pKwdO01IqpJzUNUVdoxNNpDKU9cQJZN0IoTU72xtMJtuMxxMgBi+p8oqqGCCFpZNlCJ/gS4uvDNpBv9sFoJiWPPSpR9FxhG5pVKrpZCnmwBKdLMVZWJjLAEE19qyez0EqtIpRWjAaW4ajEq0Vkpg810ymgiyK0UiiuI3XLZRyLOyrmrB1x05Z472g0+lwIp0jigTbGyWjnZqytlSlxXtPaQL5oWPN4eUUqSTOeJzxSCnJuoF0sBIqJXGAUhahLJHk8zM/hECoGBG16KQpy4t9lIqxMsIJhRSCNAlFtoWu4NiypqwFvbbECoHUkoW5lG47Iks0UgYSZjAeM57mjEZfWwbsX5H5BIgnwSYnmrLLhmKiUMzVhuYafDVPwzbd+U4GRYewgvbWPL2yj9UVeWcDGxW4KNjgTBx8eA0eGcPhDN62D/YlYWoQhCLkRy/DqR040YFvXoFMQdTU1Z2umfYvM0y2qbMJqjJoH9Ql1w4hAbyOA3w7N2Bw/B7P8hCXsallslwyjCXltoEtUCaivbHE3LjNvXnOj5gh6xg+SM3HGzXZy6F3AO5tvardzL/acERljqRCnD2LfHdN1uvwbbe9ibfesIwSFSTn8E7z8KnHee+jH6cYjjhydsI/5SZOMeF3ucIqllIpBmmMiiKMVIimk3/SEOVlQ0opH9QAiYUjW6vcfukUvh7zPv8sn/TnaBVrfDp/jA6bXKfu5NboLSQiJVsUxJkgj1pst5bIlebx6Tkeufhz7NRbXMpPfcHt3Hj631CNz+KBRznH/87vs6DmuGfxDdzYeyNX7JN8YvQUWztbvEHcyjeK1wL//vOWc/+Tv86T++/lyf33UkmNa7ZHVG0YHgGZIPIzqCZ8JCkgkpAMIduGtAoF/1cDZysuXf4AVbWNEGG/CqAzvIu7dt7O/FyX6A0px26NSGxQzAgPcyVcNwBksL0aJcFqLLUgnWL/5GZ0FaN8ykK1n8yE8yvXUGg4YOANE7g+gV7DViXlrfS3/wZOgrG3sJOIQEhNA5koI6jiEPKduHCcFw0cqOBADqMnHI8/YTFScMdBxS0nBGUNn30A8hgeeC08diu8RsM3t8J23H4c/nYXti186hw8ezaoGjq3B6fRUzU886GQh/P8MXhkAYjguy3slPCUhlMqXNvfH8FnFLT60I1BV3BAwD/dFxRdrWXYaEGZQAKBPA13HJqHv3gvjCroH4S+hc0Unn8dDK6HegVcFr6odzwsOZjzgWC5FpWApxM424ZiGX7gdigG8Mer8L7LUF3bW7EIvA7qCj44D4N+IIPeOoW3jeE1ZVAZ5RL+oAOfaAUy5WsJX6k5ZYYZZphhhq9vzOaTGWaYYYavffyJSI8f+ZEf4R3veAdvf/vbXzABPPTQQ9R1zdvf/va9x2655RaOHj3KAw888JITQFmWlOXVvtPhMDho+9qQJClRr4uxNTvmMraaBjLAKzwiWFcJQyjoV4SISxeCwIVGqjaRygKp4XKsN3hXYm3o3HZO453GC4dXoVhujQUf/Eu87YBPwJY4MQFsID1cjfQe6auQGYJAyCQUm6VFegfOobxFWIcgRskU3xTmLY1qRNTBwsgLnCNYb3mNJMZ7i6HC47BRhBGSCsHEV4z8tRUOgTMCW0nSKOW6oyvUtWFrfAn5bBa60Juw7mtReM3QJtQ6IUl6RGlKUdXk6yOEEEQHFpnvp0RakSUxSko2t3LOX7pAXVZETqK8bDrLDR5H5Uq8m5JbQeEUpW+RRYJeSxJpQb/bodvuUOYFw1pjJoJ9S4q3noiJI/jkFSg3a6Z5zaW1mjyv0R5iFzqahRIgJcYKCiexeAoMBcVu/3tzq4HgNxPLmCxyGOcpnMF6j0FSSYUTEqdblLIHooRaIqxBiH30Woco64Kh2mGLMa/pLvLtN7ZZ6fSYViUPXa6orGfS2NBPC4cXKagk5Ii4oHCoTLB5ShOP8BrhNdYJKhuUIIJgg6WFJ5LheHqb4L3GYqgJXjyJjIjjGCUnlKMrTKIatzWmOFPR6nRZ2DfPwRMHXiAa6fczer2MujZcurDB9vaILG2xuLBAHMXoWBDFQS2h4xAS76jJyzFVaUhkl0xGeC8wtcG4CiE0cZQhmw7epK0RomY43EJgMVaFCrAX1FWFtYY00XR7CUoKSjOlNCXKQ6/TQUeayWTK448+jcPRW+7Qnm/R73VoRQrT7aBExly3g3cwndSMtmuSdkR/n0bFip2BZTSskdIhhCUvHXUlSHVMIjVR1MGpHlp5uv0KrRzD0YSNzQF4wXK7x1zWo6hqtraHVHWN1A6lG9KjKKlrw9x8l/0LXdIkYTDyDIYeraE7J8kymNZgyhDJo5RDqhAF9GLSQxBIDxlltLOMI8thmVtjz/o4kF9xLMhS6HcEB+cVtYFOtkuoCOa6Cdc2d1vrGE2mrO/sfM2RHl/K+QS+8JwST5su70bVkfeCJQyEnA5osiGiq8qPXcLDC8BLsp0+7c1DWD0hmhtRJwVVD/IFyB18ahP+ryvw2j68MYMju2JECSaHBy/ABy/BNyzDW9ownwZSA8CpmqK/xrgbsqxUHQgR+SJmQiC4gxX+DvdSYTnFdkN6eKYrNZNW6M722yCtorW1SF8scZsfcD2GIQVbOB74IkiP7jLcdugVXvQi/LttT0gbAS5O4dIl+q0W+5LrePMJidI16EtAzeeufIZ/++H3oIYV/4u/ib/OCf6YDT7OFlfIqZRiHEfoKMLKsO1GBLLDEeygHMHWqGPC7fjOJq99/lGqYo3f4YN8gs9gCfOyRPI2eZxW9Dfoqj7pfE3UcWy1Ip5b6DJUhgef+Vk+dfo/UJsJ7mVUU1vPvatRc8LTXOJZLtOTy7xz/n7cwW/imZ2E3zzV5eJIIrmePye+g5ciPd506t1sJBkPHryLSoWvZBKQdQvGB0BoRNFBmqBtEYTxmIwh3QoZNepVWFtBILdX1z/B2sYn9x4TCA6sv5NzF++iXFBcN684eDRqVLbhNd0qBHE7CaMOTFJITMiw0U6ynJ9gaXJdUOo6CT7YOI0TKBXss3BXAQfLEEaOgKi6gWhwAqtgO5OMk6DEWMghrqFoh2UYGUiPjoW5JtNkuYDVZxzPfMjSWRLc+5cl+2+Fhx6D97wP1ix8+iB87tZAZoyzcD7e3IEbj8LOCJIPQvoYtG6Ffd8LagXMx+C5T0LVg/P74Mnj0Pbwdgu2ye4ZKJgI+IQOmRjEIDqwZOH/04IfPBTG50Yc1CGVCuN09/g6ASs9+JbXNG0aMuSBnI9B3gnDawTKgqDsmXOBLHrxF/dKhDyOz2RwYhG++yZYnIZvxH98pSE9djEH9KH28ICATwm4vYD/bRW+ecJebs6Wgg+34ZfnAxH8tYSvxG+UGWaYYYYZvv4xm09mmGGGGb728apJj3e96108/PDDPPjgg5/33JUrV4jjmLm5uRc8vrKywpUrV15yeT/90z/NP/tn/+zzHvcEc2uhLRIHQgSbpGDm03S+2ubmmsc13jd+N8LhRY0TEo/DNXSD9y7khPuQnhB+C7qG6HB4YZvXqWBNRGNJVQVyJVj6NPZDe5p/iSdqrLBEUJK4Xe+sUNx2InT8CxxagNr1VWHXskohhAQhwzJE2AuhBTOsk1TQ6rSRSYpWEXGU0s5atFsdBD7Y+2iFE02YdbN/dk20rm32kwIiJRo7okCKFFXB2vY2zgdFSl5OUUqSxhFKCi6trnJ5cwtvHUutPv00w1sJVY53HolF+QqFbHLjQ5G2Mg7nocin5MogvePAUoqY1ywuxeQ6oZQen7ZJOzU67pCKLq62uKrAlVOcswzLnLyuMD6YYIUjv2tWtUvu7NqRxGGEeE3tJMb7JoQ8BMMn0qOEx3hL7nbJM4NwNcOiZGM8paxLShPKguO65sxgyLhyFNWAxWhMLgUTE1F7FdrEnQ0yDQRCKKQUwRLMe4aFY+fygK1RzmhiEER7WyA8YXw31ma7x+haay7vHMbW1NZQu92A8DHD4jztssOkuLE5zlcr7N6FAo0zAq0i0iQhjSOiWKK1QGmBVIH02H2b1pKsFaG1QnuN8gprJa4G6124NTZPSkEcSwQKJXRToNHNeSiQSuOcJI4UgtCa7aXHKYuIIWm1EFGCFAneaJx3ZGlEpDVaxoH4cRqHx/gC76A0nqoGUTuqOpxLUkiyJG7s8Dz4GiU8SRzhvaMoDaN8SBwL9FywbfEu7CuPCCSUkRgbrgkIg2/sq7z3weJNBRu6qhYI4XE+2IIJ6SnKCuMcBoUSEVKDd+HoKS2oao8QQS3iHJjaYYxEiBghdPCqEoHUU8ojJJSlYzyGycSQTytqY5lMSkZpiZaSNFJoKRpru3D84kiTJQm2+tpJMv9SzyfwhecUfLDmKdPQfe4FqDrYXok6PG+TEEDuJXsZHqoGWYGsPVaVVO0xJiqo2pY6Bi8k0USTOViJDCfmHAc6gRR0zeeI5qR2PgRu+xqikSStBIec4/bUsz+GNIU68YxKWM9hp4YN82LTPthkypOsA44eJXejuB5P1lzldlHiOU3Bw35MK8rpt2pq4XCF3+MlXg57p/SrwAsMoRqLvs3xmB/7tV/hx37tV77g+36IR/ghHuGDK38ZsXUKzJRReYVLg0eJknnoHQI9jycoISQeaSHBkwnPcmaYkw43Ujy1uEheSNbFDVhREjnHQu3JnGRFzjM/2SDTFYXuUqQZO7HmSqwZKMGwsx+zdDvuyidefkP7N8LkAtRjFtAcJKEjMlyUcDqNuJhopkJQ41llwBP+7Esu5nG3zbR6ngPTz5JHXTbjw0x1DyN9Y7Vpkc4ha/YIDxSMoyU2ewfZMBqbQK8GU48oJudx9ouRfgQLz0imzGVHSHQXpducmT7LON5iobiBQ6YVSNtrJiXREIHKQlQFey3hCHZsLqg0wrEPh18251HsYLELRw7A0hxEHbCxwEcCryROhmJ7bEMOi2g+TzbHO1IwtwgrR8J7L2xBOYHTseD0cUG7K4grWF2H84NgJac87LfBcmqphHNbEI+BHjAH4xTOK9gkkBD7ZSBFD7Xg7iXotmB/BF0XSIfUhT4SvwNFBUSwvwckMBUwaGzWLo/g8Y0Q+L61BJUO37lUQ2BUzS6dlCFQvbLgu+B6sCahCF9z9+A9DIBLIlxTnk+CFVU1hXwQcoJOW7g8gb4Lp7ZJQM1D+yC4NLzWXCTkgPQBzV6WWCFhM4YrBloNqaSAQzXcUUJdwKNfxIj6asBX6jfKDDPMMMMMX9+YzSczzDDDDF8feFXljPPnz/OjP/qjvO997yNNvzR695/4iZ/gx3/8x/f+PRwOOXLkCD5OELFDxFO8sqAEjhSQyGa1PSM8E0L5IwOvwSm8dUCFUdVeccsqjxfBa78sAO+RcY7QtqkOVyE7oEliQGi8SPEqxpU1fjzF25paSayUeCVCYq1WeBfhTRfnJabOMUWJp8aLErA44al18LdOhCXCoZof+MIJhNAo2QYEThocNjwpg4LCeY93hjhOOb7vOCppM9dZZmXhCGmccHR5HiEtQkp0koDzqEQE6y9yNA5FoEAMofM8i2AuhST2JLJC4VjfvMQnHnuS8TQniSOSWCMIhVUhBEVZMs2nZHHKN971eo4uH2JSDBlujsFWRL6gzRAnNHGUoNIIYwybwxLhLOVgjakes3+py3fefzs3HN/H5Z2aU1cKitqRz3dZmq+Zj/q8pn0jc7rL1vbjrK1/guF0zIPPrfLclQGVc+TeYgBPQigjGEJZoCSYNczj0UxtROk0HotxwXIqlZ6lyCBwXKxzNgxB6cEAIWp21ixndnKcN4zyMQCntwf824efINURPSa8rj9mbGKeGC2zVnXAVfi6gBoEEqlboSAdabyQfObUDh987Al2RgXPn8uJ6OGpgHFYd68wToX97T0CG6g0ESofxhjG+RitNcPSkdWS1bWzPH/mGdrtjJvuP8Yb/Wub9JeAqoB8DN4rOmmPbtpCRYqkpZFKIq5RIYhGNtBqpxw6vIiznmqiqHJFWVnGlaWoa5yt8XWFEJI4EcRxxG5mTsjA0FirQwZJHKyvXOWpc4e1DqMtdTtHipjlhSMo2cYVDju2OOco9YBKjcP1RXSpbEZZTcnLrUAYVG2cSUkAP6yIYkmsIg4tzeNxGJ/jXDN+uz2s9Txx8gpPP7dGpx1z283LLC5kmNoSSYnzkmkpKcumsqdKtCqoa0lZhApfHGWkicaJmI1tj1KOOBakLUlVGy5v7DAtcvq9Niv75okihUgVILHGsz0KeSFVBWXhcc5jTYyUGqE0VkisAKkhzQTWetbWDXVtGU2mXNnYwZiacmwY7lSkccTyfIdWGpPEknYr5IbM93p0Wi2GrexLcm3+cuPLMZ/AF55T8KE7fe1QICGWNqC7AyoXRJsSLOwcc0wXAkmcTUMweTKAZBOkceT9TYYHRtjIMe3k1Bq66ykL57pkHr7j8Iibb5zSk9DToZi4mwmyayEEEI8Vc88lrGjBd6QVd+6v0QksLcGwBZ9eg9/egPUSLtYvTGlxeD7OeS4wZA7B25jy3aS0nGXJVFA7ZJOHsEHNv+USv8M6d80ZvvvGilbsGD3v8Of4fDblxajZ5Y+/cnjbO+D9j+PWNji1/kE2Js/Sah3mhlt+mOX2NxI7QdsGW6XMODLj6bdq7j02YGW+5GPLbX5q4a2sV46z6i04NWKpcHzrRs2RwnH7YI3Xn/kANsr4zHXfyPPLr+FcLPlYW7KpBOPrvwV38Bb47be+/Hre8w/h8Z9HbDzCG+nxdzmElsv8Tm+R39gXM/ERW5HA4fgEj3GWl/4R/P/2z/BNg23+/IX3s51dx3v2/z3Ox29gpGtsPAY/RlU1yaAJQ2+DjQTP9d7CJw/+HQayz9TBzQ6Gmw9z7smfIx+d/qJ3dy89yFuP/zCH+/dwZfsh3nXp39DKJa3tv8st08MoJcI3RUG4j8MVPyshmV7VV+7Bv/A+MtCZQMvDa2+Emw+GvJv2YiAddi3kBEEx0p422TsNuaNFIFXmUrjzjSDvBX8J3v0w2BxO3Sw5/Xci5ETQeUIQPwn7tuH4FOYjeEcJC1NYW4PfeghW14A7gSOBGNjswCiDGyK4gcAHfOdR+O+TkL/U6kPcNGYKYGqgeBwuPQn75uEvvAlOHICnNXwyhqKG338aPvgYuINQfSMwD/c4eIsLFld5cy04tQV/9CnYGkPnXmjfA1MNqy/KaKmBxyWcFbCYwOnFoCi58iSceQSKAraikDkyWIHX3w2uD+o2uO4mGE7h4tMweAi4Dnhzs6ENBho+Og+rPbh1DG/dDkqcvzwMtlfjEXz7Fz2i/uzwlfyNMsMMM8www9cvZvPJDDPMMMPXD14V6fHQQw+xtrbGvffeu/eYtZaPfOQj/PzP/zx/+Id/SFVV7OzsvID5Xl1dZf/+/S+5zCRJSJLk85+QCpRD7JmtQ+g9C53lAAgaw6jweIilpglFCM9ZLEhwMlhiOS9wtgk79wYp6tBx7+vg9d/AQ2hhJIQv29LgjQldiZFsLLRUICe8xBPjvcS5GmdNaB+W4IXHC4drKl6yWVu12/3rQ5FcCA1CBEWIBCF8aFPEgw0qEa2g2+2QdBZYnjvAkZUTpFFMOw7F/JAVIEP3viJ0iWL3ihLX1reUgFhBrDxKWISHvJxwZXONndHkZcdBr9WhtBBlLbQroQl2lt4SiQotPFLFSCUxBorKgqnRjFGs43qeI/szbr9pkfrslIfXPCPviJOUNIG5bB837LudlXSJK+0piXiK7ZEgu7CD9SGfw3jX6HTCcb961Hb7jFNAY73E+mtbVUMRJZVBGeIw5K4mZIDUCFGT2xxfCIICyCCAYVnzZLmNEpK7ezknegWpTInlHHuKI2fA2TBUZSAWZJzgpWIw3eSJs5sMRiXlxCCJGiVRUBsEFZNqtqhRgBDGBgKcc9Q+5MlUNgSp70xHnNs4TTvPGOeDvXDf3U21NoSkArSyiDgOKgQV86Iq1VVoLdGdBO9hGjYf42QThuowPtwUoBUoESpTnkYR5TRKBfVClMXISFFJR13U4XnpcZFBypg0a5PoBUQqkLHAW8vQCSbOEukUiLEuorKOaZWH09okeOsRxlFV4bxIkph2GuO9YVJOqG2NVpo0ibEOyqJifXWbqpeSH+5StyOccwghkAiMEdQOpPREkUUKi689xqqQkZJodJTgURRlODelFqQKhPVM8pLBKBAtWnpi1VixCUGJo6gdRe4oS890Eg5OrBVaBXIo6L8C8aR1UAPkhWMysYwnhvG4wtqKWBcoqalSRyfLUNKjVAicR0ASRSRRhKvrlz1/v1rw5ZhP4AvPKcJDHcO4G7rPFzaD/77KIRoKhAFRCYwKukHpQNegKpBFuKSbqKDoF5gI8lZQjrQ3FdEoIRJwLJnSXmo61qsQbAyNYsLvudWgakFcazIhOL7PcqBdYxIYZkGJsirhswWsvahhf5c0ucKYy4xZQfA9ZLyZiBoYWZiGywcABY6nCB58IoG3LgQ1S3WlWdhLkB72KRtayjfBWX9VpvIVwv2/8YN7fw+KCwyKC3TrE6zUm8wLiEQgPCIHLePp1JZ5X7PSzjk0N6V2czxc7uNSrfH6GGi4+DOSX33R5+xkP47zUwaJYisSXNaeDQX0DkP/8Cuv6If+zt6fK8S8nh6CPr8TJZzMBD4RCBmY5VW2WGXzJff3h9wOH7q4AxefBT4O/Dpv+Nsm5HaJCqiQ1iIrDyoQAk4JBvF+Ts2/gbFaworgWuRcidLtV7W/Y9XiQPc2rlt4MxvT53i2+BwRNZvlKhgfVrnJr2gEtQgP0W7qdkNO7JJ7u/C7/3PhWCE8yz1YXgxWVeMIKhlUrbZpAknrYJe1x/I1ZIjyEGtYWoHDCaxN4KkNGO4Inr9LcPY14NaBh0BcgNtLOGpCc8dxCzcaeCyH59bhkUsgThC+NojmXsOyCoqKGDjWhdtUeH6oIbchS6YWQZVhNyF/HsQEjk3gDhss1572sO3g3A6sXQxOj7hAaC9YeO3u6dScexsFPHMZrgxg/gaYl8HmavqCnRh2xxawJWBHQUvBvIOzNuyHasqelPcgMPDBUowe9FLwWxA9BOIM+BY0HSPQrEot4XISfhAsVMEuK3Nwogq3Yf6qhtSfGb6iv1FmmGGGGWb4usVsPplhhhlm+PrBqyI93va2t/H444+/4LEf/MEf5JZbbuEf/+N/zJEjR4iiiA984AO8853vBODkyZOcO3eON73pTa9y1XZjqRO8MHjKxnrGIWQoFjsvcD4DQhaGQOAIoeUQbEcECufBOd9YRjki3fzi27Wn8gp8hPAEeytpAdWEkNdIIRBxD68tOg7qCKTHe0ttKoSLCWHmEqkcKtr9xR4BAksgJYT3YZ0RSK8QUYRQMhTm3W4uRQi49l6AiQGP8QrnFWUlWV1dR2wNGayPGKwOiVQUQq6VIspi2vv6qCSi8jHLK3dS5FOmwwtU+dZeHcE7z/bmNs+fep4sTVheXqDdaeFqQxZl1AkoZ5HWYXHkzmLwRFFEmsS005Sy2mZz8zm2RkOeu3SJcZ5z0/F5Ds6t4AtNog3S2pCR4Sqcr6mZMmHM2sjxwEOfYm31GS5swpWLUDlFZ/8yraU51nau8KEr/zephVRu0pImUDfSIVWFFAZc0fiph/0ViIcIaBMqM2OuVvZ3q3s14Jg4z+UalFS02nOcmO+RZoqFxWMkiSJLQtaCNTU7axeZDnfYKQrO7exQ2ZJta3hm4imtpbJTEkDbMb7IcYVAmArhK7xXYCXOW2w9wuar2KLEm7oh62p2tUW7FmQ0ZmxhlDQGV16glCRSEukF28MNrDMMRztIJ9FEOCepLZjKB3IOT5V7bOWRUuB9U2Df9QwBxqOS8ThUrbROUVKjNcRJ+OS6cJjcQy3IRA8VJSRZTNZLQUBdFJiqITOcu1rk8gJvPdaVeOkxpaPODd45WnFCp7WCdwpbluTTTWIpSVOF9x4znpKXVaAGvUchaCcZWbIY6md1gncRSkuSOAqh4h6mdRWuDbEiliFIfZJXGOOQ1My1LWlUMByvgRwQxSlx1kEKgdIG4XM8NZWP8R5UGjOXxQghUSJGEO3JYoSwOOsoCjDO0GolSA1RHDMaeXLtSFNBHAu8EUgrQyB1DFkSxqIXoZgopGeQlyGIWEvQCoknjsEaidYZSbYMWDpZSjtLQmC7iKiNZDgWjKceKaGdhRyQ8muD8/gKzydQdkJnNwDN5bVqAZFnGgeivOp54jpY98RTiPPGjmZuz2mQdD0sxwIyBZtWDA+Ng5KwXYWCcK7pr7WISkXeK8j7OZmGt3RgeR7uqlssTA8T+RjjriDrVYT0L7AGejGWUdxHm2U0T1PwEHlQldEhosvlKuePt2quRBWPT5o4p2twZQIfPActDc/tBHLtpfCr/9evs6RfT1/eQuFWWXvkgVe9r7/U+L5v/quQHt8roEsP3hvODh5msPUorbTiTDVmrltxqbyFPzd+C0PR5anlhOfnXlqqUpmYs+sP8Kj9HOsail0yeI89/uLggWeY8htcATvh5OU/BC6xnzFvuu2tLHEPxJcgOc8v/9fHX2lxAKyf/BWG62vUq89h5IjqyhZlN9hK2TgoV0ejp7g4/nWGdHCisUvaOUldbn3xKw9M622eXPt9NqanObP9AJXNiUSwzKrboNRVWyYcu3FZ4QMbYmB3f5VRuA0LeOQ8XN6B6+bhDYcgU7B5HnZWPUbAVAtqBeUhmN4AkYYbLRzaJQZ2m0Iaa6jIw4E6HKKDGRy8EcopbHRhcwd8CRwK63RoCreMoBVBbz4oIKyAFQsnajhUwvXjQKCxAtwOcQt2nobpGbD7wOwLORzPaFiXsOThRNOLcscB+MHbQMzBmT5ciOCsgosCag2HjgeiZbgMp9sh8+OigI+pRjVyFtgIasw3Xhcs78r9UIpAeIyAqSf4bp0P153eYWivhCyX8WmohkHB4e7kKknkYX0JPtCHx2J4RsEFwCVw9Hq4PoXtg3A2Cd+Gjnk47KED7Ceocc4N4V2ng81Y/zB09sHkT5T+95XHV3pOmWGGGWaY4esTs/lkhhlmmOHrB6/qp0y32+X2229/wWPtdpvFxcW9x//23/7b/PiP/zgLCwv0ej3+/t//+7zpTW/6gqGzXwieCi9ivMiwwuDFKBivC/Ba4AV4I3G2jfDB8kohg7ZDhqByL+KgwMBjrMHhUKImSXLAB1sZBBCBa+Gdalp/C0AgnEO4EqRGpAuARKeGKLUYVzMqtqiqAik0karAS2Rk0LjgbW1jcBGGEnzRFIcVzkl8FCHiDjLSlJUht+NQBPUa4UOuh7fBusmJCC8iyqJmff0CeVUSi4RUtpBCI+kgREp3oc3xO/bTns8o6HDo2DdQ5GPOP/8hxvnVQojzntXLq/i1TbqdFtx6Ar9vAVfWdNIOkpi4KomrisJb1nyJ8ZY0iVno98kSTV6scvHKNle2pzxyapVBXrOw/2bm9h1HF5I0uoSqd7CmAleCKykYUbJDubXBe99/ko42ONfFmiVk3GKfuBvVa7O2dYn3P/JHjLYv8drjN/LNt96F9RohLSoqkaZCmHGQITSjJZRCEqBFaD8d8OLw9t3KzNAKJg4SHXPLSsqR5UUWl+a55fab6c/3WJlPOLCYUeclzzx0ktUzlzm1eYnxc59lczrlSuW5NADpLdoNaZETm0X8dIyLPIIcIUpwEm89zkpMsYWZnsNMC6xP8GgcFtOEwGt8EPYQ9CcOi0AhfagqxTImiWIkktXNy2wM1qkmY5RVxMR4pygteOOoyxJnLd44fOXxSuDawapNSIEXApxne3vKhfPbCKFpZfNEcYtWJuj3BUpANbHUY4v3grZapK0EaVfQWpI4LJvrhuk0KDCMCYoDJUCJEHBfTqbUtgrrUYQzrd+aY2GuR1nWXBpsMh5v0O5qWr0ELzzVeMQ4zwPpYT0aQavVodPrI4TH1BZnLc4rahvjvaC0FUNTIRV0+4okVeRTz3CroCotipLlrsHLku2dAdtjz9z8CitJCxlFRLJECUPlYFzHGB+z0M7YN9dCICgmgroUhHycEP5ga8fEhLDyXi9lTqdUhWJrO5BwC3OaflfgaoGyishJ0o6g1Q+ty9PaUFlLVRo2BwXGODr9mF4Wo5QgzQQKRRR3yDpdlIJICCIRMkiKUlBWgknhGYwdUsDBfZKleUH+KkON/6zwlZxPAIo5MBl7GQUmhaIb1BrT1OFksNfJiqDuSEcQTYMyotwXrjLpOmSrYFrgoqA4sK2KzRtqvIQy8aFjfRKxdHqRdJSweXyLab+kqx3fPRdEjN1xj5XqJuK6hTGOulzDiUB6fCFhxSFifogF7qXFr7HFU5SAQjNPzAqXih3+w+UBT4qK3L0ovBg4M4D/PAnbX5gvTHr8L//6p7jztv+J64/dzMbWWR5+/P941fv6S41/+Ff/AR94pM3TFwSRC7V26yqe3vgAn3nuF/G+JHrSISW8Nf4Ovq91FJWu8B/UAmfn45eMIy/qhKfO/x4fvvQEltDdDrwqwmMXDzHiaaZQCybPn8afizl+/ev44e/6R9x5+BbofQL67/+iSY/zn/mf2ZARpU4w2lPu3yZfvOqP5r1na/3TPHvhCXZMIPc94F2Frcevat1H5RU+de7foWRM7QoqM6El5jEtKOdCK4GsaJLjmxuEJyL2yAkPTBPYacOZGn7lFHziOfjOm+HEEdgXwZmTjmc+5jEeCq0wEobfAJs3Q9YKQd8LuwTLrj2Wh8SH505UcLgG2QH1WhAGbAR2o3n9jcD1oMcQbQbbrHP7YVUHdclRC2kF3zSF7x5AOwGOAQfgc5fg1z8Fl0aw8Q2wfgwGCbxPwkkJr7XwV2pYUfDWE/C9S/B0Aj+9BJ9KwIjwzaMVwz23wRtugDMattqhBeNZCWcliDHwOPAY3HMc/tpbYf8CPNOCkwK2fBBabQFcBv4YZAlL3wgHl6HcgfWPQn4WpveCfRvha0+DCxLeFYOSYUxXwFwG99wFt7wGno5gPQtEzG0O7m+E1KUMApCnNuHjnwuKluuX4PAy1F8bjolf8TllhhlmmGGGr0/M5pMZZphhhq8ffMn7t37mZ34GKSXvfOc7KcuSb/u2b+MXf/EXX/VyRNMx3nhENXmo4Uf/1ZrErmG6wHuP967p/udqceAF//Pshovv/qIWiL3PEcgmGPuq94/YLZfIZqG7gdONp4P3Cpoib8A16oPmR7u/5qOth7qxfKgtWAW1c1QuFOiFCPHK3okQEu7By9AZbqyjrmuqqmwK4x6xF+ruIPGMJiN8ZKhKjfedsJY6IolTEAIpJFKI4OwgwAtFUTmm05qyMmFdm/0igvFWs07hvUKE1AhTlxR5TVHkFFVFUdlQ+BZhP149ULuWU2ZP3VC7isF0QkWFFpJUtRFKIrxBenC2ZpQP2BpvMq0O4QVIJYkiTZpEeGERVdjPaRKTJQnOwbSA2oTPFARrr9021HAIdrU0AudBeBfsz5qQ+2Bn5VBSkiURkbO0U0EngzQmBL57j3GhIKDwaEzT7GrDDhW71mnNQW8UEGHbaiQ1AoVH7q3P1ZHqm/+LZgzuth1fTRr3zmPqEmNrbL1bfRJ79lLXelYI0TiwqeYo2GCtJqwPRKCpqasCISJc7PBN0Laz7IWbC0VQmkgNSJQKXbfhI2R44Z5fB3t6FZrz1buwz4RozjVCBg6evRDuPTs2KdCxIok1kVYI0bQvIwIBJDyR9njlQ7i6B+vCOGsuA2F8CgHeYIyhNgapBFkW4zAY7XHSooRCCYUknGMOGy4dPixMiCbk3UukFEgZDqlzNmSXEFRQ0gsiodFKYmRYJxxY4zEGrG2uWU0ujmh8jsJQCdcS48K5bZ3FeRPauRs/GSFASomUIbBdEuxgwrY3x6u51Fjb3F6QJP21jS/VfALsifu0uUosONWEjatmt5vwGnnNqelFeG53jO0uS3iCMkN7XBQyo6QPwefKgLQeaULY9q6osKsgjSDRHhF5LJ6x8GwbcEZiyxQVaVRdgy/gRdeI3avE7qNXqPibnORvcvKq4O0LoHawd8l4GaxtrbO2vUZ3fpX//O5X/8NtaX4fZRXGoXEFdT3GvyTtcBULCfzd20KWwlve/fnP98UckQjXOStCMfdf/E7nhS9qyL5huoEVa2ivSOqUrukxeInP9J0WZZEzLddf8HgrzmgnGa49x6icUJlXlk4VOIrdbawrqOGTT/w+3/LE73PlFy6Fi4eHtV/9m6S/VhM94Mjy//QFl2eKdWzUxauUPTlF87WkmYaIbUGvKjAGJu4qF/F5ECokf6sEbAn1GPzVgeK8JTcvtYd4aQs0vyfoo7l8huuQ8FiZ4+W0sfXqIIhBXM3tMI19k22+IkkProJyFM4nY8JyHcHyytOcO01hPvJNsLkKygxhg1qiHoGUkLZAp833rDqoGZQOyi1tg0oooultGYVrQVtCnMBcBIloCDUBEwm5CH8LwrK2ZbC/OpRAvw29KASfxx58DWKXHGqGggZ6HhZ8IEXqZp8qGvJVAy3wbdBRyBjPCMqLLle/qSoPUQmMwU+hckEVIiPot8C1QrB6ZcLnDHe/NuyOJxnCzH0TgSZl860i9OPgCaRHCYwq2Gj+7lqIi5Cd8vWCL+mcMsMMM8www3+zmM0nM8wwwwxfG/hTkx4f/vCHX/DvNE35hV/4BX7hF37hT7VcYQTCSHylwAQ7GeMqhNdokYQCqnV4a3He40wd8hSkQsoIISQIG2yxvEc4g/Th17PzTSYIGiEUwku0cojdH+VEAMHWCnDSYNUE76CsLLZ0gMSLBbRUeG+pbI33jsrk1LYEJ8AIvIPaWqz1WA9TazHeIQuP3h4hpMA4h7GhE16pUGQNBeim6CsUQkiMC3ZaEApfrtGpCFkjZMG0LDlzaoiOwdkUazKkFMx3Uw4s3U0SpXQ7c0QqoqUlLSWoq5rV1TVOrw7ZKcZsjIYYW5M5S2otRkCkFEJopJeUucFXhi1T47cNW7mjroI9WDm1DNcGTGtN5Rw+jfF+AtNtgmnDFjDAAiMyctost1vsW1CkqWSxo+ijsD5C+wxoE8Ut2r0WQiiOHjkErRYbgy0mZ6a40vH619zCN9x9J8NJzh9+8iGeOXeBiIq0oQ1C0HmMxVFQNCQHgMBYy4XNywymA7LVlGeunCZNE24+epg7rr8OTUUxfIw6Pk+lxpRlSVmEwvLVEn6NxqIiiej0odvF5RZflqHIXQciJcWxL/UkFjZqT2EaekMIZJNRE0zEJF5keHRYfx+qq9ZZahNs2WQV2sGtcZjGegxvEd4E26d+3HSze3Ae5yAvPeOtCqUFSSZBOMrpNq68iNYp7aRPp9NDyFCsdALijiLryoZMCNtrDJSDhmwwCXHkcB6kDkSSdKEoJyTEQqMi3xTrFQJJXiVMLoDSmt7cMov7FiCSIWBGeI4eNRw7YnBWUuWaytTYiSUvDVoL5vuKTjsOxR083lqSSKCJEBKUk1AK6rxkPN6kqg3tXod+fw4pQWmPlB4dtYjjHt4LRpMx0zwPpKDWJEIiyoJi4lBSoVVC1I6Y5DVbox2qOlgYCQ9xrImjOWIZo/EkUSB6ysKzWVmkFESRQscC4w2DbdPQgBorNHXlcU7ivKeuKvJxjveCvMioq4hpZdke1Qjh6aRt2mkrqFtqMA6iSLCyLBtyRDAYwejVNXp/VeHLNZ8AZJshmDwuAokhBVgN0kB/syEwmngo4aFuBSshQSAyAEw7KD+cBq+b8V6HnAV8k/9RQ1TU1O0tXKxwcUE2dXs8sI2g6O1g48eobcQHJpt8aMezIPv8hcl93BQdojt5DmU+zTXu/lyg5pfZYhnF05RMX4FI+JPCmAnnzr+bwfCpP9H7/6f/x//KY4/DlStwefNBTl74LxTVy1suSQNz5xX7dyRNafgFuPRft9hQXbZ1Qo1g+jJqjGfqp/g/x79MVi8Rb30v37n+LfzHl3id+POvQzz8Ubgm81tLxTfd/Ebecec3sT0d8lsPvpdHLzz9xW34F8A/+c3/GeLLkFyg6w33SceJN3r48Mu/Txw9iL7vG9BpRLT6ANHGI+A8ouHn3+Cg3YGNGn6vgAe/EDeTLsCN3wvL98D6Z+HZ34J8/Qu8uPlsD7qEZBQUAy+wXWsIwioJ50chYKDACENbfYxFPkiSzvFDt34337lyK4eXIMug1JDeK1k+6IkNLOQhv+M5A+b3AicT3wYcCwX4zSiQW/tqyGxYJydDUb/SMG6F+eiZ03DqZCAh3nQHHN4H6314di60WywbuGEN9HYYZznwmUtw4eNBAfFth+HuJVjO4JveDJsepkeDpVMb+EtlIEyuKPhIFEjSnTRYY1ngB4oQlv7YOfjIU5CXcEoFtcbcEnzrHdCdg4s6KD9IYf4uaB+Ceg7eMx/IiP0C9jvoiGAzNaWx2PpzUBdwYQCn/wDqCCa3g70XblmGNwiwY/jE0/DUBWCZENTev3o8p8DDEs54GDekS8vCs6dg52ToFaobgmezA+Wbw99rA5j8YSBavlbx5ZxTZphhhhlm+G8Hs/lkhhlmmOFrE1+9Tr0NaSBkYCJc0wkthQTbhJm7ED7unaU2Od7WaJUQR1FQMexmPniHcCb8svMet9cCpwGFFAKtgsbDC5refa62A0uDcxYnPUXpKCqHlAmtdBEtOxg/xthNnK8wrgz5HFbgrcJbGTq4beg+HDvPNLSMh1bEayAI9V8lw9PXhuDKprv7qqGTb5QeDiENQgmKumZ0eYhzV5ebpW0O3HI3hw8cp5312Ld4kDhKiWJFFEu2t3Y4efYTnDm7TsWEnGmjyGi6iaVEySh0m3tBXVq88IzyCYiCkVFYk+GJqAvHZDAhNxG19/hIh/ZixtfcJjg0OW0gZSmNmVtUtDPJfCbpIhmjUSRAitIpSZYSRRH7lpcgbSG15LmLZ6hqyc1Hj/Jd3/AWVre2eezUszxzrkJhyAh5EJ4IRwuDoaLC7u1BgfOW9eEm68ONsI/PgpKSweatyEqQJTXd+DRZdBYjHLWxTaf01ZZvhQmjSIHI2pB18PUIV0hwIZrcO0ciPPNN9MuOpcntCFZQu/2cu9HsXoRtd1ikCDkk1ldg6nC8TdWoVCQWjfXh3cIbtIpIWhEquloVNLVneKVgNDToKASTC+moijHebCBlmyyq6aQC46FsBDJpW9Lq7AlYgMBf5duB+BEiQivfbElQOQhjmnZdQCoUDqUidJSCV2ytanY2IGspFvf3mV9QFBYmJnzmYg/6HZiODRfOTZlUlqq2WCeII8lcT5MmCqRHVhaBRysRiDkE0iqoBaZ05MWI2tR0Fw+xOH8QrSSZlmgpqA2UJdTGsl2OGY1KIi1pZxBpBbWnLixOK7JME0cRk7JmWIzIyxLtBMoJ0iSh35tDOIXyjlgZnPSUhaeuIIolvQWFSgTl1JOPqiACihRCK0ztgt0dDmNqyiLHeUlZSWojqKuSfDoJeSc9Db4VSJPdbu8E5voCKWAyhmkO+YvCr2cISIchnDepA2kx7UKVhcDx1jB0fVdZY+UiArlhk0B4RHko/JqsiVpqzoddBYcy4fmkscQCg8mGmBb4qPHxb0gPp8HGE8ru80wdPHgh2E5d51p84+AO+txBiwjBo1xLemxgeQ9D4POb77+UcK5kbf3jrK1/4k/0/u//rr9FX8HTJyFSbU5f+f1XJj0stNcli+uKlyI9tj45YnBzynh/wkTAuvr8ZezivD3LBXuOll3gHaN7uG/wtpcmPd5wE5zvv4D0UFJx95Fb+etv/ktc3F7lk6cf+VOTHv/uI7/a/OVZ7oC4D+QtvDLpsbKIevM96HaC+vhp1BWBMB5Zh7F2s4db02Dd9KR5GdIj7sKRt8GJvwin3w1n/+AVSQ8IBF6UB6XgNWLDPWLQxIH4mEhYj6EWlsPuc3Ttb9FPDnLw2OvhwK0UMYxjqBXEN8DczYJ2DddvQz8H+1l4/qNhmdECiGOhAL+tYCqhfY16ydEofSTkERQSntqCjz8BB+bh5uvhsIKdDJ7phlybhStwaAvGozDOKgEnN+DT27CYwS0a7s6g34U7r4NJCs/EcFJB28FbKriuhvfG8JtJUEEciuFmYM7C/QX0Dbz3PDz/KVidwPkY1iK4+yj8d0fglhZ8jhBATgSHr4eF6+BxCf9Fw6aA+x1cb4OV18FG0VLNwXQ+qFg33geXHwR3CLgbxHHYb+Ebq6DEOPs8PPUYcAK4gReQHiXwbPO1JQN6QGrh4iU4+dlrhD8CuBd4SzjO2++D7c8AszllhhlmmGGGGWaYYYYZZvgaxFcv6QEE26pQ3BPOI6xDSh+0/o35uWj4CyUETgiE2LVTClZMSNm4TVm8s41fT1Mx8cEPZDc2OtgqiL2njLE4F2yzPLaxNBEoH5ZZlAVCeqAMVjSoJl9EBocDF4gX630weBK8fG+uABEFqx9hgSrkJGiCrUPT4LmnVWicfxpTLtfYe72wHGadZTwesrm1zjSdUteGSMdoLVCRZDQcM85HGAxRktJuH0Bq6CYRnUgHuyapacyM0M3n9ZiSiYKO0fgio/ARUna5uGooDIyHFlM4pPX0UoWwitJqShvjvcQ5A5R0u/Ncd+J6uq02Ol1GxQntPKHdatGZdkiSGKl800pd432FpwIfLKmsqammFXVR4awBLN12xg1L+0i1xrgWxmVMqinPb5XUZXXN3hOBzAkMGd4F1dBoOuHyxhrdFnQO9Gh3ryPLJkixRijIBY1HMHMSyOZ+19dCNAqO4JsU/C7mehk3Xn+M7XHB4PyE9Y2SPZ8QIZoxtnvsSrwA4W2j5vFEwhOJXSumJucjSoiyFr1+lziO8N5TG4OZ2lBA0pooigJBgUApgTUVO5tTvK9xDvpzy8RxRpwkobhlG9skPGXpENIFNYoMdlNVGcgfaz1GBN1MswkoIYLSKgKEI9EJQgZiUYgI7yRKGbwqcEJSVBWTXDGtHDu5bWxSNKVVVIWnDr5mxJFAK4HWEqUDMWN9SNhwNDZDIaEd52zYBuuCvYkROBu8iZz1lHVFjcd6ifEK6y1CCCKp0VKiVYxS4aJiDDjnEK6gVpYqL1FOEKHQSjY3jbMukIHeE4KlIdJBaaSjYBF3rbue94HElAK0EiRxhHMCrT1S7B6rYJnnlEep5sIhwDYWZs4ZnHcUFeyMw/u8iRBC7xFUM7wIIkwbsuE9dd0oPmwgIoxo8gGaWVG6a7rLY8K5pxsbLK4SD9I1lycX3usb0mTXEisET4eMjYsFbJfQj+FwK2TgHCPlzT5hjoRLrPJxYnbY4h56XI/AMcVTMALOEEKOvzJ4ZWrl4MIbef0NP8Lvfvqv7z22/74wv/5393+YSb3FwvzdtHrHYQmYB1lAchnUFNopdFuwKD0HRY3G8MeV4GcHmueM5htb7+BbO9/DME1RStGxUNYbFPnpl16hvTX3vOWW+7j1ukMcOij4V3/lUX770V/k3M5J/tp938L/69v+KpNiI6zMNShNxU+99//gp9770jkmb8oUsncE2T3AR099cQHv/po5WUhFt7vA0lKbcDRfBsog4jHEdZAP+TCe6iQ8LRXoXWXey9kPDU7De975Ra3rS6GWMEoCaZG5QATsum1pD4mFbgFGSFJzCGFej/CLCDuHF7CVwxM7UAhBdx46c5AC6HBetebh8NFAUAwLePJMUHrsqKC8nbaCwkqJcJ5FJigJvQrn3mIfDl8HS13Q7UCI7ExDhk3uIXYw6MC5MVyMA5ky14JjHVhohc8fdGDYgq0oKDy8CIRGx0HLQeJCTghbYX68XMHjNSxYkDks1VDmsHwYVAn5EMoJMIFTF4P11HgB9u0Lx+yAgXkHYwl3AzviGqKjgrVNKCbQ7cDiYojsOD4Pw2Ngl8I1BWA5fI3Ba+gswb5jYFegjrn63ZHwnXFMY4lF2P+KoHrxguDZtUhgRJbDsZEKeovQOQ5uCpf+xCNohhlmmGGGGWaYYYYZZpjhzwZftaSHF7vEgcdbj6wdunZIbRGRQUiFED545TuJcsEeB+lxIg+FQ5mhlMbicb7GuhohU4RqEQiVEu+q3QSOUOBC4r3EOsdwUlOUhkhBEvnmR3dG4lJq59gar5MbSztJmGtlaJngvUFgsT5YVhnrqfDBG5rQpfiFaklCgmpJokRSFw5nQgE3IXg8h5I+e4VmJ0AIj8Ih93IpXrjwuq64cPEMq2uXUVKjVRwK8g1pZK1nMgp+4AfmD3DzTTfTbrdZWplnbqkfXlY4hPFELic1EwQGJUqUqMmNZqNoUdSKixcUH/tMQVHDeuHIDcxnjmMLMZFMWZu0WZsUWGepqinWWY4du4fv/M7vY6G/wKX1KWvbBS6acnDlAEJI5vo9VOKQ0mEZU7sBxo7wFOALivGY7dVtBsMBdZEDFccOH+ad97+ZxV6PSanJS83F9VV+9xNDhpdG7FagBYJEp8RRhLWWospxznFpfZXxZMTSXIdjh1/HoSPHuTw+jY4+DGwTygVRQ304QtqFwPtAygjhUULiqcGPEK7mphP7uPmWG9gclWy950Ge3Ti1O9Ab7sPidjucfQ0NceabbJVIxHQIgbw5Eoun25tn5dB+FhYX6HQ7OG8p84rtjSmVscx1uyzMzQEi5JRkiu2NCadOPk1ZTLnh5qPceMvdKB2hRCuoowooGuukqi5RwxwpFZFuIaWmnFRMizyQHj4kpygpSbRACYlKFDqJURraPUhSMJWgnAhM7RmkaxCvUwnYGsRMSsnWsOTS+hTjPd2lLq25FolM6Os+SZrQa0sW+xKlBF4KcgOVFdReYfBoD9IF4shUFd4YirxmOpXURlFVEm8FtTGMBgNMWSLTBNXJ8M36t+MMrRVZ0kJphXUl5bTAO8ewnGCNxeGJvSSWCTqO0HGEFOFcHVc5UaRJkgQpJWnWdEgLAiNkwFsfck4Iai6tg6okTTIgPOe8w3kL5OioRksHRuCcQCiB8b6x0xviXMWwsOQbFiEky7155ttd1DVe7jO8EMKCLkLBFB+srpwMVla75EYdh8tjXAb1h4mgCFMGyoByzRVkN3OgDMsEKDMwcw3ZocK9JMwtGyX85iY8sAGv78PfOgwHI8l3+EXezn4u4vhPPMAv8cfcR5cf4zjzeEpOU3OBp4CfJ3SMf7VgY/gUH3/qp1/yuQ88/GMsLr2em2/9H0n6C/BNwH2QXoSVd3tap+H6A3DHCUEnqtmvz5PKdY6ttXjnZ/exMcgQ7QM83zmEVZoo1hwqBeX659h+9mdecd3+t7/2U/SX99OZ1xxePcFa9mOcW5tww4kJuvM0iHVQm69qe39yOSG75ztIbvsrvPanvulVvRcgijKOH72Hu++4AXgF32c9gc4F6MSIeIjwHqMh74YxqWqIKpiWYKZ8edgwD2MNT8yFUO+jFdxQhiaMSEBsIa2hU4C3mqj6ZkR1ewibaB0ADZ+7Av/qczCo4ftfC991W6ixuxTyGPbdBN+0BOMc/uhZePg9kLpAJGQCevfC0TdBooPyJKuDxVQ3Ct+F7roJFo5DoiDrwDCCZy7Cex+FdQvt10H2mkCkbHSgSuF7DsMP3Qi9FphDcHoRtjScasFUwaKFm+pA8Cwb6FhIL4B8BKoxfKIO6poVA988gaM1mFvh7rcHUUT7Y9B6DMwq/OZHgAS+4W74jvtCDsj+GvoWbpJwhw7ZIVsRbEewOYaPfALOPA9vugm+783BumvhFnjt0XCNKvqBlJ/zjd1XCofvgtfdAkUCW73wfbEHzBHW6UngiodYwAKBDCkl7GjwfeDNwGECw5KG52+5A26+LmSm/MY//DKMrxlmmGGGGWaYYYYZZphhhi8jvopJj90/rt6Ea2yhdtue8XtOQyEkWBD65S3eCxSu8eZpCorOBe/7xt7Ked/YDO123BM6/r3HudA1X1YGr4PtVCBY2OvcruqSvK6IlQDfQnjZdHo3BWsfur93gzl3yZUvCAFCCWQkESaskG+yKXTz3mvrmb5ZaYFH+BB//eImb+8d03yCyPOrHwJBJRNSeBF0ESolSRPm5xbpdrss7ltmfmUBYT1yYhG1I7ETMjNEehu8L4ShMBqVt8hrxeVLUza2phS1JycUJGTiaUWCVEsGpUJJ3eRUWKCi1c44sP8oi/NLTOpLDKbrpIkmSzNaaYs4DkoPITxSOqSwSGkRwiGExxlLldfURbA6E3jaWcqBfcusLMwzKSTTUlH7iiSO9/aLJFinKSnRMnQma6VwQlCZip1xTRQJvGiTpAeI4h2E0NfsQ7n3l2A34ePqUd4VegQiqqbbSZlbPkA2LOi0Wy886HujYneEXPWa8I2vSNAXyOYYh4qt1jGtVotWq4XWYb9a6yiKiqIyZHGGNc0pQJNhYAyT0YjpZIL3gnZ3HqUUtm5OLXFNSLYJOSFSelzkUNJT14HMc85hvcY2CiDpBVIE4kNriYoEaSpJW6FT2FcgvENph9AFCKiMxZeSaV4wHA0xDmyqqCJFKxJ02qEzOoolrZZESChNCJG3fm9PX92LHpy1WGOw1mGtwFqJd416y3mqsqbOS7SS4JKg0BICLSVK6uamcLYOHdTWUxYVdVkhtULHMUIotNJEOgKCgsQZE6z3kkYHpAQ6ashJF/bpC04/sXsLKhpE6Nj2FgQGKQsUV5Ueu693u8Z2vsb5itpYJrlBCMl824bXzUiPl4TfHdsNNyzqRq8VhyKq1YGocDJcU60HHBgVMgS8CEHI2jZTUtN5L3wISobQZV7GLyQ9lAtkycTD2RKenMK+BCY2fOaKiJiXbWKXs+43eJRtbuMwN3GYQyimxBQICjzZn93ue0lUZsjGaPiSz22PPkdv4Wbm+if4zd++Hn77Cy/H/HIBugOqR6a6HDx9mLZpsdVOWW9lWCkQMhTDZTmg3n7yFdftziN3wByILoxMi8W5E0xKR7v1LFKfB7WD1oZIRdT2lcPKAW5NJJ2FFdqHb33F1wqCXaK4RnoV65gsm6PdXnnlD5MmVPm1AWH2pgmrr1qsSRGuhf5LfM5v7mzywz/1w/zwT/0wq095RhFsx7Dkw3VK+zCupQflPLp2YD2iXIJyOcgyEkDDqITTG7BVwXgSVBORDOtsJCRdmE8gmcD0KTizBj3TWMIB5Q1Xr/eyOZdUo8CSMthS1Uk4l7ULhP2ohMsbcMUGdYjMCPKGBFQE7TZcvwidFpztwnoGIxWySXIZFBw9F3IvtA3XZT8BLoMfwqaFTQfjGm4YhWD0/vWwtBKuF4tt2AB2Sji9HoiUu49Br4R5oF8326jCapUy5IAMCK6n65tw/iK8ZjGQSj0PtgvpXCAzJjIoY6QPVmBGQzYHCyoY4pWERpauhzkHUxFIqj2FDuHfUhJ2XEpQYh26OgaEh04flnpQvfQpPsMMM8wwwwwzzDDDDDPM8FWNr1rSA2FxgPEa4x21gFrZIOWvCrwQ1EZS1Y010e6vYiHwQoIQKOWRssI5S1l4rBWUwlAwCaVjbxDehYBjFQrVwgmkC4XKohDYWlBbQe6DDVKkLVFUIBV0RELsEhKtEdLghcDLkLSBFEgZfqRrAWnzI9VyNZfj8zbZCeJckBqQdUgLdYDBMmwiuK/N9MAbQOFJ8WQETUnB1aI5BFsqjUCza44lheD4wQMcO7ifSKe02wtEUYsodiTpJXBw7vQpnjypQ3Bq5RAWenGbxbRHrBXduZSs3aasBTs5lJVD1RX75IRce9ZjjVOSUk24OLxCJCbkxYS4niCdpXJhe4rcsbZeUU6nnHz0NE899TTDMgc83YUe3bku3V6HONLc0V3gJgOnzl1ka2DY2hnSbs9TWovzkuX2QU4sWGze4o8/8wyddsqhfQvsX5wDP2oUFLCcznO0sx8pBFvFFqNqyNJcj1tuuJ1up8OkLBjnOWkcMZ3kPPnUSS6cu4yrICJpbMZqPFAjKBHU3oVqkDUoqVBxhvcRTgLO4FxGPiqZjnNMXQE1HokToXoV8mea9vNrCvkiaI+ofM3IBrLFC4VCkedTLlw+z7SeUJictBMTuQhiQW0d7TQjyQTGODa3t9neGlPXY5aO9IAW/eU2UoViotShyJGmMBc2g8nUMZ0ahPR4VwVrOSBppYFEiSWysW/SIlAyOhVEqUQp0FEzAhXIGJQULO7rErcOhHgdq8AJrB8yNQbrPXMLXbr9ORIdM5fFJCpYWk3qRjDR2G9ZGzJMFJ440qSxoqocV9am7Aym1LUjTTqkiaDVSUk6ElNJ5CQBH7Zhbi5GAANXMq5rpBS4SgQfFyK0iLHCYFCUCBIdk3V76EijtERpibNQ5gbjLK6cUpkxUgpavS5Z1Ar7STU1wEyj4gTvwFiHqRrVky1wzlIUgjwPeSutliGOQx6Rjhubu6RGxwXgUJHAO02cxrTawcqv04mQiUPUL2ui998sJvPwTA6fHQSLmbvacKwfiq8uOPiRDdqkow471vKxesQZW+4RIr5ReuzmeOwS88qE0GcIHdGmIT1cU4gWPrxnWMO5JqLjfAHvXoOVyPMGNeR1Ry+wU9XUWwXkYBlTyTMMkXzCD3jEe84BV76SO+xPif/x/h9Gtlvo/m+94msfOKswehErNdNBwpW4S9mLiKxnZTChUILn+gkbiWZdh0LvK+Hk4zXtsiCrKy4P13jq9IOcGm9w3ZzAaEmna/nWO76ZpfiN/Ms/+pdf1Db9+0HN6y4/wJ2nX3kFDi4s8s2vuZ2Vfp/GGxOl4NT5ET/3u1+cNRY4EA5pPKoEkUNnEhSjUoLQkJrQg/DlQubgujHsK4PqIa5D4dzoQBaW6RqD5AmsnzI3uoG50Y2BmK8BAzdG8DePQm7hDb3GHotQ6LcNSas12Ay6t8GBZVis4bYC5j0cORrUHXFDYABsazjbhlKFPI2FSXONlc39EojXhXyMNyyGZYkI/M3APjiwHz50AJI4hKzHzeGMCcRoxwUlRpnDH52B1U14fA0GBWFiPgEcgukInvpceP61El47CctMj8JxAasDaJ2GrQnYc/CpByCKwnY7AZ1F2H89RFnIL+k5GDcqGiRUKth8oeAxHXJGDCGXxDWEa1CcBlXHPgdrAgYCBh6GF2H9bFCvjU4Ai8HSapWgNhwdBe8Iie39Fx53A5wTjcL4izjfZphhhhlmmGGGGWaYYYYZvtrwVUt6eGlwAqyPAukhoVIO5x11aXAeyjyizEOWgcUHskGAEDKUjaUNagDvMBU4Jxhaw4apcUCCJEYipEfrxmPfCrQJ7xdeILzESokxOhQz2xaVThFC08u6eJGEkHRbN6oOF8gPH7I5pAs/YNPG3qp8mR+PwkE8FaQINCGs3QnIfclkN+R679UOT8jwcEQEA6yc4HHx4oD0CEWToo0lkoJbjh7j/je8nk6rzfK+A7TbXS6tP8lTpz/IYLTD6ZM7PH5qGLr/CT+sV+Zu4Oi+u2hlbQ4fy1iKO1SlZTCpqUuLMgUH1IiphLydUqSaIh9ybnAJYYZ0vKXtQyLFtNmSydRy+XLFIJrw+IMn+fTHPorqpbRu2s/c0jxzC3P053t0soyl+SP0Oos8tnyaM5emXFrfoNtdpLAO6xX7O0exi312ppv8/sefQCjLt77xBpb7x/Fuh13KaKW1xBtX7kQhePTKwzw3XuVQ7yB/8c+9leNHDnNxe5uzG5sUec7WpYs8cu4il7dGuFIQhb5MHCUeKInwSGpn8bZGOBNUAGkL7zxWZmF8OstkWDAZTjFV2RyjCCebioZ34HYprV11h0U1mR6VqylxKDQt2SKSmslkwtpklWE+IK+nZN1grdSda4V8CRHUF9OpYWNjkzPPr9FbUBy5YY5WR7HQ7yB0OGdkU6DNdseqgSq3VEVIaDamQipLEie02i2UErR6kLZC7o4zofM9iiBKrioZdjdHxCHfYl+nz0HdxVQw2haUOYgowugch2Nfv898ZxGlJHGsUVKEzta6GftNdoL3DkkZskOihHZLhWD6wZhzl3ZoJy0WunPEsabdzch6grJQyFEIVM+6CcvzCUJ4TOkp8hKcxJUS7zVCO3TsQEoMmtxLIh3T6vdDzkygrDDGUhSG2lpsOaWuh0GREQlku4WSkKpQYIoThYoynHXsbBcU04rKFAzybWpTMRoqBgNFFAkOrsTM9UJge5SEylYUV+iYRq3WqH9kglKt0E2uAWUR9bWk5wy7GC/Cp67AL+8Eq5z/4TAszDXd6haUFbS3eiw9v5+JrXi/r/lDAptxrfLwJS/h1yh5/Be4xnsPZXM9PVPAr1+ClvZMj21z6OiAzRyqwkEOTgwo5ZgB8AfO8ms+dG6XX6J98ZXAP/0L/4Rz49/js5v/4hVf++HnFLlappJL4VKYSEQE122OOb49Zqwln+0pTqWazTiox14Jn3uwYuXMgMXLI87Zx3nU/hJPiie5+9id2OhN9LtL/MXXfQfvuOnWL5r0+N+3S/7W+Q+xT3/8FV97bGmZH7r/W7jr2PHGTtJxcWuT//V3fpvfe/ihV/6wEFYEeITxqCLYqKU7ICpwbXA9SH3Ikfhyoe3gxtFVpemuyqJsN0X56ApnO39AKdY5od9B310XiOMcqOG2CK6/LpCL8VwgLypCkb9oKvZKBLKwfzccieBADfdMYclCt4J2Fc7T3fNvK4LPdGCk4Y3bcP04LEOkgIZ0H4jrIBFwfwnfPw3Evr89qEY+3YL3dsO19A013NhMvc2llo6DeQMXJ/A7J+GDp4MCo8gJvk83AX8OxqvwyCCQTkcknBjBUguOXweTG+HsGeAyXNyC8nn4yEUoFDyfwUYMJ26E+6+DpSRs65KFcfOdERVInW0FhYYHNHxA8xImptAF3m7hhIOJCO+54kCcBfFh8G2wHfZIj4uE5bvrgWOEjY5euEwDPAeceZlr2gwzzDDDDDPMMMMMM8www1czvmpJj+ANZPGu8XxpvESc9dTGYx3UxlFbF4qu+EB77BVbgwJECIfzntp5nIPaeYzzhL56H0Kom0APIWgUI/4a26Im68MFo6HKepR1wRpK+hCl3FhLITzeCbyXjXe/2I1s2CuUSa5aVL24H1vQFOCaKnSqNU5AbWrKF9UxlYBIiSYywOMwOB8K5C9eprjWI6y5KeGIpSMSFukKhFFIW6K8Q+GJhCURBq9AyNBJ3kqglXiSyFFVU3aGUFWW8aSmrixKWfoLbWIfCueapkbtmn0qJEKJUMtprKiMsYzyAmMkk7KiNIbIOoSQwWbIecoyZIjsDIeUlWB7OKCsCoypmRYlO5OcoqjJ65LaVZSmZFIUIA3DSc7OOGc0LTA27ETrLKWtkYTxYL2kNjApKkbTgsm0ZFpUFEXFcFIwGk8ZFxXWXbtvw/ENEfce4x3W1lhbBzrKX1Ohaf70BDujXqvF/vk5SgOjQmBC4j27JlniBf/tnQ1XrZyEaOyzfCBLvMc7j3PN0XZuj/TwMpB9QkikCvtUSh2suoTa2xrXLEpw1fIi0pI4CmeJkE1LrvdYa0EInJN4L7DGURYG5zzOK6QOoeeN4CrsBhnupQp2TkqB0qHDV2uN1hHO22tC5R3WWrwPaTV1s7nCij3Sw3kPwlHWBlWUlGWFtY1HlwjnhRTBo8hah3PhPc43QeiN+52UkijW2EpQViXWOOLMEdzQJFIopIzCfpMSKSXeWoxxWOuRUqJ1IK+cU0E5o0QTSh7C0PdOSynCtUSA1gLrBUoqrNQoLdBRCGyXUuyRRu6aYbR78fA+qD+UhCgKO9risC4QwzN8PryEqMkCSHQocKoaKhesd5yFonIUteGSs2zjGX+Z1sV6mDZWQevGc6G2rBoomkM3wXMRQwZseBjy+fPFq8FRWuRYtqkwL2+y+KdG8a8/inB9hN2mZQZ0qsErvuef/qeXZzHe+7ZV4ijMKV0fccj3qZhnQM6Q4iXfcwVB7CWJU5QiRukesZyjqCTn1wcs/A+vTMa8GKs1/PQTJT/9xEuzDO/j5/hFfpt38xGMtQzznJ3JZI/02J5MGUwKhtNXZine9f5neNf7n2H6X74fYyqcCpdssSvalE2Xv4clFMdQnOVLL/mwKlhZCULHf6UC6dFcikFoFC0UbaQIrKyTUDcFeuWhrUJTCQIw4XuOVI22UTQWTRIyDQtRsDEb1MEW0QAqOABSEZY5ksHKKnVhGbZ5/1AFUmGqYTmCngjKxbQO59yggtLCdgKbzZBbm0JvClUMZTeovkoRPmMkYGRgWAYVyUIXVBpIBJJA1Ix1ICcmMthjxTqoSjoRpHHYf5WEqYNhBYWEgYShD2R+0H1CUcB4DPk4kDfJAqhO4I9Uo+x48VlSV0GNooBxHPJMJs3yrCCcMLvWXs10r3xwHhOEY1ntZk+9GOJqhtxLM70zzDDDDDPMMMMMM8wwwwxf3fiqJT2cqZB+jLAFojaIskYUmrp2bE0slWUvKDz8tvPX/CAUe5p/LwUWT+4dBiiCPiJ47eMxBIN2Y3cLCCI81mSDNBXWJuQAoqknqnzowhdTBCVxDGkrFKOxGm8SrK0pfY3BNhkJ4Vdj4n34kU7o2r0250MBkZTEQhJnCa25Ll5KruyAG1bYxsDKAf1McrCrEEKyOh6zNc3BW4Sv9w7q1dKWaYrmFtd8Yp6vMdx6klxJNs4HUqLyBklKV2pesyJZiSOk1qSdLiqKWeru4+BcRmUcnzr1GA8+sY61nroOyQ6vu/n1vOmtb2ZaeiafPcP0/GbwwPAZYNFJhEojvLPo6RhjarYmUx69eJo4yrhiC8xcF93JUDJFu4ThdsHJZy/hXM1zlz/K6s4OO6MxZy5eIS9rhjsbXF7boaprLqyeY2e8TWlKxvUIITxPnF1lUnlG0ylbw1Acuzzd4KOXP4tAsp1PGNHlmY2c//i+B2i3MqZVxaQosNZQTCbUZUVR14zqinpvH4bxU2KoEUzMlOF0mzg2tKQklSF/QzqL8B6EQghNu51x/713ccvxGzl9ZZU/ePARVncGTSulQiBIhSBCYPBUPhArCo0iCdkTSqIkZGgi0aIXt8BETMbgrSGfTHC1RacpUZZhjKQ3N8cxJFJBPQFXCLqRhl6wcptMQydrrKGVgIgEc/Mt0jjGOsgrhbGCoirZHGwjBJRVi9Y0ZTLJuXR5g7KsWdzXZ+XAAlpL0lQSRcHmLdJN0cxCXjUESxweT3xMNuljjaUqPTt2CEi8D4QL2kJkAYGoIoTVOBw1BofDmQm2LjA2kBBz3YxYC5QaA4JiahlsWeraM8lrisqiJhK5HaG1IIrb7FtK2dyacvK5c+wMSvavzHE4W0RISZJ0QGZkSYJWCiFgPCwYb09QWtJZSOnNZ1jTwtQ9ENDuZrTicI2aTgrq2jbMTyA02plieUlT1gnxNKOyjvm+o1oO6rQksigVSME6d+FcViEzxXtHVVVYY+gqSacFUgiGY8t0WjEafy3pAb6CEHDvHMwfDwXT2wpYOAtP1vCbE7hsPMlkQOorRjieIn+lJf6pUXv4xDpcyiE3cHYSHn/Mw7+0YYJ+yr9CFtQXgX/BXXyaLX6dM6x9mfUi55/+56R5hKoVlOc5Ntn5Uy/zxHd1uf50RLEOS/UBbvDfiuQiv8ujvIfHMS9BCf3WgZjXqzles9hhm5Qb1Y+xKLa5MvwMP/kfP/SnXqeXwv+P3+BpzuDxnF5b5ef+4PeYb7ebZz2TsuSxc2df1TLPPvhJ9HALuegRBsQ8CNtkxVhoG8X3qgW+gS7fx+kv+TZtdGChDAqNUQwbKcEKTgRFQmIPcmjyXXhK5stDCK8oNZzvwk4ECwUcGUMSYrxgM+Rq9PpgExgr2GhCya+rQ1j6mTV418OwNoB7boL7bgvZO2clbElYqeG2YVBkRBLWerCq4L9m8IyGfR7+WhEyuY84uBLBpSH80SNwYQvWboWLrwv78dKj0H0G5g/BdfdBex6ejuGSgo0C1hvC/vgK3H9HyBBx+0MvzpqFDwo4r+FUG35zCZZbcF8JtzVEy8kEnmgFe9OKQEaMgzdmOI4+3J99Gh5/BCYxRMfh+D1hH43bQdm0IuD1zTGRhHW6cBZOPRZImkfugnPXwVgEknTPhqtD+HK5Pzy24OGW/z97/x1kWXbfd4KfY657Jn1m+ar2vhtoeIAgKBACQUqkRBlqOJSG1Ix2ZDZWq13NSiNNhGZijLQrShMxcrETM6JCgRC1MqMhKQoCCYIACRANj0Z3o72rLl+Vle7Za47ZP373ZWY1qrshGKohvW/Fq8x85ppzzz33vt/3fL/flvh4UcHLfOfjyxxzzDHHHHPMMcccc8wxx5sRb17SIziZS+9KcA7VBJQzuBrG08DUxTbS16OQiWyHdybSToRvPZCnSIHJzV6Ddpb+bIWzH+FQrPRMPyKzqomg6/aBx1Kh0eRRowqLURoVDMol+AAuqn2jqRhb+58o3z8dB9sym0SnkBl9VimK1LLS76CMZjQds6M0Ks6SJKBIFBt9iwZ2yxoXHLOJfTeqAyK01liBgCegoqJuBpTjS1TBM97ao55WpL0VitWTZDbn2ELDkcJj0oze6ipJXrBcLHCknzAYV/z2Yxd45oWn99vbGsu73vYWbn/7bUzGgUdf3qI4u4MKBhNTUCkhKQhFjnYNumowLjKpKs7tbpImBXuhIXRyYpahdYKJhsm44kozZDId8dnHvsKTr7y4v06Foiojg5HB+Zrrg/OMq+2D15Xm4tYeo6mmdhXjqRyN3XrIbj1GSgcyZXM6bLj65Iv7PeNwGUBijQM39h7BjE6qQs20HjOtFMYmGGPQRGybyaFUCtqSpSn3nTnF3adTFp8v+OwTj0EsETdxK6ZFSrczMRXVfsFTo7FoNEYrUUooQ6JSCpOC11Ql+CYw3KlwdU3a1eSxADRF0cEajWsck0mNi+BqLSqpCHUNZSUnUtGRWbhFN6VIUpoG1BiqGsqqZDwZE6MQMbiEvb2Kixd2GU+mOAx5b5E0hai0hD9byBJRkLhGZqeiZDasUWBLS6oKGuXxjcO5khAUjbfEqNCpx2SNKF/qAuUCnkjVnqHj0YTJaAeFEBSdPMNoh1IlMUJTG6YjQ+MiVe2pfWRSe/QkkFrNei9jodDsDWuuD7a5cn2PrKc4FlcwWmGtHI3UGgkrJ1KXDYOdKWlhWdro0uvnhACukQJnnomagDY8fVo2xKjxwWKtpt/N6fUSEgfe5DROehOxIYZA05Stcii2IfORpAtRKXyEyjlc01BEj0kVWiv80FNWjrqe21vdDErBmQLuMKAbKK5DOoRxBZ8fwHMOoGwfvzsIEV4YyeMwLgAXvouVyD/GKRI0v8yF7znpsX3pY3RHEkStPax9F8QH6w/nbGzB5iXF3X6JH+F+MjZ4jmt8nCe5mQ7mK0uWRWVZ7IJXCxyxp1nB88Tz1/n8Ey9/5xt1E/w6X9j//fpwwG888dh3vMytl1+iU0LRZRYNAkA6lXE5U5p36i4Fy/z0d7y2b8Ywb0O3I0xT2C4ABatOiJckLNHxD6MjZE6uW87AVh+udIARHHeI/GACTEFnMlEEKwqJUTtj5Xgty93ahS89D09sQrkG6wWEQnItLmh49xB+ZFtssK71YbMDFyz8ZiE2UD9Zw8+MYT3CtoU9C+dq+K1X4OkLwArCsjRw/jzwuJAt/Ydl30YGLlshbUatzG5tEd55DxxdEuLCe3jZw1cVnNdwNYMv9WCjA3d6yEq557ti4WyKdNFZN43sWzW2YkS2rsBLj0FYA/NOWH0Aiijqrxgls+O29tibdhn1Frz8pKhHzp+R7diHBtbbxyF0gVsQQmgHOMuc9JhjjjnmmGOOOeaYY445/sPEm5f0UFak9cHjQsBFjYsWHxU++paOaLPLkRl0h0vSEbFQUGGWZCGz7mJQKDGQQuPR32QHdUAVzJYPEPbDpeM+qeCJMtM8alSY2RG51srCoWPABPBKEbQsOUSxpgFIUSRAmhuyQkranSrDOotzsD0aEzWMa4+PKWmScHR5mSLP6RfQ64EPDrN3HdgFDr68xht+n1E8B7ZdwXsa12AAOyMZUksMJcHp1lZMQwi4akSMJRMf2PWWadmwkjvuPWJAaZRJsTZhKfWMdzYZjiPT6YiyKclwFLlCR8NEQVlJq/UKTS9PWEoC3emIxAUWigKOHCdJLTbvgDU0CoYRShXJF46wfsSJKkIZFJoiWybJF9ChoZ8eJ2n6BySS0nTzPmnWI1YT1GREW13mgG6SnjA7+gfPHxSOI9DJDCv9BGtgd1yyN4r7ZARojOmS532KvIeNDTG6G/qPih5FCWhCVBAii13L2+86xfG1Hhc2R5y7NiKGiIsWpQwesFrIP0OKJcO0oa/WgFYGoxNyk+NrxWjYoIiY1GISRVpYslQK5hU13k+JUZMmGQqNVgnOS6j2tGyYTDy+0RCEWLHRYKNmWnquXp8wnjiC8iRpjjaKrEjIck03pGysLzItczpFh7pWhAhp4tEonI40VUCpSAxt+q2SgqhSoIJuz4aA1hZ0EPuUKNZcRsv+KiQnR0VPDJ7Y1ITo6WaGXr7UWqIVaJ1AdCgSlAJrOjJNOEZirIhBiD+jwMxIBA/aJhxZXyFNc1YXC1JdobVDpzk+sySJwgeIjUInls5iRpJqjJUpzM7BtJyNE0KQhKAoCvmsc4q6kZwV1wTGY4eLbf6PQqzRmgqloEgNxhhc6smtIQTQnQSlU3z0OJWhlQGnmQwrtFLE2pEosayb4+aYBYwrpTCuIKkSbONQYcp3ZiD15oECNhbhyCKc9gv8xe33EacrRHZv0EN+rxBV+5hZIGl49gNQ51BnIv4bdcX+aHEH1jbhzkdef5mf+uKnuHz9PuAoihLFNTRXUAx5dcn2+Kk/wl33/TcUr1whS/s8l3XxSlFqcEqxtXIL4ZaPwHP/7HvWBt8KlnI4swiPXX399y2fugWubBPqgdxaeCmUNwk0fTBNwE4maG8l0utbgFKGte6dLHdvpfZjrg2eZFJvcYw17uQkC4vrPPxf/hnu+oN/iKfOwe4KdFqSohtEnVBMIa9hOFWc3YXKQbUI5RJEKzZRRLg2hs9dgKSCMz042YVhgKevwI6HZA3S43Jd27HgFKgevOc0nFyAJQVPvwCmgN4RuG9B6vg7BcQEqkTiKFY8vLeEVQ0nt+HJy5A1km8xMHD+Oowmsv+9KLndmYWjR2D5Dlg7Bvco6DZwxYjSo07h7uNCiNx5FNIE6ggXN+HKNlzehuFY9rMT4KiH1SAWW+cyKBfgoTOwsCB5LOlErLwu92E3g84ynL8A1zeFuFi4H+pFIYwmgBqAuQq5h/4aLK9IDsolBRMFLMG9t7djWh8IQtJcUC11294MdQLcW8FRB0cj3B9lwsHZDHQqbyuQdqyRdc+JkDnmmGOOOeaYY4455pjj+x1vWtLD6ZQYHLVzNM5TeUMVcurY4KiF4FAHAYt1OJg8N1NXpF6RBtVaSYm9lYpiEyRmQhW2fffsC55qba1mBWuZ868Ibbi0JrRJDuDan2k0aGcwWhEpibZBuYj2HuMhWIW3mgBC2ESZ09+NGqsUq8sZa8dzcJrqcoYbGEZVycVrm9TRU/mcij6LnWXef9/bueXIEUa+YqeZMK6mpNtfA3ZvIIEOF9xnezIr8Sto8zAmZDah21sgMSnOO8pmj0hARY2Klug85fAaSjsatcRQS9H4toWKY/cm6CQn6SyhbU6nX7N57jl2hoHtnWsMqiFLSUW/b0l0ymQa2RvXZEnk5FrKQseylnnWd65hbZdi9QTLZzYIocE3I4JvGEfPbsgJusviifu4a+00CotSomBooqeOEmPf5Zj4JtEW0xFyJGLRw13M3gimM8VGKzcQ2ufVva/9eUChrfQT3nV3n26mefzsgG9MYmtZlgGWNF1laeEYS4sd/HiTMB1Li6uEgEKpCtH9KGJoiD7j1FrGz/3Iu6hcw6987hv8i9/6OmUdmMYOVcwxOiGzGqUiJnbRsYM1gSwtSRJPqjIK3aOfLlGPNNcuTSm6huWNgixXpIklSyVzYzQYU1U7JKZHt1jC6AxtNNNGcll2dgcMByWJsezaHKM13U5OJ8/Y3at56vkrXN8ec/T4MrfeukGWW/pdQ5Er8l6XXi/DN5FhpdmdaLSOqODwacAFT+1qINLrdOh1OpJ3EcTnXbsEFQ0asNZjEsmm8LHBe09iLFkyIxwbkVpVFbEcELxj7egaR48fQylNU2mCUzgfqJrWWq6xhMYQvSP6QPCiGkm1ItGKxitGFdisy3333I5vPDaOSeIAtEF1DaQpPiiaRuzA0iJjrWvQJpBkDSFUVJVid2AIXuF6GcGn2ESxvNTBJpFyEhiNvJBQpWcyduhEYTuSA+KrknIyJkk064uLLPZzYoyEEIkBRo1iVGs8Hm0NTXTEMrBzRSqd1kYKA17PSY/XQhQHQrQzpOUq3cESWRiiw2W+v2LCXxtaw30n4UMPwsbUcvyrG4QLt7QJJckbfv47RdDCawYjBEeTSLtbB3kJdSK5CM6IPZP9Fpr9b/zvf4MHT/9ljq8cBQYYnsFwAcU1Xl2effjqNv/3wRNk+SYfffBufvWOLkG1Ew7QVLf8AO7kPf/eSY/Ti/CfPPjGpMfpd72f7a9+jb3dpyXQ3IEOMOnAqAfae6Laxmd73zLpYXXG3Ud/H28785+zPXmJ3372/81ke4u3cid/jj9Mtz7C5x+/l49pRX4Gjn0EuqvwYA3vmkLuINuGZAyXrsBvPgGXJvDyB+ClO2DFwo8HsVF66jp89svgJvDH3wk/cQZe2oa//1V49Aq8+y3wY0egl0mOhgbyo/B/fS/oKfwfZ+GjvwndDvyJ98F775B7vLOLsi9HPKx7uCXAnx1DcPD5F+D/+BJsjSVnY6iFlNlrRVxHgAcirKbw4fvgrceRS3lr//gbBXzJyDp/9C1w1x3gc2gKmHj40tPwqS9D2cBe61O66uF+B4se9lL4fAJJCj/VlT7evw6LlyV349dvgyc2YOs8fPlLUI3g7gfh7j8IowxeWhC11/nL8PRvQaeGD70b7u8LGfMZKwHjbzkNv38JOhFMVxRsL2j41xYuH8rhWPHwJ3fgw2MZAYooJMuLK/CpRK7DR5FA9G0k6NwxxxxzzDHHHHPMMcccc8zx/Y03LekR0W3gsASQ+6gIUWbJz8yHlJZw5kjEu4APkZmLQkS+PJu47yLQzuFXKHRb/D/4VqhuWPerlRIHIdK86n0B9q2v5AOSFDJbpmqfj0rtLycQQUGiDIkWK6tekRAbTbCGoAwxQNnUVNHjyQgYjE1Z7i9xZGkdW0+ZTDNqlaLtLJYy3rD9N9te1f4mxVQJvNbGYJNUsioaR4wBhQUSYnTgGqKqaSjxTFEx0rGBbk9jEkPSTdE2xZtANR1TlZHG1fgg6adJaki1RZUO5zyJiaQGilSTKY9tSmy0WA1JnuIdhAaIAR+gCoYI2LSHsbYlPTqApgwVIVT7B0EBWiuMEZLK+UjjQacVaVqQpTnBVzg/i/M9rPQ43Eo3moRZo0RRUBgyaw59TtpJqwRrM6zNiEoTYtw/GnGW5o2HqKRNoyVPNMtLiwQCS72iDd2OLa2m0UiAvFGgMaJQUqrdP7BKk2iLUYa68gwHJVGlrOhE1DJWY42sWqkgDx0lONwkaC0qkBAknNx7J4ql4DEasjSKTVsIlHXDtKrwPmCThDSxGAvaRLSSxJHgoYqROAmEIMHQ3kecC5SlKFbyJOw38cymRaHQyhC0HDttApGA0V76pxZVhpIdQemIUkGqW8GTWE1R5CilsUigrXYBFzQqRAKGEDUxSp9QStQWRkvYOIiqRBlNr1ugIoSqxk8jKI82EZUADuqWUTXWkCSgtUebGoWErnsPwWuxpfJRwsktpInGJWBNEGK2CTgXxKosykgUY2hDzxWJUWTJQdB8BJqJFO6UBqstaIVzNVUjpJ9RCm1A/weiWPiu49CAHqOiCZbKpTiSm47vbxYkMuIRgGY/Uei1oYAiheUuLGhFtJoJFidaMQo0DRFH5D51G/+D+bP8gH4r/4pP8fPqo5yrLn1nGzxTeqgDkmlGeuggDzX7KZdCzr4NBmswXpD3OiN2lP/ns4Z/+qTl4sVL3LY2gRXa6+uUPv/2m1bdQbNWN9xW73Hn3p+Eq8AnD14v/syUkPYwvSXin75I/Nxfg2f/GfHkh4g/8P+BlfsglyDp2RilALRYZQJyQ+FAXfs69lN/GX1eQssbL9d9rROUsu35LGTvzZAaWCleuxl/+ofv42/9mQ+SL6SYrEM7fAmikEvOtraBicMnjlcehskyTA189Cz8by9Jkf6bD5EiS5ZYKE7S+AlWZ2375RxlhU5YJY4KtjahWIQ8Qm1l/EuDKA+sA1NDKGG4BzsTuFpLvkWdiGWiCfKZa2OoJzAKrTpDSYD4+QHcOZXItBjlea+k/55cgG4O/XMwGEJ0UFSw5mFXwXUt93rLUTJ60iA2XFkDz0xhsAfXx/K+XSMTIYwWtUbPwBqwoUR9cqcRZcSel8BxNEwMZBHWOnBrS8hc01A6GIzh0nW5/0tSCWDPtLw/iaLCqDUs5nBcwYIXMmR5LITI2iosrcNgG/YmMB5In++uQ0jAtn2vrmA8FOtJV0ERwGoJK98DQg5LVpQrBrnfvcaB/dVsSkcvwEkHd1UHXWikJeS9E+U4LSKPikOh83PMMcccc8wxxxxzzDHHHN/HeNOSHiHQ2itZQnRUrmbclNReCoWZtqwfO8rG8ePUVcW5s6+wu7MLHJAe7lU2VVJ68KBkaqmPft/ESLWF71mGhzx3iCRoVR2+LbkcJhZ8jEx9wEbQTUQ7ERyoIPSKisi3epDppkCW5xxZXaeTZXR7kZRIUGCziOtG0hr6TpFFxQhNgyZqgyksdiGhU0eWsoiZQJamKDSziHbFjWWWmfHWfj4JCqUN1mYYY/EB6sbhfCRgZW+VbW3AUnQo0K1VkFJ7QttoB1iC1jRBoTwEBV4rfNRo2yPNLQu9lJPrisJU7LgrhL0ruCZS70TqMZSdnPHidQhDzr+yxdVzj5KHyLrz5DESiyVCd42gNC4EQrRt4bsGpUizhF6nS93UXLt6ldFoyMpqnxO3bGCt4fzFHa5e3qWXKj709odYLhQvvnKex556hmnZ4GNKaMvEfj/PJRzqRXL8B6OKp89uk1m4slUSY42UFLK2fxhCzAgxB5VitKSrRGVaci1FhVR6lMqIJiUQqWuPDw6cJyXg8DhdElQQK54g1kcoj1a1kBZKk5KQakNqIYaGrz76JM9cjNx2xwZ/ZOOdrK2viUWVBm0My6tLFN0MozNSa6WoYcQqJVWajdUey4timWSURSlNllqSBGyW8uCD64wnCywtdVlb0xgdKauK3b2G1Br6nRxrNKuJIu1oyfxQFo2h2XMMr03xzrOQZRSdiFKK6KSp0xyWFuUUaXTAK0eiIO8mKBKCdwTvpCqmDBiNSSxpnqB9oHFddnYiWgdMjKgYqaYVw90RzgWqYGiCEEbdwrDQzektJCwuSSi8i2LHRWwttyJUqqBhVazonILJBJskLC8btG4rc0F+L4oCm6RoBc6D94o8NRijiDEynDToylNXQlpEICsMnW6CJ1D7hsZFDJqFokOSGKy5cWhWQJ601nRB0UsTQjBMy8hg3OBDIOpA6SNlmJMeN4MGktZiZlJ5Pl7v8iIVL1Jx/U06rzlH88Ms804WuUTFr3Gd82+gSAkRXrgCH/86dJoJj+w+xgKXUUz4adapWeS32eIL7KAXUvKHjtHduJV3JB/kz6fL/KWP/tff0TYbf4jQiPJ3VC0tr+S13hj8VIqto0V5viyk8DsjTXTUPGjfwh/P34lPj5LaW2kUeJUDGzdd93/Nce4nsMyTN339L3/tn3Bu7V6eO/4OSt9jcPzHmWRnKJduYy9fwwFFDR0nM+IXgxT83XGoHoSQQngWwouwald49zt/lKMP3sqjrzzLJ5/6EpVTHDv2IVZX3s54/AoXLv0a0+nlm27LpSH82+depyHrNdh7B8rn6MkLGCdylShDD/kYkhFoB91NTbqn0d2ISz0+ATO7UbkJfGh4+fpv4UPJpN5id/IKAE9zll/gV+mwwcSlHK/PsDpRvG0HVvtwspH2sV5ynyhgfQM++BbYa+D6KmwOoKfhrQ0c89DPYO1+8A28bVmyLk4Z+BO3ww+tw21H4IGJ9JPLHdhO29ukRpQL9x6Dn3ovJAkc2YCphtFV2HkamhJOn4TucQk0twAJ3HUEfvbtsNnAvy3gc7moGO4GlhU8cBTeXbVkRJDcj7M78JsvwtWJBJlfSEXdoU5CbwmyAD0PwxqWEWJstYAfug1OLsH4FHy2ECLKKeHGcg2rSj6br0GeAgbKLnQj5Kug3wO6hFPH4b0VhBrur2Hg4RsFfOLd0AQIJ4XQn92zRuCcgt8wMJv2oiNsKhgoGe8e9PB2J9knZ15FfqURPjCWn1rBErKcz+dwsQu1YY455phjjjnmmGOOOeaY4/sab17SI0YIihgtMURq1zBpxrioMVpjteX48RPc9/BbGQ9HjHZ2Ge/s3jALVsLCX/WtX3lUa//iwoyDUPv/QhuOrJCix2xOf9gnPQ4mwO1bRcXINHhMVGR1JKlmy9QopVAhopzYS0Xx2CDLco4cP8pirwd+ivITHB6blZjgyFSkN4EmKCoUASOkRych6ScUjWapNlgLeZrub406RNgcWHbptvAuwe8R0NqSGCnOhxBpgseHSMSKZZgykpsRNdp30NGjdAV6T2bZaw/K4JU54HPa7BIXDcb2SLOChX6Hk+sFHVvy4t4OnhG+8TQ7UKGYrqSMOlsEpzl79SrPbW+zgqFnuhQ6Ia7eij+aEUxKg8VhQAeiqVAaenmHtc4Kk8mY87svc/3KNRYzw9HlgixPuXTuGltXt1g4uswH3/4wD956hE898lXOv3SZ3XpMHRJcNG0+y4zwOhxaLu06GJc8c7ZGEahjbPuNZWYiFtF4cgI5Smcok0CkTY1RopyJM9LDtrZbjqYqZYawc2RRSI+gSoJu5FjETDJjTCC2RE+CJUUJ6ZEofKz52qNPcnF4jne/525+9PffQyc/KAoaNMsrS0hZY9Y7oCkjzRSs1vTWukidvSVZDr2zt5iwsr4mfyvJQ3AuMJmU7O1N6XZTlpcTikKTdWEpKLxXTKeauobhtmK0OaUuG44f75F3ZLl1Cd5Blsns1RBh6D0T70isZqHISK1hMiwZ7zWEEEFZotZYq0jzHtoramfY3glYA900kNlINZ0y3NmlrhtKbam0oUhTlvvL9IqczoJmYUlspaaNzN5V7YzXGelRkxODJ1RDYjWln0SWlnOyVFNPFM1YFEXdjiXJQOuACwHvoxCGURHwjCYVPjaEYPDeYLSm1zN0i4SybigHJU3j6CQJ3TwnSTSJ+eahOU8kEF6qwvL6YBTw3lA7xcQHyhCo5qTHTaGC+Orne7BXBT5e7/Ir7LYU52tUh/89I0fzIVb505zgUYY8wehbJj1evgYwRYfHUSh+nA3+B+5kjZQSz5fYFdLjvUfp3Xsrby/O8JbeB75j0mNGHBKF4DBtsVVFmcdgAnTHcjyqHEZLB6oF3yrTdASN5gHzEA9l/xnjdJmvm+Nc0EJ6xNcgPf4SxzEE7GuQHn/p0X/KI3f8AT7ee5C9tM+FY7+f7RM/yp7VjLMEDxQNLLcz4E86WPJQ3g7Dt4HrgtsG/wTcka3wc+/4ER7qvZuPPvIxHnnhcRyGE8c/wh23/0mubT7C1vajr0l6XB7Cx59/nYas12Dv7eA66OmnMU4Rg7RhjJCNoNgRt79k12BGBlUF0l7A5xHbvPaifaw5e/0znNt6RCY5BHnzM7zCi1ygiGv8gHs7D9Yf5PQU3rcLJzuzBKsWLemxUcDvWWsnlyQQ91rjyFbZc3sG771PXrcaTAknNPzM7dJXtQIzgaqCkYXrmUx6iS3pcc8RSO8AryHVoqIYbcLOb0OzA+F90OuDTWV7sEJ63LYC2wrOLcHn+xIE/rCHMxHeUsEPlJDUkiOyncBTI/gnj8ELm7KuoCFZBn5Ilm9aFce4FuJE5bC6DD/+ILzzJPxKDn+vgK1XxeYo215xc1CrQr78IHB3hHwF1Lulv58q4d0ldDzkI7AN/Is+fP5dQsqI4ln49tlodV7BRfPNSmXfHp4HHPzxCpYbOP2qy0IS4QMTeN+03c7ZC4vwbwqxBZtjjjnmmGOOOeaYY4455vh+xpuX9MCjWruXEAJRR7AQfcR7IEamVcXeYMBkPKFybt/G6vVwWKEx+13d5LXDf4dXPTfLzTggP6JUIWIkxJneQpQPM+2Firo1RJKlGq1IrMImLU0RIlpHtAWbRLSZWWHRluMbIg21r6mahto1NK6h8TUhHNhpHcbB3/HGVxXknZSl9R4GRTMGX0eCkoL3LGh91gBx38qpJXHUgSWU1hptDUobxk3DaDJiWFpco9twZhhP2lyTWpQrKZo0alIUHZOw1E3BaI5MMyY+p+s0pla4EFGhIg0Dgs7RSZ9gUpSJmERyI3QsGQ83KcsS8KSpxVhDjFIZSJOEfidnoZuz0CtY6BV0sgSrEDVBrtFWU7rAdhWog28pplniR8S0mSgxHNAiav9ozspACqIn4kXmE4XcerXqRkgPdajPRWKU4k949Xvj4V7YWjopRVSBqETZE6InRIVSDVo1aOXkfa/uC+rVvUNsUbRk0YvV06uKNbM8CZTCGPWqzyqsNWSpIU20qB+Q3Q5tE9ASCNZo8jxFK7EDq6ZCnvhG3itWWBEfI94HvBeCsKo83olNlDbSnxovdlu1U5S1wnnIdMQkat/6zkdkm63FRsgTg7WWPLXkuSbLFNbONFyyLVZDcJGmbgg+EoMhSy0ELYSjsWSpxrbtZLXwDlof2ucollnElmZUEKLCo1HREJSGOGurg9FDyFHTWp9FYgz7arNvOo6v+sUYTZJa0J7Ggfc3J0zmEBVBaE9sbaDbiyyn4ss/HAsJ/mZDILJFw1lKLlFRfovWZX0LS6n07aC92Es1NZfLkvvCb++/7/Hzj/N7f/7DPPXzT0EOjOBzf/dz/J1/9Xf4l5/5lwfXgn8HTBNISyE/YjumRNVaWrXk4owYUQe8MnBgeRfbS4yyFpsW2CRHaanCNjZj2FmF0TevOyclGIe3k5tGtOQ+ZaEZslE+TxYXKLN1olqkUJBnrdJssI3bvU4dIhMn1knVVZi+BL4D7hL4HWh6jsSMyDuO9TTjTrXOCMWpOOFIOEsTr2Cpb1i/BTYw9NGMiVwLr6EwWrpHkquzEaSVSAE41HZtW+qmbVMvjfbq4vfrIURHiDeuPxCoCGhqyQ6KUjxPghTJvwmtgkebg7/3u2h76TIApr0n0qJWqBDbqakSUmndg41QOFholTamXV+qxI4qKHmPDvL3yqKEipdRVBp5DqtWrKamNewOxQbL9GDDwkID5Qh2aiFOArLMWsnfUwVlgMoj5EkP3BLs5bBpJAdjwUOjIfSAdWiWYLMLFzLYSiRkvDl0ENIICxFSxH4r89CPcDzCRpT336VgioSg507aOmoZr3IDxw10NCy1pEsnwloUi6ugDuxbx0i7WoRYyZB7nFLLw7/qFkAhyzt8XCPSxt98tzDHHHPMMcccc8wxxxxzzPH9hzdtdcyHMd5FqsrROEdMPaYPVRUZ156mCTz98lnObW/jnWN3e4eSg/Dx10KIB8Wtti7dGj7NZuzH9qfM9T9sJQAHhWkNs5QFdIhoV4vqA/CmpTZiaAvaCSamGEDjiMqTG02ReYq8weNwXqorRTdgskgdod5WlCgcU6CmcYbt4RaXdzqUrmJcT5iUE6b1CI2/oVB6uH4tCQkHhVStNSfvWOVdH76DUAbOfu062xfHYpClxR7ooAqvWsurgNURa0JbVG8AT2ITegs5ymZceX6Px59+mkmTMgjrWPoMBjVPDGpsrBmOFRsxJweOkLOI4dbldd5y7zGyIuEtoxX2JiV7OxXPPb3DYK+mEwesN0+idQe9+CB6YYM8VSz1NUYFnn7uab7x+JMEpbH9oxw/s8bCco+qlGL6xsoS+f0JpzcWuPXkGieOLLLWL+gCUUduO2E4tpFzZVDx+ZcrtsY1GZEOmoTIkqrpKMc0RrZiRBzaxSk7kuDJiRSoqCCOIQSCnxKdAxRGkjnYn/YMUs1pqwoz33unpGBRAzEodNBoDUr7VlkTQWmiVjgbqK2S3ukCkLDQ75L0PEfXQqsGeGOYRKG0FOfVTWZ11rWjrhzaaPI8aXNS2v6lFctLBb1uKoX3Nn+iriKTcRDSw2tUUHSLnFO3HRUyQ2ecO6swGvIsYAx4F2maSIiBaWioYk0MsN3UxKhY6Cas9AtCjAx3JgzHFeNp5NpOoHawsQZHuqCNpqFDJEWlGQsrK8QYyfuWrGuwVtMrElJr8PEgn8Nq8dcflxVXrmxRTmvW1hY4fnQZozUxFBAzrNVkVsu5n0Hazr6tm8CklGB7qzTWIoSmaRVAMScSqWsoaxA1jaF24IMhMR00gRhrpnWJjxofDG258HWRZJaFpS4+RLI6UjeR7GYHcw72FqCH2AJlObzrVpnB/co1+OwTsP0thkD/bmJC4Je4xlcZMMBxlukbfsYqePcafOQEJBammYSJb10b8Peef56bLeIv/uJf3I8oalzDcxee+7YID5Bw5PsGsDCBuoAylyJuNpa2BwgW0G3GR3uRtbQEqJb8iKjAF5ZmKWdqcnwq/Xq3t8Hjt/6ghBd8E5ZoOtcYr12El2/ycnyQE5OzfGDzv2OULvF8909yOf89LK0obl3XJJnjX1/8JL/05X9O05RsRykCh+fBfVFyPeI1iFvQO7HE9N4HUf013pnn/Lfqx6hjhZ5+Bb33ab4x2uar/sINm7mM4Y+zwPvJ+QoVv8Ael/bvMg7hvf8z3DOAU1+CZADdlwCxzsyGYBqwU+FClKetaCuiUhIibw8Ip+8E7dyBb10HdZi5f9WHooIyk/541sIv5vCcgY+M4Gd3oR/gzAjWSyEIOk4uk90AR9qxunCQeDixDLd9EMoSvngJfuXzsLEIf+SdcG8Hnr0Cv/412Aug3w8/vgyDLXjqi/DlTdC3wQP3SnbI5USUFJsWGoswFPcAb4VxAV9dgboLRx3cW4uaZXQ/xNvgagq/uAL/JocrGsavYgvWI/ywh2MBTkzg1iHkAVaRsWgM/D7kPvNMm/tRG7jYgb0EMgs/5YTsPxZhI0Ch4ccQQmeiJJtjAjym4SVEz/lAlHyO1MBXMljVsKQlx2SOOeaYY4455phjjjnmmOM/FrxpSY8QGwgR7xw+eKINaCUzyOsYKUNksrvLtd3db2PZ3/zczWZW3+zL/o3PyYxuHQOqtZQJSGFahB/h4H1RKtFKiW7DKoW1kcQGMIHQJrvaVBQtOpF8jAYIOKAmxCmTesJwOqZyJeN6xLSc4ly1v1WHNR2zmscB3SH/Kw2LqwUn71ilGTo2nx0wYEJQkgwSZ8qVtqGiUvIhZVC6jdSNUt2w2pBnCSaxVNOSy5f2KH2G63dReUFZOq4OHdp7FIoeCQWKHjk9ElaLLqfX+3R7KSeqDk3tOF+MeeXlkmoQ6FLSDTvY2CXNHKaf0ssNR5YtWnme9wOuXX4GZXOOL63SX+qS5hmNk/3tFgXdLOXoWp+lhQ79bk43s6REchU50tfcfsRgrCK/4IAGiyJHkwFLKrCoPLvAXhRSSyLGDRFLIEGM0IBYE6MmBkcIoe0dbUSyajueakmlQ8WkmXrItw8VOciCaZN0ReUBKEVQospxgA6igMgzT5ZG+p2I+RZr3qLwuPlrMYJ3gabxmBAJmb2hBK8U5Lklz28cQryL1KWoV9q6Jqm1LK5YQoDBCPZ2EEKgB2kaJGy+iYQQqFuLr6aJjCfgHKTWYFYSdAz4EJlWjnEZ2Bt7qiawsDhrJ0NQmSg9rCErLFopFhYtvSWD1kJUaC3kQzmRxrcJJAZU8ExGY0ajKStLGf0C7Mwk/lXQLSfhPUzKSF23hCJyPBIjHvRy0Ow+URqCtA0oXBB1iNYWIgTX4LxDaS32ft8CjNHkRksQu5Z29XX9xh/8jxBVCnUqBWFj4OQG6CPSl7/0zL/vrbs5HJGnGfM042/5M0rByS68dx3SFEYd2ffPuZovmO2bfubXHvu179Yms13IOGkbaDIhMaKS4nxStbPY25n2Kgqfuz9TQbd1cw0f/qgD/tf2ATwhP/7aH3FcWTnDRz+0x0MvfZoHzn4GHUsk2rnEJZGyP+Dc28RKyVRgyzN0r/9BqI6w0LzELaNPMUmXqfSH0SpwKmre14FOJ/BE/SLlxU/ItXa2U5eAp2/cz2F6DBd6kClO2JSj6k58HLPTPMGofITtOpK96jTexPO32OFvAb/MMf4ZGg6THsv3CeFx6iNw9Euw+FXQVyDdBqJYtFXy0BUoB8qrg8D1tu3C4dDz7wDxm/4XqNdaeHtBe63Rq7FCfGxa+HwXvmzhRCNqCxNhqZbH/uKUqCW6Le/fbUQtQQ7cJraEn7wGj5yHU2P44amse3MEXz8Lew7ufgDuCXBuAl94Bc6fh7f1YHSPtNNQw56G8UwJZoF14G5oUrgURTVRKzjabkfdAzIhLR67eaMBEjB+V4DbgoSIPzQSJcfroUmE8LhWyKbcHw5UGRZRHt2pRCUy1LATYQC81N785cAxhODwGi5qqKJkobxq8256+L7pj7nsY4455phjjjnmmGOOOeb4PsWblvSIIRBDxBPwMeJqTdMYQh3RMWDhW7KzAik25si8aWM0xkqosU0kyFgpjTHy3GRaMZqUhBilgI2QBq/OBtEoMgwZGo0nBC+ERoj7ocj7SpIYCK3NhY+i9KijRzUe08h+Rq3F37otYmdpxuLCAnkeSKZj0mpK4RzDnSFXzQ7jasjueIuyLhmMRofIGNUWWOOhtpmVn6W0HgNcuzLmycc3iaVna3tI2UxbZYuEeqvAPrFBqyIJwe3vZ0SJ8ZNKMLqD0RlOl4zYoyQnqgY0NFpRYzAq4fTaGidWNbGumVzdZTgeseoXmdQRXQWawR5uPMCMK47lY9KFkl5esUhNDAm7Vcl4XIJOOKE1mQVtLI4OSuU0KqNRKVOv2JnUWO0xsUHHhsHUMJrWjKaO6GExSSiKglMnz3DHfcfp7VYMsy0290quXbnKpYuXMBqOHFvn9GLOxeGES5e28HVDJAE6zE6fiLSLayK+iRA1SkseSlSSDKO0Rmnd2lOJxdU+aaYgRdPBIPoNQ0Cho7R5VKB11logQXDS9xNjyJMEpSyOBudGUE1ohp5qT9QIdpZw+jpwLrC7N6asGqFzdIJSiiRRpKlFG42+iT3WzWATRdFRhACuiTQegoq4VjiUdRSruSKEQFVNGA8blDIoLcSCVpY0KrSJxNTjTaSsPK9cGUKM1NNIRgo5HN+QdlhbihQ2YrRBkYqFlFLoVIkNV9KqLiKUlfysa2iqIAIcr9EGdLSsri7Q6+d0ewWNE/2X0dzE+qudlR4gScTyygeF9y1hFBDZTktuzY5Bmgn3VdeRppIBQgUkgF1rlE3QWlM3ism05Rrb7uID+2SIai3SfIy4GPfP/dQq0jftqP7vFzoAGlwKkwgvXIVv7MKF62KH82bBT3M3rzDg62wy/TYC1n+yAw8kUlzVHqyT4rH1vzv1y9VSzpk6l/Xmk1YdGcAnrcVRKgVmLw5yBN3mKLSZHtnrxJYMrWJsNSpoGjMlqi324oSvsclVJhytd7l915CaFIwjmkBIxjTd5wjpFj45j/IeF+DlTPFYXzPtTnk426aTjsBsAQHSPhx9GPrHD0k9HWx+A7aelVTz6ghMT6GaITpugx1TnFhEPXAnZ4YpP7ayzJO/+dmb7ke1MCWOAwRDf+k+eov34rJFBjvPUlXbkA7hrkVINKp+jlmUlp6CnojqxPWETFJOsj2+W/Ch4tLOV0jPLTBp1rnjybdRXl9hcU2xepQ3JNZrDZdzGFgYb8PWBYgezpyQcfuYhQ8HuN3AO6eifrgpomTCZCVMNHw+FUXFgoITSnJDVo/AR+6EpT7oRbicwpUEriYwCLB6HvpfhuEO6D3IHFzcgk88D51ExmsCjCronIaVk3B6A840oEqoLsNzA2gWYPmIZIfstHZdOXAiimrDzEiJCMse+l7spS5ouGpgmIHuC9F3WQlFdzOkCtYdnBhL3silXIQ8G16C1FGtraKCbeBZBQMHuxeAHeh04MwROJ7Ldm63BNj5lkQZAFcU3Ky7RODZAm4BliNcVbD17Qm+5phjjjnmmGOOOeaYY445/r3jTVseC84TQsTFQBMCdWmoJinOBUyoSdoqhOeNrRcsIvkvkFnjRTfDtD+zPMEaS5bnaKW5dG2Hc3WD8wEXDSFqGrxkJ9xgH6XoKEsXS4OjDhIRLqTHwczICDgaGhwBhUeyC5a9R1UeWzoUklngI9TBEmKgU2QcPbKIc5HB5jXGdYmuHNcvb7E7COwMN7myc47G1dRN3RIcrRE6Cr9v9KVQEnuNxPVO8T7w4vM7fOrXXiYhYMcjdF2DTom6gJbIES1BEN/vGNDK4X0jBVhjCMqS6RxrF0lsQa032eYKJQVW3yLWRVrjVEJqLO+69QwfesvtbO/t8PFHPs9L422W3BK7kwgx4DevEbbOkTaBe7qOKotYX2N8xdQpLo/GvBJHKJORJZaFTJMkGTVLRDJK1SNRBXWjGO6UKBXJVEWqKvIUNvdKlrs1oY4cyTLIEh68/y285/e8g9Gk5t4H9hiOSj722d/hn187j040tz1wC++58xSPnb3M13cfpald25OW2mMciNQE73BVoCnBBCEOwBBUDspidMRYOR4hiBJIg2RPaE2hDMukZDgmGBoMMTq8r0FFrElRSIXG10KwmI6hlxZorZm4ilhPiZM9ppuO0RXIl8GswRvxFXXd8Mr562xeH5DojMx2Sazl5Ok+R491xWbrWyQ9slyRpgbnIzujwLQU0rIJUuBfWTIsLxrGY8ezz++xtTUmzzv0+gsYY8lISZQlmkBe1HgCV3YnnDu3g0Jxut9nreiy0NOcWLboVJPESNKSjM4rfFCYBJJcoY0iba2oGgeDsRAfwQe887OTmag0Nk05dWoNbSMxaKpGoQ4Frc/OMBBXMdfar2SZxmioapiUQk64BpqZjV5rYZZkkHcUwcN04hkPA1ZDbiNGR6LShKSDUjAtDVUt2T5JIsb5tY/ULqAUGNXqiEIgeHmu0zPkHUXzJirgv5lgoxSKmwIGFXzhRfj1LbGOmbx+NvjvKv4m7+eXeZGX2fu2SI//Zgl0JiRD9JDVMjs8bQ4yM76XOD0QhdR0QRQJ3T1Zb7DS9kG3ChAjs9pnpIezkmOQNNCdvPbytxJFL7N41VCaIZHzXGHAP+Q8v8OAn5gY/mJlWTKWemVKs1jjsx2mS7+DCoaoa3TdUGv4alfxq+ua3eUhP9Z9nNV0E+x5YSKLNXjo5+DWD8uKA1AP4St/F3ZeAF/A+DbYewg1fRITnsSkExbu36D3I+sslCvcvnkff/s1SI/J+gBfBbTLWTv+YU7f82cpp5d5/qm/R7X5RYgPw/0/Dp2TqMkT6KDQdcTugh1CswrVequWKcEcEgN9p+RW4yY8d+GXePnKJ7jt4ttZrf4al1aXuPvtmsVV9Yakx9jA1xbh5Q6cuwpffxTUBP4vD8PdBdyt4f/W5ml0A3Rfp18mtaiGdhL45z34WB/uivBhD+sB7rwTPrgoqowrG/BcDs/n8EIBwwaKJ8A8IQSIbaAX4Klz8MyeXMnvH8LpKezcDos/CvkR+H0B/mAJm7vw9x+Bz78Il+8D/xGxxrvUktkLwLuDhKNnUfI2igAPTOG2Ch5N4G8vwDMW3tmD3ULIhs8oeFbf/N719hr+6ha8cwKP9+GVLkyNbPeZIMHvGvnsRQW/rWFYQ/U48BgsnISHfhDuWIPnU3hK5gHw5AI83xcLrM9oscd6NRRCeLxdAQF+R0sY/Jz3mGOOOeaYY4455phjjjm+H/GmJT3ivlIiSrhvgBgkNVihWj3DtwaNItWGXGnyNKWbZ1hr6BQt6WEtRVGgtGF3b0yiDzw2PBJEfNiCQjGjFzRaadmaeEByzLbsRvsiKY/P1ClhFnQdhZZQahZ23trkaI1NrNgIJQkhTSFJUEEIobqumUymNP7fpcJ58C23rhzDQUWqAkldY1yDNRqbtDZi7ezxiFjyEAMqSuC1hOMagrZElYJKUTolKiWKAyy61YyISkaOgUkyik6HrKrBGJr2tRBbIsB5YlOhfKTQkcQgapMmUisJuK69x4WIVlKIVkq3od6GiPzuI/gQ2pwWR1ANVWsd5LwTFY9SaGXI0i7dzjLGNNQrmm5W0usWEhAqKdyoLEFbc4g90Kh92k1SPpTSGJtireh/DA0STG2k4hA9sZUASVj1bMa+NLJG7Uei69Y8RFRCB5+ZHcMYRD0R40FnVDGgoiM4x3hcMxxUxMyQOrHu2heXHEIIEhxeN57GeZzzKO2x0pK4RuytlFYHxVJFa9il0EqOg2zn7HXpyyFC4z1N44lBtc9LMTRNJU9DEQihPTPabZud87NzYLbNjQ/oKAoSEKKoU1hMptCNzHQOYXbcDzUMh1QZHpom0jRtu0bZk1k7KqXIUotNRQlStfXm/fM5HljjhXD4c6LIaIU8aCUBszObl9m+KSUz4PdtaMJsfJPsn9i23az9ZuPDrG19iLgg4x8tkTILgZcc+YhR8KrM+TlazPpwMGKvNKpg5yZh2P8u6Ks+P63gryhYSSKTkxXVWsNXh/Dz5+GZCaigUcEQiJR4mte4dt3NMn+DH6BPSoFps4D+3dHVMA0wbsDHNn0piBVQjNBF85c4w5/jBC8y5X/kPB+/eUDGtwXj20DoAJ0AWRAOodIwCXK9sz5FodEqYlQADVV0TEKg4w19lSFJBd+MgMIpcFpRG0OVpEy9ZexhGANV294S+C1sZVSeqEUROVNXxaCYaMVOohgph68G4PegmUpDaQudNVg4Bb6GWsLE0SmgiDHim4CrHC5E6tSATshsSqoTimSJvNN9zXb6z18UVlQbRZos0uucRAdPGgOmGWKcA9+FkKFcD9100Y1DOY92ERVim6+1P6LIvnmNal//dsvVkUDZ7FA2O+yNT7E9rFlIYHsMu7UEbBcGEn3D2g/GJS2B35WWoPGxOHQyrGA4lWt3EUUvGYFhO45mVqwBfYCyudGKdBhgEMXSaRygUhIa3knhSA+ms1wOBVhIc0hrcFMY1/L+NIGOkhyMLScKk+MjWB7CtAI6YBaFdFubiH1hUoMvoSphtxQVkrNQJELWLALLiOqjF2W/lqJklHRaFYmPYvlWK9mOsYZBe51wajY5Rh7dID0/zMb+0F5jolhrRSX5XxMlQe7Kgwmyr6aCvJZMlKR9v0LWsdsSVdcRlckQCTivDi6V0G67Ca0y+tvqPXPMMcccc8wxxxxzzDHHHG8OvGlJDx+0qCtiIBBQFrGraRSqmpWFZ/ZLr48kKVhfuIWVbIHlNc2RE4YkYVYmx2YpnYVFlLEEr9neHFNWTr4oO9A0reoh3lCY9mjqaHCHdBUz8gMOCA+NZGPOtjYgM8uDTvE6x+FwWLwKhFhBdFKgrRtCUCwfOc6xU7dhTIJNF9Am5QU94cq2prkhA3W29FnJXJ6Lbej44fZKk0ivE2hqxwubY3Z2pxzrGe5ZHZJZwzgsMol9XO0Z7XpcFSi6Kf3FDiYxZIsrpHkfn3YJ2XFCkhDNOYQKCuR+SF5vUTktihk0m7spz55fYjoKLNRr3G4nHEmWybIeNjO4rEdMFzC1J2lqdO0ZVYHdiWNsDdMFTUw02hoSnZJqTaLBmppgNEY7jBLSRhtp/clkwlY5oNeJ+LBFohV7YcTTZUBFwwd2CuLVRawqWcgmpLahk1uUShmXDb/z1DlevrrN7u6QOC1ZQFGRUdNr27cCPL2VE9zywDs4traE2txB7wzw5ZTJ1lVcOWESK4ZhKMXwJCEas09s+aCog6YiUBGoCTQo9mmnKIVt1wSiijTWg4qMXc31aozRBqssSZKyM5jy65/7BovPDrnn/qO89e2n6XQsi4uGTnHg0RRj5NrVPa5c2UMpWFrosL7aRyuDVSkxwvbuhLPntyHKeaIArzK8KSTIvBfo5REXYFpHQgCbZSRZgXeOnc1NJoMhi8s9Tp3eIC9SOnmbeWENq8uLJKbAmIQkkXUORkMm05IksSwsLJCmKWvrPfIFS/SROIXdaspikXIktxRdQ1OBq9s2oiHg8M5Q7Ulxsi4j4zE4HxgOG+omkGeGXpFgjKKTKrJEapzWtOerAZNLW5n2uaoODEYNzkfy3JK1eSaVAzUL2s1pj5c8IjIARNrskJZP7Rbyi3OBSSWqNpsYbGIxRtHPFVkqtllJO0r7GCmdVMCUNWitqGsYtUqPIph5oep1YFtljrPyCN8FcuhPLf95HsyewHU+y8iOCZlHOziZwn9yAq57RWdnne7WMXaD519zgcfYuemyNpnyT3iaz3CRZ9lmcFMDmjfG396VQm+z2xagjRShL4xgUENN5JNss0VDTsEPcs93lfS4rOBrV+DSFjzQgQ8vQK7gM3vw5QEcU0v8fvMwt6h10GPQA4aq5LP6Fb6grnLX+nH+2AMfBD560+WvN6La8Trh3Po7CKZHXV7nJy4/wgdHF7iLEYvsYKjRTd1mXyjMxKCcVOUViqROhRRJga0xPPkKTC7CS1tSpZ5BRdh6Gp79FRhdgUtfguip602uXPlXvJx+jmfUrXzhoQ+ifMKHntvj4QtjSLYJ3d94w/ZSiG3RkRpKu87ebX+C9NgPsnznCczy/SgL6eiDdF/pYcoxRXUJywQ7GpNc2iPiUNMpUVeY2tK7skBiNNloioqvI5n5FjE08GRHcaWneWKg+PjjsNyBP3AGHl69cUfKFKapFNnvHYuCYi+F9z4opMG1Bv761ySnYzkI6TAyYsOUZ/ChO+Etx+HcrthPXR4yu+HCduB+De80sOrgthq6Ho6W8pYkwoaDTg0/uALL74S9WgK+n1LQBe5GrKheTuCZFPwULj0Kuy9BnQmhooAXLTxWQLUCd74DsttENfLSF8SGbe0e+LE7oKckYDxDlBjLXsb338jgUir5Iz8+gD/q4WiEk8id2N0KtoDrGTzXkzZ+UcljYOBzSzDsCGn4nl25UU8TGFm4ZOC3Lbyi4VQJf2EM1PDybXBlFVYW4KVV2Mxh08CuhilwQcEuEqj+p7ckEP6Ty/DppRtSZbii4HNtO1ycqzzmmGOOOeaYY4455phjju9jvGlJjxg0IXjRCqggM6ntLPPCoAhtad+/4bISk7OyeAtHekc5djJy212RJIn4siTUNUme011ZQdmEnesTXs6uYkJD03gaiSZnNhVOI0VFScjQODQOmZl9mII5PMeynXjIzOZfXhfSI+gMHw0NlqA8AQ8xEHykaRoihoW1DY4eP41VmtxFTIgMx9cx+mZVu5vN7mxu+EspRWKhmwcG3vPK9pSXLg1xa3BvV3Ic9nyHccgox46tyyXlCPrLCU3skOQZi71jGLtGsAUhWSGmlmi7Mls9BjI3pmN2wSeMYkEgYXuY8NLlPrp09JolumbIml0kSzvYzBDTLjHtgW9IXMRUinri2RoZJommChqsRllDohNSpaVIbWqU0RjlMUSMFkVBDIGpK7k+HrA2VYS4i9GWUZjwUhXBK/b2crjexxSa7qolNYY8syiVMK0bvvriJb72kqMTYSVGumgiCTXdQz3C0V3c4MRdD3JyY1VCZ8Mejdpmpx5TjUoa5yjrMU4F6KSozGJsCiT4aGmCot4nPEQBMwtBV0AIAec9UYHXAaUjU9cQajDGsJj2yIxlMK74nUefI6Q7DML9HDm5weJiTp5rOsXh8wu2tka88NwVOp2Ut77tFo4dX95/va49L5/f5uuPX4EQsK3Sx9ketV3EWsOpNc/6YqB2kd1JpHGQ9/oUfYtvagYXrzPd3UTfsk7v7nUWlw7K8dYYlhd7dFIhS7yPNM4zbcZcHW7TKTp0lnrkiWWlZziW5TSN5/y5EddHU/IIeV7Q68hs1QmAj2jfoGKNbxImA4sPmrKK2DzivacsK5xzJCYnTTLSRFF0Ic8PzlWQoHL7KvbAucDenpAmS8uKrJCActcIwZEm0MlE6eG9qDBmM59BFBhGS7G9yBREzaQM7I4DVe3JoyLXohpJEkWnYF/RFCOMm0hsp/0qY9BGguPHQRJ2XIxz0uN1YL20rbfyiPqNP/NG+KP9/4xs4V/hVx5hrBrSKdgajiTwY4vgDazEZda27+QCNU+x+5qkxzYl/5qX9un88G2WG39h0P7yqstDjLMMrMgj7PEFBjzIEf4mPwB85tta182wCXz6OnztPPzYBrxrRYiXL4/hFy/Dg3GBD/J2lrgDwxaWyyiGPMOAX+EqH2CDP7bxEV6L9Fh2cg55bbi08gBbi/exOrjCD+/CqdFzSOr4c0TGGG/RFehGYQcGVYv9o0JjQoIOGhJgp4TPXobNVyDuHpKutdh5EZ74KOyeZZZ1VdfbbF7/BBeM5pHk5/iFu/9LTLnE8pdf5s5nL0N/jLv1kTdsL4UUt9caqJIVtk/9BMZGFs8o9IJGhYZkMqW4tILx22R8A8M2dnqdZGqIqqRWNV45dJOQbfZIYkJKRMrd31nZeqLhhUJxsavYHUmcybEe3LN0I+kRgSqBUUfUPrcPRXWAhXi3EG5//Wvwvz4tuRpnGlFDXEvgfAqLPVg+Abd24Pkt+Kdn4amr8nkMnF6Av34E/vCikMx6KoqdmYIrAVYc9DVsLMJbHhALp4td+HgBpyJ80IkVldFwycJ4AFevwvSSLCBqWd05K1kZWQq3PAC3Rfj64/DVfwPjMdxewAdukWvE7DQrAiwGGAGPZPCxBN47gZ/fgreVh7WH8L62vV7qwqcyyc6oNbysWmuwPlwB3rMHP3QNFjycWxQi5ZqGL2l4ysB/UcPP7ohN1yOn4On7RAFywYqCwyHKlyHwDHAeOFLCT10Vkm3HwmcWJTNkhk3gumJ/HJpjjjnmmGOOOeaYY4455vh+xZuW9NgPfW7trBbyhG4mRcy1niFERYmnwrdqCgkijyEQo6QJBxWJChazJTZWM1YKw0I3kicBayPOanyUb63TqiY2HhccNpVZcKoKYvj+KkWJfHmNyPw4hWqTRQ7XmGaai8D+d/b9xA2YhRNHeQB6ZnfUflbeq4lokiQlLwoMCtN4tA/tt+1vd6qyIk97LPSOECjRZhcfR0Sdo/IeKk+I0w6ukhnCZArlFWSRaBxRa7RpMKZBmxSlDSjZy9kWhZDgXEYIRkgqJcqdxpeYWKNTiykKHLA7HFHWCjcY44elBLwrIBFlh7IaZbRUkRuHm5YM9oboVDGdTAhBMkcUSuzGYgAXiCGgfGxtThTEhEiGwmDwSNy7w6mGuhqzc/ESU7+DqkvuOLLGcDJlOBwwrUpsjDgf8GgcYlUTURiVYJRBqwQfNU001KQ0OqexPSbddRoSGt8nuh5KBbJ+gu0YrE3Iiw4Rxak77+KhvSll46hDgouGwd42ly+epa6r1katLZq0flKq7X0qKggQQyQ0Nc10h9BElD9DnivyTBF8oCrFSsVamcaZpoZeP6UoUpLE3NCdtFb0eynr6x0IUYK2iXhd0JgMYxVLS4ZeL9K4CEnEeUg7lqyjic5gVgo6tk/RKRiXgTBwNJWjqT0xKoJPiFFTN45y6mico3Z+PwNDst6FxEoTObZpakiTBKUtZaMwlVihmPZ0SFON0YbgFRFHjBqtFWmiiEZhlMEHeV+Iks1RNe36EGJCKbGq0ocKWgBaSdtFFFofGLJrBao9wb0/pCA4XFRXrQYriG2J0hL6nnhFnmq0giTVJInCtnZkM3caP1OPRSWWeigSLeHsmVV0U41SkaT1tfouCBj+g4aKMrn/jIa3WiAoVDA8+m3kZ3Trp7HuMio6OWZGwrpHwLkpTCPcQklvcYfGOcK0eTUHfQP8d2Fe9f1tgDgKqgiXaxgemhuglebYyjGOLB7hLrXGUrgVXv6OV7uPfn4P2lzExyE7DTw7go6Ba5Xk3AypeY5rFGSspHscK65T6zHLquJWDccWDWnaed11zIqxUSmCMqASFB00PSK5aDKjQrlWHeog2vaqHKQarAn0XGS1hn6jsN5I8MjhE3c2hyBdhOX7wC7tn2BmKVAs1vR6gaSy+J2nidMeTCYY10DtiCPPi2+Bj21q/vkVzefCTfrY+tvwvWPURuO1ooPFB7F5GnXAoLm63OP6xhraJ6RxhGGZoFYJrGBMxcLSLp3uiNRnJM0yJliOMeRtDJgQ98PPdke7XNi8QNW8foiNQXOcRdbp4VyP8e5LTLVlcWOdY0vH2ehbuh0okzbA27fjZ4DECelhojwAud5oONmFt6zI/dUxL1ZOqxZWEugVsGEhdbCk4O4FWdZspsmxLqwaUWztlXBhp7UgnN2eZYjHlIV6AtM9sXHaMhC6Mp4GIz9XAtxfw6iGZ3xLmlfApixqr4DzXViIcKuHVQ8nEjizAeOy3ZYgiiPd2rdpLTZdgwjTXVEfNkHsvSaJKC62lHzmZCOqEIWQEpUSdQzIodpDSJxzBh7PRAl0KRHlxlkNYyXv27XwUi67fi6Bi+11KI3y+W0lYeczvU+B3KrtFpAkoj48FiF6WHBiRXcz+Cl8/XV7zBxzzDHHHHPMMcccc8wxx5sPb1rSQxsLzuF8xGrDbeurrPUWyDt9llaPYZOMEkcZHUppUp1hlCW4iqYaE4KnsQGnA6lKWTVL5Dohzz3dPKIUlCqhzgyT2nPp2jbT2jOcDuguRXQe2a0aQlmL+oIDUkIeARWnHNAU8ro+9EyNzLTrIF9KI1Du72FEa482niQGdIx4ApWKUk5XCkuCVgm9ziLLqxsQA005xTcNFOm3TXpopVlbuZW7b/8hNnf26Hx9QGCP2DmOOfYgpsjxV/eopkMaC3rDkIQEk3rIR6jUYotdskKTZKCMJWoJ7FZADIaq7hOaVbwCY0FphWfMuL5MSkV/uSBbWGdI4PEXXsLQoK5dhO1r5JllbaVH3klobCQhkCiLcTVqMGRUDXlueo1COy5dukTTTDDatMXghOgafFURvENPA2mtSJqEGJbxcQMTO/SjHJ1oRoyTIVevnuXzn/8Y16+fo7d6hD/1w+9kUjq++tgrnD1/nUHjuTStqULEU+DxaGUobIdEWwxdhpVmq1RcCx22dALdRdQtqyjvqHFEHDaJrK0rlpcUSaLodi3GwJH3/iAf3BvifSRUiugVX3jk8/zCP/wFrly+LJUKrVFIX9EhYqImIcEgti3eB1zYo9l7Aq9TOvEoJ45qur2E6bjh2tWavDAsLwtpsbbWxZgNrDV0e+kNfcRazR23r3L0aF984tv+HZUhKsmayRJITCREIR5CBG0M2hiICe70KYI7xqiEly87qnrA9StDtq6OKIqE2+7cYHmlw97ehM3LOzSNw6WOkLSKHh3QOpClioWuxnvN8kIH3+TYRHNlT2MmsNSF5Z70624ng5iyvd2wvTPG+UiRd1hdLNDaYKxB60hZK8aloixh1J6URkNu258FFJ2W0GgJEWs1/X6O95Ek0QQvryWJFLych3ElJ3obwSPk58ybPcp7QIpNNoUkNVid4zwoo9At4YFSNG1xXLI/IDSaBEWiFL1EkaXQTQwrhYwDmVVzwuMNoKIUZJcD/HQKP9EF7Sx22uXDYfffeXlHdv4nnNmiXhwTE3AZVB14fgj/5Dycn0Z+dPUqf+SeETtNYPLyWEz1v4f4749BbNUsVxv4x1fhK8OD17Mk4w+88w/wx97/x1hUHW6tl+G//+++a+u/+9j/g37+D4Gv8NQQ/sFLQiZeLqU+fYFt/gGfZJGCD6w2/OStNWnqeXs2ZCOBUxsZawtHXnP5QYFreYk0SG4B0dKwTkWFZowhQUWDnhpMbYk24ruOaEFPQI/AxopbxoF37MBdQ0vuu0g0dSYLn81raBQsvQXe8d9CU+5LPbNuyclbr3Bnf8yRJ17AfuVvEIeKdPgeOtwH5Qh/0RM0/N465cFQ8MGbqHziD/w8E3uSrSQhiXCsgVMBegm8eBxIDZ94+ASfH63KNc2/BRUdUTdgavqdwEfe5XjbXY6lStMZJHQaxY/guQ+HD1EEHw189vHP8vd/+e9z6fql1z2GXVL+KA/zEzzEM8MR/9sT/5gX8pKf+L1/iJ99+E+xuNRn6QhsLoqaY3ksxEdRSRC9Qv4+jNzCT94K7zoixyxrSZFGSfaH1XBiAVaH8LCFv3I/TGr2b7pyA7d0QU3hyWvw95+GC621EzXka3B8FfrHYesiXPgdmDq48H4IK6JmmCgYA2+Zwh/eg90h/IMJXArIefk5iVF57n649iCcAh4ewPsmom5Z/BBMFdzTgztqSL3kf1gHz3fhK0twvYHtJyE+A9M1eOWtkK/AZy38WgKLDv7cDnxoJPeD1zRcbgmT2T3iC8A5JIz9tzeEKCkN1EbWf7nl3B8v4P+7IfedLyRw2cAtAX7Ew1qE3zHwdSv3oT3gFgWqA188BQsBbA4firDUwLt34HjJTTEewo++bo+ZY4455phjjjnmmGOOOeZ48+FNS3ooLfRBiJKjsVTkHFvs0+8vcfTkUbK8wxRHGRu0MuSmg1UJvplSTweE4KispzEeHTW5M9ioMO0M6Qg4o/EaQu0YT0pGZUPtG5JUZoArHXh1FgYctim48Vv97PnZPFEPbRKI1EkOTLJAlCFRitiqNR1p1R/i1yAh6VoZEpuQZTkxBnxwErBtvt2YW0Ap8myBpYUTVE1OknQAjbJdVPcYqiiI1uMZitKjaAPbjQfTgAloU2FMhdGuJV9sazsm1iHep6Byoo4o65BseEfjx2jtUanFqIKaMVt7A/A1ZneE2ZvQ7WX013qYVBMbjUo0WilUCKimoQmOvTBlSsNkPMZ7h4peZpqi8QFiE4jeo3zEBoUOmhAyfMghGpL2uEZVU6uK4XSP82df4cqll3jorQvce3ydaRW4/NIeu7aiCQ2NMpSHjqYCrE5ITYpSliZA5WEvWq4rg0ogzxYwSgp1UYNOoDgG/WUpjPd6ItpZAm6j7WqldJzd6zt0sy6apE2ToQ28b/tapJ35L/kQkUB0nlBNCGhMHNHtKDqFZjyITCYOpeWcskqRFwmLMUdrTZKYV3cRFhYyFhayb7eXQZt7EjZrRpdG7A0bLl2ZcuXckP5CxvqJhu5SZFo59oZTGuewfY1JdcsetueH1iQWjBLrtTyTGbuTGvDQLUTpYTQYjPi7J46oHJGAtYE8k/M+zQ3GQBzBYCokxMyKyrbhO1YLKSHh4ocsr7QQVTNVSQzsB5jbNnzXOTmEJoJtPzjL+YmxdcZB7Ne0AVAUuZH8D31guaRoyZJwEJoeoxK1l5JskNlDNnyObwWz4TWLcIdpSa6oSVTKWB1jenTE5OgIUycsXDhKvtfHsUelruJsw9a9sHMHZAPYeAzy61+jbqQfBSvKOJ/AAHh6BC8M4e6VKbtLU0YNuPQNN/E7xju7EBLZjlcqWLE35BRjtOH0xmneffe7SVV6mIn/rmCpeIjULAGw08CuO+jPAGMqnuIiGsWRPLKzDAs5rBXQT2F1yZDbjOofT/lfPv53+Ou/8texeo0fefBvcd+JP7x/TZ09ZN80gQJHH0OBbpkJ5Q3aa4IKRBsJWYRmRmR6FlxkvYTFRqGDJWCJM13mjLH0HtJlWFtuw3k0GNDFhM7yK6z8+ftv2P+/wCf5C8DA/1XUWLbwJIYzpIy4l8AfIPJWPnHmGH/1/Q9zdmkBV8O0FsVA0Ug+hNWw14Wq0Dyz1uMLx3pimefbW4TWy265D/c+CHe8FdISwjboGk4Ax0EGpDFQwbW9TfK04I2QYLiVNd7DLajmLHb7GabmIuv+rbx7zdFbhs0uDGyrXms7mPatSha+6f7EKri1L4/XRS0ZMOvLr/G6g50pfH0bnh9ArGTfugrucLBs4WoJL1yGuka8nVriuWkfyw08NIHdiag4tJLlxKtABnunYE8EjKQ1HJ2C68LOUQlMP1ELUZA5WKwgq+FcJmqObaDcBs7JfeQowm4mOSJfSsWCa6u1oNsnYpRwNzOF8LBtvy0DL81kwjO055ECtiw8aeWpC0hOSE+JYmMxynh0HbmOLQB9ACvHbiy/cgrYCPCOCm6b3HhuzTCYvsExm2OOOeaYY4455phjjjnmeBPiTUt6uNrR1A1N7TCJRqmcNFkkeMvutU2MMTiraKzY3jg9xioLOCIlkYDCY6IXkygVUESaOjCtRUGyO6wZTR1lZD8QPAaNcwneQYwWoS5mj3a2O/LF1LezwOOhb4i6tXLSUTwDYpvPMHPWnplbKDxKjdDKt0UWjdERawOpguA9QUumSdkMGI+uEyNMpyVN4whVRSfGNidE4dpvxbE1/mhdyw9tbdz/jQh1HRiOGpzTnD5ynOndNbcc2yDLIto0ZGmgmymqBqaDmrJu0FkkKQwxMfiRh6QCP8H0htgkcqyb8tYzJxlNLdd2OgwmUmD3XtQAtYOpF8sHrxQWTQw5wa1gomPdepYXDUlhiVkHn1gq4xkbT4knGkWiLVjNONOUylMmPaLqomNK7kZ066uMRyW7WwOc95isw+rSUWLM+Z2vvcyzL1zhyadfZKceQQx8+dlHaeKUwfUrXNqaMikzBoMBe5vPMa4VV4ZTLpQZQ2dwAQ6C4iuMgU43o5N36fZyskyTZdAtFP2O2CFlrQqAtqCdGFFIKCXF7OlUXo+0BfZ29qvWUOkgFm6xwZC0x1O87FFia1W1VmDWGBJjwYBNDFoZjBViLHgYXA9cuxxZWQusrECSQt14xmWNNYa8CCTJd/kkbtEpDCePZqwuWXpJYKWfYIxII3avDfG1Z2mxT4wR0zHoTGOVZrzbUGtPOdJMBwaUxjUpndwSjIRRRw3Tied8Jed5SoMh4HxkbSUnAr1+gpplOLTFoySBbkfqmc5JNoY10GnJkazN5iBCOW1wrj1PlRUbPaDxERMhjWrfdizE2LqwKTnmLRES40EhUAGhbvsFooQypiU91I3vm1WfYpT+MrPyMi1HNVPZxAjORZyPDMZzJ/abwThIAqRTMJUhna6QV72WsaiJeFQdsOOIbiK4hkCFyx3VQsRlEDoyS90nsHsSRsugcyGwtFN0xh10k9EbO0w9JkTPCwP4N+eg9HBx/L3fz91VIeOUkm176DSYDbgyhGc2ofENX3ruS/yjT/4juWa+jt3Wt4PJVwf4HVno7ScWePf9R0it5qvPbvKNl7ZZjV3eyy0cpU82vManz52jSBwPJHCLVfQ71zFXP4VKnufBF5/nZ10Hl/ZZUsmBDV1LJNYamgTqbsajp47z0nKXNBbkYZHUDzi2/Shrg+cIYUqot4CKkIBbhyYT4nnBw7Yf80u8jOElvswmjgD1Hpz9BIyvtBd8QCUkG28nWXuASlk+t/1alXn4NV7gPZxklVWa3i7T/ja1cVxNVtnTt3NxbZE1leIbOY/PWrF7Ml7shmhzhZo2iJoIvQ7cfhoWekCb/9PL4MSqWBo5A5e7cD2HVxS8pNtM9i7g4OvLEpr9RihpeISX0CheZotNRje87iq4eBkujGCjA4urYFJ4LIev57If75vA6e9y35rhdBd+6gxcKUXdcFnEhXAR9rZgcg5iS4pzFjDShme9kBB7Uzg7kjF1cRn+0NthlMDlDpRWiIutr4taaq8H13rStscnYkX1cgKfyWG9hh/WQhzsAE8jGSXbtyI2U31YV3ByBD9gZKzvBDgNVLmEvJ9Tsok7SJ9eCpIFcqqBF1L4YkdIkRly4CiiIHbt5xSwAhxByI1HjWR4PK8P7lz3kFP9SAN3jWGttWIMQN9Bv5H3PZ/BFwvJcplh+j26N5hjjjnmmGOOOeaYY4455vhe4k1LelRlRVXWVFWNiQatu6TpOr4ec/3CRYKvochQnRytNCUWi8bmirSnxWM/Nljv0dqh7RRlPNU4MLgeqKrA5csTtrYqWcaRFcgSvDc0dULTKEJIka+BTfuIN8yCa9pQ4lmYpgKUthid4GMAX0KM1MisusOkB6pBs4dmSlQ5ShUoFcnSgArQeI8zNSFqxuU2e7uXCUFRVh7XRMJkQj9GDIohhglaZvq3W6cxYvHRbr/C73/5jcC0dOzs1oRouPuW2ziysUov13Q6oKno5JHFrmE0aNjcqpnuTaGfopYyfGpockeME1STYvs7pEXNrYs56p472RlqfufZPjsTKQI3TrJLpo1m1DbAVtDEaPBNiq+XSAh0uwnH+z2yDMgjLolMk4o966gxRAOZsZBo9joGdGSSLhFZRAdNp95hcdpQ7U3YvbhN7RXHbnmAjbVbmE4m/OtPP8VwsEvdXKUsd1E4PvHV3+KRxx8h85qlKiGjYHtrm+vndxk2CWd31nluvCDZH9HQ+p0AJcYYeosFSwtLLC536XQ1RQELHYXrKbSBNAdtpYCuW1VAnktf8U5moh4m0bSW8FRrYaICExomNORoMgxRKbwxRG1EJ1Q5jApkeUK0oIwm0RqMxbYpq76JbF2KXHjW489oTt0WoROpGsdwXJFYS7//vSuU97uGu8508CGyu1GwN/RMxw0XX9llc3NIb6HD+toy1loJ6NaGqqzY3dylKiuSVJNmliQxbGwssLjUBoiLwIWtXcfWbgXRUTAhoWZlpcvp08tkmcUpSd05PP04TWBhoY2JqQOuiVij6BVqPy5HKfAuMB5VjMc1SZpQ9LsYq6hcpHYRq6GISnQ4MeJ9aJVGmiYoWX4l5IcxkNh22W5mmQVF3pIeHMyuPUx8HNZxzGa2z5ztfICqlp+TMlDVgcHhAIc59pHWkDaQjcFWCcX4FMX4BJ5dmvgygTG6CiR7oEIEV+FR1N2KycmIK2S2tw7gc7h+B3gNvREs70JSaRauLNLZWmI5TLBerBG/vgXP7AkxNf1dODSbxyULIXFiK/WBY/B2DV8+Dxf34Nq44hOPfoLPPvnZAy/G7yJGn7xOU0lmxIO3r/L/+pm3stBN+Nu/+HWeOrvDcb/In+I9vIvT/Mvtr/C/DK5gcPxXSvFDSpGoSyTmX6BVl/fXQ97qFhikK3yRlJfafm9b0mNsYGIgZjkv928jxkDHP8CC/z30qiG/5+l/yfFBIIRtfDnGuYpmGcp1qFIhN5cbuOAG/FL8Bjs8xQRPTYDpFjz1T6Saj7STSvrkD/1FOgv3MnUpvzpdf812+CiPcSfv54RaoVz8GoNbLjJIa77WOc7Z9EEGiea4tiw1cNbAk4kEexetgqxMoLJQ21as4EXV8YPvgVtOtUOZknyaEwbyCI2FswsST/HrFn41aYU87eBSH5Hi/hthQs2v8gSf5GkaAmMqDssN6hJe/Bo89hzcdQbu+EFIV+HTXfi7K3DciYLie0V63LMA/897ZN8eWYYvLsH2dXj8N+DqizBuFXIAPAk8B6MAT7W5FbM7uqUe/Mz74Sfvk2DzLxaijHj6q7Dz29B04Pr74PwGLJRwxwDqCB9bhf+9A3cbee4kEkb+ZQVXU2juB+6GooRTu3DnrhAdP6KE2DYFTLtwPYNnNDzPATmx7uBnd+FDY/g/F+CZDMaHLgJd4F5gI8ILSrI2NPAwcEeEawp+K4FdRD0yOwTXkSP4YA1v24Fb64NTXyNWcSCk1d9cg6uHvh2E/Ltx1OaYY4455phjjjnmmGOOOX538aYlPULw0GZdaMBaS5KlqFhiTEBFBzpFadVa/bTT1KJFqfZ5pVEqoNDyOxJ23ZrmH8yiDpEYPARNCIHgZXa82NK8Wuh/UKSezfm/2ePVJeRw6LMwKx8o1Gxb1MGnZYa3BLLHEGiakrIcS2FzGmiaSO0arLGkNsEGjYlilqXa6eEqarHAuBlipKwqBoOBBCobQ6/oUKQRrUP7OckWQUV0GyatiMQgRd2ybhhPFdqWTMtpm0HQSFsebq8bmm9Wwo34aPAx4IOhdgavFFOfMokZLnhoGhIidVAYk2CjRUcPviR4Q+2ydpaixibpgaohelH5aClOaq0wSioGZVUxnk4wODqJ2ELZ4Al1iQuWKoiN1LiG3Ulg1ATKRtHEVqpxg3GZBFqHGPEhEmIkHgqj10oeSTu7U2spbM+skLQ+ZFsUxIZi5qYyC/KWfHL5d7hNY0tlieVRJOoZ3SXv0Uqq9iEoqgq8kX5lrcJYtV8xV0oCuWfn0PcKWoG2CouiKBQuaIgRY0QmpZUiTSw2McRoxMorQtM01FUFpGhrJFi8taeb2amE2Coy2uJtCOCjajNG5Ix3HuoYxRYqUfvv1213NBqiOTguWrfKCi/Hdl+loRR6NoNeHeR9hBDxXgiOWXefhZDHVz18nNmStZs8GxjUwftnhMshjuYGS5MbcOhUU7zGe+bYh4oHJHU0kWAjQUWcCgQV8Da2FmMRlwQiHp8GQhKFVIyiGEGDMmrfLkvGXCFLtI+kRJYtrALTAIP6hkP1vd1HB9MGBk6I1LIl5xNgpVWcuTimduPviW3Nbjmgk3c5Yo+wsbDK+sICvY6hyFIh+hT0bWRJBToqYpF+P2lgJ0BBQ8oOigkBT2j1ixFuvKa141hQ4FFUSYpXQg5YJ7aA43yNcb5BA+xhaTyYoDFRY4KhaIb0p9fI3IgmKZhkizR+Am4kC6oHN+6cr4huKuOTd+zWQ14LXkd2kiWumQ3GxQbjbINJssYk6zFNM5xWpMgYkOk2FLsda2aqP9uOCbMrj1WwnMBGdtAEFgm6zryEYbt2/JgquG6gPDwg/NQf/paOYURsyMZUWAw9uuRkaFdwfSrjYOPE/snEG8ee1nXrezoOZe3kgEbDeg4bBegM+gYGSuwJUyPj7cjBdCzXhqqRnxMtREJIRcUQZjaTGRCgmwjx5IHdGq5OoZ5CPhZ7rJ0CtnLYauAqQhBsa7GqqhT0LHSMkFgTDTsKiihZQlFLuLlD2q/v4LBeaN2LNVUvCpH1Wu0YObBQNYjSp4uc51MkI+QwZnxrhZBoQwXdKNs163O+ve/Q7TJnmF9T5phjjjnmmGOOOeaYY47vR7xpSQ9fj8mCYy2J9ArNkY2co2f6KBdRZQ98QmMXqe0y0TeE0SaxGqPzPqbXQxnbMhet3ZMWtUHWcSzpBtcEoh1RLJaU0bPtK6rxhHJSMpk6qrrB+ZLItC25yHJms/EUMrv6cGFSATo4dAxSAI9S0Lm5m0SKYgVFB1RCVCnEgG+G1HWJmzjCaID3ga1NmLo9qiZydatmXHos0N04QhEijEr0tAEN2so32LKqmE6nbSG+zQxpHz54Xnz5WT45HtLt9Thzx20srayQGU9mHSE4pj5wvZwQcPSPJnRXFS6UuDBk6iNPXTE0FzUrC33untT0ioKz167z4pVrTKuMnT1DGjNclKI9QGoSOkmnbU+LCw1NCIxLRwyBb1QJ5/a6aDMlSXcwuuT2fsb9S7eI7cJwi9HOdUrdYe/aGo1K8A0cO3YMazVlJ+OqstT9Dqu3LBGiJi0s0/I6MZQcXYus9jJWkyVOpAmZinRUSq4s10aOr14quTz1THf6XHlhgToYro0SrFKiStmPo0+BQOMsm9tT9obXubo5ZDwMFBlMp4FpGShSxaI1dDNQKahCilGz/AnfROqxUBpea7zVqLYIL4XvAKpB5msmLUEmXdq3xfGWQ8JFT4nk26QqweiE4bbm6acV3Z5i+XjKxklLt68pOkK29boF1hi0VmTZ9z5sQAFFprBakxrD7moGOrLYT1npG5Q2bA8b9saecjJid/cq5XTM2sYGiyurZFlCZyEh7bZt0MjPo8uWlWWFd5HpMKOpPHXUvHjJg/J4FfDKk6ea46s5vdwIOdJWgRKjyWwUAkNBHaCeNpSTWvptasiLLsZobKpQGhKrKFq7qckkMnDSq11bngxRSeYHYiWmkPVVIhjDtqRJREJwTTzI8FBKlChGH+SExEPFeqWESJsRI1kbmJ4YTbdQJOpb8K/5jxBhlpmiINiG0fp5Jis7NLZinA8IpiFxntQDBDwTIpUkMuuIaWTmdhEAp1meZuA0KnOoogYCTbHHZKlkzTp+ptdw1cAjO/CpLah+l1zHjj2a8OkQ+I3gqRBbnqDhaAU/l0C2CFePw+ZR+Ee/+d1f/6/0f4v3v/OD/KGT/ym3nq5YikPceAx1F1A0+R47xz7PZvcbnNbX+DlTM27g+UuR/3EL7lIlP6U3OaYMnw6BXwsRT4e1WNFrFR6hJQmTCIVvVXLIzzzI81FnPHfsXWz3jrMzforHL77C7mSLH9zu8RPlCgu6w0PJr3PaPM6JdJHq9M9wVVteuvLrvHj5Y/hQf9O+RaSo7RXoySXGz/+z12yHDy/cyS/d+T5+sX8rJ5KHuCX5CFEXjNWDJLPLshOSIvESYJ5EWA9iD3XMwd2l3HM81SrDujXcexUeVkDSXleUFMfTdgxxQQrbn1sCnfIdV6xPssFP8kOcjsfZuvJufv4rKUUP3n0Eft8pWOqL7ZYFfngEa062/+7qO1vvtwId4Y6xEAc7DlYfhkt3w7KDow3UDfzyC/DpCwipTGv2qYEExgl8MoNncgmPf18JfQ+jE/C1H4a9En7tCnz9eVGI9Lx8/us9CF2xEvuFW+BjR+D5FIZa9v0nh/CBsfz9ywvw/9PwgRp+rJLxw3hIxvBgCf/VBPYOKTkyBSaDr+VwNhdi5zDGiHilUGJZ5ZC2zyMsROjMCP3XwNMZ/M9rYm/1IzV8sJJ71JnV1T0R/spWa6nWYjqEP/+dHqw55phjjjnmmGOOOeaYY47fZbxpSY/QTElUJLewkCqWllOWjxQkoSH3BTpqpnGBSVzGNyWlukajp6i8g8pzMBnRR6KXqXURS4yaNGtIs4oQPF5nJJ0pg+mE7WsjmrKkLh1V5agbj/MNkfoGscJsdt3+H6+Cjl4UCbzRjEeLoo+iJ7+3eSTeTfG1wleeOJ3iXc3QNgz9gHHpefnylL2R49jaBredPI3RhpohPkykYJ5J4TzEwHg6JrwqbB3EcurS1fMMr55ndXWNjZNHOJYfJ1GeRNe4CHUIDJoaowILy4ZEa8bjCXt7A6ra///Z+/N4S6+zvhf8ruEd9nzmmlWDVJIsyYM84wEwmBi4SYBOQpykE8i9DTekm3Sgu0NIXzqdoSHhphNCJ20a7v1woRNIQkiAkNgBk44BzzOWNaskVamqTtWZ9/gOa62n/1jvGSTLg2xrsO/+6rO1z9m19z7vtN/17ue3nt+Py9vCjZGw2hujlNBvZTy6vsUD1zfwvk3KKQwrsesCQamYx5HZFoGA8wqRhCAlRVVTO2FPDEFyYpF/hlYjemeO8bYTayjxPLX5GLK7TikDtoNQ0qKzmLO4vIzSiipRlAqSVkKvl6FR+MpTVXtoqVnqg+lZzmZd7m63aWtNV+fkKuOBrSkf2rzBzVnJcNzj2uwEiKKUGYaKoDRBNIe9HArvYXcYU1R392YUU6EqoCyFsgpkRtHRmoVERSPuDk/zKop7JuCbbgdt41vvdxOgmqoYDnXQKxQ7ClQzI7Npc8LjqVAkKHKlSZVhOtZcvgILS/CKexLOnHn6cdDKUlovgNhxlDSBNFEoZej2E+oQ6HYSuu34Sdna80xmJbPplPF0l2I6YokF2r0WrVZK3oEkB3ExNBeg2zakbUPtYENnjMcwKR1bWyXOB4J2BOPotSyDbkqWRtFDfCMgpJDZuIXrRlAqKs94VGK0orXSodN9+nZKmhDyqoZhKUymgk4UNouiCI2AYXQTWq7i+9YlBwHpttnPrimkSYg6rVZx1rHRHGThhBA7l1Q4FEsOOoeas3hq4wEhbh5s/mzsd08BBOOpFjbxySZlBqNe9O/vjKE7AtFCmVe4BNISWmPQDpIZmBmYUpFtJuhZQrlSMD1dIVpw2RTClEEOb1uOFkUjD3+wHQvRLwRLj1qu4/jPeI5GiHxnDm/vwakMHj4Fl25/fkSPD7T+iO+56y/yna/4TlT2GPBh9oqN6Akm4JMJ49UH2FuCVQPflsBWCT83hN/eEt5MzTebPZYUfBr4lQAJI75Dau4RDro+UDSZOs1khBDFiKTpkEBZnlq+kyvLd3J1q8Pvrv8qN2ro1y3+1HiFBaDNx6nZpXPsW7h5/i+y3r3AtNzg0vp/Jo5Dn0sN1Aoot+Gp93ze7XBv+xT/4txdfHr1Tt4whbeNhVSg1gojsUtIN+eCwf6L9rvKgGUHt9XRQm2xEVBzB7fswB2awzHl6AVGM2RUwGIGeuHL2YNPZ4UF/hhv4BVyB7+4fZZ/+0hCbwne+A3w+tsOrfYQeFUBryziry9Ed4AWOFnE214K6la43oJzJbxqCsUUHtyF910DQnMO2F84E/M7PpHAJ1P4pgreWcGtHj60CuYsTLfgYw+C+mx8PpaY1ZQCCWwfg/ecBxYOLwdXmjyT79+FD7ThVxZi1kkyhbeqKHK3JvG8ch4494x12kvh48vwaAfWdbRxPEoBXH7GaxSQAW2Jh8UXGgEuJ3AliV0eK1N4o46fmboR/c8UcPfwcHwFGI7nosecOXPmzJkzZ86cOXO+9njJih7KGEwQrAS0KMTXODdFicP7HBGLF4sPnrqsGe3OKPbGpIM2nY5Dm6SxxggI+9UuQcSjlI/WUU1HhjiPL0vcrAAnGC1oLQQVCxzPxYZ9XyBRR+45cp9qhShFpjVG7T8eDYsU0UbKWEWrlSNLK/jg8a0UnyeIqjA6FsGNVrRSi9ExZ6J0BUoprDJNFoF/us3UEbRSLC8MOLvYp9cbYIxlPCtItSfYiuAdxiT02n0IHiUFXjzKdsi6gvaBtczQWjYs5C0GgxXaScbySpczZomqTpmNWlRFFe06PIAmiMeFujFikoOZ6nKwmE0VWBI0XbQYdos2D+8YFHBt1mG7XmQqLcoAtfKEokaN9IFtlNJgtSM1AaU0VEJwcb+XKBSG3UpxzUGmFS0MqYJrY0PlchQarRKMjnsyDR6Lx4nCi24sxNQRuyOD0oo0NWQ5ZDl0W4pQKzpNKPZhaMeRg0IdztrX6tCu6WmVIukDtwM5QWZ4KVAiWKWbtwgEcaigCBJn94tEq7aAZ2tzjwcffJKllQFnb1nkDJ3ncCQ/v4hA5Q2lT5iUmp2RQ6GYlaGxiUpQ6QJaUjA5wVW4OlCXltJqVFBoFad3TwthVAjOQ1EEQhAkCNHADMrSMatnKJdQFC2KPMEASXO4eR8oQtwZqvlcWhNzRLRWaKMOltn5eOxq1di9SczpaGXRwss0tij7jnX6iLghFsji++x3epgjtlr7h8mBdRaHAkjYF8MawWtfGFPq823hOc+GcqBngALXgioDEUVr14AoUufRPiChETiKKDaFZv9JDsqCSQQ981gNruXxSZw9bgFCI5CUUcQyz1OuweclCZzywhuDZqqh6gZ8Fi1zPuvhSglXduDatefnz999oc/10WP8/sO/D/Ya5A8yqXZ5anMHQZh4eHDUnBJ1FJtmwPIZw1tPae6adLHXTjMrWpjEspBYTH4S2qvM9NO7K4OKnRKBp4taqqls73eFJMmA4wv3kuuchCWussYeQqm2cIxZX7ibcdql0oZVdZLX8GqECQlTDDWCIZAg0qWeLVDvlIRpQtW6m7AUeDsp36dyFpXBSh9Dm0/3LrJMhzO1YqEJFVIi5C7adlZaMbWacGB2edjFIsBNDZ+0scDeXYC3noA72jBImvUPxAuUp40ZHF6wfJX81BQBS0VKyWJwnKmETg3dcNht9vTnv3Ac/VtlDVduxJyL3QrGM6hKuDY6vMZwJn5OVxZgZRlUH6btmNPRVnC/jZkYl/fAr8dujLUudM/DaAYbe1Dvx3oBuMP3Pu7gfA0LPlpn/UE7igsXy2hzlXv4WAILCl6m4SSwbeCxFKZaiLJohRiNhIxjRcJFDW+qPteq6pm0BO4WuCVAoqLV1vYXeU0ucK6IWUeWZowiZgFpebpwMpfR58yZM2fOnDlz5syZ87XIS1b0sEmLpPZkwZE6jSuGTKc3SEiQsIwWTRE8pS+ZjSZcefQm29eusnKL4dzSGbLE4KmoqAGDJqDEAhVKYqdHcDWhdriipNzZpRyPkZCR2oyA4LQcBJB/qc4k+89VPL04A7GA2UoSUmvopwlWg25EGSUOhSfLQBlNr7fMydO3opRliqJAsbU35PHrBTCjlVpW+2200lxZr9idbqOUJi1SNJrSlwcZE8/EaM3LX3Yb3/76e/FieGoYuLqxTZZ4OlmNVkKWdTmz1qOqCnZ3NyjLGaa9wGAlxVjLhX6PVruF8Slp0UGHhIWzGbeanPG04r7PPsm1q9uIs+giQ0RwUjFz02gjxJGNIxoJ0gQqGJS0sf4MBs9jO5aNaQJYRvUJCreC4AlSoVRFq3KwW2CU0FWOFEGrBEsL0EzFImKpgRGGCs0w1TyVmSheNLZBozphVC5iCSQmI0tDPGZ8hfYF02CpJaMWhW0K2Vpr0laOtZbBIGOwqFhchrbVLLcUiYbcNivpiJW9xpYEE/+u0bHDI2h1aL3DfgHsHPBngQ2c/CH4D8fSm7FYNBCFwKAhDZoQkiYBpML7wGfve5Q//OzvsnZ8idsuvIl77r7tSzyKn3+8aMZlxvY0YW/iubkVBR3nBe8hqDZm4TYSEcgddbEHTjGiS1nmJImm247WXBvrgWvrDgh0WjVp6hGXkJKhEDa3C9Y3Nxn0W6wudFAmo59DrxMzcMYTx7SsSRNDv5uSGA0ti7XRjyxJo6DkvDCeOYIXrA1YE/OCep2EfsegNDRxKk9jvzAYUgit5jEOn7cvYBz9uOr94q6OnSj7uSL7otn+a+eix3PDzCDdgmCgXIa9BehsGdYeapNNDPViQb0YMxtaU9B1dGUqFsEnUCcxLDopAyGdkc4UVVcoerEFIdkDVUX7mpy4H5MpL1ygB6C6Fd9UGO6ZJZSZsHXeMVkNPLIJv/AY7I6gfBDKx5+fv//f/Ylb+Ve/++/45+/9xbgx9IQgjvWdIT4I6zP4lSegZQ6FioUFxZ/7ixk//K0Z6oGXoX75z7H15Fny4z1uP9VHbA7pSTatIg3Q9rEQW6mYWXJULNjXlbXEzg+vYNA5x5su/gjBTelh+X2VohFq5fDKM0y7XO0eo1KGV5k38r0skDNmiSdps4OjTckAH3J2Nm9lT+1Rmh6baz9Icbykqw2fsgkGhRGDxrCXtrhbVjk3jgKBAbQIS7OaTlUzTi3rnYzSqoMsD6+ifVatY/fBr7fA9uFPXYS/3IGewKn9z/z+jIxnOwdonttsjS+AoSZnlw6bXKzXePtEyPNov/VSYm8E730Y/mATUg8tF0XH9Um8R8EsjR1033gB3vlqyNrw5DJseNhU8L+0Yehh836oPhK7Zb7xlXDH6+D+x+B33g+7M+J4HhtSD7bzG2bww1ux8+jX+/AvjsPFCv7cXgx0/90e/I8DGAT4kRmcnMH9jdXUE4kQzapuctal/NDwBK8fJdwt8G3yxXelBnrETo9SwXc0i/jFXrMaoB8OBTfgSE7RnDlz5syZM2fOnDlz5nxt85IVPbSKs/tVCBAgBIfzBQqND0m0RgoFwde42jEdl4x2Z3SWSyR4VBN/emDvJB4lKtoEqfhvQgyfDiHg6xpf1Yg2aJ1Giyj15dUNjnZ4HEWhsFqRGUNiDgOV97s8REkMvLYxY6HbX0DrFO1BeSEvAlrHXaa1JrUmznbHU/kKjY7dB+hmvZ/9m6tSikGvy+mTxylr4fpki1k5JQSHVjVGgaFNluZIIHbVBIMxOUmrT5ImLC4tsLDQRUqL320htSVt9ei1++STKa32Osq6+OVZJYAiiMcH12wj3YRxy6HfhFLN8hu0ylEiTGoY1bEXxpPjydCUGCoMnuAPI+INjoS47w0awcTAaKUQUdRAiaauDTPfhH37+B5VAB+ilGCUxugoepjg0cpjlTrYT1opjFIYo0itIUktaapJEkWSACmYVMXoc8VB6r245sA4UuRWTfVb6acXHgCU7pDYW0iSLsh9eGkizJv7eAy7mAWxnyPTPB7EMxyPuDxcp3I1k8nzkFj8FSAovBicaJwLlJVHicTOiqaDxmY5gkYnYyTMkKDwzlPXsRNLmm1Z1cJoFNAqkCaeJPGAwWiFBEVwgXpWU6WWuhacawLQdYyjDxKo6oBuRDBN7PSQ/Y6exiA9iOC94Hw8hygCRsdOD9v42KkvMCXWHPzv8/AsJ40DcWQubnzlSLQ0C2XsLqhVFDFEFNnYkA8N5ArXj4KkLWKnR2hGSdHgEijz5udWwAA+i++nGvsc1VibhSqOIcqDeQH23zem8Pd6IEZYreG40tRaWO8oRguwPlU8pQzXgsKPPWH0/ISMnD/RZ3PyET595bGmt06hUPhm6kAZ4PI0PlehUcpwLNf0VnLuuStnNFvkcvc2JulF6A7oLi3hdUyVLhtxII5LTQ7BEbHjoHDLfp9H3B+JadHunEeHaLW4rWLXXq3BK8XUwMSCF6GnV7hV3047jFmVQJcMR49KreJUxs2yzdZoSpFntHvnmbYyaq0YmsOODS3RlmgpwKDyB+cVHTzWlaRVjVEeCQrxGlEmdibK4XrsEbsWEqXIW3D3Atha0FOQWghK4fX+X2xoEqhr4VmvAF72EeHb/7/wT/5fX/oBGceZgsCUVqhZc0LmYqfAS4naw/YuXLvJ0zsrid0PNDke2sByF+5YhbwVReVWiMHvVy1cB5iCXYdWD4614Nxx2N6KQt0EDme3NF5rSmDNwT3loRj3QBa7Pm6p4RUFvL8Nlwz01WHnxljHTo+HMogq1oxQBgiBpQoWRDgennFdQLR10/NBYc6cOXPmzJkzZ86cOXO+IC9Z0cMFxbASdqeOrvLcVsdqgMZhZYTB4LRB6wzRGdMSdkee/iQQZoIkgtEJqbGEIDjvEe/QWjBaI1qh8xwrCdZ7VG8JSKO4EmZ45RH91ZnKePDdWClMmpHnOWmWgQHRIdrwSCz4G21wWJRN0UkbY3K0U01HgEM1okeQQOk9Wmu8AI2I4MQ1Rf74voeFoP2vzc29zsH00QRa6YRe5piNZ1y9cgPnaoqgKAUkeHw1QbxjYBKyQRckYzZrASlKErTNwSSoJEUpQxCNqxV1Cc43tlCimc08ezIDJdRSE/BER7FYyRpknnYecK5mPB3hXE3PWhaTmNQ8qj2FDzhqSmocnimKbRSGwB4lBkeqoWXzOFs+F8gbC7NRga883SRhtZWilTCcjJn4GTmGrk0QpbEG0hCLdENfULiaSjReJoCm1erR73bJkoSlfpt2lrPUajHeU2wbYbQ5ZbJX0EJzwqa0tWaSKPZyEK2wucWmsSifpDraGVlF1nwa94vcd17s8Jf/8hlurPf48Ic6fOLjBT54qpASVNy7WuWxoBg0LsTAZWcB5VF2h1RfIVUF+mnu/i8+WQJnjmkGXYGQxCnOyIFI5VGNrKXoJhn9dBDzMdIcbQ3WKvI8dmqsrWistigltFqaNAmEYHBBEwL0un3OnFTkecKJtYxuF1qpaiykFHlmozWc0Zj9wmXTzQPqIBTWakUri8e30dEGL35mYyuHED+XNOugjtjWzHnxSSp4oITPVrEofcHDmkDIAtNjBa6vkcyhPehaYWc5dmrBO8RV+ESwi4IdCDqAS0FMvA+NaFl3oPRwvYYPjOIM8usD+Ibz8J5PPL/r5xMoF6BIIUNjJxYIsYtQ4LbV2/j+N38TO3WbDz72QT7+xMcPjtevKuNXg/s4ALezxlu5SIblg1zik1x5mu3i2uAebll5KwuDNhvrKe99X8L2tVM8sHiOvVsH3By02DbxQmVJoOPBHlnkLEASosXV1ECl489OxVyPTu1JXWCvvM6D27/PsLzBy9UZvoHbsSZnt7vIJO9ypWX49GLGXqLorrXI7lxGzxyTG49Qj/6Ipc493LJyD8Z2+WxxH4/sPUTqjrG2/B109DkWxtc5tvMY1lcoXCPxWGqdISp6HCqBiRR8onycJ9wmhdXs5QneJKysvIGVldeTimZlWtNynuqS5YnfTwhteGII/3kMg0nNrZd36U1qHlhu87ETfQp7REldAu4A14P395vskSMsLsIrX/Xcdud1hvwbPs4HeJJatSn0a+KkkOf2Ns87yxl89xm4a8DT23OPKmFNJ969y3CsiAHyYmFNwwkFKxqGAnSBu6CbwasMnNyDvoXF22Ay5fCkPgAcqG147QzaTdfEt05id8+5Go41dlH3zuCvbEex6PYm4OdcDX9pF25amj96nDVnOVdmSBAeSmve154y0kLTK8Rxp3nbJON0/YUU9Dlz5syZM2fOnDlz5syZ89IVPbxhXNbsjD19HJM6NCGfNZY9LIraLKBNBzEZ4xlsDx1LY4+fCqRg8wSTJjgcVRhR+xqrDFolYBSmlZAkChNA9VdAtwjVFq7ajXkR+svp84gc7fY4mHSoFDbLyDsd0lYOVhG0YERIUHg0WlsUAW1zTNpF2xZGW4zTaFs3gedxRmoZ4uz42OygEQTXmEzHfo/YLdP0tHAwh1Qp0DkqWcBoTycbMshrxjcqnnzgKuPplC2ZsSMFqdEst1PyxKJbyyxJHyUtppOU2Sxu36zbxiQJVmVYDEEMdaWpZuDQB6LHdOoIE0/AMWOEo0IkQSTHasVCC473YVwUzMpNCjelZ9tcaHdAFDcnNXveM40GTtQIYxQVGsFTUxCoaRvNYi6kBrpLQmcQkFmNr0bUrqSTpJzvtNAErs5uQr2DtSntrIcxFh8CPgQKCWw4z5YLB1tPK027Y1hZHdBJU25Z6jBod1hptxjvaHwl3Lw+Zmtjm0WdsJh2aZuUUQ5XOopgNe12iywzZG1YaGmSLBbYs2fUMF5+V4c7bj3HaDjiH/2jLp/4ZIFzjlI8ThkSlZCqFogmeEUdPKiAswExGpVsk5mKzEwxavxlH8vPB3kK507GDpzo65Xw9OrUkd9UC0XeWDkdihL7H7B8TXNsRR88rpQ0OT7x34MsIKEPSmGMPsjC2P98tnNLu1GcDiynFE0X1SHGKNotc2gx9Yx1CiK44BGihZxpwj3mosdLg2QGf1TAuypIgb/s4XiAkHsmp2aUtSKdCukUdGVIpm2ScY6ZFCTbgWA8yalAKoK3ULWgskeCkRXUXSCBS0P45Q14ZAZvPAff/NrnX/QIKcyWYNIGXWryzTiWKKlQAi87fiffdNsPU+oVfvrdP82nLn/qSKfcV5HhG6H+9wC8jBP8H3gbfVr8NP+ZT/MU/sjn/MTia/iG23+UVr7CjacU/2ET1rXhoyspO6uavoeFoKI9VIBeMw9h/x1yH0WPSsPMHNpZueYz3qsci7Oa6fBxPnPpf+aJ0ac4x1u5lz9BO1niyvFb2Vw4zs4g4/KS5WpqkRMdyqU2s+GQz8we4Prod7m71+bbL5yklS7yXx79NT6w/nOsuZfxHf5VnDcXWB5d5XWPvpdWNSJGTdfEaOkB8WiLI8gVhvyavJ/f4GEERVBgbIs7X/YjmLV7WQgJx8Ylx6Y15cMpj04Nk8TwqINdD6e3KpKP3eTU1pg/vHONf/aaLju52d+ccBvwRuBE3CbVM04+Kyvw+tc/t915lR1+kQ9hSbhbneM1uibXR3KoXiKsZvAXzoP7EjpQEgNpAZSwzKFG8vbmZ3rAK+MxlFjQ2/ByC2+/8+k2hNGTDLgZR7Cs+Th95wi+bRxlirzp8nnDLAa9w2GXzMUKfmibJtelD/TQQC6x6+e+rORnl3d5ynricWR5dZFyW2XnosecOXPmzJkzZ86cOXPmfBFesqIHKkaQ1yHeggASOxiC+GhipGsgoA20ujn9xS55J0dpHZ8L8RuqHAaFR+scG4utar8HI8Rg8+ARL3inCC5a43wlZuzPtLlSxEKqNgalNUpFOyq1nyB5UD3T0bqjWX4fPLUXvPeIRP8KkWj5pZQ6MnN238MBPrck+8xli7Ze0viERNukgJNY8DdJSsumpEaT5QlZYkjSNsZkaJOidArKolTSLI8GHa1KFJ+7XvvLKI0HkFEGlEWwoBKMVhgjKBXQWmONJbEJ2hh8s06xD0D2txAmmh+hDtY5WpYEkdjxIorKaxIXrS+cKIIoalHMfLSoUjYhy1sk1tJup1hj8cHhXI1Fs5gd+lApbdBas7KQsdhNaCWWlhVSPFLOGG9uUU9mDDc2GG5to5RlI53hTMJmptiegDeKWadFlqVkLY33miRTJCaQmFgxaQ5ZfPA45xmPxzg3pZUbKiXgIITQiFmNxQuKILBv3KYJKBVItMfqgHoJmnSbz7GC+kLH7Of/NxUPvc/7XLM/xfcLvfOXWMD7Qs+Nde/97o65J9VLDWeh1DAGMmlCxn20pvEWUIJ2McdDi1BnAXyIeUOu2b8Sh42jHyftQbnmMYkdFyqFbgoDD4u0WC7awNbzu4JNgLquQZTgWoEyC2w7YXMC03aFnuzitKGoi+dvOVTJvjFkhWeXWcwpSnsM7FncfnS30uSt45AN8EmfIsCshJmN+yrE033c3s1bP/Ms1lwWHIy1iih6zHTMNCiVwmtFMAlJ2ifLllDSpyTH2JTaWILWGKXohCZwGoXWCmMSsmSBVrZGMClb7iaZKih1wLaWsfkCYhK8UlTGMsnaCJ7UKazXVALDsEsN9JTQV0KixnTSXfpmfLDsxjgW2yOWO2MGVcLAj+nPKpZGOSc3AxOrWQzQDUK+M4Oxw08CydDR2ymps4o9NWbKjHQro3dzAaMTJIyo/PBpnTXFGG5uPLfd6RGmVCg8dahJfECHwJZWPJFASxRLPmZZvJgYBe3nckXbfF6Pjgz5/g+KqGLs04gZ+bO9/1FftYaWxNtRUvncbWQFukdV06e9rZAFxYLXTJXQGKQx8IrkpTecz5kzZ86cOXPmzJkzZ85Ljpes6KHMBK89lRIqINQKSoXDMwwj1P58UaNpdxyveOOtXLz7OFneJem1cFYTgkdKj4jHAsZoEpOR2h5BYFZuI25MKHfxk5u48YhqIpTjNpULhHJKTKs8SpM2DRwYOj8LQiz77IdSW8AqhbWGJLEkNsXoDKMSjBGMiYILM01wCd4pqrIAE9gbO7anjp3hHlVtgB7eK6piF63Bu5J9M29NTvwaXxCYEcvgz1g2AedmlOU2IQScn+DDjGBrVBeSNOWO03eydOLWuLZSowi0ust0BscwxsasEWUQpUEMymmMTklMTprU2MRgM0VwAqVDicFkCWmaYowwyNoYIwSd4m0r2gnJlEJmiElYHBh6oUY5uFqBBKEIgarJaWlRkROwJDHcHodHEDTKC262i9OK0i2ws2cJXlEUbbxkXJ1Z9nxCajWnFhc4c8qQppp+T5NYRajH+GqENsK9SwlJV6NsjmkNUCZB+xbGtwiVUO7O8LMxo8ccn93bRmnD1u42u8M9rDLcb9okyjLVgbFxiFak7RSbGtIko9PpYa3BpDN0OgEEVwvBw/ZowuM3tpgWM/a2H+fihWVms4qrV0eMxhWCQqk0ml4EhQoKHFSVELRglWKxk7DYtiRWHWTefoHYiTlfAUoprDbNz81jL+LyzHk6W8swnsRCsw7QmkFvL1pUlXl8vMhB90CHgF2eoF1BNvZ0Nh0qCJI1WTLE98BDuq1pr2tEwfhkYLISWE3gLwpMK82Z2R1c+NDrgF94XtfPzqB9BboJ1N2a7dsDNwP8u23Pp65Dmt9H+75/QFAZD1x/ABeepyTq3gchiQLPH/EU/4D30DZdwsm38JYT/1tQugnuVsjgPJc7XTA0dnPx/HRLFQUqGyCJDoUEBYWJeQZpI4TUGoqmu0OIReSxhqdstBQqsJSJpshv467WX+MWt0srrPKRcIpEpZRZF5e0MInmG6eaWSksusCSF6QccHHpndTpW7nh1vnIpXdR4lhcuItvvufv00qXyAcXGCfwyOo5tvI/Tl6VnL25y7HdMU/Uj/Pbs99m3V/jWxPhuzIwWc03nt5gdTGujzOgbeDO265x560fJ9/SLDywR3654HjS5vYnF6i1JhdPKp6ktHQmHWpSXnFjyl//6GU2zZjf5Hf5EJ/m5CN38MeufS8rveN8aPhe/nDvP1KF8mDX3OfgH3yZepcC+pXjlmGBaRX8Zjtl/bjhVQV83y6crr+yw2bO5/KqIuP/urH0NNFjMWjOVS/ZS/c5c+bMmTNnzpw5c+bMecnw0v3mpEuaGm6coR+iZ4WXgAszwGFsjmFGmhlOX1hFq2NUpWY61nhP7N7wUXowCEorEm1JdE4QQUlA/AxxU3w1xBcj3DSnHrVwIRDCs1UHjpaNv7A1yL7g0WSLxpvWGGPQxqCVRSuL0j6GfqtYtKeZhVy7GgLMioLxpGQ6m+KDAfIm1HlKUIKE/YRsg6IFWASPEIvoz7psoaZ2EyQIPpQEqRETIAOTWI6fOMNtF19NkEBRTPDeoWyGztoopTEqiaKHgPOCBFBiscZGOy6rMVahAyhCbJYwOTbPsFbRayvSROFNSp20AUFPFVUZUNrSblnAM5vW7M4qQpA441oFEE9KfF9LiiUDHIECweOlpnJTAuCqNo7G7ogUAYpas1Eb8sRw/OQyi8d6ZJmw0PckiSBlQiiENBVOnc1ZXLLorIvtH0PplNkuzPagGNdcG40ZlTOK2ZSr124SQmBnssvedITHUKucoAwhOLxUoMC2LCY1WNOilS5jdIrK91D5LiKBuoTg4MrmDp987AqzuuL2Cx1uPddlPCm5sTHC49DYJhw4Cho+xGK794IKceZrkmpamcEYRWAueDyfKKLwMeelyaQDZXYYNp5UUfioMpi1mm6PbL+LQ9CDaAvV2YasAFPH+Jl9JWu/AyGdKNo3DUHBeFUoM+ga+AbA1oruU8fpPfnq5339dA3ZDuQaql5gciywVcIn1uG/3gC42tyeZ7JLoKOd3lPs8BQ7pHrAmxb+DK8+87/BKItphqXrCVzKFF5BRyBvtumib0LnVZw8kDStHPsZFftdN85EcWR/JDYChYYNG3sCO6JpKQ3ZGid63wpEweTxGH9EGppQaIHby4BCSLyQBI8Jbbqd15Nmng9s/QfeffVd7Ppd3rJ8L3ec+h60TggKSmDWW+Z6f5ms9uh6i7TY45Ke8p+LGzzKQywZeHsGWRtuPwYrJ2PQeWVBWeHOW3a44+ST8fxc7cB2wRodLrCIYNDUaBwlXTY4z4yc08OaW4cjbrLJx/hD4D0s3Hgzr9n5Zs5kfW5s3McHb/wGhMM8p2vN7ctCoOUCy7Oaoqz5VGb5w75hpOF7hl/um875fCgUZ2rLmfqle5k+Z86cOXPmzJkzZ86cOS9lXrLfpsQbQhA8nqAUyqbYrE3wNVVZEnzBdCvgrk0RpfFZhiSWRLdoJQO0MrEAqaLsEIJBCHjxuDCNoodSWNvCmAKj2uimhFxJRSmhCXl9psXVkWyML4Lh0LRAiDkc41mB0iNSLYgsxHwRNF4SvMRUDkFT1p7ZcIIXxcbOkJt7YybTGVU1BgrqOmEyifkFtXPEso9DKACD8PmnXYoIezsFV54cgjIMS0MRuujEs7RUE0SR5n2qEBARBNPkIFiUxDBN19iHWaNpdxKs1gw6HRa7PbYNpCajrAy114hEczHnPUVZYRwggjUQjMOb2I2iyxJVx3VROopVZSEUXhFduCRWLNGoJgPCYA/si4QWgiFQ40gICJ6cgCFJUhYW+mRZhq/GVMUumQ0sdGtabY+mYDrcRknVVNsCpVdsbAdmLmBzIa8U2mjqIqV2KZUSQq+LMp7MZLRtI97sbWEnu3iBKsSg+crNKKtJtBMzoZkmbvChIgSHTCtCGc2pgvNIEIyHxVabTpKSqIzZzFLX0E6XWOx0SExOZtox+DtMcFWBsppgEsTGraJNoKoKPvXJJ6jNJ1lb63PPXafodfNnPzjmPG845ynrmuAD1azAVTV1VTEbjfHOUZc1VVHhg2daTahciWAJRAu5QItwYMCyb80Hh+ei2Hk2nb60QutfKmQVJO6w+2bfqkqIxXNnIB9DawQoCHkMOTb7auGRE7oifoSVgMuF8VpTrbdCPoWkTOjsdjFVylPTKU/JZ5739XufwFs8rA/gCQef3YD1CjbLL/7arybDyxfptKYcP3MHSYBWgMS0kf4FLqWaHMWyjwIHKnZx1MBEwa6NFkC9AIkI/UnNwrhCK4XNU3RisXIoLGqJmR5BxV0UJMYxrDVP6Xp1ILAcJXaGCJWm6Toh2h0CTimqYNAS8JKQWAODM5w6/nYWZMKgdysoTa0UIwOVEtYmO1zYW8dWMzb3LnOtuMG2PMLd7RG3ENMY3lfFy5GNDRh7GJhlbsluI7cDdrNX8VBylnoXNheWmZyrMJKTSBfNYaeHI2ckS9S0MTiMqtjxnuFeBlMwztMaF3TLGRfcCd6UfyO1n5LXM2yoCBgCFodwiad4kutPs7/a566Vb2N98hDbs8sHjwnCjeJJPrnzXoJZJX3wVVxcuIVTGtIjYuCcrx5fKBFKgCcTeDCLx/CdUzhTwtbeJvc9cR/jyYizHOdWTlLheIjL3GCHVus4g4W7saZD2nx+AI58rA5HFBVHlfH0+VrDOXPmzJkzZ86cOXPmzHn+eOmKHnWCD55KPLXSmLxD1luiLEqqYkRV77H9WMXWwyW1MuwOuhR5ysnVY9x94Q7arRbG6DjDXYTKqSiihJpQbyICWifk2SJZqrB6CaMtTkaMwi51CI1s0BiLHxQYjxYbPz/70cyawyDz2ntu7u6xMRxBWCLcskpiMzyWylt8EAIVKM945ri5sUFRea5tXuPG1g28DxRVBQSKMmVz26OA2ayi6YkhLrXiC1lvhSA8dWXER8prJHmLbG0V0+1gWyucO3drzB3p9Jg4h0JhVYI2CUqlKEkRURRBKEXop5aVlT7dPOXUwoCzi4tcv9niPUmP8Sw+t3Fwp6wqqtqhCOxpj1KhyfTImgVzID6G7yoHCEEC3hPXSfblI0M8dI+WBAywEI8dPKLK+FxJERLa7QG33XkPKyvLuJ1HqNY/hlU1Z1YKlpZzpsNtbl75I8rJHiZfxbROoIxhc+rRidBqeQZLmiSx6HSAzhbwOqM6sQyqTbff48zqCkYrdrbWGe5t4HxNWY7xvmY02WV3uIlzFVU5xFVTqB3VeALOU1YVRRkzaoyu0NqTBDi3sIRH8AqGeyBBsdxdYrGlSWxCluaE4Lix8Qg7O7tImpKnCxgMxoA2NaPpkH/1r/6Q+t88xFvecgd/88f+xFz0eBGYFiXbeyPqsmLn2k3G23uMd3a5+tglpqMJw609djd2KaopT20/yc50m0CLikWElJqT1Bwnfgb2cxP2z0dCLB17vH+mJd8cgP4I8qLp5GginbSPdn9lArWF/i6sPhbFjulxqHuQ1IBptrI5PA2Z5lRbDQLD1XiubU2FwRakkxaD62dRRYf/6Lb4f4d//4Kt5+wYfGAIv/QQjDzsvMCHw/qHv5WVhbdzz+sUCzWcKAGl+eTiMr/fjvkUry5h1TeWSSF2Z1yzcDWBZQ93ldD1cNfNCa96fAdvDY+fXWZzOV6y7GeqJAFsY221b3HV8rDaaP7JkcwGw+GIWDctb/vTFzRgRDXvG5+pxGBzixag/1peffwCTjy9ZAm0odBwOYWhgdPXn+Bb73svUmzxz+tP8pvuEW5vFfzFlW3OZPDeXfh/bsNkCm4Su4penV7g+7s/wCC5haf2TvHh7ROKCyhJAAEAAElEQVRsKc0Hz3iunBQGoljzhkxgycMgCEo0WhIUGkEQJYyLFtfu78IUkrJm8eYex/Qe35S/kjv7d2J8werwKt1yF0dGQY8Jjl/iP/AUN3F8rs3Zn7z4t/m9J36WndlTSHO9IwTu3/sgV6YP0tk8xd3v/jHe/sgt3HUaOm8EFr9qh9CcLwEBPtSGf7Ichdn/0xU4M4FHHnqEf/wv/zGPXX6Ed/Kt/Hd8JzuM+J/5df4rn+L4iW/l7pf/TbqdDgs19Jvdvx9MHzjMyak0OAXFfEiZM2fOnDlz5syZM2fO1yAvXdFD1EGYd5zcr9Fao7SKs+GDoyoKZrtTSmUYoplWjkG3ajo0BKWiT3gsbMTOBJEAoW4yw1OUsmhtYxcDtsni8LgmDvornb549NUCVM7FkmVdx8wRkWb5dOxkQIMSQvBUlaOsaopZwXQ6QUT2k0wI3lNXsRgRwtHOkxggG9e9mZLchH3vP8MoTV3DaOxIvYfakEmKNYZWkqKVxlmDF5pXxe2g0OgYkU0Mf4/VQ2MsSWJpZQm9VsIwTzHaNFZcMWgaBUEa3y4C+P3ulP2ttC/UhKN7q9luR7tt9p+7X8raf97+Y/pgG8QUXI0SMMbQbrfo9Tq4KqXMBIMnsx5tPIqKuppSzsYYNcAm0SIqiEAluABJrklSg1UpNm0huoVqLWKSHulgQGdlDWsUFYLTGu8rzCzFuZJaC6kv0HVJoCKIQ4IgeILUsQugDCgCiQ0YHVBak1mLoJgRqFxAYUhsC20SrLWkaUoINXmSkacpxlqU0k1IrqCU4HzNjc1ttscVt15Yoarm5usvBs4FptOKYlayuztmuLnH3tY261dvMB0O2d3YZXt9m1k55cmtx9mebOJpU7FMIKciUB8c7yVR6NyXVA9FD5HnKavhaxzrm66N/dPFPioW/ESBqRXpRCEW6lIjuUL7gCgPGkQfzojeDy4PBuq2RPufAowDW2uSIoNZzpCKx7n5gq1nSAx7PnBlKky/uD7/VWc6XCbp9uj2c/o1LBbN2TuFoY6TAeqm00LThMo3yxmP4MOzedcH1mpHLcJ6ELQ0UxD2c1Uaa6p9DgWMw9/37w/C0NX+4+pgJvvBYXHkegHASWMJqAb0zABBSJtGPRHPLNSMlcNXO7TG1/HFBkMuc5knWAvQs3Asicv7hIdxUFgfrSGH2SJe34Kk5xlPF7kxGXAz0VzqwBMprDTHV0ugqmHs4nrljSWXNMs+tTllEi/lRDy+nuAZ08n6nLLHSXXJMavo1W1qWkzVgBE1iyyT0uZk93a+586f4valtzajPEyqLfrJKrlq4aWmpkYQpn6Pqd+jS8XdG1v0simt3KBdytw88YVFgCHwBDHLZtdBVcJwNOWJa0/yyOVHWVd3M9FTRky4zgaXuEqhthic8vQqYVrWTMsalCaYFFEaEU+QKl6v2gRnLPNLhjlz5syZM2fOnDlz5nwt8tIVPXzVdD6Al0BdjShmm7hqig4dEqVI2gOSNU8QTZpkeGOxuo8oIeCoRKiDEARq8QdFd6liUcOpgFcOFxweF8UOFXDsl83liFTQLBc2diccFBnD56R87Jcl3ZHfn0lVeba3CnRlyTo5WdeAUlibgdL0pUIFTVXXzCYDdscFzjsqN8UHhziFzJplepYa5+JCztpKG2NSEnsCbRaiwCJRvljIVulnK5gkJWm1o82WUgQjiAoEsYhXBFF4p5CgyLuWQbeFUppZ6Shrj/Ga3Y2CceJoa8NSXzP0Y2osSvdIUqHTAa2F6aRiNq04TDo5eg+HHTXPNNyIQodWFqUUIoEg7mnPP3haI1tBQBNo6ZrcBPpGYapLyHQTX16nDgEviuFwhiihnDlqe4zQGSBJnyAJBIOrUoIySNKlrRbwpkveWsP01kjyFstra2SdLscWM86d1FitSFtdTA51VTLZVdRVgTYKawTvSmZjoSqgmirGbpe6rKmLgmE5Q6Fo65REpwRROG/imiiDQaO0xiQZWmtc7SnHFak1vPUNb+fC2TVubN7g/Z98Pze3NiBTZIlBhRor10nFYMMa6gtYn815/rh+dcoHP3yT4d6EJx59mJvXrlLOdtjbuERVTignjmLsCOIo7AJpPyeoDKu7oCxBB4Lajt1TPoqOWnl00xW131UlotjdebHX9qWHOnKqEBXDyyc9qBPIK5Ba0Sr65NUAVWfYG4v43TYu26DsPEYwBVUb6jy+j5LDjoPOMP6sBeoW6Nrh9B6KksCUZx8Fnh96N+4mm9wEucmX0pX41eaxpTbTNOZ2lBrWs7gUiYazHgYBFjy0PXSdoIPggcFMuEfH7C1tDEFD62KLtZctUwZFNk2RKnaF7NooJPQc9JqOES2HeS1HCerpv+93+sChtRXETpH95+8LL7bZp/tdJEqgXzoWC4eu15mM3st69SR/sH2Vwj1EYMKn2UKAazX8m21YsfCpKVQCbdvnFUvfypnOXQzy8zw0OM+ldJFHllo80lWMLey2gAQu9OFPH4O2gg9dhT+6EbtYztTQaQLesxAFo32R5yrr/Gt+mzW1wm3Jm7mj801kqotrnSFxK8xsxm7SZaYDLfVdvJHbIV/h8dXzXO0YjjnFuQpM6PC61jdysZew7q7x/uJ9bIQbB9uwciMevvab7Iwfw+UX+dby24G1r9YhNOdLQAH9y3D+k+BLuLYF7xvCpx+FyQyCUjy0tshvnriVSgsmKF4u34Is3sGT7QUwNa2t95Ffez/kK8gt34H0L8DWfchTvwPikVPfAmuve5ZeoDlz5syZM2fOnDlz5sx56fOcRY+rV6/yYz/2Y7z73e9mOp1y22238Yu/+Iu89rWvBWLuwt/+23+bX/iFX2B3d5c3v/nNvOtd7+LixYvP6e945wi+mccsnqoaUc02Ca5Chw6WnKRjSFYtwSvSWuO9wuoWIATl8CL4IE2xPxYJgxNCFfsIvA0E63HicHiccngCDjkQPfb7CvYLIwFLIGssH2Jx/dn6DvZL7/vFk2fOgayrwPZ2gcw0C2uatJOitCWxGVqnpDqhbzTOOTZ3+1zLKipXRoEmePCKMNufj/oMiUDB4iDntnMLZFmXLL+bJL0FCeBDnCqrSdBEmwx0Y8SlBW8EraI4gteIV/iKuI27CcvdFkZrClVRi2PqYWOzpJaKQVdx/ASM/BSHBdUjywKDhYA1MYi8mFXxvQ/MRo6KHvvb9Glrc3CvdYJWNoau+7rZS/sWP/v5LQYlHiR2TbRNyUJS09E1tgKZZoRyigsCQTEcFtRliRNFnawhVhFE40QjQVOFFBcSyNvM1CLB9LD5KlnvBEk3Z+3MMguLbdYWFedOxvBwr7vUpkU1K1DiqWcz0sTQyjTel8zSkmrqmSaeahYIuqbemzGsxigMKs0Rm+NEUwWNoLE6x+oMrRQmN+hEU+1NGI2m9Dspb3r9t/Cn//g7+ORnP8FnLz3Ik9eukFgFyqC1kDAjDRVWzqGYe1W80IjA9WszPvSHG2xs7HH/A49w+cqjIENEriAyRdNCSwtrDP2FAa3WMmiDsilohdIOZXaQoHB1gniN0Q6rSxTgJcdLQgh8zYgeL9R4Ak2B+4joUeUw7cYzTF7H2fvtsk9enUb7Lq3ZeUQtMV55kMnSU9StgjKPwedKDjM9smnMAVESBZEqB13UOLWHYkpg+qy5Cc8XvZt3kgkoNnmxRI9Kx4uLUsOosQZLFJzx0A3Qb0SPtoNeHdBBuBgCWoTtVPNgXzOzitZtLVbuyikKSD+m4EkVg8qT2C2iJIoecBhufpSjPZD7z5Ejz9sf2706zC/wKlr6KEBCPKfvb0Ut0C9rjo9KyskVpk/+KjeGH2AzCB+W2HHlmr94rYZ/uxNHOCdxpOqZHq9e+U5ev/pd3Ggl3LfYYS/VPJopHs3AGwgZYODcMfhTr4COgYcEHtyNVkR9HwWPJDyb6HGDf8u7SUn5k0mfk523UdkO27ZH0IpRmrDRyamMpqXO8Tr1nexYxYfbluuJ5u4ClgUWQpvX5m/mWPcu7is/xUP1/Z8jejxy7T/y6PV301/5Y0yr1zEXPV5gBPpX4OwHYTaDayX8QQ1P3IDxLB7Pj6wu4O6+QGo79P3d3B2EpxLNp3LLyE9RO38Aj/xT1OAicvIuaF2A2WfhsXehQkUyWMKefu3T8j5e6ryQY8qcOXPmzPn6ZT6ezJkzZ87XB89J9NjZ2eHNb34zb3vb23j3u9/N6uoqjzzyCIuLh2bOP/3TP83P/uzP8ku/9EucP3+en/iJn+Ad73gH999/P3n+pecIKGVRqpEOJBYfvBckKCABZbBpQt5N0B7qKtqXtLImwFxiv4DIfkrj0Y6AQ6kgBMH5QFnXzKqaynkaXQDNYaLH4U0awSNw9HvgfmHl6Gue6aRytPhSe8+wKFAokiKhW+Voo8AYjElidSXU0WTLxmwSc2TKagBqBK00WdZhIekdWHYoBZ12D5sMMLaNMTlaWUQ3hRwBTbTzojGSQoHRhtwatNFo3ULrDF97ZnWBC9HwS7QBY7CZRutAXXqkKnFeKOrAaOqZzRwmODrGkRtIDFgLvY7FSo5zgdGspq4DaEGZRmLy0lSXjm7xw3UWiV0oxCV5xhaNK6aa6dxaKXSTAxKCEHygLmqqVFGXDu8DEkK0bRAIyuKNRbRBJFbAROnY1aMTMAliDKItogwog6AJIYpt+4dZDHyPHUKKEGdLBhfbccTHTiMfmpn6YLTFmARrM5LEoTDYNMVmKUpierIoQ573yPIuJjHkCzkmM9SdGYvtAa0spawLLl15nKs3rlFUVbNs8fgOIVq9JUZhzReKRp3zfNJuJ6wd65AkgelslSyfItKnKQ+jydC0sFbT76XkuQWjwSQAzMoRRTmmrmBv11A4RVAlomOxNYgnIITwtTEv94UcTwAeH8NmFcOu4VC40Pv3HlAOlxVor0ENAU2wk6ZN5BDZjxgiWl4Fc1hI1wFmQXicmldx/cvcOl8+Lfk3Bz8nJuHYwjF6eY/RbMSNvRvU/ivr9Prvf/A0Q/fTTMM7OZqrlIUYQr7fKSlEO6pWs+myRkxoNZnvTsFEw8wqtEAaFEmAPasYGphqxWaAqzOFKwRfBfJaSFEY0XgFmQt0Cg9KUSYGpzWlhmkzCyEPkDZ/P6jDEeWoQPJsctRRK6z940U3VldBKWqjUSZjTa0yUafRKqDFH7xagBklm7JNSUUnWaKXrLCQn0JaK+zlLXYzw06iGVrNxMTtcXT48xpmOWgbjy9D7DxJBbIgZAHaLmC85rheZZpcpJAJW26TkopSC5U1KGsoE4PXmllimSWGUmum2jDVsGdgmkBpQXdgsQM/8nPJFz0OgtRxOUNFM5NhzgtML4UzPSiSmGPT91BIh9vPXmB1AmtnjnNizZJay8BbWhKvxyYJTLxGTi0hk/P41mkmeQvnQUwX2rcgvqCqp7jdBxD3tZFk/kKPKXPmzJkz5+uT+XgyZ86cOV8/PCfR4x/+w3/ImTNn+MVf/MWDx86fP3/ws4jwMz/zM/wP/8P/wHd913cB8Mu//MscO3aM3/iN3+Cd73znl/y3dLKINgWGMRqFc4qy0ijJUCoDq+gtp2QLWQwqL0uc9+S5JbEaERobpFh+MeJRIjht8KkloHBOcJVnMqu4tr3H+uYOwzraYgG0afzHgSn7hZzoOh57CsJBoKhvukJyBZlSOGAahH0TpiMpEwCMqoIHNtfJrOVWWUUrRd5qMzi2Rqu/QKgLXKHwVUXSsmRZQFRAF/EdCgIeT2os507fxrFjp6Ep0otStNuaPLdobZAwwNUSMzkaiyitDErFDJP9bIlW0uZkf5UsTektdGn32+ztjbjv/ofZG+/RDR2KJCfLMloLLbIkQ0YT/OXrlNMZN4c1+tKMyXBKpx5xW3sPldtox5QaLqz2Weml7I0qPvLABtc2p5jck3RrUEI90vjpfrZH1dwfhpaHUDUFqKNh8od9NrHDw2GUxmqDxuBCzaRSBIStGwXFXk0INcHXIIHpNIAIOs9JF1NMmqGCQknzvraNUil0u4S8hc9yJElBW0KwjIYK7+Js3HKNaA/mapQroJ7gyh2qYkJdTahnQ5yrmI4mTEYzgg9kSQerUwa9LkXpQGs6/TZpnoC2KJOhTcLi6i0sLJ8ib7dYPXOcVq9DW3l6uqYqJnz0o7/Hv/uHv8x4POHqtesQUpwzTIu4ndI0RfdS2q0crefe6y80SsEddy7S67+MuqoZj29lVkyJJeKCeE4xgIkCVaIxuuleUhrnPfd/9iEeevARNrccH/mIY3vLoxii1U2gQthFGH/NZHq8kOMJwD99DDYqKAJ0BNIKWrModtgKtBfE7jA6NgMsoi8jOsFlY5TMMHXUP9UR0UQJuBSm/Sh2JCUkM3iicvzrMPyKt9FXykpvhf/2m/9bvuHiN/D+h9/P//Rf/ifWd9e/ovf8/T+A4+dhYS12GCRymMhU6iMGgwoWnXByJiSNRVRA4TUUVjGycC1TXNJRwBgETVtgbBXXckVpwG3D+gTalbB6teTMriNpW7bSnFLg5O6UOzYmlInlydUee+2Mqzl8uhv//j1juG0a/3ah4/2+LdRhtsdhl8dB72HzD6H5N9OIDUZgmqas9yzanONPLvwllH4HeTGlMxmhRfAYAoaHuMS/5Le4wjp3LL6VN554JzpfZnPtTn6nn7FrFZdbipmGqT4ieNSAgy0Dn1qCtoVxGovaCzUcq2DVRZutpaJGVwnnsv+GevluHinv5zdGv8pNf5NZatnptkhsm5nV1EYxsZqNVFEYuGThyQRKAztZFD2WTsI33A783Fd0iMx5AVAK7jwB/TeD9/GYTgRm1UW+Y/h/pnIT8t5Z8l6GVvFa1ggUKmbr1KTUb/hO6uouhsMOn7nvdjY2Qdqvxd/1f6eq97hv5wM89qH/C/IVCqUvFC/0mDJnzpw5c74+mY8nc+bMmfP1w3MSPX7rt36Ld7zjHfyZP/NneN/73sepU6f4q3/1r/IDP/ADADz++OOsr6/z9re//eA1g8GAN7zhDXzwgx981gGgLEvKsjz4fTiMhSKlWmjlUSiUQAhR+NDKYHWCUpo0y8mSHCQQSkXwNUrH3AOk6QwgoCTOulciKGVAR997Ic6Cr2rPaFayNy2YEQs2cY49pDy97+BowT0Gex8+ogCjFJmKr28iN54908N7NqdjtFIsdtpMJyWQMNAWm2V4LfhQoppOD2sEq2W/SaUxdhJEK7r9ZU4fPw9K40kQFUtQomLsuYhFgqAVoGIYuVIGpZrit3IgQmIsvaxHK89ZWuixsNLFatBGqHxBjccZi7Upttul1e6QopBE4wyMS8/mTk05rkl8yaItCVZwJkVbWFtIufVkn42dgvue2ImOVDZgWjVKCX6W4A9sr46ag8WtKIRmRunRpJSjfQsehcQwVtXsm6CpAuhamI0dVB6lHMrEvVbXHu+iaZlWFnSKVqAlWkORpCibQ5oiNkGsiZZDGEQ0VRGDX8syZrMbQLyHUIOvCK7AuynBzfCuwNcVVVlRFTHxxegUrS15JrRbgFbk7YS0ZVEmwSYtjE1ZWl1l9cQttHpdTl84S2+hz0IOxzsw3NvkP/2Xf8Xv/OHvYFRCL18kMRkhKGov6CZs3mqNTaLoNeeFZ3m5xfJyq/ntxHN6bV07lATGexOQCkVBMdsXN0bNvQcmvBiWRl8Oz8d4Ap9/TPnwMyy/tAdbx+DxpGiaOXRB2S1iuLmJXRzSnCb37ayeSdDgs0PRwzjYc4EPy4tvI3d99zp/99f/LuFXA9NqSjttf9HXtNMVvuNlf5/Xn/vfURjDjRymyvHAQ/+MT3767/DEZUV3VVhcBU0UNDSKUkUJT44ICEmApVrIvRBUDA6fGcW6hVIrNiw8mCpqFW2VegIzA5sJ1BryGcguLFbCm0aeQVkztorMC4KiV9asDGdM8oRrS21EwdDAE63YOXGmOBQ3nI6P6SAHHR/x39RB7yDQ2D9y0AHpG9HDSOz2qIwmaE3fD7g9eyVL+YyOH7GgttAS8KR4DC0yfovfA6VYbp3lruW3UecLXOlbHm1rJlpx00J1VIPeH/oUTBVcz6GdQm2gHaDrm5uDXi0MSkfqNANzkU7rDBbL70x+CwI4Y5gmCUmSMLOKyijGRjGxMNNwI4FLKQQtsXnWQnsZztz+3I+zZ7MRm/P8ooDVXrw9nWXgzV/09aIsRft2qtbtbFwDLsPlaxCSU/jVU8yqLZ5c/x3CU7+LHHQxvbR5Ib+jzJkzZ86cr1/m48mcOXPmfP3wnESPS5cu8a53vYsf/dEf5W/9rb/FRz/6Uf7aX/trpGnK933f97G+HmeQHjt27GmvO3bs2MG/PZOf+qmf4u/8nb/zOY97VxG8RytBa0gSS5ZngAIxjbeIIN4hEvAIQUVjCd34UUiTpiEIziuQ+BzRrrE9UnhRB0kSR4PHhdhrsD/x8pm1rlh6P5RBYD/4VJGh43IcKc4/m8UVRGFmdzbjie0tumVFfmxE0ulSFVPG4zFVVeHF0O4skuaBrLWI9wGtLVonJDal213ChTgrPOjDsHKw8e8q1Ygl0iSWaBY6PQa9RZQSgp8hUqNFc3NnE6MNIz9mZ9ZhNJ4gStPqdBFgb2+X6XRKWRbsZRmjyQxxBRYX+y2UEKgZBdjyClNW2PEMWypGec1NK2yPaqrSQRCkBjfRKCWkStNqG5IkYdDvkaSaOkDlJRbwC42vFEZVpGaEwjGZVUxmJVpDq52QpOZwfQWqqVDNQCuorGATRaeVsdDrAjAZl8xmNSbPMdaijEKcJvgoeqg0Rek0dsb4GuVqdGiOSwkEX+FqkGAwxkaBqCoYjYdU0wlVOcXXM1xV4OoS52u0FZKWRUQjYgEh7Vm62oLWmLbBpJp2u8/i0jGyrMWxEydYW1vBWEXibuB213lqOuXhvT329nZ46upVRIQ873Hm5CvptZYYT68xHD+BD4FE5Wg0wyF8+sGazaLi1Jrh5DETxbA5L2m0Vhw7tspdd1/kxEmHTWtu3vTAGDhPPFvtAiPquuTXfu3/82Iu7pfE8zGewOcfU74by5MI9+0nNjW2VEi0ENLN6dqEKGS4FHwSxRHtoyhiHFgHyseODuOgzqBqQyHw0ARu7MCjBey9hOqEv/L+X+Gjj32UUTF62uNpusDS0mtoteI2VgKZ7ZEs3Maw6ca4bGGkFPXCHZw596dREignV7ly6Vew7ZO0ll+NSQf0Awwc5CkcW4NuB2RHUT+lKGtFpaO4UTaWSjMTuy/2RYmiaWyqiDkVBx6RREupvcxyM4D4wG1Xd0CEQRkYdlvMMos3BiWw4OD2yX6nyaF4YWJbI3vDR3hy54/QyrKy+Cp63XNMZuus73ycyo1Z7b2Mtf7d1H7K9b1PsDe7Gjs9AhiVMFi8h17/Trb1kI3qA6TTK2RVQVvG5CrlQnoPJ5LzFD4nNK0vXitm1uCNRqNoSdTvewFqgVLF29ELha6DsxPoVvDZOl6sdVpwYQ1uSeDapcf42NWP42cz2tOSrKy5qUccX3sLbfMGZPVVfLqToKyiTBS+2d4jE4/74yfh7DEwakbuLmPDiGNqmfc8evpZj6Hbz/45dkcPs7n7R4RwOPP/+gT+45PwGYG7FuGuJbDzMeVrAuOiUNvTcOEsDNLmY6egcimtpddx550jqrrk137n117sxf2ivJDfUebMmTNnztcv8/Fkzpw5c75+eE6iRwiB1772tfzkT/4kAPfeey/33XcfP/dzP8f3fd/3fVkL8OM//uP86I/+6MHvw+GQM2fOUBclwdUoBcYosjyl1WkRArhaCCHaV4mrCCLUBHzM4sb42HchWoOKeQv7r0E7MFX8YicJHosjFlqicVWzrkRLK3Xk92fiEZ5Z18rE0BFDjJ+OcsnRWgY8XfgQYH24x9ZkzKDXp3/sBHmrzWQ6YXN7m6p2OEkYDE5gTEKntUCSZFiTkCQpSikkKGoPomL3SswkN5gQvVh04tEmEILHhWjJtbQ44Pazt6J1QPwuIjOuXt/j/gefpCg93a0OnV47bkdjGSwuEhDWb95AoTDWYIwmSMxayQCjPEppPCWbPnDFadp+zHJ5A9GezXpGOXaMysBsUoIIvoBQGbSOmR/9vmUwaHPbbSfp99qM6hm7xZS6hvFmTjFMyMyQQVpjmHFtY8ZTxTbGGlZXluj0U7xoqma5Njdg2IR6TlNB5cLSSoczp6Ol2M0bY3a3p6jUorIEZQ3ea5zToC0pGca0MVi0q1BaY0KFVQGNx9cFVagJLsWaNtYIs9mYrc1NXDGlnOzhyylVPaOoJkjwmAxaSYIPhsoleDG0Wm3sSpegFM4oglYsrp7kjtteTrfb5cRqwrHlhLrY5caTn2Cyuc79D1/jfR99lN29IVcuP4CI0Ouu8vI73sGxldt46NLv8ukHHsW7EmMzEpNwYwve8wclCw/N+JY3ZhxbMejndBaY82JgjOHCrbdw+swJvBf+2LcL3gMHku2BqRCj0ehrQvR4PsYT+Pxjyo/T4j9Q81gjRgcNzsagai0xcgeJAocYKNtR0EgKaI+i6GFrCBWYCjobYAuYLkLdgkmA/7QLv3MVygDDl5Do8WO/8mMUVcHudPdpj7daJ7j94g+wuvbmOEVAQClNZvtsWMVNA59OYVtrzp18Cy9feAVuus4DD/1zHnngZ0lOfjOthdOkyYBXFHCxgtUWvPUCnD8N9z8B/7+hZncCYxMzPJyKP9cKxvrQQmoMTBoBJDS5HzTdNU4rbnQzyjzl5Poeb3zgOu2i5uapFTZOLlEkhjqxaOBEGYUPgQNbLYiiRUB4bPODfOyBf4QxOa+9+29xa+8cm+OH+fhD/4TR+Alec+t/z8nORYpik4cf+yUeu/G7B2O4SXqcvev/yOnVi0xnN7g8+1eM9j6AClEEH+gF/nz3r/D27iuZlF38toE6doeMU4ukFquhK7ELRtdxO+wYqMyRawMFywW8cgf6Fj4xi+uy1IPX3Qt3LQV+dfpRfvN3/0d29rbRQVAiHFt+La+58KP0+he5v9Pl3d0WtVFIChiFCHiBPIE/+zL47tdA1w9Z2Xw/rdkl/tO1e/nZD6886zH0plf+JA88/kvsjh6hOiJ6PLQH//jT0L0OP3QPXFwAa74qh+2c5xOBpIrntNTAa18J/u7DY1Bo8/b6u6ndtzGajL4mRI8X8jvKnDlz5sz5+mU+nsyZM2fO1w/Pqdx54sQJ7rrrrqc99rKXvYxf//VfB+D48eMA3LhxgxMnDu1bbty4wate9apnfc8sy8iy7HMel9BkLRCtM5RSKBU7AqKZOjFhVGJfhiCIkmhbJcTHDr+9EfYfF1D7yaTNFNCn21cdWYZneeyLEV+jjpplfFFcEFwIpJWnrB117ahrT+0CzgtKWWySYW1KnndIk5zEJqRp3G5lWVFX9dM8ypXSGBXzAYSAl7i5QgjEqACF0QajoyGUSLTEKuuaoqoxhUFZjTaGNMvR2uCD4OoKQaGDQjd5A1pplFIED3Ut1L4iKEGMQkRwzqNUTVHWqFnFtBJciAVaJYIJYFCkCjIr5IminRnaucFrQxkUVkFlNc5qrFbRdkuF5uZjcLkSjBZEmi4MiaHi6HhseBS1SOM3HwPvpbFciQW/ABKiPVZjk2a0ilnSKnbuaDwKj8Y1Ybi6OQZtjF9AorjkKpyvCcEhwRMkIARECdoolLEosWByghisbpOZNl6ESV1ReYf4+LogAe9rfO2oyinT8R7jvR12d3bY2NhmbzRiVsR2Wa0NWd6l1R5gk5wggg8B37zPrPBsbpWUFIzHZp4/+zVElqVkWfpFnzccfnELo5cCz8d4Ap9/TDmBZg3DEpaEQNqcf6CxZNKgGzur0Py+b3FFM+xo3+jm9dM7QFTTmVAFmAaow2EA9kuBq9tXn/VxrROyfIV2+3Qs6jfLrDjsfiwUzBQo26WXd6mDIFoz82NCKMgkHIyt+7aQmYGWVSQ22krVOloqjZvA7pmK9/XRXA0OA8YNjQBDfF6lApMwQ/maZT8hcY7cRWWkTGwcG3S0qUoCZD40bxyvERyeGSVOanyxC7M9sDXBV3gFNZ6ZnzLxE6pQIQJBhCIUTP0krpeAVYqZGzKud5j4PbbUlF1TopugcacdO6ZgV08Yqxm+mS5Rh5KJ2wMt1FU8NmySMGi1CMYgFryJgkTpwIUYWt520AG6Bvo59FrQ60GvD1nHQTYj5NODSRm6q1nsr7HUP8VlE1A+WldqHTOsdv/5AIgTOt7V3D714IMsqBkdXWKdY+fpzUAHJN3TmGyBuJcPqR3sTKAcw7RkPqZ8jdA0/8bzmgL7OcOGARaBRYbjrw0LjhfyO8qcOXPmzPn6ZT6ezJkzZ87XD89J9Hjzm9/MQw899LTHHn74Yc6ePQvEgKfjx4/ze7/3ewcn/OFwyIc//GF+6Id+6DktmFKKBEU7QCsIqhaqUkACEur4zVoOCyZWB/S+4bpXIArxgRAEaWwzYuCCoFxTnFGaxGis0XG2L1+ZF7UAIzw1giN2n+w/fvQ5n0sXRY8Q2owmhs29Ah80Ol+OfukqwSqLUQa0Jkig9gEpY+ZJcA4lDkSjVALK0Gu1WWr3cUF4cjxks5hhnadV1Fhg/doNxCu0FiRMQWqGoxJjDXlLoaymxsfCkwS0aAKCMrGIpGh8SYLHhwqRwLDYYzLbxTnHYn/GKy7mjIaem1cXqUuHHaXYqqL2gVk1ASoGacLxVkZqFN1WIM88OXvUuzXjwlAUgTANBK8oxppxqRn5KRvVNhJKphNPHVo4p9nYrtiZRNEiLp+gq4KFrESUYjLWjKeacqbZ2Ym2TrPpDmUxJs0s/bpNkiYs5AssDZYxxmCyCp14bC7keQeTQKZ30c5iVUrbLpAkOS1rosACCBXClCAFNRWemmAVRucoDWmmMYkisxmDfECiEzQpWjImoyGf+shHufrkJZ5od3j4U8uQpizkGf1WSl07dnbGFEXF9rBmd69NWWmci8XwipoN2UbCDbbdkKJw1FVNVY3RqmJHrrHj76Pd2+V1t10ghAs8s4g1Z84LwQs5nkAUz9/AgB+jgxLPy2Yb5KMRYiDYeINDscMlsRDdOCmiHGS7kPoohLgM6jZgoT2MxcNv78Jtt8CTM/idLVh/8WM9viABqBrLKduIFlqg3QQjFzZmSUxV7J44UQil9Gjf9qfg3MtZTM/xSlbpTyEHbiYw9qAvwWc2YXMXJlUUN9YNPGmjoFQ3uR+TRmCCGBRuQ3yfQYh5Wk7D4xZ0scvlq79JevPTbJiLtG75FhbMErsLbYYtS2kUW6liZuD4sOTC1oS89rRmE7JqxmW5wX/iAzzFTc7sGr7fvxOVDNgyt3PTwnDxVsw9/3ta9S70Xs00TSj0Eubinyc//UaWPNziIJHATrXL45/+SSqTMDv9Njj/HSx7OOsgc46Htq7z1PbPsuHW2fQ3EAlc3vogv//QTyEmY9fG4PI7br+LP/7672F5eY2dBHYT2BzDf70fntiA3MfrkTSB198O3WOwnMLaMqhM8dp7X8vfSP8Gs2p2sD/76gxnzTHyINzxyAbfeN86wY0x5hG0usmPPMsx8PP/7F9wz8rLWcnv5urwOHdMMi4/y/M+vASbbfDPGC6WPNw5g+UJnKviZdacOS8GL/SYMmfOnDlzvj6Zjydz5syZ8/XDcxI9fuRHfoQ3velN/ORP/iTf+73fy0c+8hF+/ud/np//+Z8HolDx1//6X+fv//2/z8WLFzl//jw/8RM/wcmTJ/nu7/7u57xwCdCSWHyhFuoyoJRHHaRv7JtOxNwPrWJGhifeBxdvops306C8oDyAwiSKYGLngG5SML5S0WNCYPIsZliff/KjAlrACkEyJjPN7qjCJDlJu4fVFqM0oprlC4oggviA+NBYgMQ5uQoDKkVpTSfPWV0YUPjAQ5OS9bKkXXmWJ440BDb1FpOqbLIv6rg9xaCtIbUGMQovAUHhRDBNN41SIXY07GeqBE+oC3zwbO9scHXzComG04s9FlczLl8LPHZ1wLBy4BRq5hCpwc+Akq5tc0unRctqbFphk2gy5ofbTCeBepYg04QQFKULTEOgLCr29ka42mExWHLEC5M9h6ciUYpcKYwS8rSil1ZUXrE9NRROsbcLV9djP45S2yg1pJNbUF1aecJKlrHSM1hrUKZCaUFlBpNW6EST6BE6CCbk5CYlTzSZyY70DDlECqSZWeyUj10jaYY2ilYvI2tZBnmLs4urtJOMNGhSb9haL3h042Gqz/wh6wTuV44pkKsuGW0COVM5hqNDmnVpdRYBiw9R9KilZlf2ENli6MaUtaeuPI4pnhlMb6I2HiVvTdi83kPCOeaix5wXgxd6PFHAy+lyLycJ4hhVU4rJCJdBkUTRQ3QMdBYNvpl9H1Ts5NAezAjMBHwOk1NQd8GWkE9isf4tbXhjHz46jLeXuugh7HdSxN+TRvjIA/RctJxqSVy3vhPWysDMdMjOfhsMvo3+RHHXhmZlBteyeNsW2LkKyVON3WSIHSObGi7ZRkTiMGsDFQWjRCCTGGZ+IkAucMXAkyn4cgg33gOP/jtmJ/4kx17xDha7x3AqFuFLBdtJ7CY5Udec3hjRn1Us7m3RG+/ieZCn+BU+zaPcLt/D9/CDCMv8ljnNExbGgzOYhXeSAuI0Ra2okgX04DvJjbBSw10lpNWQj3z2p7j6yM/jl+6CN/00nPhGFmu4vQRmG3xy9Ld5ePgvEfGE5lrg+t6nWB/+0dO2+yuPfSfvuPg2Lp5fY5jCMIVLN+HJK3BjPdpfKYHEwD1n4dYcrIfeFJRX3POye7jr7mYW4v6Fy1ChntQwDNz74A7lg49BsUHKf8Xw8LOKHv/2V3+b66/+Zk4f+0Y8inPy7FdBn+mD5HzORdLAw8sLODmD0y7u8zlzXgxe6DFlzpw5c+Z8fTIfT+bMmTPn64fnJHq87nWv49//+3/Pj//4j/N3/+7f5fz58/zMz/wMf+Ev/IWD5/yNv/E3mEwm/OAP/iC7u7u85S1v4T3veQ95nj+nBRPlCSrgFQSlEa1RJppehxB7MkQkhok3RZP9L+MKia0dSjUFFokdHwj4AME3vuEBOQj+lq9I8PhS0ErRbrdJsxRERZFCNKgloE+eJWR5hjYWbXRTD5JmnVRzrw+smAwVWik6vYQ8SxFlcdJGsBhtGZcFpfdoqWhrR24CSWqwQaOMIuDjdpNoCaUArXS0rIp3sfslhJifQuPjIjFPBYk2ZC7UBO9xdYGbjQkII+OhTnBesbKY0mmnzMqKoqoJIeCCIUhKHQzDGsogcaaxV9Fjxmsw4AuoC6EOwswHKgnULgabR8MpRTiQG+J/YV/4Aurg4z5XlkGvTV8lFHXCtEzxIaDJUOQ4scwqg6DZGdes74yxxsTOFgU2g7SyaJtiJyOSVgtrM4Z7M9K0Q1G0QPXROvD4pSe5ceMarqooJiN8XaOMwphomTWdpSSpZZhkFDsVmUka0UOzu7XB9ZFjR3LGBGpx0ZaLFEWKkIBO0MqSJimdVg7KUJeGEoWvK4Y76wiKyXgHH+Rg+4DQ76fccssyg8EqJ0920PMU8zkvEi/keAJQ9h3X64KdYgR4eqomN4AHO46nYkkgJPH5SmK4uSJmfAQD2nDQEqh9tLkSYug5ACZmhBj1lQnoXy3Ovv3fsXnfzzBZ//2DxxSadvskrfwY3cHt5LaPEaEutpiNnyJVnuMLXU4utVAh40w1IC9TLMLVVDFTFdPRVSh28G7ALJxhYloMDezqw26RA6VfR9EjE1jzjQXkfnZHI1qoRvBIJM5PKIBaBYrpDcLeNWR8BYpNEM+02mJ97zPM3JB26wTt1nEsOk6OQEBrRq0U0YogHYokMJE1euouVumScoFdBkjeJSSWTKCFpqdiCpdWUTyZKqi1wekYur6ZQBJs7E4JDuoR7D4MSQ9nVyiS02ibkXXPsrR0bxwvG2qisKSIHS0GCCzz0GMPM57sMbEwSWB9mCN7t7AQ+hS723zmoSs8ldcULagyMB7yAqyj8QCLFmW99mna2TJuopjtQZgo0DlqYQFVglbnYvfj1ic/5xgZdO8k0X0kmLg/Ps+BK9c/BsPLzSSLQ/IMjq/BqVXo95qu2jlzXgRe6DFlzpw5c+Z8fTIfT+bMmTPn6wcl8tJyYB4OhwwGA9540lAUsDeGQbfLd7/9Dbz+FRfxLlAXNcEHlIrx40oJ2sbcj2hrZZAAddDUXiMScK6K2QihxMssShxJD2ybx5+6wW//149ybWObEph9sYX8MsnSlIsXb+XE8WMoSTGhA2LxpHhJ0VrRyhSpjXKHQjfiTQIqibZNKlY6klCQhTFparj9Zbdw+twxXJky3u5RlZbrw5tc2b1O7WtKN8P5CkNCGlpoNCqRKHmJ7Ocfo3SCsS201qRJIE0CEjSutlFkUPvFKkGkIEgMkXc+ELzn+pVHuPr4A3jvYrVQCyvLJ7h468tJ0xaXnljniSfXKWvF7iSlrC2phralyRmJU1uVCmA8ogLiQXwUpirxOGIgu/c1IqHp1ogVtiAVNFkbugkr1rpCq5p+r8vdFy+ytLjIk5s1910tKauAqiZQFxgVyJXHICSJIU0sSjXTvjG0UmGh67FGqK2mttEvzYY2ShI6bWFxwaO1UBSesvKICOLjvTWKRAMoXEjwYqkdzGYK7xWJRDu3uqq5cfMmo/GYGmFGFHA0CYoUrVPSbBFjWiwvLXDq5DGg4tKT7+Xa9Y9hkxat3nFs0qKcjijGe4j4g/rjG97wVn74h/8mFy7cxqlTXU6d6qHnjR5fVwyHQxYWFtjb26Pf77/Yi/Oisz+mfOgNmo9upPzm5ZRMwzvPznjTao0ZQ7YeQ6Vnx6A4Hrs+nI1WV2nTyaEdJCNIpo29VQvEwqwLk4V4bsyLGA780T34e4/D/ZMXd91by/dSjZ/AlzsHjxnT4o5bv58LZ/8sSTog653DJgOuXv1PPPLwz9G2Y/7qn3gF3/2mW9nYPM6HPv4mbm6t8lBH8+meYVbeZOuBdzG59l5OLr+R19z2w3Q757hk4bEkdmhcdLAcYqF/P5y8E6Jt1n53iajDnI99eUCIYsO6hkJqykv/muLh/wXKHRg+AcU2ebLIQuccebrIK2/5S7z8lj+H0imVBo/QqgPdssYEwfoa6z1DZjyu1hmpgmWWOcFxgkm42UvYbVkqpRg1IetyZDku2dihkgMdAV0NGX3i7zH5zD8FnUL/HKQLHD/9nVy446+QJT3S4WWSyY2D7S3AloENEwWhNQ/9AHX5AMX4t/B+A6+j2GCz8wyO/TB59w2UO+9lcv2f4+ub0XJNN2Hq+4p+0yXTTle497a/wq3Hv4MhiicEZiIsbc5YuTmF4Cj1Hk7N+H+8+97POUa+9zs+yVLnHFmywFTDnoF/88vPolyc/gYYX4e9KyCHwsc3veYd/N9+4B9z+9m7DvJG5lr61xfD8ZDBNwzmYwqH48mcOXPmzPnymY8n8/Fkzpw5c74afCnjyXPq9HghiZ0emqA0XiswTcqsgiCGIKrJsGg6FA5CS9XTOj3QCvGKECAEwUugxgEKJaHpYpCndXo0Fu5fJQ7fTRtDr9tlZWUZLRnGDVBicSjqfeN4PEgMcRcfmvyM/dmTqgkN1xgJGKlIlWGhl3B8rUc1zcjqPoWx3BxvMyymOF+R65qO8WgMOjGgLKIcAXdkPRvR6KDTQ7BKEVQMWRcP0nTOxGD0ihAKgoAPgvcBVxW42YTaVcx8RS2OQb/P6nJKr9Nmd1tzI3EQNEZbFBm1ePacP9h3SAwXj45LOhZXwn4ZSjgsjzXdPoRGFuDgOYI0AbIxxBsCojQLgy7HVxbYqWfoDUB83MZe44OnrAtU8EwKh6do9l0KWNpJTT2ZkBjPVAdmWpCgoEwRZ0iTijwrMFpI0gybpCilonBCFDwSAyKKorJUtWVaem7u1FS1kKBIAEFRYfF04lqqmEUgYggYUAnW5CRJSivL6LZzQJPY+FF2dcFo+/rB9mnmXR/s5cXFnHvvXeNlLzsMXZsz538NTAaBy5OCD6uCDvAtTXaHDZCMQRdQLTRPlmZMaU43omO3hxzJ/tD7LosCdRafk9SxU+HFafP43JFrtvVJDs8DEa0Tup3zrK1+A0qneA2BQFVusL31Ccp0jzxNOHXMkjk4KwWtMvBoW3MlU0x9DcNH4dqHcGqBscwIBnYN7Ohoh1U0HQOVivkVACsOjjenaqdil8dY4hnWq5iD5REqpZhpxQhBxldh/cNQjw+Wv6h3WN+NIs4TN/8Lv/mx7z/4t5/4Uw6MYtiNQZEiWewIVX16+lhzVoWNRtxwWpOLwkjc2R4YaRjqGLZeEucETFTMH8E0nlMAbgLbnwUUrn8HU2rEJAx6t7LUvvVp/YcYmFmFAZadsOTh6tVt7nvwQYajh9m/AllYGPLabI+FNjyxs8kn7/8kk8lTX3Cvd1snaIUNbAXbFh7IYaIVJ3Sb8XJMp56Y45QK/sz3hYNrppaHzAtGIEWjm2OnVp9rzwnAUx98xgNRdWm1NMePw+nTX3Ax58yZM2fOnDlz5syZM2fOnBeUl6zoUYmhFvAihBDwweODwxMQ7WKxO3gkxIwJnEYrtW9w1CQrRHsslWjyrI3SmqIw1BNHEEHv51I0gsdXmumhtGYwWKLbHaDQaGWbUO1YckoSS5YuMytSDAYrDo3gBLzEv250glKGEGrqegYipJ2EpN0jyxLWVga0WxnVzi6zGykK4eaWo3x4E19ZZsMhrtbsTfbQYrAqRWuN0tHiCQ2qyUNRGBQKUbGjRCuD1R6tAxKgqmORPmZ5RIEhIIgEqqrAuQlVWTPem1DXNePhHsEqlDZkpKRYnK+5/NRl0jTj2sZVdifXMDrnlmM5WdIiz1O67RSUYjTzTMq4n2s3wweHq6GqFd4HJtOKsqwakaPkoOIIzc8VsUQVM04ORZJoy6USg84StKmbEHYBX4Mr6GfCrcuKXmKpvaJ2REFkPEaKmiwIvcqjNFxWCUOVxn3mEhCDrw0uWLQGEyza2ygi6XgMaBFsCIhAXWu819ROoYLFNsvpmuN2f42OLbe58/wiWaJ59Mo6j19dp9ce8Pp7LnB8ZY2d0YT1zUcpygmT8faRV+5PBU6BFGvbrK69in7/Fk6dfhlpOp9VMud/ffz2U/DZXahDFC+8hToF6YGcip0e1ULjOAjYioOPlEvjz5UFurHubUNsaMNAaxxPKTqAPxqA/kJy9r+B9Q9AuX3wkE36rKy+iU73HJomrNxk+GOv5KGOhi6EsyB9RdK/jTff/F7afsZkeDvve+gM491lnpA+o5ahtJqBh1R1mJ78FirTZ7Z4N9daC6QmCh19iZ0elnjmTSWKHYr42EQfSjCKKIoMNdR+xuTmhyn3HiLNTvDKpTdgbZ/LReCJphnxS+ETj/8CF0+c5PW33YHRmo9eeoTPPnU5SuNHujgAdNKhtfZG0oWLzCZPsbXxAapym0JBoaMlVbm/oDT3voCtT8eJCUewNPljEl+7CaxMb3LPjY+xUGwzMil7OkMjDPyMllTs7j7AXbVmota4tHwnjy/dQd4+RasT1YNB9zZuP/fnKatdJjpuX45su1SgFaCVDOgMbqfUYARO1HG75tIExqsoMnkFx7rb3Ln2JKma8pmHbvDAY5ssthb4xlvfyKmFk/zRzUf47OMf/aLb2dgOS6tvpNO/yLFTd5Fki1/iHpozZ86cOXPmzJkzZ86cOXNeGF6yokchSbQzCjU+eJyvcSFaVIlxiBZC7fDeE0M9YtqFaCEYQZTglMfhSZKcdn+JNG3BjmE0KQnBx66Q/awKDosJXy5GG1ZXT3Hq9HmMSrAqR2EwiqawDRWKyURhNPz/2fvvMEmu9LwX/H3nnIhIU77aOzQ8MBgLjh9S5Ay9aERRFCnqka5EGcovr+7u6q70cLXP6mql1V5JK+lSErmkLEVS5EgcihxyhkOOd5gZDDAYmAa60d1oW9XlK22YY/aPE5lV7WCGGKDByRdPoqozIyIjIqMiz/ne733fTFuU2FqBAgqDJC20buFcn7zoE/Ak8ynJ3Bwzsy3ue/1R9i1Os3pmlXN5RjEsuHh5yDOXLsedCDoW1r2g0SjRKJWAjsSFqBAJgKBQPom5J8EACqMDqXaIgHWKyu8QNlFp4muVR0VR9hkOtxl0+qyeX6YY5FiT4xJBxNDUKVoJVVXy9LMno8XH1iob3TXmp2e45+heju6bY2G2zaH9i4jSnF8vWNquKMucXs9TVdDPhU7fUZawvGwpiwKhwNMjEht1LgqBHdLDEkmREF9HI8qh0gTdaCCmrPmQAK4A22dhWvOe2zIOT2uKQjEcKkJR4i9uEoptlDeYvIFF0yfhFA3s2P5K1ddSbdpuQVLqUJQs/iwdUljwgeBHCh6FCQmJCDaUVJSxK7gmc47un+KH3nsHs1MJH/j4CueXzjM/c4jvfvd+3nzv/XzsC1/hK088xvr2FqVb23Ul7vY/aZCk+zh++w9z2/Hv5K67MxrNb2w58QTfmPh3J6EKULiY3WGTmJNQpTCcIao7iAoP5SApYmZHlUHRikRGkUKZgrbQHkRlhylhaju+R9GOy9vkVSA97v0J6Jy+ivRIswWO3fGnOXj4e0nqIrlTwlNzTR6Z1fj9wPtAboN3zryJ7ztzlFbHc2ljig880sR5jQ0pfkqRJ7DXwlDNcuX2H6W87Y/RUwlnTBtVEx7zPlpBjUiPlo9B1yrAQMO2iYX5to8ETC5RHZKXPdbO/wad07/M3bPv5I/ceYgDrbv56MBx8SWQHh9/4v/Onqn38Pbb/xSZSfj0U/+NTz/5UZz316k309ZBjjb+PouLd7Pdf5ZzJ/4PBttPj4mRUebIVQgB7PAqeyeIxzI6pr7E/I+F/CLvPPWfuXvjBMIMijkCDscagW5UClpFqY7wwYM/yO/c/6cIpkVbRT3K4vwb2du+E4dn2cB6PVobhc3PukgoaRTGtBjWqqXbivh6x8SHI5IgFjg4t8L3PfBJ2uYKZ088wiNPPMZde+/h3jcv8i137GF7/WEunPj/vOB5TpIZDh//UQ7e9sc5emdK1mi/4DoTTDDBBBNMMMEEE0wwwQQTTPBK4pYlPcJVJYraJiLsKkeEaEs1Ku3uVniEUC8VRvYSnqt7PGFX6nkd4C0oEeRFRpyIKNIkRWkNIQalG5OQpQ2ytIkSg6GJEo3Go8XFeokN4OO++RCijVXkIRAFiQiJRIsnBfgQYqaFdQTrCc7jg8cH8CgcitLCsIqFblEuNqRiAMMoHUR2naV4gurjHwV11MHw43MWBO9lJzNDwAeHIyoxrLXYymKriqoqqKqcoGztKjZ6R4X3AevqPBVXAR4Rj4hFpKpzWUoicVCCryCUhFDEh3f1Z+0QKdFSEkJFoCIQ/WWkLrGFscpj9NhlfI4fH4cwukjqR31O6mgQtEBmIFgIyhPEIkHQwaNQpFpItAaiAiVeh5ogGkTV2SvRriT4SKWlOqHZSgghMBwUlGVFqhXtZoJRGusd1kVbtpirYliYbTEzlTIzpZhpK2baQrsZIFiqOqNGGY02JhIu4+bj0bWdgLTRZoqZ2Tn27ltkdk5htH5R1/gEE/xhgtZgd9Wqa4fEeJcYuT85ELvzule7ftZ2WF7vCjf39e1zdKuh5mC/DoRHs3Egbp+Ac0OqqgvNvfDgT8MdP4Ja+SJpuohqHECFaP43ne5jj8ywLzTRojEmwYnQBpo2YF2gqu0fkQzJFiCDImR086S2XYrHamtxnIgmM9O0mcb5gqLYjFaBpk2ipzBBxod/rTFhzBqvyIsOypUMDRQWymId5QoykqiIyzdwcoVQdYmmf5pGMo1RDazPyW2XEK6nQgblGv1ije7gCmWS0M9XGRRr8bv2GjidMMyvMBwuM8yvUBSrlMX61/TZKCK9bmpnzdG76aDQQZO5iqbrErBUbOHoosgwzFBiaAXAW5zLKaocF8DoJmk2SxCNNtEeUTEKQg/MBNhLiISSE4oAqXbMmJIUj1BiQ4ELiqRq4XxKu+iTuXUytUomq2R6DaP3YqUiRyiUonye7wejWyTJFFnrAGphL2H/Hop5YTWDZNdo0gDTLqpNJnhtwgNdHW3eOrfsTGGCCSaYYIIJJphgggkmmODmuGWnMpmqQIFRMc4jRk0Egq19l7xHfEBExwKLcgSJRXvvdxVbArhg6W9vMpQu+XCIhBKtQCuD0pAlmnajQbvZxFlLvyxfYO+EZrPNXXe8joW5vVRlyXAwQBBmZveRhDYKhVI6Fr9DhQuDWFBXKZmYmF1RaRy1FkEgQ3M4hZnMsS2BS7misODXOvQ2Smw744m8T3u2Rd4t6eUF1nqGFpw1tYIj2jqFUcsygjiFcgovnkqVRKKgicLU1aioPLDB4/GRIvCe4AOCx6kSxFPZirIqsNbS2ejQ6/QpiwGWASHN0SagNRAEVwqVrW21dLSXypImc9OaNEm4vL5JZ5iTpZrmc5FA2NwKdDuByhf0q00qX2JtwNoQ96WsmEsspXcMXIULHkWKrtMwPHlNhOwQXR5HQCEhR/kh2g0RVyDWxQqoF0CzPVA8+lzgbOqYaTnmpxzaOQSFqBQVNNrFjJmZxYS79jTIK8v68hqD3gCXzFJl+0CntBtTNNMmzlUM+x28q3jgzv284w1H8c7z6S89y1Onltgzn/HuN+5hcSbD9pdw/Q1M0mbx0INMzdzG7MyQuXYHpQbcf7yJ4jCVbfCZR0/wiS8vUaqE4w+8k0M257lnH2LpUodYbU0AjSSHkcbraO3dz1vfvZf3fqthcV6YmoklyVERcrfdzASvXYwKyy+2K/4bDX/u9fDkGny6jkjwCqwG46JaQ9VxDVJzwnmLcYC0j7cotIe0jD9Hy7skKjyQaIO1i0d+WfG2t/wjHDF/48qVT3D+/AewZRdOvx/WHmHOzHHP0R9j+niblg20bWDGG96+Ihxb+jzd9gJX9hwnTxrs7QUeTKC7qTglKVuLCndJ89l2RpIARiM1j2rrn9sCV1T8Wrm9hD0OVref4anz/5VBsYY5+kdpHvmjZJLS2GX1tFUTSo0QVSDD/kVOn/2v9LdPMlDQU2Ak5Y7sOIce+H9RFZt8fu03qMoOl/onsL6glc7z5kM/ypG5t3Jp+1G+culX6ZUrNzxPjz53mn/8m/8NrRSPPnemJvKvhys7rJ39NXprX6YcXKIc3nh7LwZJgCkHaU08G0CyIzx35M9Qza1xcPMEx1a/gvZDFA1iy0Iaf/eatcuf4Onh45Qi6JHiaN870Hf+KCpboA20QiQ8Zl08tw/MWt65WOKAz66nnOga5qe2eduhk+zJOqwvPc3qhcfxw2nU5e9Atu9jdvUk6/IQG63LHE1X+ePvCOiG8FBpePRCwlfM2+i/9e/BB3/8BkepOLD33Rw/8kPI4l7Wv/tNPPVmWJ6G5w5AO9tZ8oCFP7UNb8q/5lM6wauMgYLfnIZPtCFvvtp7M8EEE0wwwQQTTDDBBBNM8NJxy5IeRjxW6iBnIXbpE5DgwVlwHlCIaJBAEI+Ii+VuNyI9Yoizt5687EEAay2CRUTQKqAEjFZkaUIzyxiEOr/ipoqPWMnK0gZHD93BkcO3M+wP6G5t45xHdIaQ7gofr2O1Q5z9K9EoMQQvWKcIQdBKMCqSHosG9qYeYwMbKto2Fd0hw16PopFQVDlmKkPEIColIDgH3o+6MwMiNetDQKEQL3X2qsdJiReHlrhudK0KSE16jHpUpW5hljo/I1BR2ZKiGFJVlkF3SH+rwPocJwXBFCitSJXCe0VVCVUpiBZ06hEVSHRKYjJEYL3TY6PXw4eKEAq8DxQdTdVXWEoGbGMpxwV5LTCbCi0jaBcoXKjNq/w4E8NT4LH1Wbj6ASXiK5QvUd4ST1otCUIzKOH0lUBDAkf2ekzDYbzDoNBKo7zGoAgitKYNhw6l9IeOfKNHFTZBaarmfkQnZI0209kcVTnA9TpYW3Fsb5tve/vtWOs4fW6Jp045Zqc1b7x3lqP7mritddxGSaMxzW3338nCgQcZFBfZ6j9KaXOO7U+ZbS9yacXz6x+7wKkL57nzvvt58F1vQunAxvppli7Xbem1ygeziDTvojGzl7vvn+Ud71IYgWSXt/2I9Pg61GgneIVx9fU+wbX49tsiCf7QEiA7yo3gwFjQNVsUiM+PrK8k1Nkd1NZXtiY8RiHnGuyIP1a7SI+XGffc8eeoBBwe53IuXvwdKDdg+dOw/Bna+9/HHQ/+efbOvoG5MjBfBub627z7qc9x/MoJlhaP8WSyl0FDcZR471vf0pAbLrY0Q1GcaCikAQcdLLod0sMSbZu2JBIX+y28roQzW5c4c+Y3GPSfwzQPkx76LlKdkoQdq6fV2mJpv4OWi6qOC5c+xOrKZ8bHNpXt5+AD/5A33/Y/8dzqJ/nyhV9kafsxRldzZqa4c8+38cZDf4LW8jxPr/zOTUmP01eWOXNlefxZ3gzeDegsf5rO8mdeYMkXhg6R1Ml8zM4QD5LsYWXPe3HTJQ2bcGTtBJoSRUokPRKEDAJ0Nh7n4sZF8h25HqgC7v5+TLrAnTaSHY0AMz4SILc3HG/dV1AiPDE0DPuQtgbcc/Qst01dYWXwca6c/Qihv4fs0kHM8iLD4iJbM89QzlxkTwPefR+se+GzleLimmEtuYfi7ruB60kPEWF+9n7uPv7jVAfmWPom4fy7hPPAY9cse08J3zyYkB6vZRQCDzXhP82BUy+4+AQTTDDBBBNMMMEEE0wwwS2HW5b0cHVd2vrow+597PYHooICidZQ4yK3wqPw3hG8rR2cQv1aqH1MBEShJLbtBlcXkCqPq8PSQ215pJSi3ZoizbKaGtixgwpBmG7PIkFR5RXOWoKMWn8diKs5h9GaCpFY3AiY2v9Eo3RGCArvHEXlwcFGUYHybFc2FrhqryWFQSUaUSraY4nHU9XOTLFPXyTadMUAbUFUPEfelngL1ucUtoPzFgkDCJuIKJQxKKXQiSFpZvE9giIERcASnCXgqMqScjjEVhZX9QluAGGIeAvB4R1YUWOLLCW1OYqLORZBhXEx0NZ2MPH86Ei8IGgdaY6MDCOa2iRqTHy5eFoxEsPntWiMxCqjR48tz3yobVlwjN3cg4DX9fmqtQ2iQTQuBAqiBdlW6Vnq1tYkVYbyARVUXaRSFMOA3xgQigJXgSPBGMNcW6MTxZ4pYb4ZGAyEYVdTWUM3L7m4uo53Foo+i7oiq/psXllGlyl5Z518q0+SKjaSZ5heD1i/SWFX8CGPxIsskiaWubk+e4YVU9MedL+Olx+lLgtqHBY8wLgVpHSsLK3y7LNrtFsp+xbbpImOy6mryY4bGMBNcAsjXutgXWB1vc/W9pBur/tq79YticdX4EI3fqegYmF6pNYYERVuRIQImCoSHCOCZPcfhPIx10ONiJLRa1X8Ckg7OzZZLxapbrG3fTetZIFucYW1wWlEJdxzx5/n+JEf5PKVj9cWUwGpBhxfeBfODhk52+2ZfzMqmaZSQqmFUgc6yvKYXOYsJ9motniuM6Qop2HqODJ1lGGi8QgzNlAVywz7p4GAbd2BZIcwRDIoEMgGFyE/iwRNpu+gpfZx0LZ5a7iHYWizt9Niz9IKVgkr/gpXQpe+RIscrwxJ+3Zs8whdBWXdxDCXHWRv83Ya6TxVucXZ1U+wvPUYhY22ViNIgIZ1tEtLVrmaxL85XhqF8fLQhFIrNBIfr5dKhLMNzbJOyOf3U+VvJHEDFH0IJQqDoUEVYKo3xR/pa7YpOMUGGwxhsAxLnyU09zBwsOGgbWaYbt9NYmY5v73EZ549Ac5jrhzgDVtz3DFYoqEv4JtrLJ3d5isrDtvPScpTaFoU+bP0VnPCULP30HH2LxwlFPupVs/R6X2MoQGf3vw89QYXWVr9NDbsYXj2TljcD20h7AWVwrEKbqti9sslAx/dFfVhiAqhI1HEO8EtiAAsGzidwqrAxU0I60Dv1d6zCSaYYIIJJphgggkmmGCCl45blvQoc8hLGDhILFQ24J1HApg0qX2rhnibE1CE0MaHDO8KXNUjBF/LRGIhOAQN0XQKUXXYdwHOW8pBRVWWVK7EeUsA0iTl6JHj7Nm7Hxk5dgcBV3cGqwRtE7rr3Vo9UYAO42wREJTXBBRGpRiVRqWJi2SOkgyVTAOGQTdn0BmitacMQxq5wyFYJYRUoxopqSSICEoUYgOOEidxX8U3EVKUQKo1SkkkLkwkVIZFl3IwpMp79DevYKuCqrTYskKMJpufwjRT2jPzLDQPo1WKDRoXNCFYXJUTvGXY69Hd3Ig5Hv1NqLoQLOJzFBbnwdpIKKjgSbQQgsNXMQDdUmGp8KKoVIIXRSpCUyWRwFABnQKkNHUSOarahCkQSami9nFv1NnlWoPSAApcCt7EfHI3irgosVT1Z5cQXAq+jJ8nISaOq4ANFdu+j8LS6Sku5Cp+7tUM4qchKASN8rBvLWdfZxXnHWWhGNJmsdXi2P6UZjPh4KJi71xgbQM2txN6lePCxjafeOwpjLfI9jL3pz1Mr8vTj1xEmcDmsMf6oIMXgzy6AaZFI0uZnW7RSFNed/tR7rvtdqbaOXfdeYHpvR0ac5ZgliMJRRdwKIHECEoJqayQlo+gtuf5yhf30e/B0aMLvOvdd7Kw0KKVRkuSUSTBtck3I2poglsXzsdg7sHA8sUvX+Irj10kH/Zf7d26JfHzX4VuFc/XtIkWVcbGn0FiUHmZQZFFQmNqA7JhvK2U7V25Hiq+ng5j0PkI4sBsgOnCVAW6eGn7N53t5z23/SS3z7+Tp1Y+xCfO/Ct61TpnL/w6SyufBKS+JyruXXwv33H33yU1U1QqqgtcNkXZPkhPR+WBDsKVZMgH1UMs8RFsPyW/0MSnU3D/T8L+O5mVhDdYxdESBpe/yPqz/woXLAfu/Vvooz9MGoRpB8o5li9+EnXmZ9GqxezRv8n+he/ijuIQ3+d/hMxv07w0Q2P9MS7IOj8TPsSjnMQBlQDJFCv3/1XMXT+OMzAQAOHOuXfyvmN/DRHFF6/8Ol++8IsUtkt3ePmqc6O9Z3ZYsK/TY26Yo72//gS+ihgrEgO0Qwxw31TCR2YTumI4PPMgtx+9g9R7msGRhoAOQhYUibPc++wX+Menv8A5v8Y/5fN8jouw+ig8/P/EqYSVAJsB5uceYOqBv4PMv4FPnPkiv3rm/2C6LPmz5dv5C/ZummaVucZjVHqLLwwv8nO5Y+C2kfyDCB/Hb/Vxj2/TbGb8hdnv4zsP/llOry0zPPNLnDvzVLyObsJ2h+BZWvk0W52TMHOIfvtvw4XvgTuA94FZgO/qwV/YhE0NvzwH/3pxZ/0pD391A358ux6WTXBL4uEm/MtFWK5g+fPgnwAGr/ZeTTDBBBNMMMEEE0wwwQQTvHTcsqSHdzFqwkWhQAz09qG2jYpqBvEgEr2sPAofYhd/qIPCYzW3lhSwY7QuoqJKxIOzHud83H4ARKLqQRuarTYz03M7pAe1z4eVcWuwLSu8tpD4WlniIcQsiICKRfugY9i2EO25iK3GSkUbohA0lRWsh17lKIxFiUKbJO5rohGTRL95OzqmgA+xlViCqxURdaFaooQiBA/e4WxJVQ4p8wHFoIcrcsoip8hzVKqhUeF1RmYTCAWCEEIdmO5jcLl3FluVVEWJsyXe5RAKYtp3DA0PISoxRGLQqkjYCVYJkQzyweHFR1JFYnHeo+qzGxDlo/pE1WnBElMKAj5eB34UPE+t9AgoFd9HJCp5akHQOMT96n+p8e/xA4ml/SCClZhhUlqhb0frGEYlLZG4n9NVHhkzAj4IHoNWilYqtDOYbgamW4HBELSJcoq8sqx3uiTektmCGeOxvqS33cOKZS0vuJKXuFBSSo5DmGpNs7fYT7vZ4vhBhcg0xhimplNKnSBNEInWY9SKJ2q1j1aCpsSEbcQqtjc7XL7co9lqkpeeysWPZXQmdtegJvWo1w6sC+SFY5BXrK51uXBhk7yYkB43woXONZZuPio1pH4iEIkPa4iEqoOkiMu6FMQwNh9S9bojpQfEe7MMgS5fU7iKURnzjaMcmLqPS53HUCohBMdgeJnBLhJAUITZd7CndQfNbJFCgVUw1MKa1lgRKoFKQV85zqkOp9RqPMACcFOEsE5ILfuC5gErNB2YYgu7fQobKly+RvAFEjTGgnEW3V+GjSfYrLb5d0u/x7+79gCG8fFF/iGOZ9ji8Z3XkhnIl+N3BhXU31ctM8f+1l0EHGXVYXn7q9zwDhQCypbocoiyJXJT+8lXHqlJMbX6VKAOkQerAleMY00FKjONa82RIbR9tKnS3pN5S1ZVvL5xjntkLxpHW1ogCarqoTefAaKCshKhYdpYN8QDG4NNTq6cZL7IUW4vh0MLWMOxSsE2qww4BfSpgKW4s1V8TBUpQ7eP6exe2kaQ/Aq2+zghxGaNG1FKSiUU1TZ5tQ1hAFc6MEN81OqN/RbeUMBFA9sKTuxSjcx42NCT75dbEZ5IdnlgTcFTBpYd0AF1CUI++dwmmGCCCSaYYIIJJphggtceblnSgyoWnUaBqKGK6g8lAac8Qoh2RrpFCIJ3HhcKQvCEkEHwhCA7M7VQW175gHMOH6CfC4NSKJyhPTOH1RltZViQBGNSWo1pvJV6W5FcUZg6TyOgxKJECDhc3SIvWKjjyQVBJKolrIsVMAc1/1LiwwAwmLSkPRN9Vkyi0GgEjfio7gg+4EOJBMHXpZVAVL0EQFSJKAcCDsF72NjcZG1zFWtLykGHqhjiqoKy38FbG7kKHwNYM1WiFNh8g63lgBJD5QLWekJtneMDVEWOrfrRQiwUsbUZEFFIiESUHukFQrSWCiIxiR6FuAodPBIE4+ORaC8xk4XajmxUgXQQyQgHVJEwcRa8jSkpEs+XQyNexffzAXzc10iTBGw0HEHrlPZ0i5n5Ns3VHNEOpBqTNkkiTE21MDpQ5CV5v8AHwfloSdZqaPbOt8gSYV5HRU1VOWTdwtBTDSv6Fy9iU01/dZGzzVmGQ4/vlMy4wN5Mc3xPg0QFvOwjzE1jQ8kw9LHBom2gUQUCQppqjFY0MsPsVEaWGvbsAzW1TWIdc9U0upERzDTBLJK7gkwaxDOWkKh5jGqis2lCNodMz9OcP8rs4iGm52ZoNg2NDIzecezZ3dyrbvDcBLcOQoDCBpwPPHXiLJ/61KNsbXV57uwKly9vUFUvUWLwDYK/xiGeYsBn2UZcoLENUwp8ArYdszmUj8pC5aFsxud0LjSvxGptOeOx0x7xdbg50daIAHmALwOnPJwLsPYS969fbvDV5d9gqfskFztfqS2erkcgsLT9GJ9/7mdJdAurwAtkU8eZPfxe0uY+gsBQQ2jMccfhH2S+fRe+7uJ3IiyVOStP/Gtcuo988X30m8dozj/AvXf/JJXtkecrPHXiX2ECND0o77mw/jmce+Fr65f4DOeuPXpfwuVPgrcwWIL+JQKBi70n+OTFXyAEz+XeCW5WWh24Ll/c+ggr5QXOD5+h57Zf4tn9+uGnfuCnGJq30sla9CWGjZsAvn+JcO5jUK4iiw+i9r4HUTHt2wOD3lkuLH2MMFzDrp7llH+OtSzl3OH3wswPce/mMt92+SQN5zi1707OLxxlpnmE4+oAc7nnyO3TfOt9tyHDDhceXuVfPPsloE/gCpaczzKgusn5dKHifP4ZvtARhskm3/mdPd78zfu5dOVOnnnuLXz50Z+5bp233/23WTZwIQGXzcL8vTtywGu+LOY9/FAX7tt1uWQBHhxO1IO3ItYMfLwNzyXw5CakJ2FPH9rnoFHEP9+Tr/ZOTvCHCiLRgldE0Fqjamtc7z2BUDe3jXqmooZeiE1pAohS4/lRWZb4W0z9N8EEE0wwwQQTTDDBrYFbl/Qo48412CE9ihyUCmhtEfGIScA0osLAlbiQxyoVWZ2p4WqyIsTcCTzOBSrrsE7o5opOrsidZmp2kaRtUVkb3ZgBUbiQ4KzEPAobMxO0EXRiEAXKWJQKeBdi7TyAwiLikBE5EgQffB0SDigVraeA4AeAIskCJqvVEHUBX4JBfAKiCMESfEmMFTco6tyMENURShUoE9UjLiQEJ1xZu8xTzzxBWRUQBpGkqNUYUb/QJKFBIwRmpUBrR5UP2dxcJ7iAsyXOlQQ0VWjiiUSPaF9PQOxOkq/E6l99VIz6qWOuigGTRgUNgHeooPDeEw2jotbACwTt4yMI3klcH0uQCsEjrkKCI4jH6SqSJCEFF/NSnIvH50Oocy4iCQQp2mRMzbSZW5iiNdVFtAVVKyS8IzWaxcUpGg2hs7HNZtnDOSiCxgWYahluP9xmqmVQqUFlKVXfoaohlBXVoEe3d5kBsC59tmUvqWjmVcqs0hzIDHfua5Mkin67RT7wWF8xLPs475jyCQshxSjFQjuhnWqMKWmkfbQJzO8BPb1N6jSLzNAuDc5NYasFBlVOJs1aBZWQqAVSPUtoLMDMfmRmjvbiceb3HmV2PqXdTGhlMdB8hBuRHxPcmnAB8ipQWM8jj57k3/zML7O2ukG74Wmm4EP1whv5BsT/mcP8Gmt8mS7iHI0NmB5CNQW9LCo8tCd2wxMtrco2tJYVM5cNuhSGhyvyxMeIqFoVMopy6gX4XeADLuquXir11C/XePjSr6BE44LF+pttIXBh68ssdR6PRZ/62YP7v423Lz7AVLYvFtU1qMY89xz9UZJDFitQKChdny8/8y9Yfepf4WfuZfCWO+hOH6O9+CYemLuPolznsSf/Cc+e/SUIfnxPcL7C3XSfdvDzfIxipDwbweVw8fdh6ZORba/Jk/Odr3C59xTA8xwv9N02n934IA9tfggXHFW4dYi9n/6Rn+ZTlxN+7VRKr4R27D/A988Tnv4F2HoS7v8ryMI3ISobq422u8/y9DP/lkHnFF/1DhMcvnkvxd1/CQ6/jwfOPMr/afWDzFPy2we/m0/d/W6awXBbnjAz9Nx9/wxvfu+dbA9W+cfd07z/2aWYX1ZLjEoC5c1ID0rODj/Gpzc/w/7FjO/7gT0c2X+Ih776R/jAx37yhqTHe1730zzagKVmnTWWZjckPAAWLfzY9vVipyxMrK1uRaxo+C+z8Ik2tM7B7Mdhahv2FzBfgp2QHhO8zBAlGKMRJaRJitYG7z3OxWzFSIrUCkznCcGjlMIoE4kSo9FaY63FOjshPSaYYIIJJphgggkmuCFuXdJD1R0+xM7WqOCwddE+1EHm1FZWRGIjUE/6R/5GsRPIB8ewdDhrcUFwPj4Kp6mCwmIQnaKCQusUrQygCEFwQZAwsscibru2wvKO6GY1UpQEiURAkKhw2Nn7aDWFjNUZI2IgFqpB14WDKFaQcZcTEgv5IzePUCsYdiyXRics1IHpCpTgvaeyBdbmQAnXFKEEh8JhA5S2Ii8DoQy4whNcILgqBpiLx4khSKgjUqLOJNT2VYpoUcXY3CPuUHB1fPiu0xbtxVT89IQbhNHutp3aOdfxfIdxR3V8TcX9CALjqPJQh6iPzFNG2wTrHN1ej83tbfqDAcG7ePHUn5EoSBNDI1UUaUqWpFgVcF4TXFSRVNZSVAGJvmoMK8G5eEypSZhJmygCnTzgigFBpyRZQpYolJGYSyOeobUMnEUkkGQpiQSUNyivMUrRbCRkqUFJiIEl4qicJy8rnAtReePBVp4iLyiKEhFDlk5h9BRZc4rUtJHWNGpqhnZ7hqzRwKQpyhgCgg/shC9P8JpAIN4fKuvodIb0hxWdrT7D/pBiMCRVkGrw/iX6Kn2DYANHHze+L3kDLomKDQmRvADG9xivRo6IgWDC+HahKigENgRy4i1fPGxWsO5i5u/XUtdVommaGRLdHKsyPJ6i3KKqOlct60NF6SpENK1knsxMkUrKcHiFRLdpmhmaZhaNIlMNEhG871NWG+S2gyC0skXSdI5CJ3RESHVCUyWYUJKm8zSyPWObyF7v7Is+jgHljV/wRXzsggsVzr0wSRcIlLXHTqaaLCQH0Wj6bpu+67zg+l8PvO7o6/jpP/nTrHXX6A2n8GFh/DUXv7Yc2AFUXbQtyHwgDZDVCkutUlxjnqraO3bilPYBsnQekmna7TbT+xq0K5AsJy/WwQudocM5z0Z3hbWtIZ1hyVZR0qWkkQmL85okEVzusUMHSkiaBp0o+kPPxlYcR/UGJSubJSjL6sYMjSSjM1RUun3D4x00pimz2Gew2/HzRqSHIuaaTHDrwgNbGrY1XFTQ7UNZwNQWTPUh6zsk36QsutfdfyaY4A+KSGoo1K4HMCYvRtmEIcRxcwj1HOMG95yR5XFE/QUuMJ6t+K/lG3mCCSaYYIIJJphggj8MuGVJD9sWqhKKPJDhsaGP91toMaQ0UKIpHZQ2VqKUp07Q8DgKRASTNNFpk+3ekBMX11jf6pNkbdLmHKIMVlKcJFhd4ZIEtMNjoNyZzSuAoEDSWBkLKtosWXCVRF8RrSBRdVeSBvFEagaE2KE09r/yus6eoG4RDqRKkZkYrl4C1odYaJOKOpyDUAmIxJBRCTHzQ6JVBsGD9YhWpGkKAolRCDmxLHd9EdTVllGuEi6vD0i26ywUF6vhaUhIgkFpIWmWKF2hJYmB6kGwNfnitaC0JohCqxQjSbTEqgqcczgnlFWoM0IUjpSgBCU6hsqPqyewwwgFlI7ZJ946XGV3GDAUKhhU0AQRvJQ4iUU2RdxmND9T9fl3gGO7s81nvvAlHn3iBBtdQ9FP42kJHhQkiWFuus3MVEomKQ3VpCw9m+sFg76lGpQ8e24ZbQIoAyrBukCvI2A1+w/u5VveeBepDnzhyfMMnz1PszHFvmN3MjWd4VrwzPIAHxwbnVV6g232zM7wxjtvY6bVxNsCN7IlMvGaKiphOw94H9gsC5LNioDBOYX3Kd1uj/WNJcrSodQ0x44+iEnatGeOkKRtpuYPMrPnKM3WFAcO7ac91yRpKnKr6OUwlUCaMsFrBEUdWr65MeRLnzvB0sV1Tj5+hpZ4QlOTGocRj1eTauON8Pc5ywVKBngaGnp7YX1fDJ9ObAw1HxO1EnM8vAJJA4MjFcoJynqyreh3/ytDeCbGGSEBSg8nh1+79/10to93H/lzHJl+I71E2EwVQ9fn9Llf5cLl32UnUWQHDTPNmw//Ke7Y861sl1c4c/aXyW2fty18D29c/AGUadBtZOSJZnPzcR45/4v0y3WaCw9w/4P/EJctcGnhLs6msM/DcQsmaXPstj/BnoUHaytB+OQn/+TXfN5fbhxr3sv79v4ppswsn9/4bb6w+WFcsC+84suMS+uX+NkP/yz//fO/Tph9L+z502g9hyeGt1t2roVpB4eqqFxtOUg9uPZ9JG/+Oyjf5WAFRyxIOkM5dS/ewuHbDebNLZzLOf/ob/PwV34ZXKDlAiYEZq6sMP+VC5Su4IlT0QrtruMZP/Fj8xw9mLB+osPqE9uYhuHAm/cyfWSKL36lx3/+9VVW1itOnYaNTWhkFZ//7Cqt5hb95gZbMzcmTT82A5sK7Gh4ZIhf3aN/T/CaQinwoSn4rRnobsHmQ3BkGQ5egXvXQQYDnrnwAU5e+QjO3YTInGCCrxFaG7KsgVKKxGi00jjvagI4oLRGaxWzBQuPr61tQ51p6BxxXuE92ihE4nR21BeljUFrjbOOIi8mSpAJJphgggkmmGCCb1DcsqSHT8D5OjecmGkRwgChgZEGGqHy0dJICGjZsVfyYgmA0lOYpIHDsrRZcnGlT7OdMTVn0CbFZA1UkhAkIRiJfuMu/oDabxaiFANdqxZ8tLvy4HNNsIJKBa1NzZOomLfBSENQS1HqTqNxM5KiJj0ErRSpiiSJCxJ1C0LsboJIrPj4etCh7mBSiCS1vsLXSgiF1glKCUorxqmlN0DAxf88lNfkHguKFooGKSYBaTqMisdmSGoFCngJeAGMImhNohIS1SQEH+2o6vZVqbM2Ykx4vOSURFXKmPQIu99/lBAc6Qv8SM4zUtxoFFk818qCWEZak5HfhmIUxhpJsWE+4NRzzyFogloAcxAw4xmS1kKrkTHVaiBOIzahLCx5p4MlUJYVnbKDxwJTXJ18oZidnuauu47RTANnly7TYJ1m4pheCEzPG/pl4EqnorQla1ubdAarSAJZM2F2rh0rpkWOxzMESoTghEEFlQ2oYhRW71AqBQKb2znLqz2sDRjTYH7+GCZr0Zrbj8maLC4eYN/+w2SNNrNz06TNBJVA6aCooKF3CWcmuKURAOsh99AZlJw9s8yZpy+ycmmdhEAr0SjtEanVURNchw+yOf49KCimob8HshyydTD1rVJCTXYQ1SDoQDkfEA+NDTBbMCjhSx34/MvoJNYwM9w5/x5et+c72cyEy01Nz26yuvFwtLG6wcdqVJOj82/jjYf+BKdWP8oXz/4ca91neJM7xL7GtyOpwSYJpdEMBpc5v/RhOsUK9+19CweP/RBdnXDexPBiAQ4qUGTML7yF/fNvwQP2FrtBLKQHeHD2vSykB7gwOMkX+cirsh/bg20+9dSnAOH4XTO8YfZPjO+pru6HgHheswBzDpoCbRvVHmuNA+i9BxADswUcLeOyuYp/6/N7FPotCd4LG888wXMXvoTb3bG8DDx19T7tWzR8xzdP8/p7Mi5MlZzrdUjbijvfM82e++fRSvj1D69zZQ1WV+Mjsv89ANr3DJh/242Lg8802PmeHn3VaiYhHa9RWIEnG/CBaVBdOHIW5k7AvgKODsDnJU+uPsrFc78ex7ETTPAyQimFSRKUUmil0Co2g3kf5zNGa4zROO8RylrxXivnIVrdOokESZ3vAYytsZIkwRhDJRVlMSHtJphgggkmmGCCCb5RccuSHoQojqiAKgRKl1NWPSR4St1Eq2g9BeBDoKoc3nuKCrq5wSM0Ck+aFWz1HGJaNFuBtNFGmxSlTBxAOxuDuWPbUG1hUlMWYVS4l1icDxDDPGKpWKWaoBXK7EizqbM7AtGuBJGYS0Fte6WAkXUVPh6nF0qvajfuQFChtrKJxzeywBpXpwMgHodFEHQQ1Cgbw8VB/wvLuXdvsJaTC+jd4YDe4UIglA7tPZV4SnFRMu4iFyEmILpCcASvCLUJr3euJnoCqi6MiFIYMZHo0SqSM6RoaSKi0AaUFnywlC7HeYczKVYyCLW9lsRlktQgAsOiwaCwkYSq1TXaGNKkCaKoQo4NKtoCVRrvhbjzAxCNMSlaJShx9Ht9xJfkRWDoPKWLZ9iLjgoeTDxnwQF9jDZMt9pkacr8dJPUCFqBTluo9jxk0xRBoV2gIraSK7G0Ww2MmqORNOn0SlQYIL5CuZrsSiqCDuTDAZsrXYqiQiuPVh4fhNJ18UFhfYMka5M0EprNWdKsjU4aZO1FdJLRnlqk1Z4nazZoN1PaDWhmkBjQdXeuC/HakhtcFRO8+nAeKgdV5Xjm9HM8e/Ycm2sdzjxzipXLG3S2VvBhCFLgvQXrJvZWLwIrOfz9h+Pj4R+INlf1rX7sUqj7YBz0GofYmH4dJSmd8Ay9/AzP2cBGfYudbh1jYfZ+ADa2T9AdnN/1TsLe1u0caN2DCxWXek+xXSwxm+zjyNT9pKrB8uA0y8MzFLbLmc2HqHyOmj6KSl5P4qMS5WawPufS1iM0zAyXO1+lqG1o+olipZkQVMHp7SdYs2us5xeZ2/cu2sEyM3M3CUIzCPs9NEN8rCpIBfY5oelr4ucWuyFslis81vkUU3qOS/np6wqyC9lhDk3dj6BY6j/DWn7uqtcXm8c5MHUvITgu906wlV/6A+5RYNA/x/KlD5M19jE1dz/N9m2obJGje7+Vvc3bSOdfz7lGQlPBEWC+AhCaAQpnGW4/y6X1UzR0m8WZB5jP9tFe62BPnMG6Zdza5gvsQ8TqhuXjn+9x5rmCtRMFK+cCpuE59VCXmYvw7FMt7k6+mYVZ4VJ+mqXiubqEGOEEhgb2/7VASgxlzyUGXRe7r8NdTpSjfzvgZAYfnI6kzgiHLDxQREuvZzI4k8CMh9fnsGdyq3rFsWQi2bEeLCdPn8R//jSNrSn2XX6AvcVedOcCp9eeoszX2Bg8x9euXZtggpsjhIB3juA9aIX3spPp4cM41NwHH5X7xqBEobQaq0GCj0a2SsX5U2xIGxEjNT0ioyawnTvdqJlNkKussaI6fXJTmmCCCSaYYIIJJvjDhFuW9PAhYEM0Z0rwDMoO/dxikxm0bmN0HVItCus92/2KvHBs5SmXO00qr2ilnobpYX1AZfPM7plD6QxlWpGMcCXWFgRclE4Hj3iF+JFmxII4BI1IiqAIIgQtMYQjMYSgGP0X9zvKrUUplI5dTE52gsy9BMQIEjxSp5+XgA2x1TYoH0kPrwhBxXB0BUbVQ/Y6PyTgsOQICiUZigQ8uAqC1NLv5z3DivjxB6KexqO1opVG+62i9Ax8GW2z+mUdzl5PENCo0EZCgyT1tFSJSQImWKrgkAAyyuAQMDFnHG0MykRSJTGxs8uoKRKzgFaGdlvRbCqKqmK936GwFXYYqNJobaWNQ2lPmgZaU/H3jWWNW9ZY7yilxCtHlmXMzc2jtKZ0Ayo/pKo8nY6nKAOEkmDXEGVoNBdoNlKMrthYW6OjwOqUSjVwFgoEqxM8gUAznis/AD8gS1ocP7iPxbkFjh1o0EwUWgXM1DzJwjHIUrohoSgsYkpUIycJgb3pDMbPk2jN0sqAFZWTGEiMYExganpI1oDt7W0uPHOFfq8kSSwmdZTOst7vk1eWvQfu5tidb6PRnGF+4QhTM/tQkqB0C5GEuYX9LOw9RNZIWJhPmZmF6TY0U0hjbA1lqJt2a+Jj5FYCI6XSztUywSuPysFWH3r9io986BN84P3vpxxWuAH4ElwYYn2XoBzOBVwZ8K+C1c9rGcMGNJsQDDgdHyaH6SXINmF1/xt5Ys//yoaZ5WH/M3y1e47cW9Y9gHBg8R08eN//AsAjT/9zuoMLjP5ylGjunf8jvPe2v8bQdvjwmf+d7WKJw+17+cFjf5u5dD+/f/nfs3r5PJ3iCp+58Aukl1vcefgHeevM/5WWyjDPcyPPbYdHL/0KT135bSo3oF+ugcB6M+HkQou8WOfh536RC8sfZW7/uzl231+h0TpEK1mgEQyph/t9LFhf1vBMLVh80MO+sJMjcyvh3PBp3n/pX6LF0LNb11lbHZ95kO89/j9jVMZHzv0M68sXxsSIoLhr/t287/jfovI5v3fmn78MpAdsrH2RXvcMaWMvh97wv7Bn5hhTM3fw1nv+ZzJb8szMLF+YbtAA3h2g7eM9d96BchXbF3+X5RM/z57GEY7f/Xe5Y2EPi5vL5E98iqq8RPnc8EV9EM8+V/DPfm6VLBGq3GEHAVGW5JFVdLrB3ck3877mX6d5dJ7fvvIfuLJ2ERd25EqFBpsCo4zyEFsi7Cj+ajfZoXY9iMqBj7ThS82rw8r/aA/+zhrMOPjNafjFObi3gL+3CnuGf+BTP8FLxJMN+Md74Dlbsvn+D2H/07+nqY5zz4G/xx1Ti5xYfphPnfqndPNlBuXGVaTYBBO8XPDeUVUlIoK1sREs+IAdTV5GykslJMZgkgxRUjeYBay1kaCQaLErAtZagnV1z1qdBUi0r/VxEhWzkwS00ojEhjVt4qh3OBzihhPSY4IJJphgggkmmOAPE25Z0mPkCOUBFwIuOKyzKHGU1uGCI4jCK8G6QGkDRRUYltArharuGrJmFFxrMEYhKonh0CHgQ4idQaORMLtCtyUgtXds/J2x5EJE1UHldadQIIadj7ZRF/zHOo3xazst9UGog7xjN5In7FSYr2m3j2RD/VS9jB/vTkBqa69Rt9I48Pt5cX1Pv9TbUBLD/xwxVwM/qniMCkd+nJwRXCD1LrakBw2hulp9IrWSQASlBaMVSoRExwB0ozWpSaK/b6ppZPFg0tLEc5IQrccIaO0Q5TBJoNlUaBMYNByZiUoUFFgsaZqQZRlaa6QqwSrwglaCViObLY9SjkQHkkTQeKrSYvH4ROEyF03KlEIbIWAwpDErxBfgIUmEZjNhqpmRJVEF4kNA6RSdTaFSQ1AGj0LXx68QGrpB6lMIUFVQBU9lBJPEznKTOdCeIi8Z9guGvQKbOpLKUThLvz9kWJXMVhZtUpKsQdacotmeQTAIjRhsnjXJsgZpaiKhosHoSKIp2XUd7VJ77L50JqWOVw+jCJuy8gyGjl4vZ+XKOufPnsdVjoa00GIQXaGMBakt93wMuZ/gxWPgo/1QEqgTgMAEMCWEIfTLBpthH+vMc8lPcdZBCAqjUjIxtLM9zE3dASGQJTPXbT81bWaz/aSqScvMkqkWLTPLbLqPuXQ/DT0FCC6UbBdLAOzJL2GrLmhH8NeTWEoMWsVAntz2yF0vdsX6CqUSCiwdhgxDj838Ihv9Z8mq12HSeRrNA6QkUbfmAw3i3/6m7KQ/iYfExe8A719GD6+XAYUfsFoObvp6qpvMpPtIVEZ2g1DuVLeYzfZTuiGJbl73eqINia5VffV3pPOO0pY3LQDbqoutupS2yzBfpbB9WhjarcNMeY1qQsdA4T2DUFI4h1MaE1LSEOhVXXrDZZpkeFugA4TCMdwsqcoSV2mUaTH6Jr4ZhhYur8TfJYyGdwHXKQmh4ll+nw/x+1efD9XCC3VDR4pV9YBiNObZ/XM3rlF7BIFNwy4TubjORQOdWiC7ZODZNIac5xMm/RWDJzpoOg8bDs4HOOc9stEhPbtEmrbI2ttkSR8/XGOzf4ZucQWlUoxuEULA+QlDNcHLh7EiXQJBdkiPEVlRL1Vb4Ea7YbVLlSG75i9XPzOay+1sR5SggtqZm4mMw9Njg1q8GSlRN77XfaNCdp3ViW3qBBNMMMEEE0zwGsUtS3r0hzF7IJIfikE1zVYxix8mnN8c4kOFSZqYtIUPmrzyVB6GISBJifaCVTCEaCvla4WEcgRXACHaWtXExqh7yDlPVcubExG0JFF6bVS0tho9Qi2lDr4eFMbuIh/L5oQA2lqU+BgOTgLETlOpFSoi0aJJlBqTF6hoiSUxKzs2VNZqEkFQIVYZtDHo1CAIJggqhDiwN9HiqZleb1kUmzPjBMIR6nyK0RIa5xV5qWLHlPOAQ6HIpIFCEcTjVSSRnKvwwVK5QH/oUCqggkVRIigylWCUjpZWiYndVh4SG6vrzvsYyp4M0WoDj6LTV/RywXmHLSvEe3QAb2KYdz7MqcqSPYvTHJg9zFQr42DbMjxso8UZNtqDIfig8N6xvtpno9tDS8K+hXnQjUhcoBGlaTabpFlKOazYXs+pSkc2ndJoCSrRzB9sYIiWXEHXahxyQshJTcLM7AIqa9INmlPr8Th9sp+jh2YRo8mmmqhEYxJPkniUCA2VkUiCs5ZykOOsY2NrwPpmj0BFkmyi1ZDudo+1/jpVVdEIKQ2bElTG3NQMM1qzuHCE6dk5ms0Zms0WWdJAqYTUtFHaMDuTMT+nMKmgE6EKsWPX25hpMPpdKZAkXtaWHRuTRMaGXhO8grAetnoxN+LShRW+8vDjbK5vcvbpcxifoNAE5XGqQomrXfKi3Z8Lgg+TTsWXgv9yAhpD0D5meQQFqoKsF+9ZG9tPc/7Zf8NAN7i08QVC8Myk+3jT3u9hT/M4CwtvYa9rUrg+6TWEUwies1tf5CNn/wWpZNye3sW9h34KK4EvXvkAJRWnth+6Tp2zuv0kD5/6GZRKWN54mBB2b1g4Mvcgd+/9DrRu0TWQa+h2T3Px0u9QFGtcWfscj534Z1jbY7tzEoDu9jOcfebf0mzs597Fb+PY/LtJUGTWon1gTsEhDQS4q19xOLcs24s83f/41/cDeJlxsfckv3/+36LE8Fz3kauIikDg3PYj/P7Zf4ULFZe7T161rlaad9/1IN9679tIdQNCG0h58vKTfOiJD7E12Hre9/Z2wNaFD1EOLjNs387sgT9Kv3mYropjmaLc5uTF32V95XH8/L2o2/8o7WyW3qFvgTShb+Z4dPEOzjeFY8kDXEn+JuK6rC/AQhHDp3sqBqXXBxRR/7vt4aCFRogWUw0PebnO2aUPs9E5ccN9/t47/i+sNAyDRLFx8A0spVNYRWTAwq7H6H1GweWKF+WHeCKDf70Q9+mLzVHrxASvJLZK+PAyPNmBJQWzGu4tU+Y3v5W52zOwluc2Ps+Zjc+w1HmCwvbQusnhA9/B3j1vw7uSR5/4h6/2YUzwhwgj+6pRY1R8cvw/Rg1hEuq2sKDwIYwthK21WOcQic4ACHgXcxIJ4KzFOz9uuhJVz6Jq4sQYg1YK70O01AqRgEmSOC0W2ZlBjX4ViUp17z1VWeJvIRmk1po0S+v8r7Czb7vvz2HnuR0yg13Lhdhkp0bWX/GYAcqynGSjTDDBBBNMMMEEr0ncsqTHMI8F2JqSYGDbbBcL9HPHlY2c0gaaTU2zOYUoINWg6851U6IDuGAog0KCYFzsNPTeE6So36WefgvoutXdEqhchQQhUSkiBkThRYFW9QCw9of10Y/WU69PtJ1yBFQIeBdJDnzddSkSK2pQy6qjpFqpgKgYvhcPRqN1IEnigF47hfI1wVHTJmmW0mw24zquAm8RFVAm7kcz2TVQZ1SjEMyIdMHjx329sYrhvML5UftljJBXGBrSJiHFaYvVFT548pDjXYn3UI0bAMtIzIimmTRJdQwSbCQaLRK7h+sO9gJPpE+G6KREgtAvop2PQkhEx64uAtoEgvXkwx79Xs7CdJv90wfZszCLSQSTRaLH+qgO6g2GrG9uk+c51eZlusMeKmszNT9F0p4jiAFJQYQkCRgN29uBlSVHv1eiGw1SLaSZZs9ci6lmE60bJOk0SgxOHF7VGTC1/3DPw+n1OFEIyRSHDyZxkpUliFYkWpMkBqVUDFjUmiov6IdtyqKk11vhzNkulS2pqg283ySEIcFvITi8nQXJSLKMmYVDpO0pFuYPMT09S9acotFokaUNjE5pNFoYnTA7nTE/q1BGsBpsqAU5ro41cbGupRQkde6KBYb1Z9QGzITxeMXhHGz0YL0HJ06t8LEPf4a1K1fYuHIJ41O8OLyq8MrX3ZJAiH+/PqhJUfEl4r8+vUtFt7v4UhcDQuckoXemJlNjPtNMuo93HPiT3D33bqxJKH1Gt+qRXlMECXjObT/Chc5j7M2O8GeP/N945/z38sj2x/nPF/4Rl/Mz+OB23Ysj1jsn2OydAqhJrJ3tCsKhmTfz7tv/Bmm2wHIGWwksL3+ctfUvkedXWFn7AqvrX457UCtFep1TDHpnycw0d9zdYl/z7WTBMF1YUue4TQQnoHxgvjNgul9QDU9xafU/v9yn/OuKS70TLPfjuXPXnDsIXOg8xuXuE7V119Vkk1Gad97xJn7qO/4nWukMhL0Q2nzg0Q/wuWc/9+JIj0sfYevyRyn2fzMLi29lOHOYnorfTbbscOryb/Hs6f/O/JHv4fZD72SqscjGgfcgR95BPwiPBYME4Wjzftam7iYNgQ0FCwqGAnkC1UiJsfvQBFoWjhcw66Od1IyFTu8MW91nb0p6fNdtP8WJuYy1huZsS7Oamp3w+hu8x9jS6sUQHxJzPE7XTRhWJqTHq4GtCv7H5fjYm8M9W3C4Sri9880cO/4OrnSe4jef+WmeXf9kvB8FS5YucPjgt3PvXX+JyvYnpMcELytiQ1utWR8pMkb/36W2GCk2QvDxdlQrQcb5GwJybY6ZUGeDWJRWJEkaMwRVnHeNgs610tiqoqzKMQFjatW2UjuqEhWr/2NliK0s1to4iL5FoLQiazbQWuOdw7ldd1qJ53jUACA3Iz0kkh5jFYyM7MQE+lCV1UTxMcEEE0wwwQQTvOZwy5Ie7fYMDsgINLIUpZu4kOARRJUoFT15RjZPIyeq+FN2qRtGv4f6+VB368OuIXb08xhZRakYXK6NwaiEoBViNEHtEAlBokVQUDHeQ9cm1soHVPAx5aMOyovbg3rjsVuISJSM3k/V4ejU2R1Krra7UmrUZBlJj5HMWwRcqHCuQKOjkkOELMuYnZkjz4cUxRBblbuaNkeD3xv5VuxUMGT8asDjIQQkyPicxkNSJDpBRGF9HGj7ejJjfexCL22JVopo9OQIAlZqSy+rMJVDpC7a+qik8dQnd/S5KNBGkRiDiDAsS3rDHOOExI9ID41HGBaOsvJULhB0gs5a6LSJ1glKGcCAxImPkRg+nphAq9UEDM1mgyxNSZOERBu01mgt8fNS8bOPAfWjvqj63zKS4etIaKlaoRNUJL/C6DE6No0yCdpDq9Vmbn4OaxtYV+B9A5ECpeYQCUzpedpqFp0kNOdmMY2UqelZjGmhVCPmx2iNaIXSGm10nKzU14hWO7ZW3sfCutTP1Y1x4yY7ueoqiBhNn15EY+9rBtc0Sb/qcB4qGxjkFVeubLC0NuDK0iW6nW0G/T622rEZCgR88JFcHVvzjf6WJ5PSl4JqdxX2hqfOxwCVXVBA5jUtb9gsOqwVm3SrDRLd4sD0AxSuRzdfxvocj8MHR+H6rJfLLOXPse27JO2DtFKhyFcpivWr3jzgcf7mXZW53WZjcJbMdfFmP41sllSS8bfdjJplVi/gsGzaVQa+D3i8L7FuSHd4mSudp5iWFlN+jiw0cEpwWhGcZau8wkZ+heXiOYa287Wf3FcBAY8NV5+7RDWZzfaT6CaDapNOscK1AegQu483+9ucWb1AO1tkKpsnNRmDKnneYn3TzDGT7UNJJAycElrJPPngIuiU0F5kRu+lcpB7S+ULgq/QIWBCQOcb4NZApYRsP6KnKZVmU2vS+DVJKlGJ1JY45qgERu0bI+4haBgmUbWk6uUG2RRu9jjkD8DGk9ft++ZME3UwpT2lyUL8yh0PDa69OY7+rYAZYArMLLQ06BCVtTlXr+clKlRUgL0WFl0MN7+i4YlsZzkD7Lcw526de/KLRQC2NFypR9T7bMxreTWPwwMbGlYNnMtL1rvLFMsdnJshqQ7QcAlJMPW4IcEHi/XFeP0QHHm+Rqd7Gmtvbic3wQR/UEhNdIybDwDGaoPdxfkRAXJ1KLnUc62xpVXYNX8KI1XJaOMxGN07H9X5IewKM49s8lgdIqM536ipbTzJRIng1WiudIO/9KsUFlylrhhv61pcOxW79rnnQSQn2CGQrtmlcNW/d/4xGv/LNc9f/b5hTICEXWqRq7e402U3+jxGwfQTTDDBBBNMMMEEryZuWdLjnnveHG2WvI0B29NTDGngTcHUtMN7h2iFmDh0tHi8CygfVREEQYuKMt0g6BAQ7wlaCPVA1QeFDwJ1YDni0UbIQuwAak9N08iaeASLiZ1JLse5PA6001hqMCaQpg6RgM4tRVmhxGBUAyXJVRSCD7H0bxRkJtSEicIoIQg45fBicV6oqlhY10biAyFDR+JD1WoN7xkU2wyHmyRJg2m1B21S9uzZz5tf/030h31OnznJldXleMx1R3HYPSMYl3M00YYrZlxoHIqADSVeHMpHKy2PID5GXmdJk/nZvaQmpdPvstXtEIKnsJZSKpQFVcbJwzbxGFQtLVdKkVVCVcbnVNpEJQ28F6qQIBhEW1RSYUSYnm7TarSQRHNmaYl0fQ2jQetAQGFDA4fBe4dzNgYlJnO0DtyN0gaTzqJJEQwqRM1MojK0NsxOefTtMzjnSdOMrNFEa0WjYTAmUk3eV+CjysNLHbYYdhEdSZSWawyKaFOGiwqXEAI2eEQF8AqnHARF0pzCNAJ33DXH4SN3EMSDzkFZkkSTNQ1aG6Zae2g1F/G+YDi8hK16eDWLlX2ITkkaU5hmgjEpSaOBMSkqieH2eGglYOoAc1tB7qHRAJNE4iMEqPMfSWXnalD11VGF2KlsJD5ea0WpaxHN2yJGx/lqoztwbHQca2trfORDv8UTTzxOZ73P8vm1GF5eDsZe+845HDaSuOO/31B/mJNJ5tcb2nmmBzlzqsfJ3qf58NavUYjl+OI38/2v/6csdx7n88/9LOv90+N1enaLj639Ko9sf4xk9i6O3veXOZK0Offcr3L+3PtfdHZGwHN243N0iyu0Gge4/86/yJHk29l2sfCs0XxT+z28b/aP0XPb/ObmL/HU8JHx+tYXPHnlg1zuPM6R5Bh/YvrHOZbeT54lDFoZfd/nM93f5vHV36Xrtlixl1/28/dKY7F5G9967C+zv303X135HT5/6b9QuN51y1lv+b2nPsfp1QvMtW/jzXf8DQ4v7uORyzB4no/n9rm38Z4jf44smWcrU/SNsD28yNmzv0a/WGfPbX+MN975Z6hKOOVghXjfaQVo2pLkuQ/D+fejWgdo3fdXSPa8lVzB0yout8fDnIdpB/N18PyqgosanEDq4ze3DXDSxOtgRkfFR5nsYfv1PwH3fB/8j++5bt8/fHfKm75FcfQwrJ8G/QiRvVDEEeJui6s47IAUeCNwF8y34HVtaAGngWe5sZqjEeCPdeNjXcOHp+EXFnZen3PwE5vwXb3X5vfLF5rwH+fjsf+5Lfje7qt7HE7gY1Pwy7Ow7tY5eeI/wsc+Szr/LuZu+0lmGwcxCJWKD39NldTaAWfP/3dW1r+Av4U62if4wwEh1A9B1U06IYRIRhDQ2mBMnKLGvCq/o/io8xhjMV6R1vMJ6yxVZXepEYRQW10xIjEARLC6qhX3EhubjI7vU1tk6VrpEUJsMAkBgvOEEK2wdKJRRtXESK3g3/2/0c8xCSHouult1LSym8gh/nodwq7/y2ixXUTFmIcWRfAeNyaFrt3Y1Q0xN+ZSanLHhzjHIdoNj/Y/a2a7lpKrVlNS56MowSQJSinywZBeN+aNTTDBBBNMMMEEE7xauGVJj8WFA2jFuNvVGEOFQlQgSaLxuBfBS61Z8OAC4AXl6856ETTEAVmgVioQAzuRWvmxo2cAH6XPRkV/1EZK2szwQSHW4EPAhap+o5FCQzCJI23E/bYudraIRCJDKT3uRALBOoV4hRZIVMAoMKIwShMkUGmHkxAH2F4iKWPqLv1IA6Cv6n7yVDYnr3p48TS9RYWEdrPNgf2H6PV7XFq6OO4Cv3EQ6+7n6iI+4/SRcUaJoJBg4hIhdkVpndBqTJGlDfLSIgwIWFywdfG19lTa/Q6iaIaURGmCA+Vil1KqEsTEZZ1XCBqt/LjjKs0MJJHI2ux1ESWRNJJIelS08SRRwaFBJBB0g2QqQYlCqxQlGhU0qtbMaBK0ZOgUTP0hKmXQksbt652OqRAc4KOtWT0hIAghCIhCtI4D/6Dr8xNnJvGaixMJCeCCj8GNStAmvk+73SQ1rZjLksVsliTNaE9NYZKU9vQ+2tN7qcoumyuPMRys0s9bbPdn8Bi0SVFGxcljYlDGIEoRgiABjIKGiYoP72NxLATGxzf6GxJVXwGyE3YOkfCoj3hs6f5axm6q4FYgPAJQVIHOwLG+NeDMs8/wxKMP4UpN1UsITpBg689qFPbpCbJzJLKb/Jjg6woVAmlpaRQl/d45nl37BFZr7jvw/dyz9ztIVINHzC9dtU4ZCs4OYqf94ak2Dy4+SLt9hPW1L/FSr8Lt4QW2hxeYahzk+KHvpeEhrVVaShQH02M82H4Pm3aVT3c/fNW6IThW+6dY7Z/Cpfdh1fvI/J04JUhIcL7kXHGSL/U/fUM1xGsRrWSW47Nv4/jsN7EyOINWCdygjutD4OzaRc6uXWRhag3JNhgEWO6CdTe+6wnCXOMw9yx8K63GPlYbmq1McXHl0zxx8t+wtvU4izP3sb+qKF3gYl3gUiHaPabOobefhQu/j3c5vad+4br3WKp/ftdP+PH9d0i8XwOYAGkQKoENFQ9toCK57ZIW+dRb4o37p8LVlTLg9CK84U6YvgOaQ1BfId5SdltX7SY+IG5rH3AnNIADAaYDrD4PIW4C3FvAd/bgqw34+Xn49K6c+X02Eh7w/Hewaxuonw9f7++p3a0jlxL4RCsqW769/3V+45vsx2544GwCH21DLxnA2mNw+iPoww2ygwMaaSTHrAJXK1evWj9UbHVOsHUTW7QJJni5oHapCCKZEYkIY5Ka6Kh2SA+/W6lej0lVnLN5HxXpUe0hY+WIrwPTR8sDBB/l88YYtDFj4iKEevyrolrfeT+WQfvgY/g6O8qKUV7IVWqVOOmL6pN63TgvMSgViRQ3IlJqEod6X3fJLuqn4tGOCI/x7XgkrAi7jumGZMdow1dv84bqlPq94xiz3vguSc2IhNqtfgHZOV/1I80ytFY463Zlo0wwwQQTTDDBBBO8OrhlSY978gFdFMulwwuEzBMSRcAhIYGg8cpE4gMIIRIZLjDuANJaR+m+AjIVO+5HE3lipxE+WieJxCIxaJDYNeR9RVUN8F5hnSYEQeHQJmZxiI7FeC26bpMPKA8JOtITEpcLI9U0cZJpJA4aK8CGEFUVdSeM9SEerxeUxEG3GnUYScCKj8PVYFEu5muIUuikjUhCmVe4Mio6Mm2ojKnzRq4dTd9oYOyIhhkSiYuaKiHYeuCqxxJyX0sIrC3p9rfIi4S86BMoAV93oAtGa7IsEhFFaSkrF1UF9QTG+1iEVyJohmjrUZJgCIgkGBswVUApIclSTKoQLehRh5ULeCcEFEF5EEeqDe0sQwkMqi7DaoBOm8zN7qHRmKYqKophHov+JkPplKos6HU7WFvRnp1jer5Vd4VVEBzOOopB9P3tl336ZX88sQJQSo+7m1rpNM2kjTGGdquFMQbnBVspnA/0ugXDYUWjkbKwOEOWJdAKJFlW21NFy4kA5EWF2ACqTyDF2SHOZ4iaJcummNVzgKbRUKRGoU1CI4lZKkarscpfC1EVI7XVVd2AVtl4SYxse5WPr4+xM68Z179uVAPbtdhLKjRdM7/7umP3Va/rn6/GlGzkIONDVN5YFzj97AUeefQ0a2urrF5aJxRCsJ5AWVuqRSIx1H9fgtTubzWhKbaem//hKFS/3PhR5oH9lBxmiOVJTnJxXE5+aei6bb7c+xRXqoucGDxCGQqcV5zbeAitUlZ7JxmWmzddfzC4xMWLv0mWLrC19fg1QeU7MJJwZ3Y/R9M76Lgtnsm/yrbbGL8uITBVWhYHBRtFhfEBHxxn82f4eOe36LkOK9XNj7HrOzw8+CxrdoWyMAzzlEEYsDQ8TSAwqxe5p/VGpvUcF4vTnMlPYMOLU6TcSuiWazy59hFWBs9iiy3eOfc9DF2HM/3HuVKcHy8nKI417+F48z5MOstg+yRPVr9E2LzAt9i3Y7mXk5ziLGdJ0jkWF99Ko7mf+bl3UWQtgokqj76CrLGXN+z5bobZvUhocPHcByiqbfr9cwAMB5e4fP43SbMFtjcfr0n158fS6V8a02NbCrwGpZu0F97MzNQdDJSQh9jlXwn0Ta1q2zXuGaO+GQ6HcPIkbG/Bc89BWXE1K3wDaGCBmPu0H5gmqlYSrrdVebHIBR5q7pB316Lt4cEhHKt2XncSLbKeyiLZMMLtJbwlh9bX+Va4qeHLTVg2sKrh+3qQBbi7eOF1X07kCh5twJl05zkb4MwGHD4LdnmapvwR0iNN0uY+Li1/jGXzEA0HDQfbw/N08+VXdqcn+IbGOC9ipKaobZDGGRJCrYaIodxX2VoFGI1EA7HZzIcwtte9qiCvBK13AshHqgMf4vzGeU9VVWPLq9HrrlZ6KKUwOmYyeufG+zIiYXassSJG+7ezd4zvtTEDckSE1LOpwJhIgZpnCDegLqRuR6vzOW6sCgnjc3PtfVh2ndt4HkY7FUfySmu01jEY3vvxtsIu4uPat5TRu9b7HNeDsipRTuGDxyQJWuvryZjdxwPj8+icm2SHTDDBBBNMMMEELytuWdLjHf1tzlQJKwMVPbKnFTRrtkDFEGpPUqs9wIsiEEUFUY4rNESTmjrXII12RnhPGBEUuEiiKEFUEpUhRqPFgIBzOT4fELzgbAy3aySGRlqHkisdcxyCJ5SxwyhxKQaPF8GJjhPxOspBCKQSCwMVMCREYsE7pC54BK8ggFYSJdsiCHGfvQQq7bEqkiumtr8SbUgbswQLg15BcDlpS9OcSvFJglEjkyK4uqP42kGlZdTP7wBX6zyE6HvkMLhaFeDqZctqwPp2gSD1BCV2aalaJ9JIM+ZmZ9Bas9UZUlY5AUdpy/gOuzpDpbAgfYwytJIhWhlMSEjIMEYztS/BtHQkQExUotihosrrAnzqQHmyxLCn1UYrYXlrm07eoZGk7D9wGwsLh9ne3GB15TLWOiRJEZ1g+wXrS6vk/T777zTMHT6A1oIbloSqpMwHbK+vURYFy5vLLG9dicdaBxtL3dmllWH//BEWZvbTbjVIDu3FtBpUVuiXirywPPvsMstLWywuznD//bcxM9NGGaFtphCToFON1gnWB7r9gkBJWQl5XsbPzLdBWrSa08w3FuuMmBg8bxJNM2ugjcZoVeerRCIjM5HsGJFuPkBejS/lmJtSZ3wouMoDWMn1BIVjR/0xen5kFfV8da9wzU9eYPmXE7vt6l9NxcroL61yseiY556Hv/gUv/KLv0G/16XorhIKVVspFATxtbrIRUWOAx0kqqRsnF5bVeHUSGE1wbX4f3AY4V10eB/LDPg3/KevmfRYq5b5rY3/gpGEwg8Z+gF4eHzpv/P0yodwvmRYbd90/e3tpznx5D9FRFNVPcJNiIRMGrxn+jv57rkf4Uz+NP9x9Z9fRXroEFgYlhzpDNnslyTO43A8Ovg8z+RfxQdP33dvuh/rdoXf3P6vJJJGBaQSPJ6h7QKBA+kRfmjPT3C8cS+/u/FrXCzOvCZJj43heT5x/mdJVYN3z38fP3Lob1K4Ib92+f97FemhxfCm6W/mB/f9RbbdBv99+Rf4av+LvNu9lZ+ofowpWvwiv8R5ztNsHeLue36SPXvfxTwtBswwEMWWgW0DM+3jfPuxv0ozH/C5lV/n9x//fzO021RVzEjpbj/NyfoasFWP8CLszU4+/L+Of3fU1laN/cy/6e+yv3UHW8CWQAnkGkrD2AplzFbDVTffTgce+kIkxcsSimH9ek2IAzvDhvrmngjcBhwBZkK03zJA4w9wQ+0p+G+z8DvTN379aAU/vRpJjxFKgd+dgp9bgGLczAI/3IE7yq8/6bFk4P83D59vwQ904afWY27JjH9lv1u6Cv7bDLx/dtdIz8GBE3Df70Ojt8B++TPMPPAjnF7/JJ86/S/ZGl6sVbvggiV/nvvVBBO83BAVG3ygLrIHh1KaJIlNUkhNEtTFdO92t9nU2yASJmUV7auCH1lGMVZeaCVkaYJSQllaSufqrUQdo7ceZ22c7fhwTbE90Gg0aTSadSNcJEWc91RFOQ5iH9lm+VGeCIyJjZ0tBfAO8TJWh1ATIJH02Lk5h3rcTthR8yEKpXcRLGGHVAm1FGR39t74/yN7rRF5A1Q+KmoCO3ZiiTKYJNobB1sSnB2/z64fV73fbsQgeAHvqezOTbrRzHbt6+jDGTWLRWuwEbmklKIsSrqui7OTcewEE0wwwQQTTPDy4JYlPeYqx0ylmKo8hQjagXIKJ2BrtXHQ4RpXkGtn9WGnqC51pTdILTuuO1hkZ9A4Wi5KletunuAIXhH8qLyrooJjZ1MELwQv4yrx2DcWosXSroGvGnfMj7YfkPpR64pjy6JQd3OPdjHUCouA1F3BI1MbRCFKE8TjvcM7TwgKRbQ6SYwhTdJ6EhD7251zeGd3dd+Mh89cW94eveLZHZq889ONBse71hgdpcBO6Pp12wz1ea9PSq3QIQhWVTsS9RC7hKxzuGCRoOpQQsE5sDbUg+2RZKGWy4uKdlMiuwbVGhmFDwpobdBJhtIaW1UUxZCyzKlsgfOCq3JCOaQohxTFgDLPyfM+w2G/7syt2N0Sq5Rm0JihmbRQylIUTbR2FJWQl8IwtwwGXfr9bRoNGAy7JImnkU8zzPtok+C8QxuDtUJRxOPUYkh0GucK3iMhEAwo0TFPpKaotNp5qPrCDh68i4+rGsQcUUUioAzROk4LKo3h7gHZkUPsuiKu/gu7+vXdr92o6HMzhcgrjd1EzSuNOmYFF6AsLVvbAwb9gvX1DdZX18kHfbQvx3/34GPWy3hNGN8rRhipPfDXd9RNAMBBEhQZbZqAZw8p8+PQgqhgywnkL8LSyWHH5INWKZmJldrSDRhWWy+8M8ERbB4rGs9T7BYEIwmZNEgljcT9Vdvx2KpPWWxgq85YLVDhGEgJIiTSJA0NbKgofM5uyyqHZdvfXJEiokgkI1NNjETi/7UIFyp65RoAH1z6OT649HM3XdaIIVNNEp/ig6V0A7y3pCElo4Gph02CQqkMo5t4F+jbbRBFYZpUkvILv9Z63n3yvqDIV17ScRSD6/NVyv5lnv7Yj/L0Nc/H5oQbo/23HKVEOyxvHf3BMF6HKgPdBFFkCSQm3qcKu1OEQ0A8qBLMINp0Sf1GWqChIuniR0S5AZXEZo9SRXXEQKDpY9h3ITCsv763dHzcCEmIy117jB0Nlw0UaufJDX218uOlIBCVE/k1t9g0xH3evXtedvbfBDhgo03Xyw2/a59MgGaIP0uBoYrHu2zgkmGcWQdwEXgY+It/2tJwGYmOXeKDfIX+8LWf1TPBaxjXTzXGAzORnVDycTD5jRhb2fXMODtDXb3MDd52Z52dZwOM7bOgnh8yIjKue+fx8nXcej0ADoSrjmnX7C+MLOSeb3w22o+d4xmTKtfdz8LV+7/7gHYNxsMuEmbn953cjzA+t/V8LEpNdpa9Zv9jf9do8hvG+7GjCBnP7mLzm1L1qdmx3hodi9REhzBS49QWWaLw8uIY67HwZaIMmWCCCSaYYIIJboJblvQ4smnYEyqOVgOsVpRuBhuabBQlp7pd+s4xnJ1lMDeLF4ndzyOxrYmd9ykOY0uoNR0ehXiD8hlxSFYRVBll0WUcODWyNomJxaXgU0LQseumLjJWwUVlhtREB4CvfSYAajk14hFdIuJBEiBlp+wfECyaHPAQDBISJMSgcEEiCRKGdZkzZlB4wHoNyqBwWInh6V6ZqFTB4rTFeWLwZOVJCdy+/wjTWQtlUlSzRRBh9eIKqxev4LzDqgovDhcqKl9wtY/71QPJMC66PX9FoRZxk1cFm51tRIS8iGqEePyCoDFakyajbq/4OQaE0nlwJRIqNAPEC4P1DqZnSLVhyjTRoijLkrIsUColm9qPSacxAltZidEKsmlmTYpJU1Y3LtDpr1IMcgbdHloZ9u4/xOKB27h86TRPP/M5NopLFJf7bORLiIJQFQRXRUJkMMA5Rz/vE0Kturj2/ARPp79JVZUkHcNm7wrGRNVG5SJx0+n0CeT0+6ucObNKliU0npun2Vqopfgx8Nz4BqmfIdENbn/dg7TueSPO5fQ2n6Uqtkhbd9CYa2CSjMXZHjPtAUqnGPFISAlOYYPCV4EN6+lseuxQGGwpfAUiJaLKWLVKA0EHZmYT9h1skmWaxVlDMhVVT2bExxEN0G6GFyI0bIih6FJv8yb1rZeEG73nza7O0XT461263b1Po78YR63wCFCUUFo4ffIsH/yNX+fyxYucO7VK0dnEW4voHCUWL5ZAFSehztVBmoHgiGQWgphYKXDomvKY2FvdCIKQcIo22xzE8mN0eSdHxq9WBD7KNr/HFtVLII4Oz30T9x/4fgBOLH+Q8xuff8F19kzfw32H/jjNZI7TK7/HmZWP4sP11dIi5Hyh93FWqyU23dp1oeJD1+Oh9Q9yYfAM6+UltqpVlGjuWPwW7tn3XWQkTOcFjcpyZvAUn9/6Hbr25iTHtVgpL/Hb6/+FObPImfwpyvAK+/a8wvDB8nj38+R+CEmb9MA7eMsd34nfWOe/XvgglD2e4AkcjuFwidOn/wNLSx8h8ZB5UMk0jePfT3Lgna/2oTwvfuRyzqPTCU+0DX5wBU7/Omyfgr1vh+M/QGNqlrffB687Dlc24bNPwcpWvbKHagAXHoWti7DHga5VFYvAW4lEwLqGvoL2MZh7E2QteHQK/oGJRftv70c7qM834YPT0Hs5vgxeBjiBT7Xg96Z21CMAb87hhzqwuItJOmDhz2/Bd/bhdTlMfZ1uvbmCD03FDJQjVVSyHC/h4frcrRj4SuPm5dRWf5OnL/wG65uPsTE4+7zWexNM8ErAOUdZlIgSksSgkzQWvaW2YHIO5+yOckN2iIZxAHi9Lan/Z5KEJEkIAYoipyorbAiEUETrJO/rTJC68C6gtCY1JloOW4utbD1GlHo/Lf1Bvw4138kVcfVYLFHRvgmJ++aJXXm7KIJanbGTRxIQcA6kzoU0uraHcpF0Gd93BG2i3S0j+yi/QwQFwtVkxrV3gMA450REKGu2we8OO68Hq1VZ1iTOSHnjd53cnV+UUmRZI85rqoo8z/HexzzCmgxRKjYHXmX95XeyS8bEUNh9TkAkjmDTRkri6yaLmsDZIWdkrKw3WqOVxjrHcDDATtQhE0wwwQQTTDDBDXDLkh4HupppyXk9XZzR9FyLPCjOlZbtjS3WqwqShHJuOtpI1eMhpWqrHgGNQ7uAD0IFOBQ6aCSkxO7pQJAqSpVLh/fEbvpGlNwGbyCoWFysB1w2WAg2dmGPPVENQkpUgdSBdiqgVQVi47/DiPQYDacdipwQLEIbCRkqKNIQw9c9FTYUded2VlMIChv0WMWhR939WiM6AR99aJ2KgXvYQBIChxf3s292L6rRxMzN4UXxbHGS/JKloqRQOVYqKp9TUXJ9T/8II+3JVf1LN8RoGFvakrJXXrcdqYPEjTI00gwlgrXgbAz4G1YWFzzUtk24ANtx7YbOKJNpjGhKP6B0PZRpMa3nyYJCq0C3rDBGk2RtptJ5nK/Y6ixjXYFUIAVkWZuZmWmOHDlOXmxRqj6daoXOyhrLq6MKTB3GHm4wobjRcYdAf7hNf7gNKJbXDbHsHUveu7uxhjlcvHixnhQ0gBaRVhgAJS2ZZV4O0spmmJvbz7E73oArc7rrZxh0LpLMCA13F2nDM9vu0ki7iDQQSeMEKSi8U7gAw57FO8dwW9i4YKiGoMIAFfoE5fFNTzCePQdboITWVEIzEWbbplbrxKuiJGpbAjtWVvET3YFnp9Hs2qvEBihC5FmUip3BLwd2fzI3e+/Ra69Er/qIINq9L554/lyAvISigHPnLvJbv/FrPP3U4zTVPtpqfx1mXxF0tN8LNWXrnSdUOx7XQLzZaVMXA1RN0r42u/FfCRjO0+SrNFF8N/No9jNS8OV4ujg+wfZLID2EfdP389Zjfx6A9f5pzm88xPN3c8Js6zbeePTHmWkdYVhtcHb1E3AD0qMKJV8dfJHHBw8DoyylHRR+yFe3P8Xj259mpAXUKuXw3IO847a/zBQN9nd6TOcln9v8HR7rfvolkR4bdoVPb/828d7/h19F5PE8O/gqpwdPMDNzF990zz/h9sPfx/nzH+B3l3+RXvnc+LutKNa4cP5/XOXnnjT2cmTxDvYeurVJj+9YLdkWxVMNgx9swJnfhEufgHt7cOjbSfUsbzgO3/sOePoCPHkOVjYZ38xsDktPw/LTMLCwfxiFmrMe9oaofDiTRgXCwjfB0XuBFnylBR9owZty+N+X4d0DSOfho1PQe1XPyA4cMafj5+cjaTPCD3fgff2rSY89Fv5Ytz4tgWt1WC8bSoHPtuBn5yP58q4B3FbCkxn8+/lIMD0f39Icdjiz/GGeXPqNulg6IcYneHUxsopSSpGmKUmSsuMOFQv81sbvxFH3/5h0uHZjtTrEGEOz2SSEgLVVzNoKYOu8kBGREQmUHSV6mhhkFDDu3KgeD0RyxtnhDkFwDUyoSYm49NWKC0IkcuqZ35hsCNG2CxHSJEEnmuDDTpbGLkWE0hqTpDFPxJV15sj4RNWWXIxJkNG6I3LIO7djuzUikEYD+p0zQrB1rsqu4ePu77ax2kQiSdXIMoYE/MDjnEOFGBY4+qyUqPp94ijYBWGkSIbdP+r99W48Vk7T5Lr397V1mQhj9UiapiTGUJYVZVFMSI8JJphgggkmmOCGuGVJD8KoMJ6CF5KiJOgu00XJYZ3QRtFLM/pZSu4DK4Mu3byANAEaBKVqBiR2DSmJg87oYRwL2RqFkMTuEhO9VbVRdbB5qN2watVGvY4KcT2Idk9xvLY7xSCSE0KAoGupsBoXzaNzla/3RUV7k9GMGY+rB7BB+UigKIUKGoXC161OwQe8hEhBSOyOUcHF0ON6MF1UFqltp1wd8idlhevneBTOVojyKKKXt6hoIyWmicdhrcO6aOotqh7serUrcPcPUvzaGZj74LHO1gF2kUdy3hNGZAM78vFRsLtRBmU0Shm0M2jJUMrgfYmt+hRK0+/lGKNIyowkyfChoiq7OFeiPCgnaDy9zSU2ls/Q2VjCVuV4/+Jxhqv29YVxLVm0ezs3O28jGflIB+Dr3z02lBTSR6ywvnmBCxeexFVdNlYukvdXMPk50uJxkrSJlNv0twaR8JAFRFJ8kDo0MeCsxTtPo2gx11nA2ATVAGkAmkh6JIH5xDLjChqVIw2mlrJfQxQ8n5TjmsXCrt9H6+gQSRT1Auu/WOx+nxfa5LXkyMv5/rsJldGnuJv0qGxUdxSF5dxzl1m5ssGZU2cpc49WjRgyqWL3X6jzceI8VRHqzzHOXUf06dVdc/EqEyacx40xvo+M7YlispKgUaQkCEdIeSvTDHGE2rrO6hmK5ABWFOvVMht29artDoo1lra/ihbDNC3umXoLA9tltbxI4Yc33Jei2mal8yT9cpVuvsTN7jEimpnmEaayfZS2z/bwPKW9ujwc6u+T8b9DoJsvc2n7UVpk9PtD2mXFcnEO60sExUJ6kPl0H6XPWS0uMnQ7uR8KzZ7sMDPJIrnrs1pcpPCDG+5fS8+wNztCU0/xxvn38sb5b2OjWOa3L/8sz3S+8Hwfxy2LWDpyVHZAp/ss6xtfptM7TeWH15FOsOMhDzEHLO+eobf6xVd0n18q/uyn5nf+8R2/BMVWJN0GV2DtUTr/+RD/+p/Bv36B7QSihdJF4B9871l0SDE+o5BAmli62jNzNrD/EQ/zQrV/lubiFPdUwqyLFk3qRX69lgLPZvDF5s5zuYrWVl6i9dSxCmYdzLlICFx8gRFuGmJWyOLVtT4CYCXu37Eq2nDdUcbld2Og4HwSMzX2uLit5A/ICw7rbW6puF9Ha/c7T1ShdFQMbtcBzpZQXALnS+hehHzthttc2n6MQblOCI4knaPVPoaohHxwmXy4zB9sPDfBBF87RiHmtrL1v+M92NWh4UI9PxFBia4JhoB3YRw6PtrOTsB4vaF6zjS2U4LxP8bRGCFgnUd5GYeTw67GrjFXIGOX5Gv5j1EIe6hVFRDGQelxsAsEGe/frp2OczY3et+dMd3Yrilc36yzQ3KM/hEXiA5TsvMcVy8Tdm1gpD65biS866kwXm5nf4L32MpSSoW19hoLsp3PM6gAnh2rMh+P9aox+G7b450pNIJCCexJFXsyFY/Lu3p/FKKjiiRNDMZobBXYpkFZ6jG3Y33gyrBis5wQIRNMMMEE38gQYL+G/WZk/X6ThQQezV/RXZvgFcStS3o4IVZl51HW0tzYItvok5oW840FbJJh5xZx8/OsD3v87rmLnLyyhJ3aS7HnTkKaEhoaslgoT5TCKEG8R1EnX5MAMwTtydIKJGDSBJ06CDEoO+YeeHA5BI9JUlJSokHVyDc6ltLiX4yOjxHR4UM92I1931YEV2d+JGJAVIwKD5bgA8NQ4Z0j0QmtpIFWCh0MOhhcCFTO14NmhwseAYwqMSqSB1VVYZ2lnw/JBwMgkBlFogUfhvjVHt7DYHsLnVZIcJgkEDQo3cQkMwQCG51ttnsdRCnStIHSmqoqqcqR+uQPNkn2dUk4OI/Nq1jErQu6gVqpAigETSR9WiYj0wk6TcjaLZRWGJuQVE18EGzVoSy65D1Pd92igNQkpCZBQkA5h4SASYQ0E6wxnH28y8rpL7Pa3WTQ3WTHAOlGA+XR1ONGRMjosxdGpMXV25EXWH+kA9ghSCpytsMK3WqdwZO/zTMXPkcIjqro4FyJ6CdR5pOIUjTSgiQpEQxIk/inbQlhNJGME5O3zxzlrx9+D7e1FpFjh+HQkZhK2wqExJGkOVlZotGkVqNU6yov4d2TrxDG8TPXTcqupYxGZ0EJZHrnbO2yYb/h2R69tpvUuLamPzpjcs161yIwMleL7/ty3PxG2/T1NpP6eUf8NMfLhRhY3tuEjfUe7/+V3+BTn/gY+XDAoKuYmz6GuIC4op6nB7wnXtc+2jUEKwQXJ9Kxmy6ef1+TIU7AqV3z3Qmug6aBoAhYLF0qVlE0SVlEk/JdzPJ6ZnBUWLZwDOk03srynh+jo5t8eONX+cTWb9X3L4DAuY2H2M4vMW3meOf0+/jeY/+Qs4Mn+B/LP8fl/PQN92Ol8ySfevofoVVKN7+Eu0muR6JbPHD4h7n/0A+z1nuGh079S650Hn/eY/TBcnL197jSPYFGkTiH9p6u26JjN0hUytsXvodv3vPHWSku8MHLP8vp/mPj9Ru6zXv2/BBvX/hezg2e4oOXf46Lw5M3fK+jzXv4/oM/yWJ6kK92Ps0vnf0HDF2X1fzCC38YtzjyYpWTp36e5879N4pig6LYeMF1fNVj/cyv0ln6+Cuwhy8THv0n0H0u/r7yJfjS3/+aNvPjX3o/lgPYcJAgniCbBBmSfNWR/n4J0wn9H34bg+9+A20Rjl8rAH0BbGj4D3Pwm7uCzj1wKYn34CMW/uoGvGMIX27AP1+E7RewzNpj4a9vwPfcRGay18Ff2oRvGcCCg8VrxFiXDPzMAjzahO/rxvdf/APW2K5o+Ln5GI7+nT34GxuQ7bqnn0/hXy7CtIMrJ6D/JWCrC4//Mjz3Ozfc5kef/t/YHJwDYGb+Ddx1/98izRY59+x/4sLZXyE8T67QBBN8PRFCIC8KyjJeg+Nyfa3qUEphEkFpjTaaJElBoMhzyqIcKycC4LyjrKIdqA8h2i2pWs8wmquNSIvRuMl5hnm0bRxlIkZ2I+wsX/+Mdkpql70UiHeU+bBeP+BD3PcRuSFpbNQKIeArj7VunDGI1PmKIyJkxHPUqg/ZCay4+pz5qK6AkQKjJibqwxyvMjrOG594aonMruzL0WtxDLqbFokZlOAl0O/1GaphDHW3sUFtbLsqbhxCPsqthJ1sx3qnd6ZCY0qp1tzqGGafKMU75xO+Z29KKuCtBecRk6DStA5mB6PAhZSiauA8OB9zP7dLx6+d3eBTyzsNHRNMMMEEE3zjIQHe24I/OQXZTcpw4f/P3p/HW5Jd9Z3od+0dEWe4U06VmTWqSlJpKs1CCBBmsmiMMQZj92sa7Idx98cYt9vW6254+LUx7k+bxsbYTcMH815jg8EMNhY2NqPBQghNaC4NVaWaK6uycs47nyki9l7vj7UjTtybN6uySjVzlnTq3Dwnhh1xInbsvX7r9/ulpNSfe/FPXxdxlXjhgh6ApUV7oIIvS3zYIe87lpdyyPtQFFDkrFSOQ7MRxe46uCFVqUQRJBdcdGirNQqIIoRUYZKS1BLRDPCKyxzidF4dlEbIouYE7bTA4Wmo0Xt1W6EzdAMyhJgGwan6h0YqSI3+mwbjkUgUJWhNrQGPT6ZuGU69sTBiBI1tNVFTeeNisCRzDGgMRI3Mqpqd8QxBiT1PzBwxQD0rCUGpyzIxPaJdBQ7yPKPX76MKu37Usiu893ifmb6uhHkF0hcdNiCObZJgf62lXQNW9ePIXUbPFzifkeUZkrn0+zhCiNT1lFDV1LGGagqq9HxG5TPj9ERnHhJ9ZxOXIOzUJdOtS2xPp4TqiaS99rfvoO8OEnvqbueJUvxN6n7+XSRQMgGF6eaIy5unO9sXYB2RM2ntCqgT+NazfUlNA6Q0LXrldbscWn0ZN7iAyCEYKhRiyloFQI3WAfBQV3bNtRVhtu/5BHJeTHfQ0XY5Li3owRwautpZ2v8L7Ac9rhbXclXuB0ieiWjsxbtnqfmsKThUoKyUyVjZ2Zry8P2P8OlPfooiLzi0skaRL6MyJeq4bahNXD0aHVEFtO5IV3UANFWQubBBfEaP7qUUdo9KgqaUisAI641rHBk3UnATBUpJxYRAzeXsGI8O7mDdr/CJ7H1kOGpCW/M/Ki8wKi+wlh1jeeXP8qrlt1BrSd8NrtYQptUm57bubNs1f5rMq0BN/q/g0PBWbjzydpx4imz5SY7Q+pjt6Vm2pwcbFfdliWO9m7h95UsYZKsMs9U933vJON67hduX30rUQM83htxdVypr51K2xsuHr+d4/xY+u/UBHtz9NGV8aZTJhDBle/s+mvvsyYB+wSEaKXceotx9KPWLXXbkCzTWP2/v4mB22V5PI15+6RFmKDN6OGr6XCJjBJTow1NYypG3vQrZSWOO5irSg2DzK2Pm4P4e3H+V7wcRXj2Dt0/g/gI+1zcWSHfLzS/RfHZDDZeeYBTcT9v88g7RqQXzxXxIvpDYJ6+dmQdISPnSqx1Rd/2DYtfBPT344wHcWs1N0pvlRwJ3FVxVG/Lkia/lS7/kn7K2+hru/sL/xWc+98Oc2fp0+31RHGLt8JvoD05w/szv0YiuHhzCHsPiRSziWYgY4gEsOou5+bXgnLexP0Ltqg5bo3nX1sMirWT3YaIVz5PuYCRsm0eFdk7FfNDWoSI7ZytJ8uBoCtlaKa4EQMTEtDDfjzhvW8PST3PB7ihOoybT9GRY3hx355iuOCdKu33xVyK72p65J7hnG8xjz4fN890GrZr6MpV521WVqqo6DJB5O1WAaAz+BvCI0Uak6nzr+dEALd1ja/vMtF0nwvGe43XLnr5ArK2yR3KP6+WIODIf8WLwTKWpgDAKVYTL05ojZ7I94/JFLGIRi1jEn7wQgRs8vLUPA7gq6KEezr0SYymmil0JcPzx57zJi3gW4oULevSTwbKUWFa8ADkE4qG6ZFfmxhTcjGE55Q1ScHj1KGF5SNkLxKxkOiqYbTnGOTx+SNntYYNVmgGwSUiRBrREiEEtsQ/E6MysXBQpckQz1BXUIbfhpIQEoviUSGuSVhUiipNozGbXABSCOA/iUIWytrSoqpDG31bVBKCR2XRMJY7cr5D7ghADMZZorIlaz6vzpCaKEGJAKREiEgMuWAVURU2slFgr1cxo4WU5MyktaM2RAxW1zgfUA286t5kqTiMqgvqeHUs0J2WT3slQg3dSBXQ3gZ8hDNK5mXGwDfb+ybvY741DiQQUESXr5/QG/YQaNTR2QfGImNm7Q0Gm4ANCxEmGXeYRcSZXo9In6hARR285Y2noCWPPUpkRfKCqd6iqLeY1Tgel4fdHc8xP9P0TDb27PAHHPG3ecBMGQB9cD+kfR7Iha6srHD92BO8d1cxAm17fc/TIgF7f47MCn5lfSuYtR3J7XGG9Osn9DCjKHr1dkL4j76/gXMbljcc4dfozVNWMY59/GUf6N9BjwmF9jJ7soq95Le4d70D7fYKmSZ7YpLA5W91f8aBftjlL7Xs0T0eAPFVuNd/v/wW+2HR+w8dq+DzXsk094O8uPCXMDdmbX6sOVm0WApQz86r5wufv4RMf/iiXL13izOP3stSDzCuOCqKisaapsGtMJiORRr4o6pSoM0tSxcw0rsXYHtZfQVC3YHpcJSKzdDbN4UnI8KwgOGq2gV0cAxwDGi8VwTEoz3F84w9YdgPeNR1xHa/iAmM+yHnOMs+GlnHK57c/TK0VZ6ePsF0/OTPAScYNh97K9YfezLTa5tHLH2Jr8hhHl2/n5iNfTi9fZVpt8cmH/wVb41Pszs5ddVurgxu55eg76eeHOLf1Gc5sfPJAc3QV2O5lnFnpcUEKZn6vE0EZp9y9/REigfPTU2xXlxCElw1ey6uW3kytFV/Y/QRnZg/jQ6Q/KRnUM/KyfkllF/rZGrce+QoOD2/l8vghTq1/mFl9cNXoy/JXcEf/LRQZVGt3Ui89wFSv53J4J5+/9z3PccufWuSv+x6OBnOV2nWwkUH47E8/5e2cX3szM3+M0h0jeJj1jlNnNeu79/Ho+h+hVcVb77yJ1+UncW4EfIEom4S3vRZ91ztg+eog4bXEhoffXjEvkY8PzI+jp/ClE7hjBhc8fGjJ3u+Y2efHa3jVQUOSJ4hKzPPjM30YC7x1asDI4QjvWTMz83eM4XVX2e6uMxbHA8XB35/LTN4KbJlfOgR9hc/10jNzF3jk6u0bTx7nkVPvYTA4wcVLHyXuY3GMdk/x2MO/Qp6vsnX501cH5XwPTnwpHLkDYgV3/8ur73QRi3iWQlWpq7r1+KirGhEoyzL9ncy+XZIdbszPFXz6bC4Fupe9gLPBk00BxfwxOswDw/zmRW1RzcC82dbedjasW2NoZHme2tYUsCl5keO8a8GYtNvmrxaEEOdwvpkzuhZsaIGH+REZyNPdRit7ZS/ZMyiX9thawAhtqcrtoq1kVWpWgyF1RstzGbDO8cemTfMxbFsooTY7FjV0wwSatUVNXDonGoS6qqhjTTUTypnrgFaOqlZmoSIq+FDj6hqfeYrBAJ/b/DrLPHmWAKpFLGIRi1jEIrpVr80zrZO6k2r+eVudq89skewint944YIegwn4aAnsqEAfZBlkF2ZnoKwgbMH2NivAV7iCcPgEOhiig0CQknPrjosXMy4MlJ1M2QXUCbEZdDoBl7wxYhrUihKDJW8kpIyiCK5fAEKMPcq6QCRCFs2zA4dPif3ACNXSkvTJqNkGoDZ6VMlQ8dRBmNWRGBRxikujSu8SfTrUTEeWYOkNhmivT9SKEHeIsSTGQAglihKctcMqa0xaSbTG1TYgnlUTopYGekxNP7asS+oYUYnUIemt1pU5LAOEwDCzMkmHGogiDpeZSSB1CaFGyagZEHHUlERKSMCPDWsLHIcwB41N4hWgR5OChnkq2dvvTY4yIzDBOSFbKhisDQkhMptVVh2mHsQAJ0dOJh5kF3EzoMbFDDOarxGZIVKB9AksIy5juAZHjgI7GauT46gXxpPHqesdVBPjoQUhGkDnoHgy0IPO9wfBARnG0AADPzSdw4YjMQSOgF/Drb4J6R/n+Mtu4C1veBW9Ime0tct0NOHQoYzX3THk0KGcYnCM/vAE3mcMc5OVqh6+zLk/vJ+zGxNWp0NWt5WscgwPHSH3S9x16V5+76PvY7RxmTeev53XXLqVtXiBV8U/wMvj8Jf/Mv71r0cHfepEI/cCWTqkLhDgDvhbO0fU/Np1gLK0h89yD3I3h3tiOjMNHPTFhDDv8PZDUE/0UNN9L1LbGs+OArtKGl5NxLw7yspuk90tKKfKJz7ycX7m//5HbG+tU0jBytAbQKl2LxFjW1IXNBDV2AQxaSLXTKgT6JGHxDhzgnqHqhDqjBB9KmFcxP6ITAgEAsZEcPTIGRKYUHIZpcKzQsYKcwDbsTR9lKXyPSgFt8ajfBtv4bNscJrRHtBjGkf88cbv8MmtPyBozTQc7IPRDedyXn786/iyl/8tNhOosTV5jJNrb+QrX/W/UPglPvLgT/DRB3+SOsyonmCbh5dewTte8bc4svQKPvbQP+f81ufsWbb/PIiwPsh5eK3PuvSYZPtBjwkfW/8dPr35B8R0HILjtctv5y9d/7eYxF1++fEf48zsYbIqMtyZsZxNKGb1E9aMv9hiWBzlLTd/J68+/me4+9xvcGHn7quAHsKre6/nLx/+G6wOYOfWn2Jy/YOsx1v5Qvm9L3jQo//2/51bKjgaTSpqp//0QI9Hj7yTstejLApmecbjh4bsDHLuObPOe3c+S5xc5u988CS3fvw6Mk4Dv0J091P9lb8M73z9Fw16XMjg5w+Zp0Yp5rexGk126rs34dN9k4a66E0C6wcummTV0lPsLkuB31s2U/FXlPD/uQRfOoZfWzNJLYC/e9GYHwc9V7Y8/Ooq/PrqwSOFkNoO8NkePHDMno2T9FxkC/jjq7dvZ+ch7rn3p3DiqcOUGPeOuXa27uGBu38cY8hOWgnMKyIbwq3fDK/9LqjGC9BjEc9LqCrlrGwZAF2PCVUlyzP6/Zw8z6nqirKctYkK77wVdGmYAx7NTeca1rIJXtrnkRgbNoi0I/Vmn11QpDvaFZGU9Dcmvs8y8qLAe2ceFOIQgbznyNFWvurKmDNRmraJiMlKNTJeLQAy9wNsZK1sLekcZAIdOqBIV2GqKXBTxYzIu74cMbZsxfZ87PH3mMNDNvtRAzRUE9ODDmg0L+aRTqfXACPNOUTECvpCoPIwmwiTiY1xXZEj3rNbKZenM+oQkdEMN55R9AuOncjoDx1FIfSynLxwePck+oaLWMQiFrGIl340RQABs1Lu1DJLqjEWq6M3xkff3vcksBbxoo8XLujR8Io0prGlgDrAzY0EopWWiDj6TXI6AnVFJDKOeZJbgENRGUcDPdQ5IjCOkVkMiIA3h3O7EVyqqGluhLRrA/00MRwi0mjOytxK1gZxsdVUtcKX7jA5VW7HiEYbyLqoZvrWibnhnRDqQO0rVCtiDLQmx6lKJoZOQl4DqIEUktoYY7AkakyD0bZOqBk4J2p5h97tYnPOaavPRR1enK0tjsZg2RxNGpvgbp2U7PlfN1zzvXicT3IzGlANiOQ46SGSp+qgQJaZxJa4DNFgLB0SU0cExCSwbJTtQLydB+dx0QzlxWU4p0hW4PI+PssQD2SKy3OKYkC/74gsE3WVqAFN11yINXU1S1WRjWeHHcm14cDt9IksL3A+xwlk3qUJUx9NwJlrVLuogKV0bg4Dh5H8EH71KG5wlJXVIyyvHKbXy3Hao8imrK5lrKwMWF7J6Q2O0F86ineeYa4UXhkNZ2xlnsoB5YR6ax1fFuwuCz6MOL9xmYubG4y3NlnfuMzm5SESLzCLl6jlMm40wqekevMs2M/EuBorowENYrrU98t7PBEXZj+L5Gpn+NmI/aBH97V/n5HEfkkYWFXWbFzeZrQz4/Kly2xvbbG7s8vKYJm8l2SDYmyB0baKr/2704I9k0X2LIc4lgY9smxI1MjG1rN0Ml7E0fS9tD2UXcFN76X7einr7wXRChe2ETJ6LONwHMNzgpyT5G2yQRFizNDoqHAtANaEw9HPVihcnyrOmKQEumogaEnQal49qZEQS2rJmFU7jMv1BMJePTLJGWZrLOdHKNzwij63PQ+qTOodNsvz7FSXqPVKc4UiCoMoVEh7HJFArSW11m11eKkztupL9MmZhN2XGMtIiVoT4swSMekKGciQvhsStGYUdwnUSNYj6x8h6zuy/gl873pcPEF0x57TFuer17Pcs/HMpIRRt3IJYHT2inW0fxT1CXMtsHqDd6s95gJwC/DngBuATwEfBKa0qPWXnp/wP35+nWq3QkXxWvFNn7zliv2s0Gcy3YbpZeAyymWQywxGI05Ukfwp2EpMnRl6h84lHgR29uW4NH1eijE0mlMRsM+mAtN965RixuSKmZmve5PJamLsTHIq18Y5y6S3lLmJ+ROl2iImi3W5mVA9QZRiQLqo/SyHgboqmWxscxWoAtU6MVWv8n2sqMrNJ94xwGwDPvz98OHv58Tf3OL8k6+xiEU8azF/Nl45V2pfsTHMbuSDO8/6K+61hlmR/ifGuu/gDsydyzv72zdKbcEGseeDJnCgkUeWzvoizfwktmxjgbZjmo+J5+tJU27KfHvdFmn6T7OtxovjiqPdY87XyfgcEF1Y58AuqtMknf9xxdZa7xLYMw/ubqb9r5MWaLLNCeOgrFdKL9o8W6IyqpT1yor1pIpIpfR8xJWRQRZZ8UoPWeSpFrGIRSxiEW2MFC4Ek61tVHUlGhBCenchZVzS+8DB8rOVXFrEcx4vXNCjmqRZpxrIUSpUCtIDd71JXy2twOqKZRm3JjCrYDSDjS1EhLX+CXo3Zhz1wiFRRlOFpT7a7zFS5Q8vb/KZ7V187ugv5/jMmb6O5BChnimhUpx3uMIoyy7WuDgCMHkfZ4MrJ83wsAI15kVdmyxTN9OrrjLgJQh1lUAaJ5ajx7RloxoAIWrmd6PddXa3NhEv5APF+TS4jKBRqScTwmxq9OncBodZXdFjRk1kUo+Z1CVOHFluCb5aA1rXKIGopl0vMccH81CpohLUWDDOB2OuSE4/XTJjhRKxCqbENPGxJkYT+FEx9wZBcKk6PaZpuscxlD65eHrDVQarRxHnmJW7lPWE3Bes9A+R+YIyVsyC6ccO+mY84aQmz2eoj4mAIahT6lBbWlMguiVAycnIyRK1fA3nld7gGIOVm/BZjgwi46hQeE5cP+BIcMAJ4HVEIlUoCTGwtbnLo6fOMZtOgU2s3NIDy1itf41Jd+2vAmvCZLayvMd1N76StaPXszzIueHoMv3CM6uFae1w3rO8tELR6yFCmjAIZZlTVRne9+kvXU+WL7F8aJnDJ9bIvMcdPYQEoddzLPU9Ljqk7qFlIEpgMiuZSc2o3GZnaZvpbJOHHv8M63eeppLA1pIwLWBj8xyPnb0Pnc2Q0Ta74T5OMuEwm4BBMGvpSncN/ijG9tj/XGj+3Qh1AVTBWBAiUGS2De8hb6gcnjaZ49NL7a7aA7J0t9/9+yDgpPtdA1c13iL7t3NQdGGu0EwuDzjeqMZ8iemAc4XTZ8/ya7/677n/voc4e/oUElcZFH2cS92ZChIMITG5NqtIrOuKEAOItBNhr5nJtWkzEYYYK2qd0O/3eOfb3s6bX/dGqqrkn/yLJza7/pMYkbKTAulOrQtyjgKKo4fQx3rjCpO5qqnZAoSMAkG5npK/zhrfQkFzb0f67PIGJtzGQ5ziN/ldzjCXoxpmh/iKE3+Rl6+8jVO7n+XDF97DdnWZB87/PtuTs5T1Dpd3zbHg7Oad/NG9/wgnGWe37ry6BE0nvCrDKrBcBXrh6suHOOPU2d9lZ3SKstpia2ev2fqQPt/IO/ky3sgjnOE/8Aec5jx373yMaRhRa81Dk7sAeLR+mF/e/TmGMuTB6j5qXjqGyKPyEp989Bd44OIfsDF+lEm5QS4FX770Nbx9+Ke4WJ/j93f+E49WD3N5qcdnblxjOFhlZ/DtjOsvY11OcFd243Pa5pv//P/BN90Bx5bhQw/BHz5g/S1gHdZvf/cV68wyOKVwLsIog6pLq1PscfdBrPO/BEyY0/XSGGjaL5jVytGdUxxrTNGviIDnXnKUjE1qNoiYzNT/ehFmT4FxcecA/s0anH+SEexEzPj8Cz0DGR7N7ZA+MoT//bq9BuFtKwXu6hlIctnDvz4E71+af++Bl5Xwv100f40/WIZ/vwona/g7l2ElwlumzywInwNfEuBNAS5unOaPPvMrXAlfPXvxQ9fD33wO97eIRVxrxBCZTqbMZjMz+G49PaQdQ2d5liSS0l2pbdkXjXehRd2OH6XznxYw6EpHpTfnHVny1YheISpiVXSJfR+TlLLgXYHzVpClfr6fxt8ituyNhj9BKxUlJLkuEfPz6IIzV+1t2tKNPYACLQAsqXBM7bO5QcfBgEd3MC1NUVxTqJMWEZKcl7Q+kQChrlvz9f1AEjTyVnuBmc+VntElxUtEfIVIoFZlGsxUnVKgziiisHp+Sj+vePORIV/bK8ii4l5aVRiLWMQiFrGIpxEV8IEpXAr77PA6VazSFHo1IIjAl+fwzb0DNriIF2W8cEGPuoLg5nnkCssmSg5umLKlQxgOoa5ho4ZpsPVmG4hTlm5aZunIIVDhplKT4pJAUbARI5+fzphubJH1MjI/QHoekQLJPRohVJF6pkgWyVKBDjEgGlCEipzoEotAYqpy1/a9bjIDyfxAUfABvNqx1QWoa6uDFAh1IETbhg3Eldlkl9lkhM8zlvIlCl9YRZI6NEI9Lal2x3gP2QCcV3xdkaca3RhKqrok856iV5glRhXbhF7UkkiFiyChD+qIUSjVIRLMm8RFMnIKsfLESXLvEJTM2fE7DXhqlCTjhbc6ajWDcEnnwyH0paDvCpZ6a6yu3YDzntF0nclsm15WcGzlCP28xzhEdiszg59r69Zk3hkkGw1Y0hBwviLEmuigcn0QIZeMggyXObK+x+WO3tIxlg4dN4aJi5QxQuY5dKSHOE+R9+n1llCUaTWiCjPOnb3M2TMwm+5iafkdLP2xhPltzLAZwUHV2IKlLQqcX2bt6Cs5+bJXc3S1z2tvOcrysGA0q9kta7Is58iR6xguLZuJvTf2x2QcmE5qMudZLgbkPiPkjrrvEecY+qWOcbKBVcZ6Ml+IEGaolkzqMePeiMlgl0cv38t9n/kIo3rKo+ywyQyDA8xXps9FIpEJ8AZgDSFLR+NJD45ryOw04mBgHhez2iqRc5+ADAHf9ERiZzBxutoz2pzVBgiBveDGFZVvB3wOezk619L5JcJGC3xUCfTImAM97TxQ7fiiGlPKKexsrPPhD/whH/3ox+kXfYbFMkU+BJmY1rqKUStb6YJAjDH598yzgCKCk9x+AUlGkRjjK+gU5zyvfeWNfONXvZ3JdMo/+RfXcHB/wkKpaZgd3SvDkSWgw2H+TOYBZNecYIbnEyDiE9h5BOEbWEJZwvycegRWuMQ72ObtfJxP8wE+sgf06PslXnvoK3nHdd/Kpy4f5s7Lv8dWeYGzW3dytjU1t9gYP8zG+OGndHxOlX6IDOpAHg+u9gSrBL+4/kkurn/ywO8Lct7Ka/lLfD2f5G7ezyd4jHM8Nr2Px6b37Vn2YjjPxclLswZ8Vu/wwKU/2PPZUJZ4de8NfMPKX+Dh8j4+OfkIj1YPs93PePjoEr3+UXb8VzGJX8VlgYee4xHWsS/9Lr7m6+HWo7D+MfjgwGT22jgA9Kic+VzMO/b0RaN9OwLuTp8dgDxH56gKT1V4huU6J9e/cGDbhIDjcTLGeGYEdgG4fQav34KnokRyJMBvLz856FEKfHRgr27cW9jryWLHwfuW9n62Eg2k+Y5NuLtngMf7l+CvbhrocTKBTM8k6JEBt0f4mgAPjS7zmYd/9zkFPb7j0AL0WMQLM1SVsrySrdiEzyB3Dp9ZByNqfPTGbNvACOsAo0YkyVvJHPXo+F+QSkTnrAURwXlvAEtUUwXYLwOlIM6Ri+B9U7U233YDeoQQkpdGw+41k3NtCtCczQmlQ3G7GqNzDorsY5o0x2HVM1Z0l+ZXXW7x3m1JByhhDngwZye3ySNnQJM48zXp9/uICGVZUlXV3nPbeZ+Lic3380gFj27bho1Jsxc0sXmwJ6thOCspBJaLjK+uIz7uldJaxCIWsYhF/MmMCNxV2euaIiSnXYX/6oWbKV/EU4wX7k+ZBqHkTdVObWXUEpLBuYOYQJE6NrQLcDkMhsmpOIcxVsUSk0zWtIStMbkqt5YVbyPiJTJwEeeE3VnN9nhKBezEQCQiSbIEdUluKRq0oSElBiLSyFMpSZEryVyh1tymakcdZrshEBKjg27RTCNXo3MJGwFchoojVEotwQapqgbAxJIQS1Qj02k0ua3aaN5oYpuIwZgxztIANuAzA06celTNs0OSOYOPGXk0+SqkShJYtVXyqiTvkICIw/vMEtdeyVVTdXoBkiFkeO1jKY+coDkeR88NySTD5RkiJjGWZznIErnP8N6BU7Ko9CUmb4PELIgm4YWa8WAINvh1mcc5JYrDuQzE0cv69LM+4gVfeCQTsryfAB8QycHlVu2ER5PRfTOQd07weIaDASdOHGF1ZYhlhQaoOkJcIcYezkW8q1uKe0NtN4q9gORWUd7rc93R46wuLTPo9VB61CED8WQ+xzsDi6wgyo5DxFHkjVE7CDM0zqinkdnEGAK74wlxOjWAQwOK4jMly+y3j3GGxorJ1gYbpx5mtrvD2e0LbMUZU6oEVc1rxhxzL42mk4idVwNkdAupbCpIy4l3Mv+sec+ceYs4MdDAw1yPWO2zrmRWs17QeRvqtP8uWr+nOm/fe3c7zbHBHEi5GnZzEJAiaUPd7ZRJha82bJOqqjn9wMOce/QxHrj/IcY7WxROLJeotVUQtP2FgR02v41pkiyIK9L+o62Dtn1KEhpCNXBobcDx40dZXVqiIOPs6UtMZ9MDjmYR8yurqfEMqdLT0YhbKX4+sYb0ncdRpH/ne7Zj145BYo4ZBacZMOAEp3gHkZP0kfTqxVVmuw/x+ez9bMzOcsvyGzjcu56L00e5NH0s/bZP8YhcwerKKxkMrufoypvJs+WnNNHvuyVuGLyC5ewQ6+V5zk0fotaaB3iMD/Fp7uMUO4wR4CZWeTmHqIk8wAbnGT3l9j4TMegd48jy7Tx++SMHfv+K4+/iS2797/Gu4FOn/hX3nv3NJz23h1jhFdzIgD6Tgb1mccL50QPsVpdZ6l3H0eXbWc6O4FZfyfmVIZv1MQbu7RwrV3DFIS5c+ihZcQg99Ap06QYQYQCE79GmIBaNE8rRA4TZeQ7lx7h1eDtFFM589h/x+Gf/Cbp6G3zlP4NbvgF3+n1kn/+/kemleT5J2XMFAmj/CJM3/vdUt34922Phs6fhwjY8tm4gbAteCPC/6Bz1TfJUwxxuOw6HejAewc4WVFXJ+uZD7Ow+zp4U2AFUu53dmi9sTNicVJyb3csjejBYl0ZAKHV77wGcyeH0EtTLT/gT7YnP9E1myincWhnz4lrlTBTzLnmwMPmqpxq1mMH4+5bgVGHyVxGTwPrg0AzN94co3FzDy6+em33CGDvhZ4Gf3btVbrnxz/LqV/w1NNZ84cGf5fTZ/3zg+t4PWFt5Jf3+cabTi2zt3E8Ik2ve/+59u0+v4YtYxPMce8AEoBHhbeZazrk24S7iyLLGU0/3bYf558K+Qedeaaz2IazS4huiauzdptNJA9Im7996giTAQ5LccGzHhbTggiTwZA8bY99zvwUw9viQ7F24XbfLvNB5m5w4vPd7pbH2nVtxXTTE5n8+gR4ikrxBJM1rOyCM0Mp92XRpPhKf70/bOfKeNjabEEFUTCoYyAUy5/AiRNGDCCWLWMQiFrGIRTxpXDkKWMSLPV64oEdeAAp5aaPBcmqOx3jaaX81ha3M9AhmBYQM+kuw2rMZcBjCJbWZcb82hsVmgI0ZA418XTnm7URjM2SBmCn3XCj5zNnISJTT11XUywFlSCxzVDIDDlxtzIygILUN7tKgWWuTrlKFOpm5ea/kGYAQQk4gM8Cjqi3pGRvWhRBi8srQSBQTlVPnIB+gQDlR6klFnlX08hLRQKy3KKsxGgO7O1M0RnpZj35mtGIRxWUAFXUoDYBxOfkgw0fQWYbU4HyS+BJHL+bk6ghxxqwcU8eKSpVJGmbXaRDuXEGR9/E+o8hr8ry2Aa7rgeQ46ZO5VQRPjCM0jDGatYESeZ7jZIbDsTQc4PwaTiKZ1Ag1PRfpiSVIpi5QiVGWMwWJMKqFWYUBA/2cLPOoFKgMEZexvHSI4WAtmdYnarjUBCZEdeRyBO9W7JpLyecYxEzyBJzzFBkcu+4Qq6sr9pszA0pCgPFMqWoosh7D3hJOPN47k0QTR5718OLNW0RyxDuy4TK+6JNlnjoWjEvTve0XgnNCDBmzMpJ7wUsP5zKWelAsC6GeMt05R12OmO5M2bo0YjYZ8eh9H+P8o3dRac04TKkJdkU6IFW1RZS6DkxnFSEEppMR0zhKaaiIw7fJ/Bylz5zHAnPz7iYlXAdL9O81Jkw5NjFww3cyUQ4YeNNI3A+KNEm57hyl+TtGqOIccFEM8Oj7qye6ukBG9+8mZxcxrXSYW9XD/AHXlb/qRqOQ0ABCdYTtqbFXGqmuyXjKb/3Wr/Mff/VXmI5Ldi7PWOnldnJqc7cVH81MSzX59HSNKT3OD5GsB3FKDDugZsEdCSiBmjFKzStufS3f9vV/iuXBEpfPBD7+wc8zK2cHtHwRjhwhJpk9JSZjAgM2cmw67tp3k7rKcPTJ0hXiGKRlG/mr5oqMwIwlPkDBR3gTE64nMOUonhN4rudCrfzsud/lty69h1tX3sjX3vBdDLM1/vDsL/BHZ3/pQG+NJ4s8X+Xlt30HN93057hOl1iqr0OCtiD7k8WR4iR/5uRf4/aVt/Kx9d/hN8/8/xjXm/wm7+eDfJoJU85zGYfwVdzC9/JWRlT8OB/jd3jwyXfwLMR1q6/nS1/zP/OeD3zzgd8/vvEJtienAcfu7Pw1gUmv5Cb+B/4it8iNnD56kkdvuoELs9P83iM/zr0bH+Dk2pt45+3/M6uDm8h6x/hE7zBjXeWY/h0KHbFx7o/4zN0/CpJx4o6/xeHlbwOEoxFWBbYELgvE2Qbxnl+Ax/4zu9f/Ke5/8/fhBseZ+b39IA6K697K8tt+CBcrAtb/FgqHFXrYsMYBtc95fPUk6zWcugA/90GTDtwYQ9kwZZtOrmP/1Vwix5fgr7wd3nQDnP4c3P2HsLU+4qMPvIe7T7/nSmm1fYmk00F5TxkpolJUYwq9WjJd05NmhhjtFsWkpn7mOGxe96Q/UxvbzgzJC4U/uwPftWl/X0tE4FfX4KeOwPbT8LmdCfzmCvzx0DxBziY5sI8O4VR+8KDaK/y3W/C96099f1cP5fzFj7C9+xAojKfnrrpkv3eUV73iu7nx5J/mzPn38dm7f4zR+PQ17+n8r7802VyLeOlHDJFyWh5cxUKSpypyk//NMnq9npWXhMY/kbYPNKkp+7sFUUSaMjiLBgNo2BpWBkVUpSrLvRKQHfxjT7SGkOwFmtNnznmKnuvsp9ncHCxo/BqrKpgcVqfNza6tQEtsXtQ5tgaAcN6R5bkxTLTbTt2D+zQbbAunGhN4cdRVDWL+lZJkxBowwolHvE9zFTGJq8YHRBIIlCSxWsyp3b8t58SRizJ00HcwyD15qohyC9BjEYtYxCIW8XSjW+G6iBd9vHBBD2dmb4n3i2XnU7pV01UY1UwCgoeYgTpjiBTesqIjDzO1GWcWLTtbRygDXpXrCFzXDkwjEWG9DKzuVuCU/uGKgkjUmjpEVAxAiY3Ym09JMtV5xiIaA8WSmY2hHiR+szEJEmOEqGY07gIxmlgUaVEkWhLe+Aa2LkqsrerHE8CXJoejlb1CTVmWaAh4dURXNLU+kCjSMdZWmewcIhmtDbkmMz8PxlAQJKZMSVPJhKIS29J8URtUOufJXEaWCb3CzUEPl+GlR+YGCN4G1ckcKIqxSLx3Se8WMu/J8x5QI8mQ3YnisXNfEVJyXvCaKNnJQ8G5NGjOUrpacsRlZHmfvD9Io2yHCoQ4MT8TcW2Suakoakb23QkNIhRFzrA/oE2Zq2kH55Oasor08yFL/UN455PpukuASR/nPF58Yp8I0Tuik4RIOEIUxDkyaQb6CnXAaUR9RL3iMiFzdl3EMKGudinHY2bb20x3d9g89wgXHr2HMlbsxDGVhj1zvKbgNyJUeMwGfl4B5jFhH4e2sGIBFAjZ/CpqU7zabLObD9P5Mg2wsL8wWOTKici1zEui7vXWaD5rJk+durD2vckfdv/u1vp355Td9fZUz3U+O7CtTZdSg5OIrwPTyYQzj5/mnns+j0TPSnGU3PXs/Md0A7j5hpvJ6d6TkhkLSRKImHZmFYrRfHSIrCz1ufnEdSz1h2yeucDW+g6zagF6HBxd+MuuAG0zwPuvkMZNhgSANEyPRuBN25cylzb0bCPMKFDWUKDAM8SzxqM6RWfnOT87xfW9mznRu4EjvRs4ml9HQQEJ1rqyKvPq4VzO0vBmjhx6IytlgJ0pobKks3cFLpZoMuE+KHLX41jvRm4cvJLD+XG8eAKRc1zmHJfb5TzCEfrczhF2KFnhGrSBnqXo5atct/Qqvu9bt/nwF36EP77vnxLiHDCaVptMq82ntM0hfW7mJK+Qm3H5TZTDW1Cf08uMflBkyxxZejmrSy9jK4PLGQTp0/e3kgGji59ksv0wEWU2vUQdZ6g4K89IfV4UiNUIth+Gy5+jXr6ZWmd7O0maPk1wvUNkhw/h00+nWL/ci2Zq7dUGcJVAntnzeDqDx0pbWrWBqI2tKOqQqEhtFcTGY40UAtcvwyuOAH24NAM/mdDfehQufY55T3lwTNJrf2TsnSsUgKMp8LD7TjGmxD09uNS/9t+riWGEYwFeNTvYn6MbAmRqw5ePVLbu9CoPnyAJ3D/g+yhwLrdXNza8vQ6KTOH0GCbOJLeuidN1DWXKs3KdWfnkSIqTnKXBjRxafTVb2/fh3JPfv+V//D4u/Ku3sf5br2H3zPPD6lrEIp6JiPEJ7rgm4e+0lapq5gNRoWGVo/O+uVkPdI9klLSJ/z0IQRvGutjblhbsnjeoUz0EokJXTqrZUWtofgDooaS5ZXSt9LLu2cN84NzMcWiM3NG2AKkBIJxzaFvgNB94S+c/zd9dxjgNw0M7+5of5Z7jaAAP22dzzEpM419JTBE7QGm3Z/JkQuYhd5B5Y37sN3xfxCIWsYhFLOLJoskAeF7ISfJFPJ144f6emRhzo04DQNe3Ur4YIaZElTiIPmVEtw0kcMvQOwZZZuXhVQVam24DNdADSbXr6kEzmEC4WKIerpvUvKVfMcsdrxquMF7qszuF81sTpvWYcxI4JzUUnvzwEr7vOtlgS2SLd0iMUNdoiA3mYBl6TKYKDeBiksty1NEG2pbcNYAnBquGDLXYIaOEVF1cliXTaopqYDqbMgsGdtR1QOvIVGeEOhAFZmrJNGJAY20sEi8El4CQukZjJNY1xFlKsno7FgkMBn2Qgn7WYzkbAjApK8q6xvuMfpHjXEaeZeRekuRVgU/yVk5rICJekLyXTkbETNIhyyRhSCU+KkgAKdN7jUplTIWyJgbzPJlWZp4wrYVQCVFgojD1IExBJoh46nLMZLJu+FkdDUvSmqgV4hxxtSQOd/HOUxQ9nPOWEIg9y1RpA0RZRb4gCYwy8KefFRROyPM+RZHjncfnHp8nI0OnRDGgxiUzw8yrAWbp3yJQ1VMmsxkaA2E2QasKhyNrJK1cibiKqpyweekM0/Eu5SQw2a6pyhmXL59hEmtqDdTaFPMmqS4g4ogYcDZPrNq3PYQbcaymGvY+kQLl5Si3oKwBQ+Yp4VZ+qk3az9XjXGJ3iMwxSSf2mWKfheTBmLl5XqeZkO2Xtmq6goGfzwMV22YuewELmH/fBedrNS8Ol/bpOsuReoV2LpW+aCqrwbqgmNqeFOOoo1kIhWg2QgR48IF7+cRH38f65Yvce9c99IoVAxNFUUm+NqkCLUa1fWHgKLBnsheZoQREZmSSdpDavbLU51Uvu42jq8vcdF2PC6fvpHAZUq1y/OiQWfnC7daf7zCpqv1XjVWgWzSeH0pglCDnPp6VBAuax4dVrE/MC4kensSqwyVgRFNiFyJbRB5hSOTP0uNl3MQN04q3nH0/g+wQ1VbG9fx5LrLJB/kUj3H1iu394RRWajhWKtOdx/jY479POTnPWGre9vLvYVJu8NDF97K++8CB629Xl/nI5f/EQ6PP8uDuZ5iG8YHLKcqnOMdP8Ulm1NzbAUSe6zi0O+L1Dz/G4XzGQ+ublgz5IuM05/lV/gvH9AjrW2tcevQw2/U6F8cPAXB59wE++ci/pFccZupg5uCorPJOeR3Xy2E2LmWcq9/FiBn3PH4/p8ofJyJt3zFuclblBmwmXxTd98KS44dqI6YGtb6rBkoPtbO/I6YzuxrgSG1/r6U+1amBC6KBrUsfZ+PCR1iSPm9d+gpu7t1GfzZmeXeTGGb8MffzSR5mYznyOxfhrsOw/ig8fjeMd0ec3/rsUwLgunEYx9fS5+Vk6YlT0UN5IzXKbpIIPcj/6qlFJfDhIfijdu6eKG6o4U+P4PoK3jw11sX4gAquIPCxgTFQrlX+98kiAp/qwz8/YkDLvU9gjOgwduUzCTOU1RanHv9P7Ow+xMbW3ZTl5pOuc/auT+MuLXM0DCjitUthLWIRL4Zw3iXviUaKyaSkQl1ZKUOIxKYYJfUtzgmQJR8OSUl7OgDllcn/7l+t5FTL8J+XUOwNmzu0ccUz7mBQZe8mBHGCz3zyAsEK90hASrtY+tv7PUwQJAERiZI9b6fsxWOvAOyTp0cyJm+3n86xyTwm2WoB1M5DDF2gpDGCjybTnPazd7dz8KkncHMhHMngRJGR5zm1BKuGW8QiFrGIRSziGuM6ga/ycJODt2QwWKDnL5l44WbHGtCjyi3x3MsMyIgzqEzuBVwCLiqIWxAnlnXtL0Heh9kOzEZQzWB3y96LFej3aD1BNEOrQNguUQIn84rrhyUUPeLyCrp0jPPlLndtnmdjUlKhPIaiw5xidYjPPVpDqKwaSJxHvFXFECJaJw3/RvPH1amqJn0oSiQjxswS62qgRgyBWJmXBlGRaMnzSkqCBLQuCeUUjYFYTc2rIyixMs2hupowEZPMKsURMJO+uq4s3eCVkFmiz4XkOxIqNCaGgLcErcs9/cEAX2Ss9JY5PFhDgNFkl9lsYgCHmCeGc7m9ROj5nNwlQKo2GS9XZLheHxElZ4aTGnWCpkSwhBkuzlCJaBZQiQQpCTIzc+eyJMwCVayZ1iVBIzE4NBhrZDp1abCM0agFJuMcX+R2jOMKqaL5bLjMjA3LMXpokyLvM+AwWVYYwBZNSk01RzT9NjTsiQYwcAyKHk5yvC/IihxxDt/L8IW3iZNq8j8Bpw4nQpY1QI8xWVBla7bBeHedUM6YXbxMvbuL1jPidAcNNbOwQxl2mE1nXD53kclojGqORmMQTOKUWQwpvaRJhkoS0CF2jeGZi1TFFmAYAC8HbkLopwr1AuUGlOOYlMoSe8EIRwf0iCZ1pQqFg+QXafhkTCBIIgyVMUlBCfTECFkNGCLMfT7afaSuIJMr53jzieRehkbDMGlq9afRXiJQyNwLpJnEtQCI0thn7Ik0/yJGkn8MVKXhqc3xi8J9d93Fv/zpn+T8uTPkfkC/t4pohFASo+lfGTNMCHUkhDnYAVZR1+g0B50RmeKpyFxlVXtAjbC2MuCdb3wjr77lZnY2vsD5Rz6CxsDqypdw/bHXMXkCU88/6WGgh11hQobgiFQJ4AgJtHCYhNgukRk5R8g5jlBgAn8zIhU1uygldi/1bIKfQMpG9sp6jU2UiwzJ+Asc5Vs5hh9XZNPfBym4Jb6Nr9L/B/dzhkc5+5RBj9Uajs/goe1H+NCjP8ul0f18ycu/hy+7/d3sTs+zNXnsqqDHZnWR91/8dzg8QWuqq0hsReBjnOFOzqNA+QwkrJ9uHN4Z8abRKU6wwx/rBm5/x/A04hTn+Nf8Dk6FuOGIW1ahWquxpi7t3MPG6CG7NlJf9AZu5i38Jb6C26lixiz+WS6xw4899h/40OMfIHY6kjmuYf1BG13NPgzAuK6GQ6VJYp1zltifeajSaG23Sf6UcLS2ZP/hYMyFAliO4ELg1OmPsPW5H2VFjvC1xwa8c+kwa6N1rr/0MHW1yf/J73An/4VLUvMfPpiA6QChtqRciDOu7HWvLY7g+EsM+XoGREoiIyCSUaFMmAuWfHGziQr4wyF8aPDkW/qSCbxmBjdU8LYJvGF68NGVAv/XUfjEwM79MxER+NgQ7hzYPssn2K7HnrfPJOgxKzd4+NSv8Yj7j6jWhPDkbMAzn/04N104wrG4Sk8X7MFFvHRCxMAAn/k2OQ+CxtjKEpu/Bi3AIcmjrzHp7npdtP1Iw3oQ88Po7BEbD2ib9A+h7vqVd0LbZ0y7duvp0S5yBQhAdwkBcMagF9nXPhoyx55tNoDDfLErd9JdptO4ziLpPHmHiAEfDqtuct4Y7Rojoa4TmBET+KPpXNgJj3EvWNEwaPY6D6b9IfQdvKznuLEQru978iJnJgZoLWIRi1jEIhZxrXFc4L/J4R3e0s75AvR4ycQLF/RQLKOTMef/JjNx02BqRqPaDvDA2zLBKnAIEUIFsZ6PKi2jaOs1tNsIEu1vn9tgmMzZTLUKDOvAKgEkcB3KSRTw9EPE15FZCeNpJChorpb1bdgoaaeqIbU9JdMJaMqwSpvi1aQha/JJok0btWUXKPZ9jIEYKxswJokmTeiKVfMkGS3BJLXEBow48xZwjeYGHU+DKO1AXbxlh73z5M6bbJO49vtMMkICODLvWsZCI1+UubmfgyQ/E+eTDBWKozk+A3gAJFpVj0pin0gkhIoqVMQQCSEQQjAAJAaCatKhNVp2bBTBBCRdF3UQYq24EPGhRqIZtjutUckoqykyy9EYyX1uoEes7OUcZDniLIvvdP57guLEUWQlmWTErE8MtYEeAVxly8TYTHQy0MyYHnmaADSpMI2MxtuMRlvEqqTa3SKMRoRqRjXdIYaKWdhhFnYpZzNG0xHT2TRVp8eUhKxbe9hGAqpJ6Dct3p/iaWSseliyLEcpEIok5pN3oJJ2gpTYDhI7l2ZzGJ1tC+yZ0DUKAQ1TomFOPJHpcvc5c9Bi+gTfdbfhZM5Q2ackc0WV3b65p701bY57XxqhKis21y8zmYy5cO4M490Rs/EE6ef4wu7X5t4VBU1yeM02pbkv09UQO3J7JAPLBhBqQZ0YGU+nbI9GTMsK9ZnJo/UcxdAAzUUcFI2cm8Fidh00zA7HPhExGum/7pVj3zSyQfuvnINHRs1v51ByGq+YGo27KBl9tonscJgxN+N4OT0a1xjjYmUojhkVG+ww69Sfq9aMZhfYGD3E1uQ0k3qTWb3LuNpkNLvApLy8R/rpyjMSKeO1Gd9XRKp90hy5HzDMj+JdxqTaYlJt8sR35MHhcBxilSWGzJixwRZVy77ZG1OdciGcIzJlhx2eLhuhG4HIhJTYVdiP6UQNxH0smClbXOICZ1kmUFAxYJ1dJnGbEHefvF31GHYfM6R1tgkoWaw4OjnLyd0HEeC82LBhdQhFf55vEuBEZWCXVwOTK7WhzSxCGSrC+BxUO3gKlqfbHHY7+Ok6W+U5JvUGYy4DOyiBZzql/TJ6HMGzlO6kmBgfxpB6BvsnMQDhale4S4DQaoQjcc4GmTjYSEPF/VEKjNzVr2JJ22zYNWDL7jiTtzpom4gBNFcFURSWgSWF8164cJXFnn4oIU6vUVfLIjtUUh3aYrR2gd1YwvYz3qhFLOIZD/NY3A8kXLlMI9sEpOc8qaonzcgaSacOA9c5SUVTHYPv/QU5mrYhMh9fNnNYzFzbFKtSMVVkLqeb/hvbOZ+tLO029u/oKsdHB+jY9y/7aN5oaZ5UV8hBSXs+2rY1yzQMl70Hnf4/l6mSLmjSgBrdtnQwmnkbuhDKfDlRk+zKndBPZuW9TCgyx7FMOJwLh3Jh6MUKIRbD4EUsYhGLWMQTxBA4Qko1p6remxwccrCUEkbPgJjAIl4g8cIFPWINRYSBGpCxm8EUy6C7gYEHWQlFZRoQfgVYgWoFthRcBdsj2N0E1BLYvb55f0xTSlhMxEZQfPIJkWIIK2ayzfYEtitW6ymvKiZUWc0tKF8J1JkynU6pVDi9G/j8esVYlfGqZ7LkiGLgjPOeqBOqZOAdnWV6NVRUyXzczKpN70DFhB9cjGQpMxq0Jmi9hxKtdUmst1BVJC4hLIGrifkY9TUarVrGao3thWRJdsqRZRVZViWQwjw8UJeqn+3OFxzOCT3vzfMheqrSUIVMe2SuIMsj/aUK740OrsFkfLxTM/V2njzPbSKiEdEa1UBZzoihNnmgVFnqnL2CRsqqIsbILJRMQ0mMSjmFUAqBSKmWII7RDAfRxojPqrBcohDUZSDWNrD3vsb5iIsRHwMSHeOdCinHaQB9Fu/MF0ayrE2K2g+DTULUMv4iAe8cK0VOkXnIlqF3FETIZB0nWwbuaEppR4+LZpYcJSOKM4PFWW3HWQuTAEQlq0pcqJlVNTvTKXUMlIyoGJsBeTmjJqQEbJ2SSt3a8ka8qpkuCcb7CO03AqzhOIpjGVhOaamMDM8gWZpPCZR78iR1hEkJvjJcL8a9sk8Na709Z3ZIlGkjISQae0pUuQSO5UnqqtFR7EYjT0VavmOHkZLJ88+awul5HRj0xTTvYW6e3viDNMs066qb/8wNkNNgpiFAVScfk9pel89d4Nf+3b/irrs+xeULFwizmqX+Mmikmm1bbVqqhNOYoVHStWoArgGRLgFCCaRFEQKCMYXGIfVNzo5/Z2eX933i43z0rh4vu36JN7zqdpYGBWtra6wsT8mnC6bHQWFuTDPsl/cIKwney/D02+9tGcExxLOMY7lNikRKAjvYb+Qw1xsD4ec9bRcQEYSCjB7WC9UEdlPyt0QTnNHnXm6h4nsI/Ne8DBuG3YjSZ8YhKlZ4iLP8Mv+FB3i8PaZpvcOnT/8bHln/MLuzC+xMzxK15uEL72Vncpo6zriwfdezdk6PL7+Gt9/yV1kujvO5s/+Bz5/9dcLTMGRfYsg38XV8OW/lfh7m3/HbnObsgcveyyl+gvfQo+BBThOeJ9bJGTb4Gd7Hv+fjGIyfUVJxr3FBn3wDG/fAnT8K2cAkr2LFoel5/qsH/gVvO/Mb/JHCg9FYHu+8Bb7spLHUXGKWrY7h6Db4GtgFmcIXAvzbCk7HyGj7AWKYkTHj+PaD3DY+xKfqh/jV8EHOsM59nKN+KlnwpxDfzy28mh0iU8xRZAnS0+rqEMUzH4MIf2EbvmHXvD9eVtmd+eEh/Moa7B5QCByB+4urszF6Ct+0C39uZw6iKPAHS/BLh2DraZijZ8BbAnx5DT/61Fd/VuLGv1jy+InPcc/JxxmXEX7n+W7RIhbxxJFlGXmRJ6kqbcEETchDw8wQEfIiN/+OznhVErjReFk0gId3LkEHmorGHHlRJMNtYzCgEOLcNLzZcIyaPEU64IkImfcGhlY1dV0jzNkjdQhUdZX8MJrjsCKv5t/ti/0lF/tLeTqh8z/mQMMB5RoNuN4wW1r/EDs3WeZx3jJCVgeXpKhSIWHb3gR0KNFY0iF935wjne+w2U9n9426MC5GiumMrK45kXtuH+Ysecf1az2Orw0YeuHGnrDihbV+jg8hqSwsslWLWMQiFrGIg+MNwLfjOAZormiurDl4WTZ//sjzJ2ywiGc4nhLoEULgH/yDf8Av/uIvcu7cOW644Qb+6l/9q/y9v/f35jRfVX7oh36In/mZn2Fzc5N3vvOd/PRP/zS33377U2tZDDajHEYIDkZqiUbnQHJje7gashoz2+7b56Fn5g4SLDs7nVimc9ADn5ggdcpmJnkpJJmNi4DPoZc8P7ZLmE3puZLjeQkSuTE1r3KO9apmEiqynZpT61NiVGbiUe+s+ro3wMzLo8lkKKCWJFMtkyxVDaI2cBRppXREFa+aCCmRQMq8RpIheI3GaRrNLwN9kAr8zJgS4oniU0V5qv13BS5fRpynyCb08uSl0VCRcUBuoEdqiMeYAA6I0RGCVUDnmpOJkPvAsBfweSBWSigbqoWlofNC6A9SRVVlOkgh1FRaE0Nl68xssKy5EjMlhEA1rajrwFQrRrE0aaHSo7VLfgtWAa/NhELFrpkmCZEquOoQqYIiEsmKGuciLtRksQR11DNHKEOS3KpNDKprEhjTbxBjGqina0sCuYfQz+hnDs1Wif0TIIKPp/HxHA5tbY+JHq0zVIWSgoCnqiKT0YwQlJoBNUOcCH0vFE4YVYH1aU2lgUrG1DKxJHxsmByBuCd13y2p2vtZwyppq7oQBgiHcQxRekQ8yXuEPNXBV3MwoLkto/l0xEYGKoEdDWnqINaHkkARrBK5WSfIHKAQfzATg7T/5pZtjGibdnWPtvt39wxkcmVH16SlG9CkLQwTiDI/hgbsUDUJr6o2UMQFe422d/jUxz/E+9//u/TzPsv9VXpZj7KaEOoZCHjnjGmlgoZsz0RP01HbvmKSQlMysWuyAYwUoRCTv5lOZ9x76hRBa6S4nTevvIrB2pDBqmOwVKGTgyvkX2jxnD5PAFoT5RJjxjWibQ4hR4gJiKgN8KWPo0DaHpAEVjSgSJ56yCZzOofitHMFOjySrkADRWYJPBljklpb5DzEEQq+kqN4jgA3AK9GWWbCCaYc45Pcz+/w0T1HVMcpp7c+yemtT+75/PLufVzeve9pnKOnFiu9E7zqundxZHgbF3a/wN3nfoPwNPIMPXJez6v4Br6aQ6zyu7z/qsueZ4PzbHwRrX5mYosJH+KLOMeT83D69/d8NKx2eO3FD/PlDs4EAzQkh1cM4WtWrR/zwYYt/V1Y2gRfQr4Oftf65UkJ5ztYhqdmZXqJIzzKLvfzPu7kQdaffruvIb6eI8wYE6gxybcCAwAP9ox5tqIA3jSFb90xRoxgz50Hc/itZTNRv2pcBfTIFO6YwrduW38Mdtdvevg1ha2n0U4H3Bzhy15Ak6vDbw7ct36Gh8dnGL9ILD2e+2fKIl5I4ZyQ58aoDokF3z6LEzLQMBG8z/BJirj1skgAhiX2M5McdQZQCBBiJMaIc44sz9PcyYrbVDH54JCKi7ThtMW2EMg8A23fvaLAal7Kds6R+dwYKLUVvxhwEzsARyppiqnCiGY42Rxjt9ynGYhf/YE8J3zs7+zm/3YJ8Ol6dMyPXVoJKZMDM7Z+DMGKeDQV3KmaL2OaKMievTTMGvODvGICIfa8y6qavCw5JBm34Tjk4JVDx8vWcjIvDDOXjMwdopoAlgXosYinH4vnySIW8dKOGxDehXAzEL2iNlVpc7GtdMoiXhLxlECPf/yP/zE//dM/zc///M9zxx138IlPfILv/u7vZm1tjb/9t/82AD/6oz/KT/zET/DzP//z3HbbbfzgD/4g3/AN38Ddd99Nv9+/9p2NxUrAC29ZSK+QJz+CWKUBX4SQoQHKGAgoGZ5cpzZ46ilIQSrIBR/thTEDCAlEECHmGepMZsPN0hXeaNgoUGcGkqhp2zin9EOJOOFEUO7IHWMRRkt9JisF26Hm/vEmW6HCZYrPrWqmSQpLdNY2yRCXJZkbJcYqGU0n/VKBIEnyqpO4diJkUgDGjIhMgWApVHFED8FbpY1Lvg6mSRsQieQevG8G4LkNxtVSfYINZJ04hEiuNUJEXEhlpkImgpcM79U+qiBWkbpOAITaDCOEijKmQX1dI3VNiJFJVVGHSCwjcZa0bSNowBgQtTEgyhAJIZoBtmYEHJFI1ejAQgJYJMlQefOPSLRzUVPoN3O8aKbR0VOnJExQT0RwOhe+sSx8mkp0OjzXVC/hLIENTEohBkXqCsKuzSJimQb2QiYugUgeVY+qUMVIiObpMEtsiZJAyRRBqNTO7zREjNMRqZt6Zp33v4KQp4RroJFJ2ptwbaYVSkT2fKeMUdbTlbOa0u8qwtA7HI5ZFEbR+vxlrLMIaqpxhA5rw1TAaCSMSyP7tF4eqdl2DqX9ufDeTldjLt4tuu2CGjD39OiCIt16tibdXEdro2NuUC4yPxNNe6LOgZQIrWxX3bA8UvcSFWaVgR11pUxHkboKnD/9AOcee5CzZx9ja2OTIhvgJTeGVfq9nWQG9EQxOYPk6YI0rCTTR3F2wRJSIwRFvE+G62r3nTYyMULE48SEkvp5n7XhkLXhEv1M8Cp4fXHoGD+nzxOA1LeltAd2V5hJvNWgx7RUTgOFRQKOCk1AB8QEdMCcW2XrswdSbCSzYG9CQdN6c0+RTs+DUqXq+G2E88A2nikFmxznLF9Nzg0c5mFm3MMkwZIWy8Uxblh5PT2/zMXxg1wY3df6CT1bsTM7z/0X38ty7zgXdr9wTftb8fDqJTiUQz4tyMd9+jpgh0f4fT7AOo/yJQivZJUHKbmPKQWOOxhwAznnqPg8E0ZXGYnezIDXsYJHuIcdHn6OE+1fTOwofCwaqfWiLvPVHKWMDt1a54/ObtlVlWo1ign0xlb74WcGkNwVbRvdGFHyUU4D8G38ynNyHJ4PpX2fTOBgjo1dmopp2J+McwqHMT+LGbCOyUH1MQp6BMZcA09E4abagIm1CLse/tPK3pKAXQ/vGsGWg7t78JiRMK8paoG7+rbNLmby6b6ZlD9pVMBFTC4qsQbLNwm/DPzytTXhOYmNu4WlsMptNw0ZTyNw/vlu0pPGc/9MWcRzEU1hlsXe3qNhZSCOPDMAQsTGXF0T7GbZOejhk/dEkqySOcuDtE3XyvbaBlrWg7P5RAhY0VoMViBT18SYHIvSfMHY6DZvAtAoNB7eCFRlSV1V1mZN8zeNqV0yZ0ukMaCqSQBrs72OzlTjD9eCPcp8DtscG21TEivezlcMgVCHBhtql9/D9Egjp9gWgAnSgC8JEILESEFbdYKD8Jd2/K4RTdsXweaP0my+O5tRRJWgyjgqeVBjgLcFaglckrn+rC5Aj0V8EbF4nixiES+9WMbzepY4ScHbqRgyQ6TRqw1X1gpc49xgES/8eEqgx4c//GG+5Vu+hW/6pm8C4NZbb+VXfuVX+NjHPgbYIO/Hf/zH+Xt/7+/xLd/yLQD8wi/8AidOnODXf/3X+fZv//YrtjmbzZjN5orS29tJOHhDgByKPJVrRxhOLfs4nlnmdewhFgQiu1IydTUDCazh8HibPR9askGQGFODWTB2SBAYK9QQvWPWz4mZTc17uynTHRPIEoC6SOXeFYQKL5FlP2HJzVim4NbhgOgz4pE14skV7t9e5+fPfIGLW5fJV4/gjxyHLEOCJAqwR2Q5JegjzkWiRkKYUsUZlcsQZ5IojoBrpIm0sacWcllGiUwkUOsWDqGXjHqDV0IeUBGc5Ih4JCq+Lq2qxguuMLAjz4Y4l5OpUiSzbl94fO5sf3UJWpOJI5eAONCiB3mO1Goz/ajEKlLWwQa8tekAVS4y8TWRiA8RFyIRoVTjVbhZjRtXEJUq89SZeZNErYBIXddUZU1EqD0E503qKtZojDiX4SRLIE2BSPLfSKCFCc+IJSZDIBKJmpwsVMxrAwBJNsZ2aTRCUKEWq+wXKJxJFdUxo1aPD+Y9khPxTMjFtPZLJlRpctW2KclmqSp1OSXWJRFnjByEWSyZJLNQl1JDgUitScaqoVKktoKQ4+klLklJkwxqEoENh6KZKIY2qUs6ti0iu0SW7GxQApUXlntmTL8zc1TREk5LaUtFkiMLFcxmBnD0+nB4CEVhxKrRyA53uAS9LGGLKRfqXAI+BHKf/Db2MTEaiao6vWdipud2FB12SHs06XOFaZ1M1dkLtCQVAjtbLtn9JAZHTOvOERBaq6A6wO7YupxyHBldKpmOJvz+f/4dfu93f47ZdEI5qljuHWq7DJs0Znhnx17WEFTJXUaW/GGCRlRD6qm8JQLVKglBcC7Hice5Ck+V6vs8tRqzwDkDRVYGa9xw5ChH1pYIQYkB/DV6NDzf8Ww8T+DqzxQhSzbjzZUTiYxT9WSdgEGPw5h+JlM1I6b7RlLZh6NI65TpHWL6DedXpsORYSweQwmVuQQWgCNJGlK3oElgQmSGo8YxRsjIGZDT41WU/G0GjLmFf8MlfpwZmx1pp+NLt/Ou2/5fHB3exocf+zkujx8h6rNbon1h917e98A/wUnGpNokaPWk61zfg++8Ad64AksXl1g7fZyt2vGzfJR/zQd4E56/QZ+XcQM/xzqnKDmM5//JUb6BNd7LNv+Is4yukv5+G4f4Pl5JD8eP8yCnGL9oCnUuAr+QTMm/Vq/jb/N2+iHj585+mp+6tJ2qZm1ZiQaAWBEFkMCSy/vyPJcY8/N8mvfw7MmcXS1y1rAnmpmz2btHWhHG7rJwG3ArcAm4E2NNHMJ4TzXwGNcmjvW2CXzfJViK8POH4GdPJAYfBq580w78wEXz9vgnxxLocY0xE2OJfGi4dy607Q6Wy7oipsBngfsxAOQFismd/u2M6+64gVe+7SZ2RoEXA+jxnM5RFvGchDghLwqyzO+BO9oCMufIix7Op5ItsWUkCFFiy0ZoGdwd2SqXGB1FrzeXV0r0hy7DogEynCRARdWkrNTmO7ExPw9J3qrTMZg9hwEErgVdKqqEPIS6JoTavs8CIg7v7bVnDK+a2BT7wGKXAKEExgjSSnspioZg8sHi8D5LYIamwiNPv9/Dec9sOmU8mqAJcGn8OLoeG4a/KKGurcCNBmixtsWQwBpvgJGmz+j29s3vIGLrJCNG17gHJmYHMh/DN2fBA2VU1qtIJcIkagvgaIjz0ZUIhI6X5yIW8TRi8TxZxCJeenEdOf8d1/M1HKLPFsucA0oEJUrYm1yCBejxEoqnVBL8FV/xFbz3ve/lvvtM0uEzn/kMH/zgB/nGb/xGAB5++GHOnTvHu971rnadtbU13vGOd/CRj3zkwG3+yI/8CGtra+3r5ptvti+iM1mrIMkZUlOJ45xtYZlRWy6qEpwSJdEFCMmp2SVXbUmjJp2/GhdlAXVCTLqs1DrPuDbJ0ECTDU8giOJDIKtrhjFyxMExLxz3jpPOc1yEpbqkX07p1xUDFfoqFBGKGMkiiVXhUwXTvCK/MSsP6RU1DebUkmeiAVE1Vgre6osTg0OS0Z5zksz6wHszG8+8I3ORTCI+fe6SWXnmjOrtnSNz0nk1ieqIE8VLxGEgjWv8SWIk1jGZjTevYAPjqqQsZ8yq+ausSso6UIVIFRKwEQJVCJR1oKwjdTQ2Rx0iIVq1VIi06cOYKn5MNslYDiq0RkRNiDTSXfalRogqRHVEuued9t3Mo5sXBBVjkzdpS4UYhRDFJI+CWjurmlBVVHWgrKCshbIWZpW9l8GkisoQmaVjr7S53JRaA7UGKg3M1GStAgbUNBwNe82Tq5IAknn1erd33v/vLhRgl/gMy8FM098zEUqxxM5MhCnSuiC0t0PaREysCjN7bOeKrdF324TOe1PN5bqvA1rYIVvsS43NlztwHSNLEJrzmv5uX7QEr/lncb5e40nS/B0TyFOWynRSs7szYXtrlwvnL/DYow9x7uxpZrMZXjJEjMmjSY7KaCWJFaQuVbBJU87W+TW1rWKbGz3aNG9uBKmdY00sAvGtb44XjyND1CP6NETln4d4Np4ncPVnirRT5zmvqGFZaHulifXJe763B8DcqyNVU7ZL6J73eUi7Vw74VA68ZxsJrhkwAnZxbOHYYMAuN+F4BQXXk7OCw9yc7LXqhlzXu4kT/Vs5VBxn4Jcp3CAlE56dqMKYzcljrI8fpgob9DKlSGAm2CO472DgDLwEexwfyuFYAce9cIKMYzgCO1zmPCVbXI9wGwVHk7uQRzhExklyDpGlTw+OAY7rKDhOj+GzeOzPRlRYavlhhW0yDjPgGEOqMufxEZwewemxvR6bwqkSTlXwSIBHFM4p7IedaiLn2H3WJa0OihHCGGEEjFHqZszTgoTzEIyQO4SOoBxJdJOWf3Ut0Ve4roajAcYOHiz2vsbOPD6uq83346mECqxn8NC+bV7MrmJiDvMxZIk9bLeBdZDL4C4+tf0/2/F1t8Iv/nnYOi9I3WNteYW15eXnu1nXFM/pHGURz0m0AEUyHt/z8mYobq/Mku0HLdcu75PEVPKqcHNT8u7L+fRdwwBpGzN/adRWXjeEYJJOMbTJ/xjnr4bx0P0shGCvZp1GFir9u91dh33S/XcD4DTH4tPL+c4rHZ9rmCtpjuect+W9Mx+ULGuZ/05cmkO6lgHTMucbEkYDwDSSVrrveKO2krfG+ODAgfxB3eWVT4V5NN3oTJVZVEo1v78qKrMQmdWROnSLxBagxyKefiyeJ4tYxEsvPMJhMk5SsEzGLM1T2rlTU/iqV87fF/HijqfE9PiBH/gBtre3ec1rXoP3nhACP/zDP8x3fud3AnDu3DkATpw4sWe9EydOtN/tj7/7d/8u/9P/9D+1/97e3raHwNFlk6IaTdK4JwcpIGTE2kOISNZD+j2cBJa8p5CKnBwXkwNNHZMJgJKcrwEPLlEOswlkM5x3FNQoDh89hMbBprDlQgnVyMAUacqLjN1gI8AK4sSWu+BgVHFsNuYbOcSXDHJ8sYwnJwTHxdGY7Sqw4Qvu7y0xchniICatn8IPyXxBVdeMx1Mb/MYatDKrVK0S6wPKhnKdOfouJ0MYqNWNl+og2mB1kBcUWYZoDT0TyHF9xfUiIo7MJ3p3rPFhBhqJpVBPSRTu2iqV4hTC1AbA2RjJCgg1Wo1BA2VQytBQmkuIgUqUmUv10LWV15sgTGWJxlCjVPZZMCChAR1UlToqVWiS6QGtK1TrVj8WNa8RAcQZRc3hCWLeJFnu6WcZISrTRlIIUE0px2SejkZCo2WlMZ1jQV0PkQyRQHQVUSIaA6IZqFISqIlkLkedlYtWGqjMPZ1IhVJb5xksUVrH0IrhGJvIZlF950GVWrswx/6wFKDiCAizlGgNexK3zXtXjDDu20aTVHdEYMsJ0Vll7flyTA4cC5Ej5BxGOUbNELt98hx8YXvwOWQeqqQ4F8JctirUUCZVIJeKuBpPkC77okxeGQBZlqx3EiAR1dgWk2QUIF7mklkd6awWL2CecG1On3dmZK6dZRt1vCYN3hpWiX1fVdb2slTWz4/Z3qo4e/oxPvvxP2Zr/RIP3Xs3uQzseghQxTpNgBMs4QTzHlI8mroNoU5VgOociEclEnSSKgxAfZIri7VNJAkGmJBOWHoEBytFZGNnyoMPb7G+UnFoucfysEDrF0dd+7PxPIGrP1McA4w/ZUwYoUiAgAmH2XuOI0/33tTu3ZSktTs2abthtYkKyQPH5PIiM+ZSVxVz3pZPEIc9U5SKwKRzz84hFIPEmnY6XBI1s2+t33wLGX+Ho0w66y+XA264PKYY7fJ2eSPLN/4tNqoLfGr99zk9eXb9PbzAHSfg9SdhVMLHT8PjW/DKJfiqw9Bz8JFN+NQ2XJzBr5+Hj25CsTuhHy/gybiZI/xdbuQW4Pg+yHOTwL9ng7uYcD9TNri6b83n2OYneIgM4RNsvmjTHndzmZ/kTgocH+c88UV4JP+ISzQQXw/ha8j5Um5AmFGxjkHtFjXwKLCLwX0T7NffAU4zl7e6lvh8D37yqA3/PjG4EiT/xAD+2VGTqvrcc6FAodhBPIgd4GPACIY1nCjhoeegCdcaD2/Ar90L1x0S/tJr+tw8XTGNxxdBPKdzlEU8Y5Hl5p8BNMX+KckvyT8jwzufio4SU1IaxoYz5rqjTdbbNvN2eyYhav9s+oK2HkeSLFVbkGJP2tjMZbQj25RW1mjFXZp8KjQxPfQgSaW2Ukj2AQjzBonYWCIE043VJM/UBTgaoMSYGK41EtcYW1mrziZpzNsb0KWR8O1iODGt652jnM2oq7plerRVTO1xG5CgqtRJflhEcJrObdq4HUfD8EibaNrVFkgZ6wXvW0+QrpF5t8cWQEWYilA6EwU9F4XtCPeOKuqNCRqV2awkhsjta0PefDy333ORslrEFxGL58kiFvHSi3Uq/i0X+CQ7RKYEJhQa+FMx8CU1eByu7iHqiL4mZiULAP2lEU8J9PjVX/1VfumXfolf/uVf5o477uDOO+/k3e9+NzfccAPf9V3f9bQa0Ov16PV6V35xZBkmI9ie2LVWFJAVaFBiMM0c1+8jSz2cRIZOQCpjfkxThjWEeSn3JJVAFh56yecjG0E2Q7yQSwI6Yg+qZD+tqbawrmE2Na+GPDNdHsT0EqRxD0gVwBcVLk45Isq78jV0sGKZXArKELlvd8KZ3TGP9gacXS2Y5oJmHsUkkPJ8iPMRrUbU4x3quiZoTdSaTCJDP8VJILqM2heoCHnmKDLzgehnjgyB0hNmHifCUtFjmGeolCilTQIKxRcREW2re7RWtCqJIVBNI+VU0Qh1MBCiriuqcoqq4l2BSIZljk2KKqijTi7QqmYIHESoxGjpoTbNWIiIiq1DTU2dJhlN1ZBQ12b8XGPFkQr2ewImRGVGzyEaCAARkRlIiaOgdoITT54LPe+pJTKrk7yMgpkMCk4i4sxsPsRggIfUOK1su9IjimkyBVen39pBrNsUJChBM/AZIo6qLqnVSa4WLwAAl9lJREFUdHlbh5Y4N8yuoE2LOjU5sZ5k9MWbCX0M7cTu4DCid0ip0QbgkEaLsI2D9PWbNH9T0Z4RBXa8o3RQxcC0GuMUbiXjRgqmRF5FtH25OeiBgywVv9e1Kb+BARySbr8YwWdQZHarhGCgh3dmAqsY+2VU2oRogCVIu/4aVaXMSjuyPIcsk3Zi3GCPjTyVkEAPnT+iMme3bASqxOpQTaQxSBJz89MjascyHsN0Etm8MGHj0oiH7rmf9/+X3+Di+dPEMCJjAM4md7XW+ya7JruGkJLWBmLV7YQ9Sx40FUGniNZECnC9dvKrsYGymkmlM2k5MBYSyubOjIdPbbG5UnPbjassFUlP7EUQz8bzBK7+TPH0gUny8YCMXgIrYM7yyBIwYf1U7NwnAELduceS/1G7DsCU2Pp/NEysHg17RJLklYnNVSgV0go3aFv9rsnLp2GcmPNHTIBK5A1kvI7DaVkDCEblgHPrE6bFLkurd/Dyk2/lXPkIZ8YPPOugh3PwmhPw5++AiyN4bMtAj5cP4L+5HpYz2K7hzh24VMFvXWzO0AR0ynH6/BC38J3chmOE4wxVkh4D2CLwG2zwW0h7Fq4Wd7PDfexiv9aLESqw+AIbPMAmMJdbfLHF/8nl9u9VPIe5iXdyEmFEYJf9oMfjwJn07+YJuIPhBHDt0457enB/uiVr2bueAnf2DRhpvn/WQ7ED+wiG5iRzkqUAt7zAQI9HtuCxHTi6KrzlUo+vK5fmVQkv8HhO5yiLeEbCTMP9HKSgSYy7uZ9EAjhUE90bxWW+/d47k2xy3pMlCaeG6QBYgh2MNd94UDReF2DyUjT/TKO12IAe2oIeDYPDCmcCjQm6piKUVoqWTrq9QSD2AR7NMZnSlLQyWlHnDIoW1BEzZq+qyuZf3uPJEi7ROJQxr/zpJPtjW+jVKdhLy8XoQM0jsqwq6rR9cQ2lg44/BxDtGLuG7s1v2By3nZsEtLjGE8TGrEqqoE3H7w3dSuNvaUnQ3aNI9ULMnKCNNq5CL0A+qdndmlHVgUs7U2ZloBTPa4+toCIvymfmIl44sXieLGIRL73YoOY/cKnDHFdWgJUIbw2QRYcve0gooDch+msR1V3EiyGeEujxfd/3ffzAD/xAq1P4hje8gVOnTvEjP/IjfNd3fRcnT54E4Pz581x//fXteufPn+fNb37zU2tZXaesKTbqqUsa83GRaFXezqcMq5pQc8PC0EbU35LYNvLxlt1UmWvviIessLPgkwRWdLYdFVu/MTMXLLPjxV7dChIlLecwk/SIOCULaX+1g9KSzUtFj7UVYegcIU6YlSWiOUgPp4rzNUhE1HxDVCKSZJa8QO48uRO8y5BUUp85waeBf+YdXoQ8CiFV1HsXDShhrlGrwUgGligvTbgllmhtyda6jtSVDXTrdApCmFc8hVCnqUFEXUoQajQQIiVkFUmqYKaKH0NsPQsMdDDYI0hMFVxWKa/aGHPrHq5C4+aQ0sBpkB1otMiElCWXlNUmUoeaMohVzkfs91VJ6UyX9HftADU20mLWliaL3hgMahS0lcTStkVW7W0VaE0teLKbp6nfJiW9u4P5xNNplwg0OrxPltxpluhWiV9bUqyBPPZua55INJktqzavyCkZUBKZSo+ph4oBUQWXromGYaGpKd28f8PkiGDIlRj+2MhHpUKw9h2SB0baVvI/3KfHL/N9pHedn4J59V76vplvNtui2+Zm3eaygVbxLkYDPsppxeVLZzlz+hwXLzzGdLJNVU0QrRNwJ52JL01BX9r3vKEC7b1H+rUaIETUAD4DcoJtE5NUs4+b7URUG+NrW382m3Fpc4O6Ljl5rIeykq7RF348p88TaAGD7r9j6xBgP1wDMeyVvIqpJ4KuJ4e053neH8z9C5rP5+9zw/LuVS2d9RNg3EIfTbu00xa7gw2Gafoi60u3YsmZ6hSblIynfUZFn4vl40zjaM95cAjXMeQYw3RtlUBgg5rzlHtgnW4cdnBd8uTR1JFIEFztyRVumSqHt0HH8MrKKMNHQuDctKbvlaW6xx1aMCJwVmeMW1BWmRA4w4T72cGEkCaUzDjfgS26aaknigiU19CLvtCjcY15MUe3/ZeoeTeP8G4eYav3zVDVON1GOAQJ2L3iV1NgDLpri7AC9A0wH6aPJphiVPd2i6Qh10HxZN8/WxGwiodpCdvnYLRFHWFcwVd988d59P6f5dH7fpYYZ0+2pWc1FBvznd+c8r0/9n6+98fez9Zvvvt5bdO1xnP9TFnEE4dznbmSdJ+TtE85k+H17bJNAryVoOr4cKg6XFM44uegh0tggsk5pX3qnMmgpI90zlrQODf7buWQ5uSG9rOGzQHaylDRzKOaha84rqv022mAOJ8XpIY1z3mdt6cBKTSCOpe+mwMxBtrMxwzt+p2WNCBMw/Rg/7fRWMjihFAHO85WGsrmcg2g04ynm3F2V/qqlWFthigtsCPpd50XfbXLN+dqD/CR1k1tb5ZRkTT/9kTvqZx5q+yqsFkrVa3sBqVMjP7u6G0Ri3i6sXieLGIRL71QuGKeOwXOKHwhQhaVTCNCzSqRI8/1XGERz1o8JdBjPB7PKcgpvPdt5cxtt93GyZMnee9739t2+Nvb23z0ox/le7/3e59ay7bXTZC/8pZRLTeBaj6I8oJky5CtpBFYSl7X1RwsqaNtQx1kfSs5jwrTZPSb9aA3MH+PviafDyy7EgJUU9PWcfW8VL0Qc1VWjOmh0AqLqoLUKdMr1nY8zDxMMrLCccONhzh6pMdoa53Rqfu4MB5RDNfoDdfwDgahRHyNqyIDXxNF0UqJwdgoK70evdz8R0wSa16l7jLI+4YD9XJYyW1g62Rmiaq6pp5WNhFw4JwSo1BVU0IQcIo6G2jX00iYGhsiqE9JWUsaqkYbIIdUe+zUxt4hIqEBO3IimYEaSb4qJn8S63Dqtv69SdrVaFukrsncLsEQzDMaVtUcW339GU06jAQ6iAacVAhCmM0YV5Y9duoQLQgaqFK1twtq7AqiMWoSo8HErSK9TMkEVB2hLohat8CKpvYqYkaHOjEaOpHoMqLOS0wt4VoBBoXY0XisQtxRaU0VK0vQpyM+eMCu6Xjrzr+56tLz86ZpjzBI6dqKBHcpVOqMVaGBKgFCY46wywn6znOhKHBZRu5fxvEyp5gZayIorcWOqklapaI5fGbzlKZSToCi7yj6QgwwCp0mptckrS+YHY8T82CRNHFqAAwRu60lXRKN91RbCNYBOupOrrsV+4rWftXUXQRra+5tclbOYLwNly9u88E/+k988uPvYzoasb15wWTsUvLZfkk7kKhJT1/tym1wWC8xFacpoQVhG76PQjInx0WcmxnDSQsCHo+SiV3rITpbX8CJSe1dWD/Phz63yerSkMOHvpzbbryhnSy+0OM5fZ4ANTsJNjVWRc0uc86ApG/6OIakX4s5dFW2n2m6Pxz9FuBo2B2OIhmUK11z9CapEVvz85DuwuYR3P3NUkWkccT2tLGR2epKbjXMrcfr8/zi7s/xgIMw8tSXPbM44czkgT3nocDz53gV38ZrySmBsygjfo91fpYzB0pHOeArevBfD2HojRAZM8gmGb3Ly2SV5/jjNddt1dQh4+atVXbp8fndHX7p1CVmonz19CQ/yvU8wIj/L4/weXba7e9Q8285xQe4gMG/U5TIo1RJwm8RL6V45Prv4vrzdzOYbuB5G+bicUBETBLqzrTIlwK3whHgdUAf8wN/iP3g+AswAjZc2dmEu/81PPaH7AL3R/AaGe8+QowvUBmprZc/3y24pniunymLuHr4zJPnuZlr7/fGgHYuJwji5wl05z2mfOTxvpGwSt6HTTIdWq8KgKYSxgpPLDtfh5oQI04E7/3cOLthbcQkTRUidR3mgIF0i5Lm21RIDIwmGd/5b8PgaICBLvDRrY9T5vOHfR4d2gE0Yow23RJBHa1ZeuOXsV+stmlojHNmYxfwaJkmzqd9zueNViDUAU2SZJW4BHq0G5wfj090bpMfS8U/tLtJhYHNfqRleuyX+TJASxLI0TmQBvho1nEO6fehKKjFMXLCRIQyOi5MTYqsSjWOm9rMCvWF/0xYxAs6Fs+TRSziT0ZMgd+u4bMRRCMSxzgcXyeBb88Wc9CXSjwl0OObv/mb+eEf/mFuueUW7rjjDj796U/zz/7ZP+Ov/bW/Btjg5t3vfjf/8B/+Q26//XZuu+02fvAHf5AbbriBb/3Wb31qLZtNIPo5sBCmEMcGdvR8qvrIwBU2smqfSwG0oi0njwA5uBw0h1ilpCVQ9CDvmfBzURtw4lMGFbXtBGNeGGXCm5tmc9Zq5r4eUexvF8EFS2SGVBIbHNRWAbw8XGH5+DJLOqGsdxlNNlAPvshRD1GmoDUShdxZUtVy51bZ289yisJYK+plT1WSc+CyiHjF0qg2YDTKdEDUDMdDmDMSYozMZjVVFc2cITcgJc4isTKpKTsbgnNq0lsoIRgbJIqZySngQsSFiOKoyRJbA0JKFDZcB6vEJdW0z6NKnzUpv3kFVfPqVES1Q+TGWR6ai0BQVG3rdTDGkMfRY5DSyJGY6oCi+jaR2fwvpNSkE6soBUCFGB1R/Z5WNowUQQmp+l9FUHFWnaSOprarSV7OpwgCZCjOwKEnlLTqxtMZyjfVVkKOwS2xAV+ahHzachSr/qoZUHKYmeSM/ZDdvGAqa9TB4eu5rFRMwIFqkrlKmECmhhPGgLGGALyS96wtdZKa8i4pwGHSV2W0OVNn7rRHh1gj87Ix7L1haDRGi8K8YK0xXN8/+WzaXifWU0PkQuw4qhmMRzMee/Q+7rn7I3g8fdc3KTgy2o5Apb1CG5aPqMkKmGW2NlPCeSXfHmjCDkY0mO8OQiS3BL2CSHN92f2IgngD5UbTEdujDVaGA3ZGEwzWenGYNz+nzxMMmNAkL0W6yyMTmitmXn/o91Qa0vZa2v7dyFqZ/0dNTIJ1jjzdYTHdpbGTPIlEg3ZpWGvmC9K9n7uDK2n3Do3U1RzwMMBFaH7zbd3gc9VDfI5RVzXoishwvIoj/Gluo2CCgQybPM6M3lVYQgLc6OEre7CSQRhCLCDHM3QFjgzdccQdOwc3s4RnyOWq5vOVY5vIN7HM13EdRyj4Nzy+Z/slkbvZ4m62rt7wRbxkYnP5jVx3WXByGeEGu5avNq/YxFCNIYZ0YGDHSYUl4Lzs6dpfWNE9pkgyM5/Cpc/B6f9CCbwYiPM6XXu+m3BN8Vw/UxZx9XAi+CyZYzegBfMyAidmpG2fASmB7jIDKLz3ZN7owt5nrSRSI5fUJNPbbLvOZZcixhoPdUDdPLmuLaN7ztoIIVBXFVHn4+G9YMS8zY3kVet5gaYxZ5em0CAfHdhEGoZyB0Todg7S7CO91EACSWBLdK41TjfPRCVKbGdENt5VQuyOL5tlY2qzqRg0TXcdoAW1f0s6Vyogae7SsGHmh5JArAawkjm3RdMJbNgcZquRfm+YAz3sM2VvtqDsG+x3TmtmzwgVqNK2K3XsNEVN0c7XBG1HWYtU1SK+mFg8TxaxiD8ZEYAHFR4MkMplAXjvFP7X6fPYsEU8o/GUQI+f/Mmf5Ad/8Af5m3/zb3LhwgVuuOEGvud7voe///f/frvM93//9zMajfjrf/2vs7m5yVd+5Vfyu7/7u/T7T9EtMs+AHmS5ZSSrsQEfmYNeZplSBKb7kkQ1qdwbk7wiYMOt2jKwXqFoHJBL0yquBcpUNl5NIO7aQK2fmB0qBmLU2Gy7EMukzirL0koBS700GkttbdZBuKzKuQhl5dja3GVUDLl3a4Oxg6xf4DOHl9qACgmIBPLCk/tUAVMpWoF3StYz4CFoJNRpKJ4GtSFi1GunuCriSqvijy6CKFUVmZS1GcwlTaKoSlUFQlS0DgkEgFhHogarOo81UR3ialys077S5EISmUZAWp0h8+rQTppv/r95d9IVeOlCG+nHOeCi0Cf4rvt5aNL5zJkhSkVJwBESlwOgSvVAlvSf24GLzUKoU+Vl1EDQkBgolmWfH4+m7TfHkmTE2lS3ADWy7yhtT7aWtsDNMxFXlzeyYlMTQKpkjegOMVxa4tWvejnXHTtCVkSKgWn1LpUnGFRHWZaMm7KCVZcxeM0rqSVHqgT9NPOhdOobLLL5yIgNgsscJtokjTWLSV2ldkmYtzxvkliNup3OFekaJocxKABJynbsvX5iWqfx+lCzfWn3GaKBHWCYpheoZpH1ixVlGTh1/+Pcf9fDrF8+z/qlS/TyPo4MJ72UqG4mlWlCafNaMgUVbZEWUQPgGiDPNzPq9urplNyhrd+IXRd20K2RudGzMGbUFNUaVUHoI9LH95VsZUo2fX7lUa41ntPnCbQghZBjTIsp8+l3IxUlneUb0KH7t2UuEwyF4ua/IxApkT3MDEdkSmOePt++sFceqwGFG4g5S+BJs58qrTOj8RIBxxS4E+ER4C7GV7A0hh7uWIOTfQgeqhwKAsfiWTbi5yhCRT67gKvH3FTu8q2TnC1tEEXlIpFPEdhCyaoBxWRIzylVNSJkM85PAneHKbu41E7zFvJs4ZjwUUaMCJQon2CTX+Q0jzLmwhOhMot40cfLX/5XOJ/B6L5/feD3//nGFT7Tu4Xh9Aifv/44hzNPDyNz5JjlxXlgJsBx4I0gPcgOGcRXAo8IFMBlXsAsj11ad/bBKVgqQQPsquGSg+GNHDn6NrJsma3Nz7O1eVcq2Hhhxd2bH36+m3BN8Vw/U/4khs/8nGGRwkCAbiUK5tORmVG1yVcl0L6RouowPfZQD1K49FmXIaIkeaku0NAm9mFuLD438I7RPDskSMuUaAEB2gFXC3jQ/kvSsUHDhJDWwyLtv03yz9cCmW+781l7DA0rRbsjh2b9Zp9yxXrd2NPuhgGD4BOpNMQ470fabdE5VklDz7k0VePtaL+N29MGlflx2M/SMHO6gA8tAiPzU7Pn92uLk5p2iZmog43V987stLOumFffAXO/BsAqqxqta+5dH/EbpxxRlUd2pwvgYxFPOxbPk0UsYhGLeOmE6F4R0Oc9tre3WVtbY/OGt7HqlkCHoBVMT0O1bkyEpdxYF+MCJj1jWTT+GT5CES0TmpWQVRi2s4oxPsQynKpmTl5WptNRDo1Zkl2A7Jwt1z8E+RJMBbYyY24cxV5VDRe3YTyD4QqsHQUcbGzAzjaNWYACn2XGh5iw5YX7V4ecHRaMY+RyVVKpMvA9BlkP75R+b0aWBYpezmBlYBOFEKG2Km+NHo2OqgqU09omAMn0LqDMFIIqMqtx0ySV0BPIhDpEpqWto3Fe8dQkbgOOCt9J6AVCFMraEZLxuEiTiG0qijqJZrrJBxusmoy17lkO9q4nHDSU/WKjU2XVftJMZLoTkoZavb9Fbt863W21dV+d9SyhaknKmjkbZP9RP3k7v7gQaKvZu7/I/NglSetodjuav5qTJ6/nO/7bb+NNb7yDtcNw/U1mGD7azpjsmgO4D4JEob9WsHx0gPhObVs6Xd05a1S7RUKYMzmcGCCS+QYas5d39mpke8UZWBJqe486F/Nq8cwkRSWJndH4hzSgSFnDZGoMD5+sf2JMt3uD+QVbtvDWpo31irvv3mF9fcbHP/xe/vD3fp3pZBuN5yFuoZqZrg9C0BlBp6ARqUNrTDK/Fyq7DrQBtqIlsiUHEaLURDHKikhm12AMEAJzESXFU5AxRPCEzBMzD1oRq000zgzwYJnVlQH/3Xe8jW/+htcwmZZ843f8U7a2tlhdXX2GrqsXbzTPlIu8nEMs4Rig1JScp2aT5n43GKKPY9C575v+ogFPS5QSIcOznO55C+sJ7He37wcInop1Si4CpHV6gO/0F4HGbyQyRalxDMlYRRBqRkTG+/oou4MuoPwYNf+RyIzIVoKbm7hhAH/jlfDOYzDtwe4SRAfHyoIjVUFeKquXA71JpNrKqS700SDtFfhJav4PptxN4H+Q4/x9uZ41iUzlcSo2+IDCjwZpjZiVxpHEElxTItsEIrBCxhKeCmWb6kXvV7GIq8df/Iun+egSnP6Fmw78/ui7K7KywsXIoXdmHP+WgmJZOKywDJwD/lhgHQzhmFnfvtSHIp9LCTa9awVXyw8+v3EK+B3gcTgxhht3IOw8ymMf+37WH/q3nDj5dbz+TT/EYOlG7v/CP+f+L/zU8+7pcVD84+8/xP/7RzcXzxTmz5M/iSEi9AY9siyxSVOS2zuPc74FE8D8NXzL2shw3iGJ3bFH3ih5djjnCCFSl8a6cM7hG5mkxO5o/NNg73sMYY8fBkAdAjEYG0JStj3Gju9FSthHjYS0fhdosMR+c+TzY5IWiNmT7rf9dKSaYpIy7R5ng5M0DBNUk3F5YsE3VTrNlqXrZxKJdUg+hNK2v+tt0rBpqrqirqvO+WjOTRrteJMGm/ulsJe94eQKYKsBrIQG5Nr7fTeV0IIVDeih+75nft1kWWbnq5UeowVquiyT5pw3c9Zmm6pKVVVsb21TzUr63jHMDIDbqSLTrmngIl5QsXie/Ml+nixiEYtYxDMV1/I8eUpMj+c0vCMili5pvBpQk3pxzSBWkqyUzLVqmrLvNpfcDCI7tmYCbcpVa1q6QrM+aVDpDSxoM7Ld/HSTNY0psdkMAqVZX8HZoG2qgY1Ysa5wsXacn8W5KJPMB3GqjW5rQNUEiGycFxEXiGpeCDFJVoUYEuhhA+GgUAfzmZCqRqpkjpBYMSFE6hBb0CPGpqLQBoWBSFAhImjHXLxWSx5Lp7qoOQ3daNQbmm9lfpafsBLz2Ul9HVwRdGUt0X5gwkL2fB/3TW/orDN/n6e9m+vt4HY8WTu/uHCAoQEOh2soCDhUHNL8SuIgH0K+RNFbZjA8zNLyUVZWhbXDQp6D84LLEy0/OlDwRRLmiZ3brFvg1733mH/WFAJ2i7WaOzLGOZjRbELTAhrnbA+wW1XShaVu/q5pu7FZX+efdaWsWgP1ZgKoqYhPoCortja3WL884vKli6xfvkhV7jLolxS5CVWZTMFeoKqdorbH0DA87FporrtGkmH+aWyX33Oy2s/286N0H0I4B+5QoaxrxuWUSfliEEx5PqJhVsylqq68/1rhhc5ne8GGeUriSlCzAYv3sq2a/qBT8djZV3fLXQvOvSDt/v5EUDwBZYOSM1cRyRGMOVU4I0n2k31MLy8JrjShr8LASfGOQpq92L6LTs83U2FLjdkyxfgs68A5Imf37LXb/81jm5rtA/xCFvEiid4RvNqgUTGCbASYrV+xqF+6kWwJsr+jxDdA/DOYPNUfAR+Dy4FW09B5OD41QLzIYOBJTlcpHCR8sO1jg5CE2fbG/rv2WsKz926F/WOZpxgKUpoVXLh13qLz6fXmv/CZVmJVxON8D+/6OPfCGo4P+vDVXw5vfSNc2tl8vpuziOcoGimo7g3UjHQac3HnfRqOJDDAG+jRjluUPUbkzrsW9HDJX6NhCdjYMCXcYwMmNNtpJKzSKKgdV5GkntjD6rAceXrvAByanmiNNFQDGHRMODrPZCzpngZ13dy++Yt0CqKaKV+7TgI3VHEYQ8J1wIhWkouIxkbk1vzcUMFJ48kxHw0byEAaqDb/6LapWXzOimkAAiSNI5pBizbHPgcurgCg2jHQ3p007ZDOfubXRhrb6lw+q3tGVdL5b4ZB7YC5WaY93Pa8AiYXTOf3TtdFTFLA5nXSKA8oQZVRHRjVLzy23CIWsYhFLGIRi3j+4oU1y+pGv8flyQ7nth9DQ8VS2KUfpxTqWemVZN7jpIfLhzaSqicQSzuiZhRaRmOA2DQZqCAP0G+SXjVkKSWfJZMC3wd/XSpPXzaz8yLCMFVzawU7lRmmlyOIUygL2K1AMttfVqB5Tji0TCgyLu5u8oXti2xo5KJ6JrUQVKmS6Zy6CvUBJ5FZWeKlppjUVNOQqL8VosFMl6MQVSiDMK3E5HvKGqkDUaEMNhGQGJEEatSIWZlEqOpoNiStud0cz6lUKdW+V2kmGZiXQEqXN5JNzRk0K945wLHfhvOgtOILP7pJxvknTxzdo+8AbG3sQeIO+P6gMLDi6tvshrE7xBVk+SrOFQx7PZZ7fcR7pOhDluMEMkn6vsUJpHeMtZUBW5ce54G7lMFqwelzS2S5g7pAQkavyDl6dIVBP0fUEqQkLNDJPEGk0NrhCAZyZMkYPMkftxMnVQiVSUw1LBBNr4jhiXUyGEfS95okq2JihySwRL2BMGBdQQN4CEkNqsEno20vtmiLLVvPbL2Ljz7OR/7wV3j4kYe5eO4cXjYgq9BYUZV274vWdq2r3W+2T5uMOSJeggGyzb2NA3p2/4hHXA5oMr6v0q9sjA+nzd2kyREipl5qbBPH6NHKp4MEkRyn4JgRKuWz95yh1EhdLRLLB4XDExlTcQkTsxsRMQMaS7MIjgGOPqAEppisVBd4AkcGyZy88efQJOLXyFQZXF+nrRZkHEnrzs3PgQRy1ChlAkxKIhWOgsYEXZITj+DT+h7hMHAdBTWee4DTBx7zVgW/fRY+swmv9fANheOwA11WdEkNvFSoc/icr3gfI0bMmW8GaNjV+Mfs8CM8ToGmc6c8hskLLeJPQHzJ/8bJAC+rDXR4qAcXM+AP/8crFr17CQqFW2YwOg2X32/XGKcwtKIDkm+dhgffD/0VqF4D4WbYkQQ6KPAYcD9oAbPXQH3S9r8fVrOe1u7MGpOPerKnbAZcB6yl9Zo78wIGUDydGmE3g5XPwvBB9oGBFmc+908Zb3wOgO3t+7jvnp8gz1dYv/wpVF84fXdVwRcegI0tWknKRby0wznH8soy/UHfiqsSA6IBC0Qan440Lk1zB+e9gRnsTaY7l+SSnJ+blnfkllrAv/XXiMmDMCIqbWFWO/7W+Ui8larS+audtNAAJPM2dotq2lAbj3rn0t8dRoZV19HAMMhckmue0LflmvPRlbXqxh7mA4K42DIgmnOlqolxElswZ95gK0RDfUeWq20AgrXLpwK3GAMx+aU45ttvmBQNIGXH1JGqauStmnU65779bZG590dM21SMHdKY0LfslHlhUKiTtySCE9+CQ6EZ5As4Mek05x0ClFVFXQViDMymM+o6dFqk82KoEKnrF07fuYhFLGIRi1jEIl5Y8YIFPbSfsz2Z8PDIQI+jwAqwJJ5ebfIhiOLyXsqM7hro0S3bqxzMEujR6Jv2K/BlYnRIMiEI9hKslN0fMZaH71n5YV7DYJI8sysYT1LGdmKgRzWEcdLKic620e8TjxylHvbZ9MIj4xGboWamShVNZ7au02DdB5PaIeJ1htNA4WviNOBFEFfhpLIEaBrrzjRjEnMDMKYVUiZQpAE90qGpQFmmqszkY9CAFS6NwxtpoCrCrE3W7k8YWAouJtCj8eQwC9056PHSGXY+VaimOStXiy6Aca0ZhGadZpr2ROtZykakT5av4rM+S0urHF05hM9yZGkF6fXxIvS8UdelN0B6Q4qsx87mBR4dj8iWliguHcZnOcv5gKHvs7LS59DKAD/MbfLSzFHSq5GfiglIkEY2qjBpqVTYtueoUJOvqhMZKWZ2HcbEIDEdZloSVXOtxiSZhUtnY24/kCZWtk7jLdK0TxvWiM7biRpYUk8hzmD93AU++8nf4u57PkWRLVNkazgvhKDUakbjVluvqCZ7cjXmlU3DAt6lJLkzRogtZ4CUugyVLO18ijRU/gQlWjI7T1ee3WGWEJ/ZOtHbC5uo2u8NTitCHXjgoUuc3yxNNmERB4QnsEvJBfZ76NjToBFmKhLo2YAizRIgqcdrfF2ESKQith4VDYBiUKBtNydjNX2bpXVDksqK6e//f3t/Hm1Jdtd3op+9d0Scc+69OVRmzaoqqTRACSRhISEhYR7th1aDocFgN270hC0PDzdGLAv7tQ3PLOzV7cbimV5+D7tpvLAXeK0GGxszGNRgWZbEICNVSaWxJNWgUs1VOecdzxARe//eH7+9I+LcvFmVVWQp773a31wnz7lxIuLEjmHviN/39/t+W9QQvY7HvKXvhS3Jj6TgSJTHuh3DV1GywHKKy5Ee2y18+KxeU/8dhj9nLDdamN8SqG8SrZIyev3d7zy/YnwU4uqRztLPMOWzTDEs945ZPOIrA+Zrf4iTNbw63k9cWIWzY/YkPb40gZdN4YYGzp2G9S1dhgYiz6hDloHt07B9EUZHYOV6GN0BOwxIj1PAJ0EmUN8E3HyZ7UMrRCqU8Kh57lHcoWqlt6A3w6M4vUGJjxcC08DqQ3Diw3uTHmce/uUuMDvdeYzHHnkiJgLsrxSR1sOjT8BjT3abm3HIYaxhZXWFo8eP4n2gaZousC3x2aAL9w8y+p3rKzisXZZJIhEdiexY8rSQmMziNVu/Iz2S1JReEz5cSibovKFbV3cTmLJRhtUGA1mmrhoitbnbPmIw3w5Ij0hqROpDn5WGy5sow6X3ZT4RNuyuhpDBcgYjfUWIcw5nnVbVt21XtdK9SJ8tODpFgEQoDP05ksm797bzRHHWYY1VeayY8WPsHhJjZrivTGd0HtL+NcNjaXtj+Eg0Kfmj3zun5EW/7dGtLEh8DEqkip5bKtNlo+m9pYjnUtO0+OBpm5ad6ZR6kauYMzIyMjIyMp4/9i3pYdqaEZ7jpUOccATLCobxqMStrGAKRzMzzBZbKu/kZ0iYU4ijlDLeeAl2In20P8RwTXJMC/Gm1BOjpUKnOyUGaq/vTYDaRBktC2I1+ChV3NqqjwCjEdZ52/D0bIttmXOmntEgeAOtCG16gAhR0zWGuMxg21qEug2a9WJCF2hKGY5tLOuVmL2espr8IAEoPSM06PQgfUZ+gM58OSmCDb9LGD5mGGLJNr1jBCQxlv0Q/EoZWPsreKB4Ids0XGb5SHSPbPHBzkiJYaRB8yh/1vqWRdNig8EUC4xAYQ0kPV8xmCCIa5jZESY0FKbBl2CLAlOW+LIEu8b29hquKClHlnLVkhL9RIgm9oNLYHApEHrSIWXVWavTjFVpE2MHCXoDQmLYTIn/2Rgoc9H7g+HvEYm+uF/Ss2+qDklEivdxewO0TcvZJ59i/fRZvvSl+5lP51isPqSFhiQd1SsM98Fy0xk+p200hDRNLCbqZnXZchIwKZjdRZH6yimlFJMjw14STIbhTumEkYyuv24WTHemhByh2hNataHHb+g7YWIENhEZnil0/h0NJtaz6RmQ6poMSfZuWBU2lMaSrkeF/oQeEl29TEbaHq3oUJJj99ZL3LpAy1m2eYpnOEXNOWbP0W59XQA+K8K5AItaaHbopN3EwGNzWMjl+/H92KtmvPg48vLvZ/ry7yWcvRcpbkLK2wi26NRW7I8IpY+JFIW+ynpGs/4YWzvr1GsnKdwdiHP4jafwW6dUWvHYS2F0VGWvboCwAjsLWH8Stkbgj6OsxBpwC9hR9PQA6hnsrMeqvSP6EqNXZu+o9dwIaOHJZvyp5NAzv8LlqYF1+rISAdluqJ96gump3fRhhOy+wsK+JhX287ZlXB0453BFQVEUuEKzRUwM5gcragKe7umWyAT93PtCxBUO7gsxvQzVMukROo8N732U9pXOiDzdJ0mcV2LZRiqQ6E5M6e/6dZt23RubATHAwKtiV/UFRCmqJF9lbd++AXGTEnCGl8WSOXkkaIakBya1X6WeiPtC4jypKen3ldiId4Kx7RJEl4VIYsTPiahJv59uC5cIDd0IG0ufjbW6jtiSREyk6gyXbrRN2o2mE1DoKkbibWyq7LGD35P4XJvuV7ttiNuh0sngvcd7TRazkSgxVokaY2CxqGnqhtZ7JUwyMjIyMjIyMl4A9i3pwfwCN9ia1WMTEKGgwlFg11Yob7oBipILT53m9Nkv4YPHS4sQWGWF6811lNaxcrxhfKxVR+XNmboYswL1GoiD1kYDdNFUbwakh7Ew92AKJTuamBJbFJpCHqIYghFwk+iqjEZUm5pzfsbvPX2WR5znMbFsGUtthbk0LFqPDYGibTASaAzMWw0ajCVQAI0PzHyjpcJBsJHM8NYSYsDaBi3bWIRAs5vUGHA7XeBYLg2jIuCkJzFSSHdwu979ra4G/QN7WkfKqLy2t6QGDVk4OimzfRWiG0bzhxg8Je65jN/1fWpnNMhwAjicHMXJETCC9w1earanBl8X+hC3M4WyoLSWSelwsSTfOEdZFvjr1plMxpTFiPH6EayzVJOGYtRyZO1GinLMsQ3LyRtH3HJkgisMISgfaCTWmZh+85K1TSIZFq0+Ao1FrbcxYEsoqxgKjg9QVnopK+Ill6o0jIFypJegDHaNdXpJQuQkg5J8tY/XQQvSxmlR5s14sB62N3f4T//p1/mjD/1fzHa2uXjuImN7FC+eutkCLJUd4SgQ4/E0+kArLsociW4jBqGg9prxV8T9odekZi5aPIXRK0Ul4xwBS4hXlqHFMI/H2UYBpUDojr3DUAGCkVhrZbQr8yawub3J1s52L4uQsYSWLTyLSDZY1LFCq2scqxgsnikLnoZYgSEELBMKJvH77UiKRBgwUkXZKYsZlBqGJZ8NPaFtVx+nxIaJRIYSXgU2Hl+t5oiBjM7oXEhG53/Ew/wrvsA5Wp5g84rafx/CP8EzEkNYF8LO8vcXWtjORUIZu/CK27+bhx/+D2xPn6K94y8wf8UP0hZH1BuphZHASR+rLDyMami2znD+c7/AqVN/THHbt3LktT8C1RG2Hvotdh7+NTj2CvhTPwo3vB5uB74Z2gKefgDOfxbaW2D+VrQM4059ryy8/BjcBJw9Aw98FKY7wOuB1+kt2YyesLiSXrAFngbOscSxM+cKkzg2gbvRko5WX2Fnm40/+PfsfPI/XskaMjKuOcaTCUeOH6UoCsrRCEETW+xIvTu8b/Ftqj7cRXgA2FS5oOsLQb0dQjIQT6RFkqcSCN4T2jZWy8bAPnQBdQZSUaniwQwzXER6Pw3itpgUhO+D/rqtA1LD2J4kSUTIsCIlvdt++bQdNt43dyREJCdCq/KWPoTOwHxJFird8y5JScWqUFEJYWPojN8Ruv2RvBuTgbmE5d6tMxUXicdI942LcmO2a4ddaq+xlhBUDjX4QCfhaQy2shgXty/u7uAD4kNPUgXBFZaqKjHG4qz6togIvlVZNOfUqBwGklrpGAOz2YzpdBql07oD0u33oYRZrmDOyMjIyMjIeKHYv6RHu2BkPKMyZpxQASWMVmBylFCW1O4M236L1vtObgkqjqCp4N6BjD3GtTCdIW2DkSJGQokPqen2V7XZ9U4d/dy6ePPtIjmSzIxTOnkR72irgROzQAjMQ8MT7RZfpOZCMaYdreAN+BDwQXVbnXiMSCcPZONWWCIPE1vkgr4E3aRgoBAoI6uRQmKhb0VvlE5fyTG8VR4m0zP4bvgMYXd9p/nQ/eeUt/xcbhNfPsTjsw9qTvbGs+0lc5nv95qWzsO4WMwQtzJCaBGpEfE0bYMJdSyPCNDWeOewvsDZvoTdVwWziUXsgqodIU2Ls4bGz3F+gTGWrZ0ZzrWsHdNzPklRdVll+qzUJwEaJRqSl0YbCYiyUPLBGN2sjuDon3M7ci7tFumfpTuCIxEbpN9NWcdGL1Mff8+HnjQJIcpjBTBeCI0wny144olH+ex9H8diGNsxzpTxOm3jw2qBMUWXa68Z/moKn64FJWcMPj4hupjlaEiNUWE4I70zTjKL7oUcJBIfDILng4fbSD2a7oqLD8Gx31Ht4+c6z75yEbpKj3ThuEg89KSFelVMu4BFWlKJEhePf5QwS1mXSzbISd4q+QIN1yNI1PTpK0JsXHcKjaR1FXE9/TaoU4gnAE+zyb1c4MLz6OvW4wtEmeqsFJFxGVSjk9z1+v+Zl33VD3Lx7N24rUfh/CeQ696Ilxaf+mTRpIxxCIxEGANjgflih/ri/WydvZvVIy9lramx1jPbegLOflyTTOotXckq8BLtQ2f3wewplNdPFllrYNb0ZvWIwEmB+RTcaWALeCXdZfZ8w2KCEiXPXiu1x0LpvQbOAv/jcppIw6X+ZhkZ+xWucIzGY5Ulcn2Wf+dVQUDC4H5kINU0+LNLUgGWki/Us6OXohKU9PBtX+2u/UmqVJCOJIl/df4c/UqX25BG0N2kx7DKw8SKhOF6TKyuSBWXXeVC8q0YtGNIpCwRMpG0UWmqnsBJ1ROGvtLBJr3WKLk1lKnqTM+NqDxq9zuBgFVJVEO3bNqmbncMyJalipZh1Qe9BFlHLg1ktIzt1ytxcYnrSW0KIeB9ULIo7StrunuWEOfRqpnuLOkec9Jvtd5TL+qcqJORkZGRkZHxomLfkh6Pbm9wHQEnDc4YxmVB5QrsvMGtb0PhWG0DN6+sEETw5YjgCibuCGujG3HGshNOsX5hndC2NLNAaISR1IxlG0fBSnWU8bgCGpAF4KEaK7ESgJ0GFgv16JiMlOxoBWlrDbaGAsQQwoK2acAaXGFwa2u0fsb2YouLAXYQmuD1gTwEbAiYEGilJw7SDWxN74/gYyC4FI0BpJtJEZW/WsT7xKGcwzDMltaZqIDhtDRvzP/pQu5hMN8uOmhALD2XfEQiqRwmhvn0sUmlWfotuNpIW/hi0TDD4GZ6AkvVJS2XVpdYYEySzjGd+fGsC5wuR1CeC0OqCX3CjBJtQea0YmL2W4sJgjFKgBixWtUUfSiID7ViHF4spvXUi5mGVG1LsAFnHZUdURUTvD+CocBawUXSwRW9ZFR3Dou22MVn1bZV1bgAFE4feMrCaFGUGbRGIoHBgDShl2RLXhw2TkukoI+kixet2oD+yPvQy1t1EnAthO1AqIUnnrif+++/h/WL53jysQcZF1UnwdCKNqq0Lj4Gx5KTTgBFA9AhHk0xkciIFVh6PEyUopPBEU4G5RJpD70yk160/p08PVwMgPsByaEVTMlLIu0nE88B/e388Hg5BOYEPBKp5e5BPBIZ0slNlfGIqNSUZQXHKmAIbNNZaabzi5bAHIPDRSIFWoKKGmIZxQoOvVICHksZ158IktQvJpmtBh9FD0GwjDmD8BGmPIPwx8yY52Od8SLB+znnT/8RSGBn+1EWM3W4aAxMrcpsOmBVwG0/zuYz/xU3v0CJJmQ0szMsth8HYCXArS0UZYW/8S1sUiOrL4HVW5eCj7aEE3fCkQLmJ+D8io6o16M2Hm4O08fgoQuwXkP9KnT5W1gOhr7YCKiFzjMwugg3nLqco05Gxv6FtZZqVGk2flnQtg0heKx3nWeDi2bXyVwclsmMFM7ujMRJUlZAl85BTwSIdJJWErRyQOfsg/VmeDGbfpROxEX3t9XRWafHZWNFg0nEwIDs6O6XUvsTGUAiPQYJN3E7jTExwK9ebs6pibv3gcVsjvehIwyIVR/p3mCYOLEknzUgZRi0xzrLaDTCOdsRNel7iXqx+luBVPFirWMymVCVJW3bMp/PO+IlyYT51hNC0EoLZzvvD2u1qqRihIhgnXppdL+5i+ASDCEyIFVVMUQIwmIxp23aripDRKI/h4YZWt/ifejOEYBmUS/tp4yMjIyMjIyMFwP7lvR4aP0C1xnDBKG0jpMrI9ZGFcWsZhzWscZy1HuOra2pVvTKMaQaY8dHKI/eiBc4/+gFnnpiizYEpqJhpSNSc5KWkSu5cXWNanWEEYkaODWsrGFWj0EboDkPsymMDBx1UBTIRiDM5iAamjIUeF8zrxfgDOPJcdzoKG3jWPcXOFdDLYGFV1NbfIvzLSGG2YQYKEZvtpOsgkc3QVBzzWSwmfRih1JUQ6vrIdI0R+cZ2r3vJjhgOQSfkDSyw2D+Ibmy1zJ9sH+MNUKJWqA3sqC3Sb/axITw4tqoD/de2hsFKkheoUculf8nJEHyCkOFowICnvMIW/RH+koJj3Sk474TC17PHM8UzxwbLIWJD63UiJmp5hMWEyJpU+gDU5CCQIG0jvnU4JsaR0HDAmtLVt0tmPIG2vF1GAqKSHgUBbhSqylstL1JUmoVWlkkAXwDizouM1YTyKqEUbF8vnYm6KmZ9KSGjw/QifRoRcmVjhRMp1K8VnzkgQzR/Dxui3gIC8GvB9qp5wsf/zi/8h/+CRsbZ7G+ZFKM8SGwaFu8eJyByinpQXCadScOMZalK9AImEQLGlKvEDA0mP6BGCLl4ePnZIhtOtojUOC7wLuanxtqTKosiHJLoIfeEE+d0JNxKYiecSkCOyR3JNP1Q5q9qlUgqf5GiUzHCpYKywTHEcDQsr7H/m0JTCPpMcZQxGNVE2iwVDgm8QjukEzPHSukyjTp3J0Vamau2+RYxbHCKRb8Eht8jDmLSJ1mZLwY8O2UU0/8Dmee+s+IeHyrWmi1ga2YRVEARwLU619k/b7/Hb/xABDvL4IneJWBWwtwZwPVaMTGbd/OUy/7M2AcFCtLv1lUcOur4bZXwQULO5WODS8B3iCwmMHHPg2PfAHCK6H9M8AJiF3llw8t8BBwN4xn8PILmfTIOHhwzrG6tkpZVUr713Ws7lDjazMwlNbM/HjvEQ3NkZ4ACaE3ye58JdKNG3RJ/iEF4aOnhRHpKhckVi/Yzhiu39YkSUVar1GpqGQgbqM5dqQ4uqyaTtbKDsiZEJe3tvutZFoedlWkINC2nqbRRDdXOGzhaOqGzc1Nmnq5nmuYDLEXOgmnPVAUejyKsogyWgaMpSgKrHVdUk4QwUXyxDnH0SNHWFtbY75YsLm5Sdu2nVeGj5UUTdOob4sUWGspS+K+c5RlCQZG1YjJeIwAs+mMuq4H2wzirErQGkNRljjraJqG2WxO27ZMt6dsb+/0/ibIMoGV9k86jv3EjIyMjIyMjIwXFfuW9KhFqGNAMIhlHqDwQkFAao8zgUI8ZbwxdaYCO8GaqgtjGdHQYjBGbyINOGMxpsDYgmCFVlpEWkLU4jHSYkODSSnmErDisaLRXRHNFNZbORfvwVuMtEhy+oslvx0pELN+UgaRZu4S1dt70mNYTTGsVxgSHFxm2u5n/l0x5O7zMGx+pdhNbDz3PeqwekF2/b3XGg8qhEvbeLl5np0men6/OczoH1JWSqCYaDdvItnUzZU0kMWQNKP0T0FCiwSLYDujRXAYU2JN9AUZmC4mY/L0bCpo/F/Qpg6UCeIDanow7atDzHDTpd8zKeNuzz3ZX5YqrxW3I/32JVRaImBaoa4bNjc2mG8s2Lhwge2NdXa2tpgUa4yKotuTS/l30pMI6YF2dz2FdP+bpaVT5uPl6i+kn3PXN7oOSQ/weyyBqJeIueQKz3g29BJhSVZKpypkaT71/BhHEqQ/it353i2X1pUIMT8gqLSn7k3N+z4wjSMq7pGuUxvnCnGZ/tfUhcQyxhEIzHaJ+VTAUWxnxgyGZ5634E9GBoDg2+ku/xqHb3eYz06Bn6rip4EwO4VfnMMvLuy9KpPOfAvlKlSry51og8pUAWEEfqJfr+iilAtVw/JbUE/VxJwWzQQZo+Wx2+jNzYgXflfb0medVHFdl+tSG2AH7ALGWSYu46AjmVNDfCgRjAg+EQe7/TXSDVq670oSSVHqKd2sJfPpxGMkf4YlOaPhTV8nyZQKHeKdmLn0QkzyU70/Rlwwvczeyy01O7Vd1B8xJE8OekJH/UxisoqJroGtJ/ieILlSpAqYveC9ofUeYw3BBKxYjNFkGufoK05Eb7BTJUUiakSGd7/De5nhvYr2xB0pFeW7uu8Hx7pvW3+89HnBYq3uLyVX0itc4ruRE3AyMjIyMjIy9gP2L+lRVMzsiNaNsBjmraVoGozxFNZjMIyZMpYdqmKVE+YYK+1NMJtjNs9ipOZkM2dyZIwYQ1uNCNZRlmPGo1UIUG9uc2b9cWrxbMmClkA1bRkVmxgxFFOLFcOoXnBk4wKFMRi/jim2NRPdz0gitqPWY6zD+lUkTDDSMEFYRW/8piHEEJhqwa+KGnKOUFuR1sICeDrAbBAAhr7aYjgtkR6XhusUSdLKsPzcnqY10OUW71Upkn7LD159uHB5O+SSW1tBVbJrggh1DPyGJaeRF4LUqrRlX04Mf3N4ZKbokdtd5ZG+30LJMYvvrKmHVSFX+lCQQvo9DA5jogST9RirltiFCTFjrsWaRXwg1ACvDRYfYmDV60NpcIVqkjDClmsUo5KiGDNZWWFt7Qgrq2uUkxF2XCI46hmEJlZhxG3pOpIAi/jMG1StSQ3LSyU96hZmCyVBqkqVtoJXzw+JfKGNnIy1+vKJ2DC6S4VYRTJX4qOM6wctuug0paOp+WynZbrZcu7UKT7yn9/H048+wlOnHkKaipE9hhGhaWeAoTAOiWSm9+lBLyDSdFQEJEpCt9kbvaaDGMSU8XnfY2LlURKuGp5DqcYrdORGPKJRUFnEQlcxkL5NJEjPKAUJ3fcSz7MrP6e+smAY4RhH/w4z2K9DAsQTqLE4LNdTcD3CFM86WrmhvaaJRuQqT1ZF43GD0NBwDonrgUDLdvyczMstgqdlO/7iTuwToK/46GUsAmMsDS/B8UPcwFngQ2zy61xkZ9AnvIKC/4EVbusq0gz/T85/GfZsxlcEJLB++r/SNtvgKuZG7yP8ztOEKH+1F3YMPBH76I3hTUn6/BTwAWjX4Omvg4074QjwpwQmHi48Avd8HhZTOHcOVRhMA44HvohWXqwBr0VvrF4IzgOfRgmUrwLuYu875NSNt1DWcCKTHhkHECEE5rMZTdN0clAQqyqikbdtLH31aLyvGBAMnZ+E9IbTEpJp+fLvxXh6/Ny7WnXkhEmeG7abNjQiHyZ4GLTqwrnhBZqktfRH1LfC9tuEdNuIqL8iBpq6YT6b44On9xTpA/bJwwKhMzdPBMTVhB6POfXCdoSPAZXeMjZuh+/ab4zBFQUhCFvbW4QgtL5dOgYiolUZziW6Q8kd72nbFglC27YECTRNo/tEhNl0xqKu8a2nXiz66pf429babj+00bS8aXJHmJGRkZGRkbE/sW9JD+9KGjfGF6sgsDOvkSa5V+iN3yozVpkxKSpWRitMzAmkPQfNJkZmHCkajk5KjaxOVlWTZ7wGq9fh25bT2xts7JxjBpxDQ9cT5qywgcVRcZSCMattw6jVMmZX7GCLecwK0pt4J+q7YcQhoY6VH1qFMgbmScuWniCoDNwk+pw+NzCzGj4/HS4N5wu9cFMYvA8S6S/Bcs75pXnoaZ2GXv5qiGGVSXolq7/hb+6dqS4kl9yrS08MSY8Xy7fj2bA7q6tv5+Xnn3dz/sm39tI1WFR+wLqAsYIlYEXJD2s81rR9FpzEGpBQqIeGb6FtIBTQVhinVs6uLHBlSTUaMR6PqUYjXFliywLB0S5APCSvbWNU0sqgkmytTxlhOo9xeglaC/MapnNwsbypNEqepOdHMVEoynbWI6ngQpEMylto6iixZaEaDXZy6D9KgHoR2NluOXfmIp/+9Ed58L5P4EXbXZoVgkwJokFpaxwYiw+CDz62I1XQ9O2E/oGdZFpJcrBRdkaQS67Dy1GEgj7sJ51nJT1i5U2Xq9dffSlDUZcPJMGmXO1xeRhKLBMK1gBDoKavpkg9mfprCILlGJYbCZzFcwY1ONde03QEhou1F0pvN5ynZXPpd5UASZ4fRzCM6clPfZdoe7zXFa7b4zlJxbdxBKFkh8B7WWdnMOdNOL6DCV8bvUIy6ZFxdSFMN+5nunH/81pqYeF8lEacJXukRHpY4AJwEcIRuPASuHAnvAx4WYAbA3z0NHzxs2qvRkEvZ6WZFHAK+CwqdfUyXjjpsQXcj5IfR1Di43KIZbnOw1p2LM84gAgh0NQNrW+jx4PtiIcUdO+NzPv/U8DbJNNtIJX2iggh+jl09yKmL+ToKjC6EUq63+x+2yafjZ700HsjunUaA4UrcIWDAb8SQsCH0JEF1lgkOnl15cfpfi3ePzVNw/bOdlfNca0gIpfIZT0XrNXq0tl8Fv0z3BK7ZFAZK1sU+OBpU8VK9N0I3rNY1AQftPAjHu9FvehksXa2p1ed4MnIyMjIyMjI+HJi35IeIRQEa4kewXrbahqQZAptaLDMsAQJXPQXaZsRxq9jmx2QBSYsMLbF2cBY5hS2wYWS0rYQhEpKVotVSmOQwtEYw8gaRs6qKbAfQXC0wXOurjHiKaSlDGAESjFqW2sdwanuqnEBwzaGBRO8khpYipg93uLxeBbos/UUDZvPBRaydwg9ERMyeCXigsE0WK7uGMSAu/hAIKlAONaM08+FwVlD8DFrh16gJRmrp/z00OeaxylfTuJh2KLDn82eTLR1f0ezbOjO/3RUDQYTTKz66LPJ9emyjQ+TDpN0jX1QogSLcyOcKyhcRWErimJEUY0pyjG2LDGFxTiDEAi+xQdHG08k47rkQNr4YBtMrLCgP081q44lWSx96CTJM2N2FyiIVoAMswNBSRUTlOyQGDgLRKIlQL1QA3WkxYSatm144tFHeexLT3D2mafY2jqLl5oQZe0kusyEJE+UjMi7IxArOkxQ+47B0QkkE+qkdx0w3ZUyrGrSY9FfM8OIX39Vp3/a4FTh4Ze+73dPbzi5THR8ZVwbLwRqHh6Zuq6Xq+O0Kl5vLl4/hsAmnorABoFFRz70xyJ97t2RlFgZkYiR5TPGkszRdV273ZLSOnRrUyUJRvBmjhWPkYLe72MZFwncw4I3cfpq77rnhbdxHUTiSLF8YW8SeIia9eclsphxkFC6Fa5f+ypWRtcjx15LXY7xFup0+Q1vUuASrnYGPGlgx8L56yC8PE5cj+9DDG+MngUFmmRSxlXsANKipMsW8Ax9Jsg68EhcaLcy5aKFhx+Bxx9jsRCe2oa/9k3v48HT7+Pjj/0i82b9ivdTRsY1Q7wGlyQyJf7XVXCkOlTplkmVEmLAmrC0Ov0wTIwyg0l91Ub6qiM/rHYKap7u+uqPOH+fEMLgpjHSJqav4Fj25IBgtSKjqeuuWmMo1QRa6SHhYN4zqVF5S2MM1hi8c4OjpccuEUYhJvKAynNZZ5EQaOpW980gOycRHr4jsDIyMjIyMjIyDi72L+nhKwKlkg8EAjXBzTChwgY1mp1RsEOFE892/SUqeRJpG8J8rvIyRkP2EwO3mhmrxrCyCkfrNSyWo36V1ZFFyoJb11aQosCMHHZc4kNgezZlXi9Yn015/OIO87Zm7AOjoCGy68UxwVIVEyYrx3DWMCq2qNigkMBJGm4GPI6L0Yq8EU8jKpYyRcVo2qCvANHidhkOfVAfVl8Mb0OTjbIbvIYW2el76AmUl5sRL7cTKmdZXXFUpWG+qNnenuGDp8ZT07JFEqpKv9uXOSd8+W6JU0sO+014ojYcpdUALNJEiSVLQYXFxbC6V1moUGCkwBqHs6MoEdCo6Dhg7FizwkSQVgP9o3LMymiMcyXj0VHKakw1Ocpk7TpcNaFcnWDHBaYySGgJTU3bOBZR2qootGJjiYyLFR0C3QkYghaUGCJZsbuEyIBNpUbJlDwo6QFokKzQ5ZpWqzwENS3H6bXDQte9s6WyV9LMCbOzLGZbfPiDv84f/P57WcwWTNdntEHL+SVEgs+oiTiYTkoruT7ozw+MQyJ8lCvTCi71X9Aw9wJ9EK9JRtQiJdJ5NSQZpeGVqlJnIoLvdJkT3djLpiWCRpdL4vV98H1ZCC9jNxxrWCqSvJSwwLODZUTBGK3aUNcMgJYnaHkG4ry6/9VUnujZocReBegVa5lE4sRF8qMnKPsqEj3mWuGxLPmXvEEso2h0bvB2inc7GCkIbY1IScsOuyvPvkjL/zdKZl1L/FNeQWAKNCzJosQ98AUW/G+c55N7jnYZhwGroxt4450/yJ0nv5mHjx7j7pXr2CqhTdJUw27L7HqhPMQfWygMTF8B7c3AJvAR4OE9fvAKSI8V4BXAUVRR60tAuwA+AzyIdrkztHt9DDgbF0xdcSDqgi7g7t+BT/yfbPqWj3qoBGb1Rer22l9/GRlXAuUNUmWHideiXpAiSfwxJpekiytEmj/yIkL01LA2Zq4kssL0nm2YgWE40WM8VnxEMkSrO6ySHtE8HehsPtRQ3aocayQ11HzcQFBviUR4+NAH6kWEtmmZTqf4tu3WOUQnX3UAISIs5jX1ormUwBogJQ+lRAQTj0UvByaYucVsa/819F45qPsmIyMjIyMjIyNh35IeiF26IRMTNc5NiNlGGnhssZpTGnaY+ynBhy47xdBi8DTAcQIOKIoWv/CapSQOZytwJbaaQFlgxgVMKtrgWYSGlobQwI5pmdLSAI3AGMMCR4HF2ALnSpw1OBNwMtegMvqgPYphsPhIQMoJTyGh53K6GKpB7IoNXIIUSu0eWOhjC+lvtei1HKFgZCxHnGNUWKZNwMT9ucBTYvAIJZcapcO1Ca32ttKHGab7Z5eCpom0stiYre5F9MFRUia5HZxtDVqSAZjeUFtCrDUwlsKWOFfquy2xrsS5CleUWOcwTh9Ik0GlPlQKRgxWLnVYsem/mIyXVA5SItklD5x9k5cnxqoQga59oOvxqXTJ9LP7WP3R1NAswC8amq0dZjsbnDv9JE88/gXEQylrWEptjzrsxN/XKo8kRZ2yFPWZXEiG8HQPj8PajGENx6V1VcuB32GDd1/Jw/kuR3EmRH2wpTRk34XWMy5FXyGlSGbh0u1D7WVN570z41J6tz9n+kzWPl3dRIpar8FUWRIDPiSCbHhs+945XfF017AScRgh2AYTpBs1LIEKS0XoaJQdhIc7IcSri2rw+bmUu1/DStxLuh/7Shhtd03gGPZ5rTPjYMAYhzWOUXGE61bu5MZjr+X0JHqW7S5w2+umJ3LAjVHiA9CbqFX0JBzHaYMbJ4OS7eLoZRAZzNcR2TBBqz06j/IarfLYrQI3hY5XTJZdrdcqj3oGp56C85+jDQ0Xn/9uysjYJ+glpC6LXTdtu/06eq5kMA5G8qRbdSRWOtJjaFBu6HxErLGdfFYiLtL81hiCYWkET8+IifDoTb37oH3rW61auMbyVS8Wrh4pkcmNjIyMjIyMjMOJfUt6SDFFXEGwuolBLMIKQSxGlMwwHlw7Bgk07YI6eJX5iQ4VJsrNtKbggj3CtqkYhxHntnc0NNUuKHyDM4aq3cZZQzmvqOoREgJMt3H1nON1y6tsSVM6RkVBVRQaMGaMM446eNbnWwgea+ZYA9vecHMoWYkZ3k/LHESYStuFJYdExOXQBarjyw6mJxKkQitBxgZOOBhZKCyUziBimNcVTetikK/FIJykBdnBt4admWVeG5qmpZWaQKAg4NDg+CtIzhT99qTqjzlwEbr85+dqy/A9fd5r+lKoccDgDPfB7mWGoctEMYV9FQROW76HJACpGJ3oFBCPsSR5JYmZXERTRkvogqYG6yzOWTUCt6223wpEfWQbNCBvjcFG3V/rSnAjjCuxxRhXjnFuhLUlziiJV1iPNZ4ggTaEzm/DGGgaaKIElS303TmonD4n18SKDUlbGQ3MnVZ2mHgCC70/TgpkLYX7PZi4AmfAVXGdfvDADUgbmG/PmW62nHn6izz0ud9na+Msj3/pYZwUHcWYCIsQHc+tLXDG6rliPEGEYAJiVRvaSbIHT2JX8QyT5WtzKcArFmOq7pztv0vnYkodHrbUDN6H5Mnu81ewMf04tUXPLsFEkiXkB9hL0LJJ211d0HtsGAILUujdsYLg8dHDoycgQCKpYKkouA4TTdH1KDQxpN+ABV/MVJ2qdZg2ESkLknig0hzJDF2jwY4xJhrYe6ZAQEKjKnWiW2AQvo4VfpjrOEvgQ6xz35K7x9XHj2CRQpBC+P/Nn33elnW0yiMFmborDhBuwPMXqHjjgJr/3y7RLMo4aLCm4PYTb+b2E29hZXILo2N3sl7C1Gp/vWc3B/1NQIMaks8G31ngJcAd8e/U2Z4HPgFmAicsnHgz1Gtw9rjyFR1a4FHgGeUunrS66MWgYw6Cln68hV7Sajr4nVSI1wAXHoLHPwjT03DmY6ixVUbGQUWfAmCNiYbZ0HlsQE880BMVoiUekYyw/btN97dD8qP/LQSMNRRu4M+xdAOcCBDTkR5qkA519OnQHDglM5p5NOMe+IiEtEwcK0X6KpCMjIyMjIyMjIyvTOxf0qPciYSHQ3CImQCTGP1UA1hbVxg/IkjLopnRsKCgpKSM0jT6f2tKzhUnwa5i/Qy32MaKZyI1FQ2VCaz5ljIIK/WYtXaCCYLMphR1zXEKbrAjrLMU4zHFZExrCjbMCgtTsjW9wDPr56h9TRPDYiMst1JxpynYZsHnwgwfq036vOzY1svsgyEhIINpQ6V4i3purgKrBm4vYcXBamk4UlkkWHbCmEVbIbS0zAGvxJEsaIF6GokF6QOoyS90gvqDDn/bo/GB7fg+57mFp8wer+E6U1vS9PSIIqYnPQJ0cr5D8ifFUNI2aL2DzuGjieG1pz2GW61nwPKUlA2u+eFlmh4rnbCCWLoHviApS13PIussRWkxCNa2umaT9gaaJR4C1lmwFuMstigxxRiKElsq6VEUY5ypcKakMIbStriO9FACKSoVUNcqLeUsjEb6bq2SbkG0IiqE/viZSFqMolWBjVm/IXl0SIwjRTLDD2SyTCRXRmMoK51/MQxcAaENzDenbJ+f8eiDD/LB9/02Fy88TdNOseLi/tR9FiSRYYbCFDjr8MHjY958sIIvRH08vGCCHiMf6ah07IaxPA3rJpkrhxEXfyPl4g/9G/Z6CB+epcMzezgNPcbUsXLA4rsaMovrSI+M3Wi4SENBMiAvOIpjjUCNZwetHVzBsYrQEpgqgYGKyulxV2LEUFFyMwXH8GzRcjEuUxOoEevxoxpxAbsocG0k72nQnir5e/RXvKGgiBJcStCs62gSwIS+ZzQE3sAab+AmTuE5R/Oikx7/LyxSBMLkuUkPz0UurWKi669uRHg7IzwV6crJpMfBhzUFLz35zXzTq/4OplxlY1yxXsCO20V6wKU3AYn0eAD4Iv1w6YA3ocQH9B3uOWAdbAXXfyO84hthp4Sp24P0+CLwceVSHi+UbJcWQoOWffwZ4DUo4fEMWvkxJD0aoBY4dz989v+ArUd0Ycm9bMYBh+kJDWsHBEYkHYJo1YQZECHKV5i4jJZu2GRqPujyhxUkqerCRvkqNeDuoYk8g98xWnUbosyS923cDjqZq+3tHWbT2WU9J7q7/mt/85+RkZGRkZGRkXENsW9JD1ON9f45aGYrknTzBTFRNsMANvTl1hKfnk2MpsaSajGmy/gPBIK0qshvoxWxEaz3FI0gbYvxKiUirQcfKI3gjIYyxcRorTFYEawEyhAYi8TEen0AGBnHpBgxsgWrbeBoo5JXC/Q5vqUnC5r49xAWOlmpI4Vlzal/wKJVeaF0J29QwmOCKj8Uoi8XIj8k4EQrNwK99fIwPz3G0jWrPa4zkR528D4U1Cnj767EbZ+iZtaNNbQC2yIsdj1z7EV87CYw2OPzcJ/sfn4xu6b364rl9fS5+eyx/OWmXW300lPpYSwsbZvGg8xgO5PAFQPt5HR+RzLEACY9CKY6hCix1BENukesVdkR4xy4AmMd1pYYV2C7V4l1hT6UOoe10dTZOJUdMBbEqJ7zQFVpicgSDXCJqO9HG7S6w5h+Hp8Ut4JeqkmySmRQtRGXSTsnPddKJFJC9PwIAXzj8U3LbDrn4oVTXDi7zsX1U8xmWywWM0Q0yJx6AH0A7497EMGIXHqeDn5TRPuJbqnupNmLykvnXiItUvTs+eLSCo90ZvffSTd9ryUyeljGg72USEP1QDEdmWXQHi1RpVFrvK+9WrpKJcpVJWPyrppHdMxS1i/QVz30smem61V7ulcG60x/p98bGq2riFbDGp6bCdwZW2hwfGkPk/MhXsGY3kgdwMWe8tKz5/UY/iccaxiVt5PAxWMVk9ntlPVJhBrPNupR0gz2wVIKb7evUr837mltBGGbkzhWsYy4mxnv4Sy/lz0/DgScmzAaXU9VHsGt3EQzWoNiQu1U0qoxsV8ado/LtyA99NJTpBuObbScNJWXpm610bd2BostqIvYyw5PvTkqU9UABYQxevOyg960LOL7dlx/zJwogt5HSdPQ7JwjzHZg+ymoN6BdolUyMg4oJCbRsFRhYaK8lOkMv+PdaCrMGEhTLVV6dFJV/fcJyUR88Mv9exouRZAQaKP3hh9IFQeviTf6m6Gflis4MjIyMjIyMjIyngP7lvQoT7ycot0hzC9A8Nh6Bn6KmIpgjyI4cDNkvI2EgGmh8CXWjBAzJhhLYQLWajZ0YEYQjzEzQrGjocPS0biCIC3tFogExtSMxWsQtA1ICBwBbjKOkSkosZQlGnGdblI1gZPNnKOmIDhDXVhqZ3CjCePjN2OrCS9bP8PXnd1hFjwL9Pl7A1Vd2EblFs6yTA5MgOuAiTG85rpV7jqxxqL2PH1mh61pg0jAd1IrkagIMIoMyqIWWhs0UNXOonyL1kPYGBxPy6Vw3ghNfHT0klmOSKbQe5TsrshIucubVcHGqOSiCH8wb3iw0ejFML4RBr85DPnBsuF6J2G1R2AkVXUIGlAv4sOYjUFzDTGqybAdtHOZSNG/BmHKwYNYT8WYGKS7dMnldg3bkb7Td/31ioLKVBr0lwYfCbxEd3kMPm5lwKqojjFUVh9EnXVYC0EMC8BbDcIb2xNXzoMxAWPqaC5ZYVyFNY7CjXG2wlgHbgTGUU2OUo2PUhQV45XrqEYTqpUjrBxZxZUV1egIzh2hsKuMilVGxQSomC0MzkERpdSchcrEyo2AGp0H2F7ArNb5xvFYmXiQrYUyqCxW66GOB7RwKs1mjBqlW6PESYuSKYsFLGq9/JoafCtsnN1g/cwF1tfP8NG7/y8effxzbK2fZ2t+nta00atjhEiLhIW+4wiUgMGHgJUmPnlHH5Wg55M+kTd4WozYeMz0rApYxBjEVNoo8Yi03TnicPF8D11w/cpxuXl1erqOhnMlYnc/1DXtR4x5FSWbtJxF8LR2C2N2sDKmDNdhKGjZpOFC1yuosfkIy0okBhJZYPBsITR4tvFskiSrwECw2LlVHj4kH5CeoFLyomLo+QEBzxaeJLcFy54gFQVHMIwQGhY8QYXne9nhjVgsY0pO8N/z5LPuh5/hFTScoeE8Wh20iqGMbfbdFoLlBHBH3ApicrvBIn5By/lIHNX00nGpz09t9QMiJABD0p3BuyEww+C4Hc8P0/B7f7LDnfFlwtFjd/HyV/5VVldfij36Ku5bLYn8OBjYLMCnzIlIVnQ3A4mvHZbAQt+5Ceo4vh3nP83SQC4BzjwIO6e1MnAr2uB083i0KsShJauvj+8PAp9CSY/PoMblkVwxDRyv4YYG2p1znPrCv2br9D0wfRoWF8jIOAxQ6adAEMG6iqJwGKvJLcb2Hhx0hHefaKUJZf37sEIjeXJ0SToITdPQio6P6gkXBtshnQSV9556US/5cpAIkXhnnhy420Pq0ZGRkZGRkZGRkXF1sW9JD7d6PXZhkHYDfMCYBiMNgqWVimBKsDPELLTsOTisqGyJ2FJvjG2Jsa0Gq3wdpW0WGKtB4aYwtKWjaQ072xp8rfCMjN5Mh/gAPgdWsLTGUWEprVZPjNo5xaJhHDwj9EZ/7ixNaVTv5+gRZLLGyXqbl1irniOxfWfRxMIRvYR1ev43KOGwBhwx8PKVEV9/Yo3prGFyseECgWCgjdnqKTlSoMuSbIGa9JCimb/DnOKURJkqShxKaBynJzjK+Hk1fl5B5a+T7FU1+GyBc85ydlRySoT765ZHWY5tpEeU3aSHi9OH+fC7Kz2GcYzkZEGsBnAmrkd6+S2QS9b1bGbsyzGYVINxKVmy+/PwN4biVXo8U+a4xeEYUWBQtftoQ97NmWo/INVqRNtla3AGCmsojMMbUWGjVBbh4q/EagX9tUifmBJrC6wtKKoxzlVgCrAjjHEU5ZhiNKIoRhTVhLJapazGlKMKV5YUxQhrJjg7xtkRpasAR90anCg5Udjos2GUoBCBtlWiom5h4XUfFS5+3wJtJEicHrM2QNPG/RbJE2eiXJbGj1XmLOi6BfAttLW+b6/POf/URc6eP8VDD36cBx7+CASDCepdIpSIuC5TXYOwyZrcEIIKV6Xce92ffaVH7wsTBrU6pg9jp8oyAGm6h/N09Jdlra4O9kqSznTHs6PkBhxCyzm0f1ggJlDisEywjCLpoFJRhhFJespSxiuy9wQR5gR8lMGaxeNe6TyClr5154uP60w9iBmsq6+E0HMzarxhujNSl3BYxljGtCxoWcfheR3C6zA4SkYcec798D1cz4JtFlxAZb7GWEaRwGhi/5WuhgGC0RcgtPgYve7PumGFio/fNZEUGVLLz36mHgf+9HO2ImO/YDy+kZtv/laOHn81Zx084/QsH4veH8wtKs2YbnKGRU+w3JENC9ciic55VEcTLhmQRWDrDGw9TX/jtLt0NHXPK8BLgVvRrBOHVo48HV/Jv0NgpYGTc6i3t7nwzEfh8d/+k+yijIx9h+RrlqQTjVUTcZuID2NwTi/cEAI+xDFsUMHR1SCaZFJuYpWw7eYVEXyraT0ASbG1l5+SSHgEmrphOp0RfCY0MjIyMjIyMjIyrg72LenRTrdovceHEQSHNYKxBokmr4hFZazGGr40Pr7HgIoYfLA0UsQApyAmBmSk0pClR3PqfaCUAofDDR6qrajZsMezxYIFLUXtKXYqrBdGtcH5klIC45S5Lw5CiWmg2N7B1C0rsxk3CTTdk7ylcgXz8YQtazlSz1hb7HShLkGfz08AEwEzXbB+YZtF7ZGmpsTjY6bUbpnsRCCwa1qSqari51H8rDIpfUXHWpyv3DU9vU92LZOSNwWofODIosGL8MYgHIvtqel9QDbQRM9NNMlySHoM22JJwTVhmBBqiNUdaBa12xUFSf4RvWKw9DX0gz2VAno9USHdMsLwoS4JvyybWPeSM8vBvLTP0/Z220AgxKqO0NWh9GtKAjqQHiqtqqilfSOWxvREnI0/ZCkxxuLMGEeFsYItAsZCWa1RjY5hXEFVjXClHlUxEwyO0coa45U1CldSTia4sqKoxpSFEiRlMaIqSwqn6bPeC4Xo/u8kq5zu81YvPTr1N6A0MDI6vW10frySF44owRZ3XxGXKWLliDFRGYhl347Gx8qPhWe+WdMuWp558hEefujTbGycZmfjAqYJGqiWkW63eILMEQkMxdrSGWZM53yCSBGPXZ+ZPjzLpDtHUhWPStxBNNCM3wTamLF/9R1lDP21qx676Rccfcr0bsG8jMA2IBQcRWjwMidIg5Eikg3aG6mnR4rIDuvPwFBgGZHk0nQ/a5VFX8GQqn3KpT5AIgmQaFthgeBI8ln6XsVtrSNhIPRG6pZkhK6VIEkUL1F1Bb0b0DK+i4Jv5Bh/mZtpWSdQd8upF4lSuEM3mOGZvtyfDSs5JC5H91k/paoOvwfhcWW4CCQJsLPAv8Vzz66lU++5BdxH4NxVvta+UuFMxU1Hv4YTKy9jWl/kmc3PMGvWObr2cq479moktJzfuI+d6ZN4YGbBWsOWhc1IUqd7jW2rUocd0gA5xJDouPRk25szNoPvh/MOMxkccCN6M7WCVopsAqfob7a6+z0oPDjvaS4+xPmzD9BsP0k9fQaAtcmt3HDstThbcX7zfi5uf3GPhmRkHBAISJD+/I+Eh1YVa8VG4QqM0WpYF/QOWf039lwdxKoN7z2dvLAIi0VNXUc/LHNpTbT36rPm25ZOyzQjIyMjIyMjIyPjKmDfkh6LjXMYUxDCESBgTYEtFiAO4+PTqikwrKGSTTtg6l7iRYQmOBoZxYz4FtXWsTHoK0gzQ+oFJjgmooGsYAzBagDIyhQjNQ0tp9nGiMHujLCzMRZLEUZYKahMy4ptcSaw5sdMpKJoBVufw1nhunrGVwUIOIQKwTEbrXHbyZtZlBVPrz/Nk/WMVgJTOvlpDWyK4C7u8OTmTP0M2sBI+hBdQJ/rPb0sVSISEimRqjZGqOl5Gd+TlFWSrxr6d6QqjxSH6OkaxZBoSX+v1i0rjecG4DYRapTY2EKJjwdRT9F14LNotUva1mHMQ6G/2g4Ccf33FmejsbC4mEbaS/5gwNmg+yek7H7BxwCcUh66TBHFviDl/vfhOwa/qobRLs6bzJADlgaDj4bpLalSxLI7RNjSSpTFMcnKWDCRpUnHC0CsBesiCaNBwgZLkEjLGK3+MKbQag7jKN0Kzo6xVrCVyrqtrJ7gyNqNuMJRjtToXKgIsgoUjFdWGK+uqgl6Nca6gvFojfHoGIWrmIzWGI8muHJEEEPjoQxKDlljsC6SHqKSViJQlWpU7oCx1QqPxsNsoYSNiTvXOTCxasMZGMdKEOfAur5iRESrQ4wo+TFvhFkDi82azafXWWxP+dyn7uaeP/515rMtdrZPUywCxjicXdNjFy4SwibgEFbi2d1gTA0INnqWiDi8lAgWQ4NhEY+lZvprsLkmBXkFixHBRo8gT4uPkbSWgI+m11fbVtwBq2gdwgxhkxDPywq9ygWtT8sYwnMew4iKmxA8rWzg/TQe2waPkmUFJ9BKhq2OZEg+FZYRJhLvQk1QITosR1E6cxvPDPXdWIlkReq5PC2bBOZAGytKTKwyUSLSMcFQxIoT1fRRomUMQBtdlpUQSeeVo5fLqvZs+08xYZWWNZ6JQodtR5AoAdLQ08opKt0TF3oW9+TFslzVkK6+uvVH6XeOA98PfNeu703si7+I8DPUmfS4SqiKVV57y5/nT932/Ty98Sn+ywP/K/N2k1tu/NO87qvfTeunfPJz/x92pk/SGFi3MHdwxsEzhRYEmUhee9EqWmBZG3MvpCyN3eSFH3zefbMgDG8clnMQSuCrgK8DLgAfQ288puhNySCbohBYq6GoW6aPf4D1z/08od6kWZwH4MZjr+UbX/3/ZlJdx70P/RwbO48QJJPLGQcXIYgmigmR8LAUhcNZh3OOqqqw1uJDIAQlJtqmwQc1WuvubKIUVfpeq2fRStsQ2NmZMp9d/p5EE9XoJa0yMjIyMjIyMjIyrhL2LekhbU0wFjEamImhVjSknMxiDcbEJnQuezFobYha/qYP5ZgUfrFRK9YgQTACVnqz2mGIMuW/+ig3YkPARpmqRCqk5/FCIlkQrMqmNBogNb5lLEMbV61SOepKalcxNa4jOyr0WTyRAQagDSzasBQHGJIRCcMKjGREnkiNkr6SI5EeR+P3I5bNys1g+fRbw3foBXuGpIcVJWlMXL9BSY/NwXtSlTiGYRa1eYd5w70ITKx22DOzN36fNIOTdkbSIzLCJVrDQBIZHxoD23Q8BsTK7kTT9Fcg1WSYwdJpHaY7D8zgN3r0NQKpYqSPt/T/S9xeNS4f7F9jERPNlmPbrFUPG2Mczo1wdoRxgouVHkUxpqwmOOcoK0NRGkQqgijNVZRjirLCWIsrSoxzamhu00sffJ2NGeHCkgG4xF0jEs3Lk2+z9HEoZ6IfRzQrTxUiaV0hRKIjVY4MjkFaL9LP39Qt80VgPpuxs7nJfGuHjY3zrF88RV1PCe1c+VAMRixCZFDwg/3e03fGCKYzKO+PyO6zbvg+DOJKN7fsWurqi0055yisw4lQeMGKdFu013ZmLEO9OKL81JJUlekC+3rllvF6vjSV3Axq22RpP/eaOv3VrFSm6c6p3pS8JxV2p733klamO6N0bJLOM6P3zhgul+D5JhpOseDp2CZtr56PSfRw2Mulc9UOpgRSjdveBEfY9fnFDVQVwA3xNUTqkRfACSyrg95pZ4/1rDCmxVM/h9n7VyqMKbBuRFEeYVKdYK26kUl1Pa46BuUaxfhGJkfupGl3cOOTUK7hiwm1VUPj2uj9S0gdeT+0Ki4dXJenD7uw4Q3PcL7L8WuXm1ahVR6bqIH5RZYKuJzGfan/ieHZHDucHTOpTjIZnaQsVi7TkIyMA4Z4s6W+Gelea5l86MzKCd29dYDec4Ogy0WZqhDCgPQYVH9kZGRkZGRkZGRkfJmxb0kPu2iw1hJMNN02NdY08QY9ZQytgKwiYmkpCdZrgMdE6SuJWjqAMVUMIzUIU13cVGBXEKCNgd1g6pjdG2iNj6EgG/1CLNY6jAPE4/02XgQvgSaUWGCGoTINlkBhFli8ui7H7PAQs4PrOrB1UWhcwc5skyC9hMhQ/hp6o/AkOR3Q5/jxYF6Dkhmaw6/P+MPPyZg8yVNVLFeFDP01EumREi6HAi/pMf9yVR/D7YHeE2QEvALVa1/YgteNjzN1Iy40U55ebLAjgc8CDwMFjjWzSkFB62qcU1Nf2gKCQ12mPcbE8HWsltBDLerd4lvECFiDKQAxlH4USTANdBvAiJ4VATVYHDqBDOMn1kBlox5T8BCapbmMhtfjXwVCGUOEmpGtrh5JJinE3Pxomo2JmlH62ZgSY1RiwBVKchRlhSmqKDkwjhIEJc5WYCzOFUpYOEsxKrHOUlWrFKM1lS0oHaawWhniVjCmwBUliErnFNUKRVVRFGNwgriAqwzlOK63NOCERmBnrkRFp9OuHt4QokftMCgVCQ5fK+lRVTCOuusmaBawifvXWK3qcKEXlhIiYVLDfF7z5ANf5NRTz7B+8TSPPfxptrcu8syT9zOtNwm+iRuixpsiSh/quspIS8yJYbmub/BSY6gRHCo/ZFHRqKY7ngFH8vQwsa5DWMTmq7RQqsl5MeCs46tf+jJeeftLmc3mPPjwo1xcX6cWj4T0m6l3yJmSeyHQRFkoPWqBefe3tzMMBidHKOQIQhslq7T6IxGZoav2MVHmSk3HvdEKDCtjio7ydfF356jnR5K40+9s7IG1GkSrSVo2Yt8fsEwA0IoM0223dIRDkpJKMozb1DyDweGZMjwPelpZ1266Xr8nWSSajneJA3HrEyG0TOTJHtOuBTwBuB7L/8Aqb6XQ48GU/3mPCqu/xdv5BPfzh9zLPFZiZfQ4euJ13PSSb6cq1jg1P8MHH3oPG2XBxiv+W6T67zhz/Ov51NqYECwXXvW9cONXszh6J2eOXo8bwXYkpwkse2ukMsa9Kj2GPGB/ivbyU8Nlhstejvcb/q4HHkLLTXfie8pUCVAGuL2G61u45zn2zfmtL/CJL/4chZvw1LmPIJKDuBmHA3XdsL25jbHJiNxijdH7SmtwZUFRxqeDSIi0TctsNieEJO8JIHgfOsIkeXq0Ta6IysjIyMjIyMjIuDbYv6RH7bG2BqtPvtY1WNuCpKATQAVB5WhaU9BS4KyjsCnTPj45i8WESqWQaDHMADBGrbmDEYJpYrbSHGSGSFAPBTQ8VUqldQfOYErRjKagmvBChQS189bQlFqLS3SzqBDGMQDjo0hI3SzYXt+mNTCXPqwEl1ZUNNApuC/Q0OZRtJpi6L9RxekVcAy4jp4IGdFXglwuiTJJLJnB570smHcTM32Y7FJPEQcxdKfbeydgbUE1vo5idISHZxe4t97mnASeAu4DRlgKM2FiRjRuhqs0xOcZ45sSY2uwOxgTKBCKSD0EAiESFz6oya4pHFQOE6wGGb0D48G0kagwWNHgu8SQJrrk0pGwBgrntWpEUtDR4CkQbBdC1GklgXFcW9L3t+q5ARgalcUR2wU0xUZXcAxFKLG4SFYUGGcpRmOK0RjrSsbVEYqiUoNyV+k2WQELtiioJmtYF6WvrHp+GFuqZJYrsNVYTSuDOswaHGUxoRytqHGlA3EBW1rKkVaAmFgK1A5ID1dGmSrloNS7Q6DRZEDKZF4ewDfgPbgKJqWeL4tY/UEkPEw64Y0W5YRC332Apob5ds3TDz3MF++7jzPnH+Yz97+Pze0zEFKRj5JIWnkTkFCDMZFQrGJQd0EvBufig3py00kBaI2KJQLEd0dQujofnV9F5iTWVw2N6a82nLO88rY7+NZv+EZOX1znifPbPL45g5BkjgYuvJn02BMqOqaaNkpALJTYMp5gazBg/RgrI4QCS4XKQKVzAlTirGEoRSWmxpttwFBwjFJOoL1RHeef4tnu+gztA1yUrNJeNh1DJUeUcHGdAOFyK1LEticbkqxeQ82UIZGxd2+vPXyqcrFLfiE1l1Z2pM/777xK23eCiu9hBcMKni1a5nuSHj/In+eX+V3u5rOZ9NgDR49/DS/7qr+BtSUPfvp/5fGHf4lw8zcQXvvTcNMbOIfjvGh9aFj5syDfxsJazhZO+201GVq+iRmSHrurOYaQXZ+H/O3wMkhp5n7XNDP4LmVlBOBLaDbFUL8T/a5s4fYpvHL+3KTHha0vsr79iGavSztIkMjIONhomoam2ZWwYejudiarE1ZWJxhrKazDGMNisWB7a5u2zYRGRkZGRkZGRkbG/sW+JT2AGPxMsjEGxOkzsJRA9EMwu+oQhJjBLWBSiTX0WakALj4gB0zMzO5COkZ/B4m+DAGMuD4ZUXpj5WR8S+cLkRIVZSlEpHGAFCo1XYjVEM0zgVEXEoPWpPXrK1VmDAmGNbRqYihLNXye98Sse3qiIxEau6sxdldvLIf7L13G7JonCb4MEyyH4bYwmM9EkqH0Na6ds+IbTsTv7wTOA6U1HC8NpTVsW1hH8BjmtqApR2AsUqhHi5ECEReDIxZjBYLBmujuYkx3bJLUlZh+C7WkP+5pk+Ikg9ZJ2uohDWK6Y56ks1RyKjqOiJpaWwRn9Jx1xkV5AIM1EufX4JHBYsr4wuCkxIjDFg47KjHOUo7GuNEYZwuKahzJDq32wBisE4xDCQpr1FDcGKwtIunh9OUczhUY63DW4MTiigJjbWegbqx+TxIXk/4MMMZQONOZlUssmIjFTNiCWAkVpa7iJWnjyWFjERYoUdHt02F2cFwmeJ20tbHNhdPr7Gxscv7cM2ysn2Z76yJtUxN8IJkd98fGxHBtC2JIMjzpe+nIyZTLPrwK0sYMdVh6CR/p5pW4TsE6izUFQVrdD1cRZWGZTErGVUUbPKcvbHB+Y4u6qSP5Ngxo73XVZfTQfdNTzKYjNKz086hj0rDXIk4zLAc6L5VZFOMJZtFlw6a+Qn8ndJSH6Xrj4bYlMmJ3evvebTF79LjmkvNYiYFL48t9Gn1yK+m9S/S1bFa+/wiPIQxCQYulxg6EyXZjwiluZotXY9g0IxblDTTFUeZ+m4v1aRpZfFm3+2rDFauMV27F2hH14hyL2RmGfYEtj1Ku3AKu0tSMpR1laI+8lFm5grEFi7VbaU98NazcANPTcPFBZHQSGd+knbwr02JJOXL5ZuG5sFeWx+7T7XKn3V43MLvXk26ohuRJkrQKUHqo2obF9ik2ti5ewQarP9g+vxReEP7DD/2f/Mz7fpa7H/n4td6UjP0C6Z+YvPe0TYuxFrEBayyt93o9ZGRkZGRkZGRkZOxj7F/SwxWIM4hViSkjJQQ1abXxPluwBKYa1DGab28kQNBKDuvAWI2girRI8Ii1iF0DI1i3wNoZIiXiVxApMGaEserz4WoNzAoSfzQQgqGpY4ApjON2mOWwUuJepN/OlC3e4PBR5qgwajs7lhpi1qmPskE+aGa80EtTDf03xqhslYFOsKcBZigxsoV6daZKi1F8HR0sP4nLJymrveIVhp5wgb1jGXt5f2itgomCKSGSN1anhkCYnkNmFzgeWl4ThAbLq4DvQ/CFYXHM4CvDgwv49MwzxXF+tMaWu45gG9pilWA8ofX4VqPrKc9fywrmIB4xjWb8YwjGgDOEYAmhQI0Ya63WMYJ1WnKQwo5gkLZExOIkUIhWh3iK6K8Rg/kmmkA6pX/aVrrfLE2lpIazmLLAGIN1I6wxiKnAHgVTMBoZxuMUyKwAlZ9y1US9NaoSV5bqv+EqrHFIsISgAfxyDGWlAc4QK42cG1OVqxjjEKtkjysrRpNVrC1w1mhVlHG4sojtqXCFVooII9rWYp3DFQWWkpFzrEy03aXRk817WMyU5BhPYFzpOVC30etDdLoxUI0h2vQQFbM0fuX1+2RIE1qYT6FuhM9/9gvc84e/z/bmRU4/+nnWzz7BopniF4GClQH9kMiJgBpRpwzEgOmy7AsEgyUwdGEJ3RWQwsaWRLam9QmGNhImiS4x1jIZV5TlmLoOTGdT9SG5Sjh+bMJXv/IGJuOKc+sX+M0PfYR5veDMhbPg55hOfgj6XkLIRuaXwnbG3U38e4RhEgOkkRITS8s2iQbX8yVE03FForfVxDxgcBThGGICvtyhcZvYUFHWx7FSYBnhOEIiGXp/DR/p3ERWFDjK7vxL/kF7EVtmIEZoo08J9EEqYUFI54AZSPXJcoR4SBSydC7tPol30ynXIvJrBteeDKaYeDQ2MWzHNuwdjJvwy3wz57iDgpk7wZM3/kXOH38rD29/ivc984ucXTzx5WnKi4S1o6/izrt+mMnqbTz96K/zxJf+DcHPuu/HJ17Dybv+R9zqraw7NSAfYmN8Cw+vHAUMG1/138NL3wLbT8IXfwOmZ+Bl3w1f/ZehPNLrYkI/+O81DfYmCtK04Tb0hUXPrtSXxoq0/FBrM73awXypW4yZIGsLODEHO9vg6Yf/DU888f7L/NBXBn7mfT/Lg6e/eK03I2Ofoqkbgk9Swdrrqrl5Jj0yMjIyMjIyMjL2N/Yt6SHWghXEarBSvJoSG7EYsTELSWsoBMFYwRqLER81FtDM9vhkLJKMwI2aoxsBt0DcHAkhylOh0VxX6deGaCqtsii9sbLEAHsRg08pC1yWHvTF6H8agtFagUR6FJguVGVNi5N+GTEag0vF5isoQVGiFR7Jj2MUv08ExxyVvxI614JOvjqRIkkGq6SvzhhWeOzl07G78uPScNilUNEk3TdDg2+LwYhAMyMQGGG4Mf76bTHIXFvDxZFhPgYfhKemwhawKCqaaoK3JcaBN57GNIionoalxBoH1mkAPXhElBARUWPwYIxWCImNvg8xuqJ8B8b2ERgRowbiUmBijY56pDswhbbbqGm4tYKNQRgjYEQrEApTKEHhonyVMbiiwDmHmBFiV8FUVBPDZALGWIQRmALrKopyVUmPslCpKxN9ZYzFtyCNnqOuIBqVtzS+RUSluFysCPHJ690VuKLCuYLCGZw1sRLExkoYi7EqnQUFIcRqliiD5ayhKsDZtI+0IqOJ5Ec56s+HRNxZC0UZbUsiw2YkEkapKEsG51IkDZsG6rlw7sx5Hrr/c2xtXmD7/CPMt08jolSEpRjExmTwKRDw3Tnen6MuCmCBjaRIWDrzh+d1yvLXALVKWKWakfjJQFE4yrLAB9cXWlwljMclN16/xmRccerMJg88dpYQWgxTered4dVaXN0NOETo++pENJQqeYeJ0odKiEhn9t1XQIQYLTUMxpRBxYhlhOBp7Iy22Mb5CaU5AlLGZarB8mmdQ1FD7YXtbv2dJezulW3sUcvB+tNIpNvbkRPxvEzURU+OXMl+202DX5vzKxE0ht2Ui36TpMvSXOuDthoKHKsY7uMO4A4sc7vKQytfw9PH/m+IeCZu9cvWlhcL1egEJ254M2tHv5qNC5/WsWqAYnwjqze/leLoK9lxWrAhg0NaB7gYT7vmxF1Q3AXP/DF8+v+As5+AY3eBb1mymWGP98tVasgen6902u5Tb1hZkkiNJTMoetIjjTUB8ELZwloLUi+4ePFzXDj1Ab7S8BP/E/zhf4U/vodc4ZHxrAg+dKRHRkZGRkZGRkZGxkHCviU9LA6SUaQRTKXEhvEBFlHaColSRZbeErqJojzJLEAjqCa0mBCFPoxFjCBeaycklEgwSAATArS1PktLEYMGGviWwVO1ftKnbQ01aQBVFU1iUEaGIjrxeT2abydb3RaVQ0r1BUYCpvdYBpalqupInliEFavh1xWBQnpyJNkZp1VULOd/p9cmGgtI+eEFvbn5Co5xl+3uY5sj8QSRBAgsO4UoCWVj8FWiQa+NwTdt4zBakrQndJ96Gg0keljZMYxqx8sax0Icc+fYmJRM10acr1se2tliu63ZNiXbVGAcpRvhTKGyG2WhlR6hRGSMiKEJBV4MLghF1CgLUmhA00iMjkuUbIqhPlto6Q0BL0YJL1tRuCqSCAJWcA6KSiM+zhd4r8FNa1S+ypYOOyqU9LAWaw2YCtwaxhSMK6hKJV3ETcAqgWOdenLYoog+HQZnS6yx0ftcSYmqclSlntfOTMAIzq3hygkGizN6LZRFxaia4FyBs2BdrPRwY4wpKcoRReWwzuIqi62sVks5QayPUTI9z1NsyThYWdHPhdNCG9FTXEO5pn+ZdI1IH5/q1MaA6SzQ7gS2NzZ59KGH2Vxf57H7P8l0/Wnq6RZtO8MjiAkESYHdlPmeKj3Stjn6wG9XuzOYkoLXw+jd0CthcN3G73ZPFQks6jkheOpm3hl4/klgcIztGqWpYF7w1FNbuALWNxYgic6ERMKAyk0cWzvG2spxJASePJuzdi9F6gV7YsDHSg1DEYP7qSLIdARF8uboo6gpmN4O4rEqlWd9QcEKNoxA0vkVuvGhl6SykfZOvhnpLCzR6pLkKXO5KC9LbdGaulQ9ktYXqW2J0y5zavb+H5ee+zCs6tiLcLhy9L+TCKNEqPQkT7qaicdDYjWMoogj39C/JkmHKWVEt4VpzPJxX6TjWcTj1mLDNic2P00hE2R6H9/TtpxjlZ2VV7K98irE6NiOgTPzJ3h4+1PMQ1/x8+WCtRXXXfd1HD12F8bY7jhOLWzFbmtVYCywcvzV1OPr2LKwSF1aeQRueiMcuYPm5NezMTqCtTC39IU/EcFEySsTe5kATG6AV34H3PS1cNubtJSvYJmEEC5PfMCl2pfp+8RKy67v0uc0fS9jsctlYgyrTlIbGhh7uGEO41bwFx5k8/QnaaenWWw9zFciPvM5OH0WrsKQlZGRkZGRkZGRkZGRsS+xr0kPi2biGwtmLNiRYGpRG48WNVy2miHrfIUJBZhkVIxm6ccnZhMaaD1WrJIVxiCUhFAh4gitBRF8aBA/1xBJoVn1EiyeMj5XNxiaGFZJNtpt1BHX8FZ6iEzSGx7BRwMDZwRnhCCeuVcTYhMDNwah9C0u5p6nZ3ZPMjBXO+wSS2kDzqmR98hL54+QRHp2+3wKsA48ilaFJKrBsCyddST+fQsla1Roncocg8fj8Kikl2OBo0EoEFYjGTKN2fMGGOEZATUu0jDaRrVUFybo6VejFIyPuc8troFj6w5nHMdcwVe7ArEV4egYObnC/etTfvPMBZ6ebnN2cgN+ohJR43KF0lWIaQm2QYw6aEto8QLGB1qRSDJFosW0sSJA8CGACMFr4N5gVCLNgG89i0WJiDAqxoyKWNJQCDgoCks1jhUYYUwIY1IWNsZSVCXluMKY5AYiGOMwxRhj9HiWLmiVSrUKxSiSAwJiMM5F7whL4So9L0UJMGMMo2pEWVZQWMy41FIMozb3KuqkV1RZVIzHqzjnMM70pIedYG2JLQuKkZqnu7HDjgusseCCSs0Zo9eLxDoDA1UBa2tKeCxmKkslqMm5tTER10ZyI56MyRsnCJF8UaJva92zsdly+sln+K/v+x1OP/kwG+efZuv0I7S+oZE2hjE9njkS66ZcR2Ckn+iDqX3gNAnRSTwCqftLwVgfg9Nqai5dpC4hBVshRd1CCMzm28wNsXLoT54N6UzB0eIG1tx1LHY2eOD+p2ipqVuDSArspvRmUCkzxy3X38gdN7+Utm0z6bEHYp0ZKdrqY12cVgGMB8dbA+RqVF5hmEbiY5kg0OoPPVdSX2+bCttOMFJgBr2xRPlCiZUiui1JHnERqxS0YsQyIrDAL7k/JSomHXNJo00cYRJBUMdpun6VP1tcNrLZr9PGa+TZTGmfnfAYVoTsPacjeZuk7U/kj/7dkgZ2yyQSTguEWdxOldjTyssoexmJdE16GGNwMZ1gMdjvvbSd6ZZf4NqL3Hr2g9x2/j5eIVt8g6+pzXU8dfRbeeLm/wfejQnRA+rei/+ZU/NHmNdfftLDuTEvuf27ePkr/ooS4XH6Mw4ei13YSzycDLAoRmyOj7JFYBor5hifgLt+AF767czdmDPF0Vj1SE84DIjoelgcEoAjL4WvfxeYBtwKlLEqNnWVCbuJizStV2LrObuUP5LmGc67u9sdnpbDfInhdu7FDaZLPW7nagtfsw0na+Hhxz7CfZ/7GRaL8/hmi69EfOgPoa6jR11GRkZGRkZGRkZGRsYhxL4lPaKDOCQSQTWD4ncpW5TuwbZ7zk6B4vhZFzX0TpvEMgqjmbhi9em/k0QQJAQlRaSv6kirXg7rDEM7y59TBjoxU7Tf9m7LESMEWY4FBJbjAum5PU33MbTUYmhToA0N4qdqjd0xhfSLJX1MYffWpPkTZdHE13IOfB+CM0vrScJVSfplOWUzBQrNIDi4tJaYUWukiL9qsUHXNsYysnqcTHTFPhmE67ww80IrlsYUYIroTeLxRqiNIRiL2BIxSmhZAjYZjIueTxIFwFSazPf7JWr8OyfReNthvVYDWVfiimqJ9HCF1UoMa0HGOBlp2ySSHmVJUVTq6UGIFSNayYGxWBuw1ivp4UqMU4JFgp5X1jl9YbFWiQixug/VJyRWgliHKSplHLrKHA3hFlicc1irL2NNrBRxWGu1osTEafGFSS89XN05Pzg5U7WG6eYZnOUdAdiTHhJi2FP6lwGCCLPplI2LO2xcPM/6hbNcvHCa+fY6bTvHh7bLTH42k+Xlv3alMi9dp7u/Gy69V+rw7t+K/ZD4QYWHYfcWPF9oPE9DtIsA88bTSIssmV9f+htFYahKPX4Ze2H38evPn9RbL2N36nr6K5KNHflEDODHwLpYlqsaUoAf+mqGfs2XP1uG52I6b4fR3OF3l14HLM2/fN6YpU+xH1nSCdo9nr1Y2GsfJ4+TJN/luqn9vBbTCTimaX070jhkuhHPDtab3oXSb1N4S0nNBMEbhzcVtVnFmxHeCmKEG8yIk2YFYYXWFniXPFS4pFpieCR2cwBD+NDQtDuDc2PXnrEVtlihqK6LPksV1o6wxSrGlpQORoWuf9LCJECw0FpYhBpfTJDxCRhfDys3weotiBj88m3UpYdjdxdjK11Hf2q88FNi+dZg+SZnr3mHy1zuN59tHQRoZjCfY1qwU7CNR2ZnaGbP0NbrL7AhBxc/fte/4l8/+o84tfPYFS8zHsM820RlZGRkZGRkZGRkZBww7FvSoy23NKgUgGAIc8G2gdAa8KrLEEIM1UvQ6oxgEEkeD6LEhbFKbphjmnYuU4zfwiDgo2dDDOdr4F29GxBo/ZwQGhBLiBnWiFZ0qLiVVmpgAmKiPrtIZ34uKShmhMLFJ/ggEFoNx9iRhnWkxQZ18DA4gnGRuPGkPOHkzSEx9FlLwZYvsEAhHounInCElgphZGBiYwA18kdHgZdzaS6vNep3sRDYEd0bZ2m4ELPiU+WJxVOwwAJreMbxuxGthpXsGOdWdIvbGSLbaGbv0dgyifuuRdjQPeRWMOUxxBhsM8a1MywFgqXFY0KJbY6paffpBtm4yPWLmv97c5xtu8a8uIH5+CS1aTndPsN2s8UFM+Zxc5S5KVhUJXU5wgAjJyquJSlwKYj3hOBxJhpwG9Q/ptWdZ51grRBCYC20iAjOVThXgjFKiFgAq+easUyqiqKq9Bz1WpFRFgVVqVJV4rV6CGugdGChsIHCeiVCqjWsGxOM5nJjoCwryjJKgyW3exsl34ylrMa4YqQVGmWBtVoV4oyNob/kB1Ji3SgSLtFjw6g0j9DgjKEsjMpb2RR0tJoLHjWtWo/6mBh9SQvb0xibslCs6OnbtOrrUQGV04qOENTgXATaWOlROu2Imvmc++79EPfe/RG2Ns/z5KOfZWfrIm09pQ1zhBCvQ0sSedN4WMrgJmaAJ5melIY8dP1IAcZE20GSzVkOgkNP8SVZnTRNLllvn6acutSUpf9C0OLkLIVsYaWOW1T2/QkpfTlRlfpe+7NMmxaftbf3RG3O00ZfqERQgJ4/tqOEQzx/fDQvT9UGqSpPr0FLheU4UODZpOU8qafuqxnSudgi0aFJz6ga01U9mPi9zh+Yk+SXJPpV7T7HkuxTEk7UkaZFBZ4mcVqqdgCtnCjoZbZ0nQN787gfKlz0OJEoNdhXjzz3OfXcwle+a08/74BoHlyvQhuv8ZKCUVwimbM7HCtxOwWWjpegxvGr6DFeINQd+SEELCWGI6RoulbZeD0PxHBy80HG/jfwNlCXZ2ndNqs7Dbf5P8WOfT1PXf9SnjnxEry1zAuHNwZJeRMGdhwsLDiBFa/vKe9hGMc/vXkfn3vq19lZnNlzb62ceB0nX/o9uOoom9MzfPbT/wt27Q6Kl38f9ujLmQjc0UIpsCYqb7UjcMHAVuGY3frNSBkrM46+WnWrhhUSQzJhSIQsmyD18ySFt7BrGXbNu3u9uznjYZbF8PthhsdwfRYtQx0uO+y+h139cD2CEh5ffC888Ufs+MAXGph44eLG52jbGV+JuOPM+ymbzee1zH/zTfCfvvJsTzIyMjIyMjIyMjIyDjj2Lenhix1cqBCvpuJSC9IIEgwhGI0uBA3CGrw6JktAfRxiYMc65UTEgVnFmArEg7+oy1BgCEp82JSpG2IGqeCTB0gnP5U8LtIzd0tIUQAbn+DjNkEKKxmsEZyNwR6v2fsYh7OVZvmHgDMaDvM4pRJMlPaKW9CHbDXHeEcsQcZoyE4lpMZ4ajwjhGNWA80FGmxxAquoETr03p4Gukz+CwhPiopNXcCzE0mXVD0yIjCm7kJ6AagQSrwKttgJrjgC0hDCjOBnGFaBlRhYXGCjlFVgitCoZ8VoFSixocC1JZCM3wUrBfgxxhvC+ZbAFseM8AaOggVXXIcbHWM77HBfvcGp+ime4DgbVDgzRooRrRtjgMqlo2dRI3NoxUPwWGsYVwbnDBIc4tW7xLqAsQImQCS2xBaIKWJ1g5Y4eG9oWtVwqiYFk5VCs2obSwhQuYLK6TnkmwrvS5VnKyWSHh7nAsY6inIFa8cEC95q1dFoPGY0GiEB2oUheCVkXBm00qOcYN0Yaw2lU8+QwloqowblYpRIMrbsfEJMIj1Qo0qtqAoUznZSWinI2okpiRIZieBwRo3MF7We+uMVGK8qqeGnUPt4nlnlHH0LbaPztrHiw4pyOO2i5kv338t//eC/w7cL2jAnSNtdkxobS12WYLtrM9U4aUZ9iN/vrZ8yjLQFek+B3dn8KTCb8sttF2Lt17U76pdIj2GU8PnDiMfKOlbAigOpCJd01cm5J21NoPHrzNsdfHgxM/MPLlqzQWCCkxVSFUHft6fKKEi9m4/SSMlfQ4+4ek0YShzHsYyBlobTMVA/JoX/pSPN2gHZ4OOZm8zNe7JNzc0XGNr4m223roT+fB3Wi4R4piafEIvviBYTZZ9K0jkjl1wXCkuJYw0leuaRDOgJmz8ppBs1htMSgbd7aojbVOFYQfC0UQbMMo773ZGkwXpyRskLlSZzeFx37fTSZgWWiuTc0h8b9QU7vvMYJ3Y2CXbObPQgTXGOO5rX8Fb/nbT2Jj5z/I18/vbXUbuC7aqgtlZvR1Be4WIFWw4qgeMNVLG/dHF3J/LjwVO/y8NnPnBZ0mN89JVc/8ofwJVrPPnJ/4VTD/0r7PWvp7rtm3Hu5by8hVe0ygekdRoDmwYuWgvX/yk4+XXxR612R6lYbFggk8pIh2TCbtKjLzXted/dVSF7F+3sPrSXvhhsz+5uNd2AlPHvRLwM1y17TEunWr2AJz8Mn/kFZuJ5NO6ry1dGHX7cdOFuSp6fTNvXvy6THhkZGRkZGRkZGRkZBw/7jvRIMjFTEXx8AZQElSQSCCE9geuTrYnVHiRz6hSwFAEJag4uXgkPSSavg6xuUZNqwRAkZtfr1sR5k6BJWIoHhBRiTRo96TdZDq9aiXJKSMyo13edN8TvdSnfBVvVNtzQ2yxrPKLPlPUxEqGyThpOG8UQjo1ER4EqMA23O8U1OknsuM1bIuygpMcU2InzphzopLhexFciPQKah15IoIj7OEgK1gmJwnAEkpdG2scmHh/wBOlb34fxGFinq5K+bm7AiMGFFudbdmiYBc8sEPOyPY3xtKGl9e0gBD3YkwI+eHwQ9e0IcW+HoJH9uB1GBqSHYSC3FiWgUCLOeyVA2hbaNijp0VpEDG06D7GEVs9hicF+jW4HJGilhzDXoiQLrdVolnpiBCQYNQr3YLwQREkRKwbrAtaq54a1hmCMBrsi6QEWbIG1Qas+PLgYlw8+yshJQ1kYnLOYtgFXY40luAJnHK4saNtKKzoS6SFKbkji/OL7dAZ1A6HRbOTCQlND2y6THt6BLGC2s0ldzwi+wYeWIClAOwxQDa+swTU8+Ld3VI091jP8f6/56dZ9+e+X5929/hcCQfePD8Tr6NJt2r1+Ea1Gan2gjfo1V8NU/TBAuv6NKAOo13bfH6ZpySdDx5VEaGsvr+uwsQ+zBIro5dTgmcdRxw3Wn4y1PaGjTMzg3exxXln6sS0F/pdjwEJPyS0f39TH6m9KV0ORxpG9rxG67XDxldqextG97c1fPKR9o3VNuj+FEKkgbU8RCctAP96nlhUEqkiS+u449vQlHd2hx37Yh9BRJTUh1MxCSx0CpbQ0UuNlwczPWLQ71FKwsAWNtZ1CpjdQG2iCjpl15CYt0CZiIu7Mxs8JcnliVEJDaKcAeL9AQkvwNaHZwdSbHYFsE5kCNA6V2xqSCOlL6CWqdldXJA61VwIbHpD+tbuAbTfpMbyx2E1eMJgnDcjD5XYvk+YfEh17kR5h1zQzmFZvQrtQZn6P6+krEVPawT3ulaFWS6I8ppD3QUZGRsbVQO5L8z7IyMjIuBq4kr7UyD7rcZ988kluv/32a70ZGRkZGQcaTzzxBLfddtu13oxrjjymZGRkZPzJkceUPJ5kZGRkXA3k8SSPJxkZGRlXA1cynuw70iOEwNNPP42IcMcdd/DEE09w9OjRa71Zf2Jsbm5y++23H5r2QG7TQcBhaw/kNj0XRIStrS1uvfVWrLXPvcAhRwiBBx54gK/5mq/J58w+xmFrD+Q2HQQctvbA1W9THlN65PHk4OCwtemwtQdymw4C8njy4iHHvA4Ocpv2Pw5beyC36bnwfMaTfSdvZa3ltttuY3NTjRaPHj16aA4yHL72QG7TQcBhaw/kNj0bjh07dhW25nDAWstLXvISIJ8zBwGHrT2Q23QQcNjaA1e3TXlMUeTx5ODhsLXpsLUHcpsOAvJ4cvWRY14HD7lN+x+HrT2Q2/RsuNLx5CubYs/IyMjIyMjIyMjIyMjIyMjIyMjIyMjIODTIpEdGRkZGRkZGRkZGRkZGRkZGRkZGRkZGxqHAviU9RqMR//Af/kNGo9G13pSrgsPWHshtOgg4bO2B3KaM54/DuH8PW5sOW3sgt+kg4LC1Bw5nm/YTDuP+zW3a/zhs7YHcpoOAw9ae/YjDto8PW3sgt+kg4LC1B3Kbrib2nZF5RkZGRkZGRkZGRkZGRkZGRkZGRkZGRkbGC8G+rfTIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMh4PsikR0ZGRkZGRkZGRkZGRkZGRkZGRkZGRkbGoUAmPTIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyDgUy6ZGRkZGRkZGRkZGRkZGRkZGRkZGRkZGRcSiQSY+MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjEOBfUl6/NzP/Rwve9nLGI/HvPnNb+aee+651pt0xXjPe97DN3zDN3DkyBFuvPFGvud7vocHHnhgaZ75fM673vUuTp48ydraGn/hL/wFTp8+fY22+Pnhp3/6pzHG8KM/+qPdtIPYnqeeeoof+IEf4OTJk0wmE1772tfy8Y9/vPteRPgH/+AfcMsttzCZTHjb297GQw89dA23+PLw3vOTP/mT3HnnnUwmE17xilfwj/7RP0JEunn2e3v+8A//kO/6ru/i1ltvxRjDb/3Wby19fyXbf+HCBd7xjndw9OhRjh8/zl//63+d7e3tL2MrlvFsbWqahh/7sR/jta99Laurq9x666385b/8l3n66aeX1rHf2nRQcVDHlDyeHIz2HKbxBPKYkrCf+t88nuwf5PFk/+IwjCl5PNl/bTps4wnkMWW/4KCOJ3D4x5TDMJ7A4RpT8nii2G9974EYT2Sf4Vd/9Velqir5xV/8Rfnc5z4nP/iDPyjHjx+X06dPX+tNuyJ827d9m/zSL/2S3HffffKpT31KvuM7vkPuuOMO2d7e7ub5oR/6Ibn99tvlAx/4gHz84x+Xb/zGb5S3vvWt13Crrwz33HOPvOxlL5PXve518u53v7ubftDac+HCBXnpS18qf+Wv/BW5++675Utf+pK8733vky9+8YvdPD/90z8tx44dk9/6rd+ST3/60/Ld3/3dcuedd8psNruGW743fuqnfkpOnjwp733ve+WRRx6RX/u1X5O1tTX52Z/92W6e/d6e3/3d35Wf+ImfkN/4jd8QQH7zN39z6fsr2f5v//Zvl6/7uq+Tj370o/JHf/RH8spXvlLe/va3f5lb0uPZ2rS+vi5ve9vb5N/9u38n999/v3zkIx+RN73pTfKGN7xhaR37rU0HEQd5TMnjyf5vz2EbT0TymJKwn/rfPJ7sD+TxZP/iMIwpeTzZn206bOOJSB5T9gMO8ngicrjHlMMwnogcvjEljyeK/db3HoTxZN+RHm9605vkXe96V/e3915uvfVWec973nMNt+qF48yZMwLIH/zBH4iIHviyLOXXfu3Xunm+8IUvCCAf+chHrtVmPie2trbkVa96lbz//e+Xb/mWb+kGgIPYnh/7sR+TP/2n//Rlvw8hyM033yw/8zM/001bX1+X0Wgk//bf/tsvxyY+L3znd36n/LW/9teWpv35P//n5R3veIeIHLz27O4sr2T7P//5zwsgH/vYx7p5fu/3fk+MMfLUU0992bb9cthrUNuNe+65RwB57LHHRGT/t+mg4DCNKXk82X84bOOJSB5TRPZ3/5vHk2uHPJ7sTxyWMSWPJ4r93KbDNp6I5DHlWuEwjScih2dMOSzjicjhG1PyeLL/+979Op7sK3mruq659957edvb3tZNs9bytre9jY985CPXcMteODY2NgA4ceIEAPfeey9N0yy18a677uKOO+7Y121817vexXd+53cubTcczPb89m//Nm984xv5vu/7Pm688UZe//rX8y//5b/svn/kkUc4derUUpuOHTvGm9/85n3Zpre+9a184AMf4MEHHwTg05/+NB/+8If5s3/2zwIHrz27cSXb/5GPfITjx4/zxje+sZvnbW97G9Za7r777i/7Nr8QbGxsYIzh+PHjwOFo07XGYRtT8niy/3DYxhPIYwoc/P43jydXH3k82b84LGNKHk8U+71NQ3wljCeQx5SrjcM2nsDhGVMOy3gCh29MyePJ4eh7r8V4UlyVtVwlnDt3Du89N91009L0m266ifvvv/8abdULRwiBH/3RH+WbvumbeM1rXgPAqVOnqKqqO8gJN910E6dOnboGW/nc+NVf/VU+8YlP8LGPfeyS7w5ie770pS/x8z//8/ydv/N3+Pt//+/zsY99jL/1t/4WVVXxzne+s9vuvc7D/dimH//xH2dzc5O77roL5xzee37qp36Kd7zjHQAHrj27cSXbf+rUKW688cal74ui4MSJEweijfP5nB/7sR/j7W9/O0ePHgUOfpv2Aw7TmJLHk/3ZnsM2nkAeU9I8B7X/zePJi4M8nuxPHKYxJY8nPfZzm4Y47OMJ5DHlxcBhGk/g8Iwph2k8gcM3puTx5OD3vddqPNlXpMdhw7ve9S7uu+8+PvzhD1/rTXnBeOKJJ3j3u9/N+9//fsbj8bXenKuCEAJvfOMb+cf/+B8D8PrXv5777ruPf/Ev/gXvfOc7r/HWPX/8+3//7/mVX/kV/s2/+Td87dd+LZ/61Kf40R/9UW699dYD2Z6vNDRNw1/8i38REeHnf/7nr/XmZOxT5PFkf+KwjSeQx5SDjDyeZFwJDsN4AodvTMnjScZ+Qx5TMq4Eh2FMOWzjCRy+MSWPJwcb13I82VfyVtdffz3OOU6fPr00/fTp09x8883XaKteGH7kR36E9773vXzoQx/itttu66bffPPN1HXN+vr60vz7tY333nsvZ86c4eu//uspioKiKPiDP/gD/tk/+2cURcFNN910oNoDcMstt/A1X/M1S9Ne/epX8/jjjwN0231QzsO/+3f/Lj/+4z/O93//9/Pa176Wv/SX/hJ/+2//bd7znvcAB689u3El23/zzTdz5syZpe/btuXChQv7uo2p83/sscd4//vf3zHecHDbtJ9wWMaUPJ7sz/bA4RtPII8paZ6D1v/m8eTFRR5P9h8O25iSx5Me+7lNQxzW8QTymPJi4rCMJ3B4xpTDNp7A4RtT8nhycPveaz2e7CvSo6oq3vCGN/CBD3ygmxZC4AMf+ABvectbruGWXTlEhB/5kR/hN3/zN/ngBz/InXfeufT9G97wBsqyXGrjAw88wOOPP74v2/it3/qtfPazn+VTn/pU93rjG9/IO97xju7zQWoPwDd90zfxwAMPLE178MEHeelLXwrAnXfeyc0337zUps3NTe6+++592abpdIq1y5eyc44QAnDw2rMbV7L9b3nLW1hfX+fee+/t5vngBz9ICIE3v/nNX/ZtvhKkzv+hhx7iv/yX/8LJkyeXvj+IbdpvOOhjSh5P9nd74PCNJ5DHFDh4/W8eT1585PFk/+GwjSl5PFHs9zYNcRjHE8hjyouNgz6ewOEbUw7beAKHb0zJ48nB7Hv3xXhyVezQryJ+9Vd/VUajkfzrf/2v5fOf/7z8jb/xN+T48eNy6tSpa71pV4S/+Tf/phw7dkx+//d/X5555pnuNZ1Ou3l+6Id+SO644w754Ac/KB//+MflLW95i7zlLW+5hlv9/PAt3/It8u53v7v7+6C155577pGiKOSnfuqn5KGHHpJf+ZVfkZWVFfnlX/7lbp6f/umfluPHj8t//I//UT7zmc/In/tzf07uvPNOmc1m13DL98Y73/lOeclLXiLvfe975ZFHHpHf+I3fkOuvv17+3t/7e908+709W1tb8slPflI++clPCiD/9J/+U/nkJz8pjz32mIhc2fZ/+7d/u7z+9a+Xu+++Wz784Q/Lq171Knn7299+rZr0rG2q61q++7u/W2677Tb51Kc+tdRXLBaLfdumg4iDPKbk8WT/t+ewjScieUxJ2E/9bx5P9gfyeLL/cZDHlDye7M82HbbxRCSPKfsBB3k8EfnKGFMO8ngicvjGlDyeKPZb33sQxpN9R3qIiPzzf/7P5Y477pCqquRNb3qTfPSjH73Wm3TFAPZ8/dIv/VI3z2w2kx/+4R+W6667TlZWVuR7v/d75Zlnnrl2G/08sXsAOIjt+Z3f+R15zWteI6PRSO666y75hV/4haXvQwjykz/5k3LTTTfJaDSSb/3Wb5UHHnjgGm3ts2Nzc1Pe/e53yx133CHj8Vhe/vKXy0/8xE8sdST7vT0f+tCH9rxu3vnOd4rIlW3/+fPn5e1vf7usra3J0aNH5a/+1b8qW1tb16A1imdr0yOPPHLZvuJDH/rQvm3TQcVBHVPyeHIw2nOYxhORPKYk7Kf+N48n+wd5PNnfOOhjSh5P9l+bDtt4IpLHlP2CgzqeiHxljCkHfTwROVxjSh5PFPut7z0I44kREXnuepCMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIz9jX3l6ZGRkZGRkZGRkZGRkZGRkZGRkZGRkZGRkfFCkUmPjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIxDgUx6ZGRkZGRkZGRkZGRkZGRkZGRkZGRkZGQcCmTSIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyPjUCCTHhkZGRkZGRkZGRkZGRkZGRkZGRkZGRkZhwKZ9MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIOBTIpEdGRkZGRkZGRkZGRkZGRkZGRkZGRkZGxqFAJj0yMjIyMjIyMjIyMjIyMjIyMjIyMjIyMg4FMumRkZGRkZGRkZGRkZGRkZGRkZGRkZGRkXEokEmPjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIxDgUx6ZGRkZGRkZGRkZGRkZGRkZGRkZGRkZGQcCvz/ATn22Q1gfAkGAAAAAElFTkSuQmCC", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "info = info_from_trace(trace)\n", - "latent_labd = info[\"latent_color_space_d\"]\n", - "observed_labd = info[\"observed_color_space_d\"]\n", - "\n", - "def normalize_lab(lab):\n", - " l = lab[...,0:1]\n", - " ab = lab[...,1:3]\n", - " length = jnp.linalg.norm(ab, axis=-1, keepdims=True)\n", - " black_or_white = length < 20.0\n", - " black = black_or_white * (l < 50.0)\n", - " white = black_or_white * (l >= 50.0)\n", - " ab_normalized = ab / length * 100.0\n", - "\n", - " return jnp.concatenate([(black * 0.0 + white * 100.0 + (1.0 - black_or_white)* 50.0), (~black) * ab_normalized + 0.001], axis=-1)\n", - "\n", - "\n", - "\n", - "\n", - "fig,ax = plt.subplots(1,4, figsize=(20,10))\n", - "ax[0].imshow(trace.get_retval()[\"rgbd\"][...,:3])\n", - "ax[1].imshow(b3d.colors.lab_to_rgb(normalize_lab(observed_labd)))\n", - "ax[2].imshow(trace.get_retval()[\"latent_rgbd\"][...,:3])\n", - "ax[3].imshow(b3d.colors.lab_to_rgb(normalize_lab(latent_labd)))\n", - "\n", - "normalized_observed_lab = normalize_lab(observed_labd)\n", - "normalized_latent_lab = normalize_lab(latent_labd)\n", - "\n", - "rr.log(\"img\", rr.Image(normalize_lab(observed_labd)))\n", - "rr.log(\"img/latent\", rr.Image(normalize_lab(latent_labd)))\n", - "rr.log(\"img/rgb\", rr.Image(trace.get_retval()[\"rgbd\"][...,:3]))\n", - "rr.log(\"img/rgb/latent\", rr.Image(trace.get_retval()[\"latent_rgbd\"][...,:3]))\n", - "angle = jnp.arctan2(normalized_observed_lab[...,1], normalized_observed_lab[...,2]) * 180.0 / jnp.pi\n", - "latent_angle = jnp.arctan2(normalized_latent_lab[...,1], normalized_latent_lab[...,2]) * 180.0 / jnp.pi\n", - "rr.log(\"img/angle\", rr.DepthImage(jnp.arctan2(normalized_observed_lab[...,1], normalized_observed_lab[...,2]) * 180.0 / jnp.pi) )\n", - "rr.log(\"img/angle/latent\", rr.DepthImage(jnp.arctan2(normalized_latent_lab[...,1], normalized_latent_lab[...,2]) * 180.0 / jnp.pi))\n", - "rr.log(\"img/angle/diff\", rr.DepthImage(jnp.minimum(jnp.abs(angle - latent_angle), 360.0 - jnp.abs(angle - latent_angle))))" - ] - }, - { - "cell_type": "code", - "execution_count": 597, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0.], dtype=float32)" - ] - }, - "execution_count": 597, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "jnp.minimum(jnp.zeros(10), jnp.ones(10))" - ] - }, - { - "cell_type": "code", - "execution_count": 504, + "execution_count": 826, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "[0.03172414 0.33631578 0.085 0.03 ]\n", - "5707.9937\n" + "[0.1 0.2 0.01 0.002]\n", + "3570.5098\n" ] } ], @@ -333,9 +325,9 @@ "]:\n", " key = jax.random.split(key, 2)[-1]\n", " outlier_probability_sweep = jnp.linspace(0.01, 0.1, 30)\n", - " lightness_variance_sweep = jnp.linspace(0.03, 1.0, 20)\n", - " color_variance_sweep = jnp.linspace(0.03, 0.1, 15)\n", - " depth_variance_sweep = jnp.linspace(0.03, 0.05, 15)\n", + " lightness_variance_sweep = jnp.linspace(0.2, 1.0, 20)\n", + " color_variance_sweep = jnp.linspace(0.01, 0.05, 15)\n", + " depth_variance_sweep = jnp.linspace(0.001, 0.002, 15)\n", " # arguments = Pytree.const((\"outlier_probability_background\", \"lightness_variance_background\", \"color_variance_background\", \"depth_variance_background\",))\n", " sweeps = [outlier_probability_sweep, lightness_variance_sweep, color_variance_sweep, depth_variance_sweep]\n", "\n", @@ -366,97 +358,31 @@ }, { "cell_type": "code", - "execution_count": 532, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 532, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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+Sjq3HqXSNMuPQzrGsougYywni0kCbLeEkxrE6IT88Cuw3RxJ3EDZ/knr0arsJ4nbZDJDWE4K6AxY9rIjoKA6dRe54cupHvgOtaN34+XG8fOTAOi4TXvhKeaj/8PQln+Lk+o7my+5EOKnJGFGCHFKxhjmFn7IYmUXWpexlMIYhVLJ0sJ4GiwLy3JxvAz16iztdhtLWSQa9NJAYQyd+5IEjEXSGS1M2yySyzkkOsZ181iWQxIt4qVGSec3kcQNDBG2lSJbvBTLyYFJOuvaKKuz5UHzGJbVaYnxUkMEtf0n1EMnIUH9KJbtYbvZE4676SFai7upHb2bxuxD+IVJQBFUD2EA283i96+jPb+HxuwjFCevO6uvuxDipyNhRghxSq32UcrVXUAAdPZB6oSIzl5LqKUWFxRaK4IgwFIW4KGNoRUEWNrgOi6WBVGUdBYOVhY6MbRaZWx1H6X+S0m5aaLWYRy3n1R2LcZEJFEVS9koK4/l5DtTstUzy2NF7Vm89DBuehiATP/F1OfuJw6rOF5h+TyjE5KwhuPm8NIjJ9SzM7NKEdQOkYQNkrBJu3IIHbU6m4FbDm52CDfdR2P6PtL9G7GcFI5fOOFaQohzT8KMEOKUGs19aB2ik8bShpKd8KIsu7PAHc9MzbaVTT4/QRIGGGMIwiYkCcq20Mai3Qw6g26VhU4SwqgzALfeiljVfw2ZzBhaRyRRGZO0iIMQNzVM34pfoL7wGFF7Bjc1tLQHlCZqz6F1SH7waizLAyBVXEd+9GVUj/2AOFjE9fsxaMLmLEopnPQwtpc/oZ46CQALy/JpVw6SRAGOn8fNjaCUQscB7fJBmrOPY7lZGuV5bMcjO3QRxcmXkSqMn5s3RAhxUhJmhBCnFEVVLOUtjXFhaS07dfxJBjCdDSUdJ0UUaDAhab+A0RHtRoUgSIiiEFCdqd1Ls6EAgjAgiB0mJ94EdIJFEpUBheP1gXLw0hNUZ39Iq/YkTw8odrwSfePbyfZdtlwUpSz6JrbjpodozN5P1JoFFJnSBjLFTdSm70fH7eUxM9DpSmvXDuHnJrBTfUTNObzcOLb37O4oRRI1CWuH8Esb8LODJHGL8sEf0Jx/ktHLbiRdWnXq17G5SHtxP0YnOOkS6f41qOPGFAkhToeEGSHEKdl2Bm0iHGeAzmIxSxtDwjOhZGm/SaOWpmejiRNDFLaxLIsosgjajaVp3J3HWdbTG0l2wkSl8sTyc1q2j2Uf3xVUGHoJmeIm2vV96LiF5aSxvSGC1iKL0w/gpUpkiys7KxBbDvmhq8kNXE4cVlHKwvYKndYXDbXZXTheAdsrYHRI2JrFTfXTv3oHrYV9KMvBJAHwTJiJmrPErTK2m1167iy2l8VND9Cce4L5p77Jiqve9UzoW6KTiMU936Z66B7i5iIohbIc0gNrGNj8elJ9k2f6LRPiRUnCjBDilLKZVVRqD2JbeRyn2JkSvdSkopSFMnqpn6kz3TpJYhzHRcdgrM4O2m4qTavV6HQxGUOiO4vm2fbS/k6WvdxN9Fwcr0Cu/3K0Tpg59H1mD99GuzkHGGzbI1day4r1ryNbmOiUz3JwU/3Lj7edNIMbfolUcTW1mfuIgwrKciiOX0t+5GpS+UmC8iHc/CpMXCNqTGO5WTAJQe0IylJY3iBY6aWp5QqlFKniBK2FfbQrh05onVl44g4Wn/gmbm6QzMhmlLJIohbN2SeJ219i7CVvx8sNn6m3S4gXLQkzQohTymQmyWc3Ua4+hOetJUkexOilbQmAzuhYWN7XwOil3a5jAIyysC2rs8WBTnh6IydjDNpoXOViWR59g1c97zJNH/guh/Z8FdfNUCitwXJ84qhJZf5xwqDCusv+HensiYN8AWw3Q3HFy8mPvpQkqmNZLraXe+a4n8dJ9eNlNxLVjxA1Z9FxiLI8nMwo2oDjF5b2hlp6jJdFx22SoHbcc4X1WWqH7sHND+NlB59VhjSZ4Y00ph6ldvh+BjbveN51F0KcnOyaLYQ4JUs5DA/+DAN9W3G9FRhdwJjO9OzlsTNGAS4Yt9PNYhS2nSLRBstyOhtDGp553FKLhtEGsLGsDMakmDryQxr1Y8vPrXVC0FokaJc7ey8BjfJ+Dj76BcLaIcLGYaqz99Gs7EVZFsWBTTSrh5k/et9Prpft4qb6jgsyAJn+DbiZQXQckBm+gvzkK8lNvBw7MwGWhwL8/PGDfXUSdhYAdI5f36Y1v4+oVcbNDJzw/EpZuNkB6kcfRCfRTyyvEOK5ScuMEOI52XaKwf6X0WjMYjkbwBxBJ/MkOun8IcfCMtbylOkk0YCN0QbHdQlaIVEUYVn2UigxJFp11qFJImzb5tC+b+O6GTwvx8DQpaTSgyzMPEyrMQ0osoUV9PWvZf7Qt6mX95ArrsayPbSOaFb2ErUXyQ1sIZUZZHHmQcbWvBrbOfniec/FSRXpX/sa5p74Ks35PbiZQZTlYjkOQfUI+dGrOovsPUtQO4ZfGCdVXHnc/SYJl7uiTsZyfHQSYnQMJ1mxWAjx/EmYEUL8RPXGQRqtI/T3XYox66jXHyJoH0JrsJTurMyrLGzHRScKoyMcx8EYQ6vZRBsLnYClbOI4IQhiEq2xLHBTinL5IH3960jZPk888ncoA6W+jfjpPowxlOef5Ni+f8ExMY7Xh7M0vdqyfYyTIWrP06odxE0PkcQtdBK+oDADkB+9AtvNUjt2L+3yAbTR5Ecuw/EHwPLROsK2bHQSEdaOYXRM3+rrT2iZcdJFQKGT6KTbK8TtCn5hHOsUKxYLIZ4/CTNCiJMKoyrVxkGiqMbC4sNEcQPL8lDKJ5O5BJ00gGhpB+3ONGNbWSjfwrZttEmoVsrUGw0cu7ObdhQlhGFnDydLKTw3j+eksJTN3OwjxEGdsFnBdn1S2UHcpdV6bdumVX6cVtjCxqB1jLW06aNSFrabJWzNorFIZ0ex3fRp1T0zsIHMwAbioNqZTu3naS3uY/7J22lXDmKSzvgfLz/K0OqfIT925QnXSA+uxy+MEyweJD247rhjSdhER23yE1ejLOntF+J0SZgRQpxgsbKbqbm7CaIyKJtadQ9at0FZFHJriaIplAWuu4IoqpOYNibRKKXRJgDVmZKtjUMqU6TdqAGaOIg6ezNZCsvOkMmOE0UNXC+P42aZm32UtJfrLLrXLi+HGZMEeI5PnOjO2jXNOTK50eXyWrZP2J7HtBaZ3PBzy0HndD17hd/MwAZSfWtolw+QBDUsJ0WqbzX2s9aseTbbTTNw0euYeeAfaEw9hpcfQtkecatMEtbJT1xNfsXlZ6Scz8UYQzB3mKA8BYDfP4bfv+KU3V9C9CIJM0KI49Qahzky831Qinx2dWewbtKmXt9HvXUMYyIcVUbh4LhZLMuhXjsCxqCNwhgbgwbLJooVrlcgiSKCdoNYayzLxrF9PL+A66RJdEgQlikUVlMJ9uB7WWxF5xpPUzZYNrZtk8oOYqI69eph/FQJZTmE7TJRu8z4+uvoHz2xleTZkqhNbW4PlenHicM6Xqaf4vBmcoPrfmIIsiyHTP+65zzn2bIjFzF6zdupHryb5uweiNq42QH6N91AfuKqE7qmzrSovsjsj75G48hudNDq7DPlp8lNXszQ1T+Lky2e1ecX4lyRMCOEOM5idTdJEpDPPTOgNeUP0modBWyCcBblPLMrttZRZ9aStonjFmBQysFxvKVxK6Yzc8hKg6nh2A5aG5I4JAhr2LYPurO1Acomjtt4bhbXeWbROscr4Lg56o05Boe3kM+PUpl7gkZ9ChO1wMSMrn4l6y5/J46bOWXdoqDGkUe/Tm3uCSzbw3J8WrVjVKYepjR+OeObbsCyf/KaNz+NdP8q0v2riIM6RsfYXg7LPnMfvXG7Tv3w47QXp1CWRXpwkuz4RjCG6Z3/h/rBR0gNrcQZ7owziptVKnvuQUcBY6/4t1juma2vEN0gYUYIsSxOWtSbR/C847+xe14fmfQKGo2DxLqGb/loZaGTFnESADZR1ESbGDA4tiKOYixslKUwNmhLYXSDVhSgtSYKExYXy7iuT6EwgueXSaVK6KiJVyrip/uWn18pCyc1hMUBXMsinRkgs/p6gnaZoDGN52UZXvtzuP7xU61/3Mzef6U6+zi5/jXHhZY4bLJ4+D787BBDq7aeyZd0mfMTyvZCNKae4thdX6a9cHRprR8DyiI7uo7C+CYahx8jM74By3mmrk6mQGZsPfWDj9A8+gS5VZec8XIJca5JmBFCLDPGYDBLO18/QylFPr8Ox8lQLj+ANgqlE2zbJeUPUmnuI0k6Y2UcR3X2O2oHxDrCsTozeRqNOgabMGwQxwaw0FqTtBskyTGarQbDQ2vpH9yMY/tEQQ3PL2CMIWyXCYImY6tfQy7XR7t+CINBKZtscZLS6FbShVPvjQQQNOepzuwmlRs5ofXF8TI4fp7KsQfpX3HFC54JdS6F1TmO3vkPhPUFcis2Le/1pOOQxtE91J68Fy9TOC7IPM1yfZRSNI7ukTAjLggSZoQQyxw7Rdrrp946iucev7u0UhaeP0CucAnFTJ6wfRiI0UlInLRRChzXwbIUtWqdZGkqNhjCMMBYCsu2SeJOI4JtO2Ac4iRCm87spExhLVe9/APMH7ufxfk9NGpHAfD8AmOrXs7EmtdgWw7txhF0EmA7afzsipNOff5xQWOBOKiTyo+e9LiXLhE05ohaZez8yVcQPp9UDz5Ce/EY+ZUXH7cnlOV4ZMfXM3v3V5a7Ak/KdknC5jkoqRBnn4QZIcQypSz6ipuoNQ8TRXVc95muEWMSmq1pCtlVrBh5OfOLP6TZfIJ6cAjXc7GUi9bQbifU6p0F43zfI9GaOE5I+RmCeg3HTWEpq9MCZLl4fpE4DhkevZokgTAKWbfll2nWp55ZNC8/Tjo7tFyWTHHtC6ibWuqK0Z0BxT/GGNM5rnpjqnT9yOM46fwJm1tCJ9BYXoagMnvKx+uwhVeQfaHEhUHCjBDiOKX8OlrteeYWH6QdLOA4nZ2z4yQglx5jfPhaPK+PoYFXMm/5VGvTQJY4bqONwnYciqUiQbOJMRpjNNlMH7alSMKYrO1jUHhuP1EUEQZ14rhFpXwIheKxh/4P2ewQufwY2fzYGatXKj/SaX1pLpDKDZ1wPGjOk86P4mf6T/Lo849J4uU1akwSk4QtFArbz4Bl4RYH0Y0KQWUWN1vsbAy6NPA4rMzgZArkVl502uWIm3Xaxw6g4wgnWyQ9thJlP0eLkBBngYQZIcRxlLIZG9pKLjNOpfYUrWAe2/Yo5tZSzK9dnmUURQu0WgexlINSGbTRxEmApRSpdJYk1izMzaEshWu7eG5nHIplWzi2R9BuEgRNjIlx3BT5/Dit1iK16hGeePQrXHTpm0ifwWDh+nn6xi5j+qlvYzsp3NQz3WhBYx6TRPSvuGJ57Mn5Lj2yhvqxPZg4pjV7iKTdBAVutkhqYAIcj8zQWsqP3oUOA+x0Dq84gO152KkMg1e9rnPeC2S0ZvGBnVQe2ElYngNjUI5LesVqBre9lvTYc49hEuJM6np76sc+9rHl/Uuevm3evHn5eLvd5r3vfS8DAwPkcjne/OY3Mz093cUSC3HhU8qikFvF5Nir2bj6Layb/AUG+y5dDjLGGKq1R2m3pnGcNHGUEIQJJgHo7KCdymSxXA+FheN4YAypVJY4irBshyiqo1Rn9+x0uh/LsvG8HCOjl1GvHWVm6uEzXq/B1S9jYOVWolaZ6uxu6vN7qc7sRichI+teSXF0yxl/zrMlP3ERYXmWhcfuJAlaOOkstp8hqC4w+9C3CY4eREea1NBq/NIIJgppHtlHWK3Sf8mr6dvyitN6/sVddzL7va+io4jM5Aayay7C6x+mtucRjnzlbwhmj/3kiwhxhpwXLTNbtmzhm9/85vLPjvNMsT7wgQ/wta99jb//+7+nWCzyvve9jze96U384Ac/6EZRhRCA1gHN5kG00bhukcQYABw3hVKGJInwPJd8Lk+1UieTGUKZiCQxNBo1Ws0qWgckiYXnF8jnV9BqlRkY3EAmMwBGMzfzGBOrtmGfwU0YLdtjbNMNlEYvob6wnyRq4qaK5AbWkMr11vgRE4Y4Xg4nnScJG51FBo3BxAE2Nkmjjl8axi8NYzDosI0B2rOHaU0f6nRTOS/stY0bVcq77sTJFvEHR9FRSP3gU7SOHUK3W1Qee4C42WDlL7+HzLi00Iiz77wIM47jMDp64gyDSqXC//pf/4u//du/5dWvfjUAf/VXf8VFF13ED3/4Q172sped66IKIZZEcQ3LdgnDBrbtYdsuOmlgjOkMSlUK38uQSjlEsWZwYAW246OUxcL8MWphFdvJYFk2rdYinlekXq2y+7Fv46ey5HMDS7tqn9kdpZWyyJQmyJReeBfL+aB28FFSfePkV26hNX+IoDqLsiy88Y2Es1ME81PE7To+w52xNF5nv6rM8Epas4dpTR8gu2L9C3ru1pH9RJV5Mqs2oqOQ8sP30Z4+gp1KY6czmDhi8YG7UG6KFT97I7k1G89k1YU4wXkRZvbs2cP4+DipVIpt27Zxyy23sHLlSu69916iKGL79u3L527evJmVK1eyc+fOU4aZIAgIgmD552q1etbrIMSLiWX5WFaGOJrHmE73cCpVIo4cdNJCmxiFwbJ9bCuhHdRpNcqgoFAaxU/lSWIXS3lEsaZansdSNXL5GM/LMzezl0y2n3VTTzCx8opuV/e8FNbmsFNZvPwAXn5g+X4dBixMH8P20+igdcLjLNfH6IS4UXnBz62jEFAoy6Z5aD+tqcP4A0NYT7f0GIPl+cSNKrM/uJ3MxGpZaVicVV0fM7N161ZuvfVWbrvtNv7iL/6Cffv2cf3111Or1ZiamsLzPEql0nGPGRkZYWpq6pTXvOWWWygWi8u3ycnJs1wLIV5clFLkc+vAxKA6eygZY7DtNJbt4LoeRiuCVotGs0rYbtMK2iRJgo4DgnZAOtNPOjNIHIExFo7rYkwLx7XI5kqkM/089vBt1KoyRu5k7FQOHQUnHrAsUNZSN9KJAcIYDZjlmU0vhJPNg2WRtJs0jx3ETqWfCTKADttYforMxFra00doHHzqBT+XEM9H18PM61//et7ylrdw2WWXsWPHDr7+9a9TLpf50pe+9IKvefPNN1OpVJZvhw4dOoMlFkIAFAuX4fuj2Ba4rk0cN1AqwbIdjIEosllcLNNq1gFoNivMzs5y6Og0UeTgp4o0mzWCoEE6lQNjCNp1apUjZPMjjE1cQbMxz9TRx7pc0/NTfvIidByi4+i4+y3HxckU0EmEmz9xNlhUW8TNFEgNvfAveekVa0iNrKB1eD+63cb2n1kxWScxSdAiPTaJnUpjtCZu1F7wcwnxfHQ9zPy4UqnExo0befLJJxkdHSUMQ8rl8nHnTE9Pn3SMzdN836dQKBx3E0KcWanUECNDryabXU06NYjRCWEUYEyaJCmwOF8jSRJ8P0OiDfMLNY4enWN2rky1HuClCmgDtpMiCFrUm3XqjToai1L/ahzHx/OzLM4f6HZVz0u5iU1kV2ygcewpokalsxWF1oSVOXAssiOrievl5bBjjCGsLRBW58ivvxKv8MKnvVuux+C2G7DzBaLqPHG9RhK2CWanaO5/AhKDbodEi/MYo6WLSZx158WYmWer1+s89dRTvP3tb+fqq6/GdV3uuOMO3vzmNwOwe/duDh48yLZt27pcUiFELrcO1y1RyB9idvZBFhYP0ag3WVxcZOrYInEUYlk+xlgY4xNEVaKwTRgeAmURRxHVSoVEJ2htAE0Ygevdx9p1WzuDia3z7jvXecH204xufSNzqTyNI08QlKfBgJvvY+SlbyA9MM78g/9Ka3p/Z5aTMTjZAv2XvoKBy64/7efPrtrAxM+/nbBcYf7e78PsNEQRbr6A5fg0D+6l/tRjpIbHSI9KV784u7oeZn73d3+XN77xjaxatYqjR4/y0Y9+FNu2eetb30qxWOTd7343N910E/39/RQKBX77t3+bbdu2yUwmIc4Tvj+A7w/QV7qCRMdUq8d46KGvUFmssNBskM1msW2HWm2OMAxJ4pgoDtm3/3GCRpMkjshmcriOgzEJYFhYOAzYFIsDDA2/sBk3LwZutsjYtb9AUJ4hrM6jlIXfP4qb7ex6nhlbS3NqH3GjirJd0sOTeMXBM/LcSdCmsucJlJdDa5twYQ63UML1s9j5EiYKSMIWJtY09z+J1zfwky8qxAvU9TBz+PBh3vrWtzI/P8/Q0BDXXXcdP/zhDxka6iw3/pnPfAbLsnjzm99MEATs2LGDP//zP+9yqYUQPy4IF2k0j9Buz+A4VXJ5B6MHCcKAer1Go1HFth0sBXEcEgRtmu02AEmthm1bOI5Nyrdx7CZTU49TKr2CkbHTX3L/Qvf0ejI/znJ9cpObT/KI02O0Zvpfb2fhvh/iFvvIjk3iODZxENA8ephwYZ7cytX0XXoNbjpP9dH7KVx8BZZ//u9GLnpT18PMF77whec8nkql+OxnP8tnP/vZc1QiIcRPq9E8wmL5YZKkjeN0ZjSl0haF4gRTxw4zM3Nwaf0ZSOKQOI5J4gRLWSQ6JtIxcWwRtCEONe2gST43QKE0STpT6nb1xI9pHTtM+dEHSI1OQByhUOTWXYwOWiRhm7BSIbd6E/k1nXVo2seOEMzPkB6X7iZxdkhntBDitMRxg3LlUQyadHoE1y2Qz43RbsUkiSaXz+I4NtBZJTjRoLVZuiUkcUIUauLIEMWaZjsgDDStdptEx92tnDipxuH96KCNm8vTeV87Y5ucbAG/bxiv0EewON85Wanlc4Q4WyTMCCFOS6s9Qxw38NzS8n39/SspFEepVuaBmL7+AVwnjVIOSllorYjjhHYQEkUJoHBcF9d1QSkSbahWK8zPH+lWtcRzSNqt5Q057Uy2s0Bfq7l8XDkuSRgCEFfKuPkSXknGzIizR8KMEOK0RFEVpWyUUkBnCnArqJHNDhNGEVGUkE6nl76hu9TrbRrNBkEQohONMQZtDEmSYCl7KexEKKWoVRcwRr7Rn2/cfBGdxBhjsLwU/ugKklZjaWVg0FEbN5sjabeIygvkNl+Kncl2udTiQtb1MTNCiN6m1DNdSFHU5ujUo1SrMwRhCMoBDO0gZHp2liAICVpNQKMTA1qTzaTxXB8DxJ3lgEFZ+KksURTQaCySy73wNVHEmZdbvR6vUCKYnyE1OEJ65VqSVpNg+gg6joiDEKUT2lNHyG+5kuIVW7tdZHGBkzAjhDgtvj9ApfYk1eo+Fir7iKImmaxNJpvCYgVR1ObgoRkajSYKcF2PJImwFRQLgxRyeTzXxRhDHEUEYZskUdiOh+P6aJ10u4rix/j9gwy97BVMffdfaBzci9c/RHrl2s6u3DPHKEyuZuCqa8ltuJjMqnWyaJ446yTMCCFOi+f20w4WaTQOEcchCnuptSahUPIpLwZUKwHFwjCNehnX9YjjBgPFfnwvRStoEScxtlI4jstA/witoE3QThgaXEVGZjOdl/oufylONs/iQ/fSmjoKRpNbt4mJN95I6ZIrj9urSYizTcKMEOK0NJqHieIW4KOTNo7bCTIKBXg4TopU2iZJcjQaNXL5YVwVkfJtGo0aSaJRgO14hFGM58Vks3lcx+KiLa/EkT+K5yWlFIUNF5Nft5moWsYYs7T6r7xf4tyTAcBCiNNSqT0FBhxngDhxwKTApNAmg1JFXM9nxcQkRicYo2k2ymRzeRzHx3VTOI6LMYowiAiCiFYrxiSK9RtfwsbN1xNFAeXFaSrlWXQiXU7nG2VZeKV+/L4BCTKia6RlRghxWsKohrIcXDsFyiVOLGz7mT9qyrIpFIsU+8ZwnBRxFJHL9mFZNiiXhYUZmo2AOIqxHZc4aYNKk8tP8Ngjd7Lvqfup1xZRStE/MM7GzVtZvfay5dlTQgghYUYIcVocO40xCZ6fJu3naDQrpFKdKdYAjuMRx5okibn44p+hXJ6hVT+EYyniBJqNAGV5DI+M098/TiZTpF5f5O67/pmHHryTVSsvplgcQhvN7MxBZqYP0GxW2XLp6W+WKIS4MEiYEUKclkJuFbXGARIdUiqOkuiEdruOZdlYFiiliSMX38thDExMXEx5MUNtcR+N2jSpVJ516y4nm+vHsmwa9XmUZdFs1LFtn1y+H9/PAJBO5ygvTvPwg99lxcQmSn0n7kckhHjxkTAjhDgtxcI6Fqt7aDSP4Do5BvonaLUqtNplIMK2Srzy+jdRr9fY8+SPqCxOoawUfQNrqVYDcrkBstkS7XaNxYVjtNtNatUajUaTdtDi2NQ+Vq/a8szzlYY5fPAxjh55QsKMEAKQMCOEOE22nWJy7NUcnfkBzeZRgrCGURHplI/jDJDNTOB4bSYnV7Nu7TXUanMYDEZrvvwPnyQK61QrMyyWZ4iimHR6AKUCPE/TatXYv/dB+vtGKRQ6y+ErpbAsm2aj0uWaCyHOFxJmhBCnzfMKrFrxOuqNQ8zM7SJKmmRSI9h2ZxXfdrtGFD1BqagZGOjsnFwuT2NZLtV6jWp1gXq1Qv/gCjw/i+N4hEGbVCpHFMccOrSbi7dcy9NDfhOd4C11PQkhhIQZIcQZoZQi0TG2k8F1B5mdO8z8/IPESYRl2fSV+oiimGx6mEajxqOPfBvLtmg1GzQbDTw/TbO+SBy28VIZFhenyBcGGegbpVKepVEvk8uVaDQq+H6GsfF13a6yEOI8IWFGCHFGaJ3QbM1gtOKpgw9SqcyRTudJpbIkccTU9FGarTK+N8r8zFGq1XkuuvhaWq0GM9OHcbJ5LNun0SijLItcvg/XdjFooigkDFqU45BaZY6LL30Fg0OT3a6yEOI8IWFGCHFGGJOgdczc/DGq1Xn6+kawlAUYXMfB91M02ws89vidWNqiWBjE83w2bX4pR4/sIwybaJNgOy6ZTIH1G15KrTLH3MxB2q0qc/OHGR5exZXX7OCSy37mtNeZidp1WpVpwkYZy7Lx84OkiyOy8JsQPUjCjBDijLAsB60N5cos6VQOSwEqQqkYMCggm/E5emQKB59SaRSAUmmIVau3cOzoXgYGxzDGEARNsrkSQ0Mr0SjWb3oJ173i3zA0NEEmWzztsjYWDlM+9Ahx0EDZLkZrarP7SeUH6V91OW46f9rPIYQ4dyTMCCHOCKUsFDkgxvVyoAKSJEQbg1IWrmNhWRaeDzrUxHGI6/oopVizdguV8hwLCzPksnmUsoijgMNzT1AqjfAzr7qRiclNZ6ScQWORxYMPY4wmVRxdbuExOqFdnWXh4IMMbXhZZ4ViIURPkL2ZhBBnTD43ThxbaFOj3ixTa9RpNBs0WtWl/ze4nk+pP0+9Nrf8uL6+YbZc8jJy2RJT04eoVhap16uMr1jHq1595oIMQHP+MEnUws/2HddVpZa6moLaHEF19ow9nxDi7JOWGSHEGVMsDON7w5Sre3A9G9dxUMoi0RBFmka4SDZdYmhwnLmZOcqLR0ml0hw98iRHjh6k0aiQ8nMMDq5h9ZrL2Xbtz5HJ5M5Y+YwxtKoz2G76pMct28FoTdiqkl7qBhNCnP8kzAghzqhisY9yzSIKQbkOjmPj2BaOneB5DtlMhlQmx6rV4xw5cB+PPXofhw8fwXEcCvk86UwOpWz2PvUQtuVw7XVvxPP8M1xK2aRSiAuJdDMJIc6YdlDDsqGvNIrnpjrrztgG2wHXdcnnSjiORbM9jzFVLMtQq7UYHBxjYmItA4Mr8LwUUVQjiWs89NAPeHLP/WesfEopUvkhkqh10uM6iTvje1IyAFiIXiItM0KIMyZJOjOXSoVRfN9DKY0xGrBwXQ+Foh3UwUC9MU21VsMYi1LfIEmSUK/XqFUrBEETUESx4jvf+hKe57N23WVnZFBupn8FzYXDhM0KXuaZmVFGa4LaPH5hgFRh6LSfRwhx7kiYEUKcMa7rY9suGBfXdjCEWJaPUjYGQxyHnfOcLEE8B5ai0Wywf/9eWq0mUdDG9TxyuTyuY+EZnyBss2f33Ti2w+q1l552GVP5AUoTWygfeYxWeQrL8TBGY5IYL9dP/8rLsGz5aBSil8hvrBDijPG9LMX8CLPz+/H9PGFUIdExxsRgDHESkcsOkssO0G7O0WjUmJ2dIZ8vopMYgyEIAuI4Jp/PYVk2A4MD+KksBw8+yvjEBjwvddrlzA2twsuWaJaPLS+alyoMky6NYLunf30hxLklYUYIcUYND66j2arQaB7DtlM4jkOShERxiO+lcewMjWaNVrtNs9kkl81hWwqTgOd6WJZNq92iWq1SLGUZHp4glysxP3eU8uIMwyMrz0g5vUzxuG4mIUTvkgHAQogzKp0qsHryavpKKzFGkyQx2kAcaxqNBrPzR5ieOUS9GZArFBkaHiYIAtrtFtoY4iTG6IRms0Wh0M/g4FhnrIwxaJ10u3pCiPOQtMwIIc64dCrP6omXMjXrU63PsLAwQxTGeJ6PbTtEcUCjqXH8FJNrV2O05tixIzSb9c4qwV6afGGIiRVrcByXIGjieh7p9Jlbc0YIceGQMCOEOCts22WofzNz84dptxukUhmUAq1jXNvHMi4a8FMu45PrSKezlBcXyGRL5PIDNBo1PC+F1ppKeZbRsbUUioPdrpYQ4jwkYUYIcdbYtk8YJvh+Hs9NY9AAKCxSmSyLi3PYlqIZRrTjFG66H22g1aqjVGdpu7mZg5T6Rtiw6ZrT3in7xSput6keOkj96BFMnJAeHKSwahWpUl+3iybEGSFhRghx1miToE2C56Q7wSZqonWEMQZDgu+7JEmE67q4rk+cJNRbNexWk5WT68gX+hgdW8f4xAYyGVnI7oVoLSxw+PvfozE1heXYKMtm8ck9zD36CGMveSl96zd0u4hCnDYJM0KIs8axfTwnQ6O5iCYhSULM0hTtJIlwXBdlQTqrmDk2h04SPC9NodDPq1/77xgensS2ZffqF0pHEUfu/D7N6SnyExNYS6+lMYbW3BxH7/ohfrFIZmi4yyUV4vRImBFCnDVKKYYGV1PZN402EUopDJokSTDaoJTCcVwGBvvxnX7CtiGXK7K4OMtieY6xsdXdrkJPqx09QmN6mtzY+HKQgc77khkaonrgAOW9eyXMiJ4nYUYIcVaNDG/k2MwTlMtHsWwLx/HROkabBGUUnpfHd1O4/TY6ygJQr1ep1srdLfgFoL24CEmC5bonPe7mctSOHD7HpRLizJMwI4Q4q1zHY2R4LWHUJArbxHGMTjTGWKTTRVwnBRhQBujs45QkMf4Z3yn7RciY53HO2S+GEGebhBkhxFmX8nLk8n2k3CxxEtNqNSiX53Gd1HLXUxRFVMpNLGxQMDw80e1i97xUfz9YFjqKTto6EzXqlNat70LJhDizJMwIIc66TKYP23LQJsb307iOTxAEtFp1LEvRDtssLlR44rG9hEHAxMRalDp514h4/vLjK8iOjlI/doz8ihWoZw8Anp/DSWcorVnb5VIKcfpkOwMhxFmXTfdRyA6R6IQobGFMTKnUh+M61GoVGrU69WoDz/MplQao1xt87etf5NjUoW4XvadZrsuKbS8nMzJC9chh6keP0Jg6RvXgQZRlM/6ybWSGZfCv6H3SMiOEOOuUshjsX0uiE8KwCQpsy6HZCNHawXU8FCED/UM4jodSinJ5lu9972tsf80vMjAw2u0q9Kz0wABrXrtjadG8o5gkJj04RGHlSlJ9/d0unhBnhIQZIcQ5kUmXGBncQKU+TRB0xszUaw38VJ5GrYltOXhuBqU6Dca5XIFKdY4HH/o+l27ZxsDguKwA/AI56TT9GzfRv3FTt4sixFkhYUYIcc5k0iXSqQJh2KRWeZQjhxcYG83SbrWwLA+lLJQC17XwvAxJnFCtzvPk3l0kuk1/3wpQFnOz00RRgO+nGRwcwXbko0yIFzP5BBBCnFNKWfh+jmymjyjUtNtNjDHYdqdFxnMtbFvRakdgIJsp0Go2adQrzM9Nc/jgUSrlMsZoLMuif2CYi7Zcydj4ZJdr9sJoranPzlKfnUEnCX42R3FsDC+b7XbRhOgZEmaEEF0xObGK0ZEVLFSmGOgv4TgemATbhiTRBO2AoaFRbKczq6nVajN1bD9RlDA0PIptO0RRyOLCHD+6+3ts3fYqhkfGu1yrn07UbnP4/vtYPHwIHcUoW2G0wc/lWXHZ5fSvWtXtIgrRE2Q2kxCiK2zH4eprXsKKiRVk8xlyhQyFvgJe2qfRbJDJZOnr6ycM26RTGeZmpzDGUCqVsO3O9zDX9RgeGafdavLkE49gns8icecJYwxHHtjF3L69ZEolShMrKI6NUxwfR8cRh+67l9rMTLeLKURPkDAjhDjnjDEsVmbI5Hw2btiCpRxq1SpBu4WfSjE+McHEilVgOvs3pfw0zUYd309zsiVri6V+ZmePUatVzn1lXqDW4iLlI4fJDgzg+M+sdqyUIjswQBy0Wdi/r4slFKJ3SDeTEOKcC6M29cYinptmdKRAsdDHocNP0WrVUAr8TIqg2QZtGBmeIO1n0Fpj2xZanzijyXFckjgmjqMu1OaFaSwuEAcBucHBkx7383mq09MkUYR9ir2VhBAdEmaEEOdcO2igdYLjd/5Ip9NZVq/eRK26wNz8MRSaQqnEQGGEfL5Is9nAcW0ajQZRZOG5aXw/tXy9oN3C81KkUuluVemnZwBOPdX86W0ejNbnrEhC9CoJM0KIcy7RCajje7k912dgYIxcrkC1NgdAOp0iDNssLs7QbDY4dOAQtXpIKpVicHCYiYmVOI5DpbLIps2XkcnkulGdF8TP57FsmyQMsT3vhONBo0FhZPSkx4QQx5MwI4Q45xzbAaMxS2Nins110zhOGgXEOmF66hj79+8naCckiYNjR8RxxP79e1mYmyGfz1Es9uH7KeZnpyiWBnB6oFsmNzREfmiIyvQUxdFRlPVMuAsbDTCGgdVrZKFAIZ4HCTNCiHMu5eewHZcoDvHczuDXOImp1as0Ww3iJCKdyhG3Yg4cmsIYn8GhEXK5fhbmp6lVFtBJzLGpI2SzGxlfsZJmo8rePWVy+SKr1m4ikz11K02SJBzat5e9TzzBwvwcqXSatRs3sWb9etKZc7O+i2VZTFx5FfHdd1E5egwn5WPZNlGrjbItRjZfTGlCdg4X4vmQMCOEOOc816eQHaBcnaGtY4xRlKtlWkELBbiOhzGGaqOC4zlkCjl0bEilM4xPrKHZN8TMscNoY+Okssvry2itqVYWOLjvCTZsvuykKwMnccyd3/k2jzxwP0ZrUpkMC3OzHHhqD3tWr+VVr3s9hWLpnLwO6VKJddddT/nIYRYPHULHEcWxcUqTKymMjBzXWiOEODUJM0KIrijmB3Acl8XKLAuVeYKwjec4eF4a1+mME6mbOrZjYzkKY8AknWnZURCAgkKxSLvVQmvN7OwMx44cpdFsoIwm0YrNWy7Dtu3jnnf3o4/w4L0/YnBkhGzumdabOI7Yt2c3loLXvP7nSOdy56SLx8tkGN6wkeENG8/6cwlxoZIwI4ToCqUUuUyRdhDgNupoz5D2M8cFCNuycDwXgyFJQtqNEKMM9UYV23Fotlr0lXLsuu8+9u/bR5IkuK5LvV5ldm6R2bl5rr3uFXhLg2iTOObxhx7ET/nHBZkwaFNfXMTWmofvuYf+XJ6J1WsYWLGC3DlqpRFCvHASZoQQXaO1Joja2LaNrewTWkLS6Sx2pUyz1aDVaDN9bBqlLJI4JGq3OXrkCPv3HqBSqTI+Osqq1atJpdJksmn8VJZHHtxFPp/n6pdsBaBer1NeXKBQKi0/Rxi0KU9PEYUR2XyeWr1OEATUFuZp1+us2LRJAo0Q5zkJM0KILjPYloPBnDC7KQgC4iShUqlyYP9BHn9kN67vQqKpLJaZn5sjCmJ832NmZo69+w9wxRWXUyrkKRQKtL2Q3Y89wuaLtpDOZLAshVIK/ay1WxqLi0RhSCqTxdBpMXI8n1xfP/XyAnOHD5MtFGVWkRDnMQkzQoiusSwLz03RDgJsyyZJYizbptlqUqnWqNfraK1xPZ8wSlC2xeGDR6gsLmI7Dr7jkuiQVrsNKIxOuPuuu3nFz7yCVDqLwuLwwf088fCDjIyM4KczDAwOcuTQIXL5AnEYErRauJ4PSlGvVUlnsvQN9AOQyuZpViu06nUy+Xx3XywhxClJmBFCdFU2naPVbpD4KWq1KvVmnVq9SRwnWCiUZeGlcmzYdBGO43F4/yGKpT7S6TSFXI44TlhcWKBaqeC4Nq12m2NT06ycWE2zWiGJYxQKUDSqFYaHhji0fx/zszPkcnm01jieR7vVorq4yOZLLiWfLwCdzTCTOCFZ2iYhiWNalSpRuzMAOZXLkcqfm4HCQohTkzAjhOiqtJ+hmO8jjELaUUC93iKJNa5ro1AkGhwXsnmbdRs20qjV2fP4bsIwJDGGfD5PqVhkamqK8uIijuNy6MBBLt28hUarSbGvn4GhIVzPw/U8JlauptVqs3/fXg7t30u9XAYDfjrN+o2bueSyK5bLlsQxtmPjOC6tao3Z/QcI6o3lvS4t2yLb38/g6pU43vm/UJ8QFyoJM0KIrlJKUciWOHj0CM12RJwYHNdd2rrIwfUcXAOxE4HWXH711VTLFQ4fOoRSijAKyaQyjIyMEIYhnuMShhHVapl2O+DKzReTSqUwxhBHEVprVq5cydqNm6hUq+x99GGiZpNVGzYyODSM9ay1Xdr1Grm+fizbZmr3k0TtgHSxsHxOEkVUZ2fBaEY2rpcWGiG6RMKMEKLrWu025XqNODIk2mBj4/upZ60Ro3CNh207WLbNlssuZ2Z6mi9+4f8cd503vmEHA/39tJpNypUKl112BRddtIU4iqhXq4TtAGM0SRzjRwkrVkyybsMGjux5gqDZIokj1NIO3O1GHdfzGZyYoD6/SNBsku0rHT913HVJ53PUF8sUazXShcI5fNWEEE/rmeUlP/vZz7J69WpSqRRbt27l7rvv7naRhBBnSK1ZQ+un92qySC0FmSTRJFovzT4yeJ5HJpPl//kP/w9f/sevnXCdr3ztG9z6//4dq9asZuOmzVx51TVYlkV1cZGg1ewMGk6lcFwXpSzmp6Zo1BtMbNxMcWiQOAhoVCqE7Tb5/gEmNm0mVyzRWFjA9byTtrzYrotJEtq1BsYYynPzPLHrYR6+616efOhRaovls/8CCvEi1xMtM1/84he56aab+NznPsfWrVv5kz/5E3bs2MHu3bsZHh7udvGEEKcpiRMUnTEoruti2TZa6+O6fEARJxGvf+UNP/F64+MrSKU6m1UGrRZhEOCn0ijF0nUVqWwGY6C2uEixr4/JTRcRtJokUWecjJ/JopTCGIPR+jm3FjBKEccxD/3wR+x/dDftVgulLIzWZPJZNlx+CRsuv+TH6iOEOFN64jfr05/+NL/+67/Ou971Li6++GI+97nPkclk+Mu//MtuF00IcQa4nodlWTiuh+f5aP30ejMGltaf0UnM8x2R8v6bfh/X9YiCNq1GHdu2l4JMZ2aS4/nYjovrecRxTLPRQClFKpMlWyySyj4zQ0kphZ/LEYXhSZ/LaI0ycHjfAXbf9wB+Os346lWMrZpkbPVKLNvh4bt+xKE9e8/IayWEONF5H2bCMOTee+9l+/bty/dZlsX27dvZuXPnSR8TBAHVavW4mxDi/JVNZ8ims53tCxwXy7JIkmT5pnUCwI7rX/O8rzmxchWZfKEz6DeOicIQnRg8P00qm38mrBiFSfRzXis/OIClVGdK9rMYY2jV6ijHYerQEdLZLNnCM+vRKKUo9JWwbYd9jzxOkiTPu/xCiOfvvA8zc3NzJEnCyMjIcfePjIwwNTV10sfccsstFIvF5dvk5OS5KKoQ4gVK+ykG+wdJpVJYjo3r+rie19nmwO5MjXY9/6e6pp/JMzA6Rr7Uj+35pHP5TqtLLr/c3WOMwQC2+9w97plSkdL4GHE7oFGuEDZbBI0mzcUyjuvi5nM0anXyfaWTPr7Q10dlfkHGzwhxlpz3YeaFuPnmm6lUKsu3Q4cOdbtIQojnoJRifHCElSMTZP10Z0sB28XzUnheCsdxf+ppzwcPHubgwSOUBoewHQ/bcbF/7DpBq4Xne2SetenkqcrXP7mC0U3ryQ8MoJTCcmz6J1YwtnkjfjaDMeaUY2KUZXUGOGvzU9VBCPH8nPcDgAcHB7Ftm+np6ePun56eZnR09KSP8X0f3//pvsUJIbrLtm1WjIzRVyjy1OGDNJoNwijCGA10BuLe/v3v8NrrXvm8rlcuVzhw4CClvksp9JeoLixgOy6O52G0JgwCbMtiYGQEd2lX7eeilCLb30e2vw+jNSi1HIxycUw6m6FZqx/XzfS0Zq1GJp876TEhxOk771tmPM/j6quv5o477li+T2vNHXfcwbZt27pYMiHE2ZBJZxgbGmGgNMDIwBAYRb1ap1ap8cTuJ5/XNf76r79IHCcsLJSZm51jeMUKhleswHVd4jAkiRNyhTyjK1dS6O/7qcuoLOu4Fp5cscD4mtVU5ueJo+i4c8MgoFGtsnLjOryUfMkS4mw471tmAG666Sbe8Y53cM011/DSl76UP/mTP6HRaPCud72r20UTQpwFfYUC2hiarRYpz2e6Pk0mk8G2HT78n/4z/+nD//GUj/2f/79bMcaQJIY4brN/3yEGBgcplkoU+vuJo6jTjeX+9F1Xz+Wiqy+nWatxbP9BXM/H9T2CVhudJKzevJF1l158xp5LCHG8nggzN954I7Ozs3zkIx9hamqKK664gttuu+2EQcFCiAuDbdkMlvpop9PoOGHvU/uYmZrmqSf2oOOEX/uN/0CjUefv/vp/H/e43/5/fpc4NjixQZGANtRqDZ58Yi+5XI7VayfJZjNnpczpXJaXbn8lR/cf4PCefbQaDfqGB5lcv4ax1StxXNm7SYizRRljLvgRadVqlWKxSKVSoSDLjQvRc/71Bz/ge//6fQ4cOEg2m0VrzfzCIs1Gg2w2x8T4CpqtFq7jcdGmi3AsB6XAYCiWSmzauJZqtU42l2HTpnW4simkED3h+f797omWGSHEi9u2rVvJpNN8+f9+laf27iWbzeA4DgMDg/SV+ojiiHYQMDo8hm3ZGPX0dzSLdivk2NQsxUKe6aMzJEnC0NAAQ8MDuNJaIsQFQVpmhBA9Y7Fc5itf/ToHDh4ELBYWykRRiNaa4YEhJles7GxOqcBoMAaUssFojE5wHBvXdfE8l2KpwOaLNzAxOd7tagkhTkFaZoQQF5y+Uokbf/nfcODAQe6+51607oyv6esboJgvkcQRRifoRBGGIWEYEUUhcRhj2zb5fHZps8oMzUaT++99ENu2GRuX8XdC9DIJM0KInuJ7Hhs3rAflsGrVehr1Oo16i2azhU4MxkCr1SZamrWk44TO6BkIw4jZ2UVqlSb9g0WUMux9cj8jo0OyCaQQPUx+e4UQPcnzXGzbolgqoAGtwSiLKIpJkgTb7nxXM9rgOC6+66ITTaPRJIxCpo7N0WpFzM0uUKvVu1sZIcRpkTAjhOhJfcUClmWRyaTJZtJgKbSBRrPdWUfGsZd24nbwPBdtDO12SBTGaNPZsLZea1Cv1Ul+wkaTQojzm4QZIURPyudzDA/1U2+0SKV8HNvGUhBFMUEYE8UJGIXRhkajRb3eJIpjjDG0W20sSxHFEWGY4MlUbSF6moQZIURPsizFqpUrWL1ynEIxh2VZJEmCtbSpY5JoEm1oBzG1ag2daDBgAJ0YWq2AOIrJF/NYSj4KhehlMgBYCNGzbNtixfgIw0MDFPM57rnnQSqVGmG73dkIEkil04RhSBSGWLaNsiziJCasBoxPjHZWEj9zuxoIIbpAvo4IIXqe6zqsX7+Ka6+9inw+D0rRarUIoxjHcejr6yedzWKMQdGZzl0s9TE4NEz/QJGUbAApRE+TMCOEuCAopVi9eoLXv/4VTE6sIJfN49g2cRJj2RaZTI6+gWFK/cPkiwM4foZWK2RouF+mZQvR4+Q3WAhxQVm5coztr72WsbExBvoHyRcKWLaH46bw/TR+ysdxbYyGarXFvn1TvAgWQhfigiZhRghxwRkfH2bzRWvJFwrkckW0sUFZWLaFwiLRCo1CY7HrgSfZv+9ot4sshDgNMgBYCHFBWr9+gvn5MrsfP0irHaKUwmCIY40yncX0LKUwwJf/8fts2LiCSy9dQ6GQo6+/2O3iCyF+ChJmhBAXpEIhy/iKYR58cB8Gg6UsdKJp1VvUm02iKMRWClBYSnHs6DT33P0AIyMF1q1bxTUvvZSBgb5uV0MI8TxIN5MQ4oIUhhHTM4vk8ml8z8O2bSqVOvMLC7RbLTAQhCGL5TLziws0Gg3AwbY9HnjgMW77+ndYXKh0uxpCiOdBwowQ4oI0N1+lXm8xNFgiSTStVptqtYqyLHzfx7YtojDCti0cx6XRalGrN2m1ItasneDIkWkefPDxbldDCPE8SJgRQlyQoigGIJNNYzs29XqdOI5xbBuAJE5IdGdDSsuyO5tQ1htMTS2y96lj2JbDE7v30Wy2ulkNIcTzIGNmhBAXJM9b2jUbQzabJtEGpSyUUqAU2iztbWDAGI1SFkmiCYOYSrmBTiLqjTbtdkAmk+5uZYQQz0laZoQQF6TBgSKFQoZms43l2KRSPsYYtF4KMUt7GHTWmFFgDJZl02y2WFio02wF1CoN2q2om9UQQjwPEmaEEBck13XYsG4CP+WRJAl+KoVldzahNAZsx8GybZIkBgXKtrAsRRCGBEHE9PQClu2zMF/rdlWEED+BdDMJIS5YK1YMYTs2jmXTbAakUmnq9TqeUji2TTqVptVuEYUhtm0RtAOSJKbVbpHLZkmnCuzbP80ll63tdlWEEM9BwowQ4oI2OtLPa7dfw9q1Y/zonifYtesxqtU6cRR3WmlQGAPNRhOMwXE9+voGmFixAqVs5ueqhGGE57ndrooQ4hQkzAghLni2bbFxwyRr14xz+eXr+Kcv/4BarU6cJFjGxvVcojAEBZ7n4Xo+nqMol+ssLlTZt/cYGzZOyIaUQpynJMwIIV40HMdmy5bVGKP4/r8+zOJCjaAdYjB4+TyWUmitWZhfoFqpEYYR8/ML1Jt1tmxZw/WvuJyhIVkVWIjzjXzNEEK86KxfP8Zll61lYKCA67m4rgsY4ihiemqW6ak52u0I23HwPI9atckPvv8gX/7H71Euy4BgIc43EmaEEC86qZTHlVet5eprNpAvZEAp0ikfP+1RrzewHBvX9cAoolgTRwaweOThfey6f0+3iy+E+DESZoQQL0rptM/V12zgTW+6lnVrx0ilPMoLNeqNNkkCYRgTxZpmI2B2rsriQoNqtcm9P3qcOE66XXwhxLNImBFCvKhNTA7xlhuv54bXXY2yOwvp2crCdm0sy8IYQxxpWkFEsxGye/dh7r/vCR566CmmpxaWFt0TQnSTDAAWQrzoOY5NJpPGth0USwsEJxqtDXpp1WAdacKgRbPZ5p/+8V8ZGiqRSnusWTvOddddRiab6nIthHjxkpYZIYQApmfKZDIZlLKJogitDYnWGG0wxhCFAVprLMvhqafmKFcC0pkUjzy8j+9+dxdJortdBSFetCTMCCEEEIUx6XSKTC6L1pogCEiSBK01URiSJDG242JZDu0g5IFdT/Hdbz+CUg5P7jnM0aNz3a6CEC9aEmaEEAIoFDI4nktfqY9sJodt2+gkIUlitE6wbRfX8TsL5xkwBubnqzywax9HDs9z+NBMt6sgxIuWjJkRQghgfLyPYjFDOpMhF2tcP0UUhhhtaDQaaG1Qyn5mwO/S4Jp6vYmlDEcPL3S1/EK8mEnLjBBCAH19Oa64Yg3FUhbHsXFsj3Q6SzqTxXG9pd22DVrrpRHCoLWhXm8xM1Pm7nv2cN+9e6hWm92tiBAvQhJmhBBiyWWXruTlL9/EyEgJ27ExBuJE47g+xkAUJYAFSqETTbsd0Gq1aQcRe5+a4n/+j3/mL/78//Lgrqe6XRUhXlSkm0kIIZYopbj22k309WX56lfuZe9TU0SxRlkOvp+h1W6gkxhlW7SabeI4BhSu6xBFMXOzVarVOgf3T/PGn7+W7TdchePY3a6WEBc8aZkRQohnsW2LSy5Zya+/Zzv5Ug7LslEK0tkshXwR1/eJI02iDY7royyHOO6sKJwvZikWC4RRzLe+dT8/uvuJbldHiBcFCTNCCHES2sCq1SOkMmkUFnGiUbaHny7hpXM4bgplOYACZdFshuhEE4UJ2UyKMIx55JH9VCuNbldFiAuehBkhhDiJRiMgnfLo78uTymbIZtNoLLRRaAMYg04SlLIwBlrtiLm5GpVqi9nZGvOzNR5/7CgPP3Sg21UR4oInY2aEEOIkbNvCT7msWz9CqxXSaLZRSoOlcRwXZVmY5TDT2fKg2UoIwwSMJp/PcnD/Av/wpbuIQsO1123C9eQjV4izQX6zhBDiJIYG8xQKKcIgZv36UZ7Yc4xaLcS2LOxUhjBoEQUBGoNjL32UGojCCAXEEeRKLmGU8M9fv58wirn2uk1MHVug3Q5JpTwmJ4fwfLer9RTiQiBhRgghTiKVctmwfpT77t/P0HCemZkys7O1zgrACjLZImE7IAzaJAAKjDbYlo3npwijGGNgfLyfmekqX/mnu/jhnQ/jew6J1liWYmSkj5e9/GI2XzTZ7eoK0dMkzAghxClctHkMrQ1P7DlGoZjBtjvDDF3HBs8jXxygUa8QBi2MBtt28TwPx7ZJEkOtEbFv3zQzUwtUqzVyuRSXX76a9RvHcV2bqalFvvH1e3Bsi/UbV3S5tkL0LhkALIQQp2BZFpdeMsGO117Kq37mIgYG8igUSgHGYNsOpb5BCqVB0ukcnuvjui5+KoVlOdTrbRqNgDAM8X2HTCbF9GyVRx89jNaGyZVDRGHMvfc80VlZWAjxgkiYEUKInyCXS3HVVav5mVdspFBKY9sWWpulXQ0UqVSaVCZHOp0hk8lhjEU7iMBAudygVm1hjIXrOQwM5FlcqDM9UwFgeKTEkSPzzEyXu1hDIXqbhBkhhHgelFK85tVb2PqSdQwM5snmfRQKYwy2beN5LtooWq2QVitcamlRhGFCojXNZkil0qLdivBSLlNTZYwBz3OIo4QwjLtdRSF6loQZIYR4norFDP/mzdfwKze+jGu3baCvr7Mppec5OJ6DsqzOhpRLm1KiWNpl26CNptmMOHJkEZ1o4jBGa0293iad9sjl0t2unhA9S8KMEEL8FDIZnysuX8mvvusVfOQjv8CWSyZIYo1ODK7v4XpeZ1HgpVYby7JwXB+MIYwSFhebzM3W8FMuGJieXmTthnH6B/LdrpoQPUtmMwkhxAs0MdHPm37par4QJjTrAXMLDSwrg1/zWVhYRAGu52K7Lq1GjXazTRRaNJttBgZyPPrIQdatH2Prts3drooQPU3CjBBCnIZ02mN0tMT4eIkHHjhEebFJqxmTyWY7C+uFMVGsSYyLJkaHIcpS7Nkzi5fOkC8V2Hnnk8RxwthYH+s3jDI4KK00Qvw0JMwIIcRpyGQ8PN8hjjXj4yUWFxvESUwqncJ2bMqLNcIwxhhDKpvBtvIYbJTn8MijM+zbt8DmzWP09Wd59NHD3HfvXl75qi2sXjOEMYZ02uss1CeEOCUJM0IIcRoGB/OMjRY5eGiB0ZECY2MlDh9epN2OQVkY5aBscG0Ly7YB0DqhvFgj0Zp63SGVnqfRihgbLTI1Veazf/bPjK/oJ5f1GR4pcullq7jo4onlRfuEEMeTMCOEEKfBshRXX72KarXN0WMVxsZLrF4zyBO7pwjaMVqD7dgoy0IphbIUzWZzaUsDizjRzM3VSad97p86gI4TkigklXJxHJu773qKnT/Yw7Uv38i/ufFlOI58bAvx4+S3QgghTtPIcIHXvGYzjz52jIMHF1izepB6tc3MTA2tNUmsOxtUOhZhEBJFydKUbQUYgiBhdrZGtVLH8xzGRgvsfWqWxfkmrWZArdbm8ceO8tCDh/j133gNq9cOd7vKQpxXJMwIIcQZMDSY52euz9NoBARBzJVXruILX7ibfXtnqEdtLKsTXJIkAdNZhM9SYExnCne10qDRiKg3YxYXmniOWtqFOyaONc1GwPe/9zizM1Xe+e5Xsu3lG1FKdbvaQpwXJMwIIcQZlM36ZLM+L33Jag4fLtNshrT2zWJZilTapVlvoSwLtEYbg0KRxJow0YDV6WaKY+IQ9u+dJ5fz8DwbnRiMSdi/d4a//d/fp9SX5eItE92urhDnBRlNJoQQZ4FtW7xs6xouu2ySXD6N1oYwiEl0Z1VgC4VOOlseaKPQBoxJAI2lOh1Qcawpl1vMztVpNgPCMKHVitjzxBS3fXUXSSKbUwoBEmaEEOKsmZzs402/dCXXXruOfCGNZVs4roVtW+TyaXzf7Wx9oDsBxkCnCwrQ2pBojTaQxJooSgjaCfV6QKMRcO89+ziwf7bLNRTi/CDdTEIIcRatWFHife99FV9bPcTDDx9lfr7GgQOzBEFIvNS1lMQJSimMsTsL7CUak5ilKyi0Mdi2wvVswiCm2YyYmqqwZ880xVKWJ5+YotUK6evPsn79CNlcqptVFuKcU6YzpP6CVq1WKRaLVCoVCoVCt4sjhHgRCoKY/fvneWDXIe68cy/z81UWFmvUqm2iMMZPuUSRIWq3aTVaxFGMUWApG2M0KAtbmaWBwxau5/KSrWuJ4phjR8sAZDM+GzaN8ZZfeSlXXLm6q/UV4kx4vn+/u9rNtHr16s66C8+6feITnzjunAcffJDrr7+eVCrF5OQkn/zkJ7tUWiGEeOF832HTphF++cZr+MBNr2H7a7ewatUI+XwG3/NROLi2w9DIAH4mA5ZCGYMxBoMCbdBGYdk2ylLU6y3u+OYj7H1qlmIpw+BgnsQY7r93L3/x//0mux8/2u0qC3HOdL2b6Y//+I/59V//9eWf8/ln9iSpVqvccMMNbN++nc997nM89NBD/Oqv/iqlUon3vOc93SiuEEKctlWrBnjTm65kxYoS//efHuDJPdO0WiGe56CNwbI9UqnO3k5aayzAKAXKIkk6g4WbrQiloN2OmZ2p0z+QZXi4QKuVYv/eOW772gNs3DQm07fFi0LXw0w+n2d0dPSkx/7mb/6GMAz5y7/8SzzPY8uWLezatYtPf/rTEmaEED0tn0+xfftFrF07xN9/6R7u+ObjNBsh2hjAYPseDhZxFGGMRqFAKbSyiYKQJDGkUi5KKeI44ejRMkmsGRkp4PsODz5wkIWFBgMDuW5XVYizruuzmT7xiU8wMDDAlVdeyac+9SniOF4+tnPnTl7xilfged7yfTt27GD37t0sLi52o7hCCHFGrV07yE0fvIF3vuvlrFzdT7GYJpdPkcn6oBTK8bCcFMr2sGwPhUWy1P0URXDkSIVjx2rUqwGHDi1QrbZIZTwqlRZJnHS7ekKcE11tmfmd3/kdrrrqKvr7+7nzzju5+eabOXbsGJ/+9KcBmJqaYs2aNcc9ZmRkZPlYX1/fSa8bBAFBECz/XK1Wz1INhBDi9LmuzRt//jKCMOHeew/QakVk0i4/uPMpknYCSwN/jQatFAprafaTQSfQbIS02xGOrdijZsmkHCZX91MoZrpdNSHOiTPeMvMHf/AHJwzq/fHb448/DsBNN93EK1/5Si677DJ+8zd/k//23/4bf/Znf3ZcEHkhbrnlForF4vJtcnLyTFRNCCHOmk6302ZWrRygUmlRrrRJpXwsx8a2bSzLZqkHCtt2QVlorTGd1WnQiSGKNZVyk2NTZdZvGCOVcrtbKSHOkTPeMvPBD36Qd77znc95ztq1a096/9atW4njmP3797Np0yZGR0eZnp4+7pynfz7VOBuAm2++mZtuumn552q1KoFGCHHem5zs49d+7VpSaZe77t6P5znk852VgNutGCwDGmxH4fkpwnYLnSSdHbkBHUOj0SabT9Ooa/btnWNisg/XtbtdNSHOqjMeZoaGhhgaGnpBj921axeWZTE83NkRdtu2bfzhH/4hURThup1vGLfffjubNm06ZRcTgO/7+L7/gsoghBDd1Nef5d3vvpYVEyX+7m9/xOxsHcvSBEGCMmAMWJaFn8qgFERhiE6SpfYZhZ9K4Xk5/uWbezgyVWPVqgF+/ucv4aVbV3e3YkKcRV1bNG/nzp3cddddvOpVryKfz7Nz504+8IEP8PrXv57Pf/7zAFQqFTZt2sQNN9zAhz70IR5++GF+9Vd/lc985jM/1WwmWTRPCNGL/vqvf8RXv/oQzUbEwkKDarWNTnRnrExnMycMurPAnu4srJfJpFFYtNoR+UIKnRjSaZdffuuVvPOdW+nrk3E0onc837/fXRsA7Ps+X/jCF/jYxz5GEASsWbOGD3zgA8d1DxWLRf7lX/6F9773vVx99dUMDg7ykY98RKZlCyFeFLZv38hiucmP7j5ItRocv2aMAaVAKRvPs0m0BmOhlE0YRsSJJo4TLMtibr7O//wfO5k6WuX3/2A7AwPZ7lVKiLNAtjMQQojz2NRUjR/etZ9v3r6be+7eT7MeYtmqs3+TMViWQmtDHGtsy8KyFPVGhGUpMhkPrQ1BEBOFCZ7n8JKtq/jPH/9Z1q0b7HbVhPiJnu/fbwkzQgjRA+bmGtx55z7+5v+9h/3752k2A5K4s8W2bUGSgMIiiGKSRON7nXGGUdRZuytJOtO7Hcfm8itW8P/5j9u56iqZGCHOb+d9N5MQQojnb3Awy8///CW89rWb+N53n+I7332CRx46Shwb8nm/E3AaMSY0OE5n9lIUxaAslALLaDzfQSmLI0fK/OX/upt164YoFmWHbdH7JMwIIUQPSadddrxuMztet5l9++b53nef4siRMlGUsGf3HEopPM8hCmNAdVpttEZZCte1SRJDsS/D3qcWuP++w7zyVeu7XSUhTlvXtzMQQgjxwqxZM8Db/t01/Nu3XcNvvfd6Nm4ewrEt4jghSTor7HUGBivcpdYa17XJ5zutMU8+Nd/F0gtx5kjLjBBC9DDHsVi9up/Vq/vp78/w4T/8Grt3zxDFGqXAdRxsR2G7FihFPp/Cdx0CN8axZUdtcWGQlhkhhLhAXH31Sv7bZ97Etm1rOztqo3BdC9dzcB2bTNpjbKxAqxWSy3ts3jzS7SILcUZImBFCiAvIRReNcMt/fSO/fOOVlPqyWJZNOu3R359ldLxAojXawMUXjbJx0wtbrV2I8410MwkhxAVmcrLEx/7o9WzeNMI//MODzM83sB2LODakMi6XXDLKjTdeQX+/rAYsLgyyzowQQlzAZmfr7LxzP3v3LpBKOVx62RibNw0zMCirAIvzn6wzI4QQgqGhHD//C5d0uxhCnFUyZkYIIYQQPU3CjBBCCCF6moQZIYQQQvQ0CTNCCCGE6GkSZoQQQgjR0yTMCCGEEKKnSZgRQgghRE+TMCOEEEKIniZhRgghhBA9TcKMEEIIIXqahBkhhBBC9DQJM0IIIYToaRJmhBBCCNHTJMwIIYQQoqdJmBFCCCFET5MwI4QQQoieJmFGCCGEED1NwowQQgghepqEGSGEEEL0NAkzQgghhOhpEmaEEEII0dMkzAghhBCip0mYEUIIIURPkzAjhBBCiJ4mYUYIIYQQPU3CjBBCCCF6moQZIYQQQvQ0CTNCCCGE6GkSZoQQQgjR0yTMCCGEEKKnSZgRQgghRE+TMCOEEEKIniZhRgghhBA9TcKMEEIIIXqahBkhhBBC9DQJM0IIIYToaRJmhBBCCNHTJMwIIYQQoqdJmBFCCCFET5MwI4QQQoieJmFGCCGEED1NwowQQgghepqEGSGEEEL0NAkzQgghhOhpEmaEEEII0dMkzAghhBCip0mYEUIIIURPkzAjhBBCiJ4mYUYIIYQQPU3CjBBCCCF6moQZIYQQQvQ0CTNCCCGE6GlnLcx8/OMf59prryWTyVAqlU56zsGDB3nDG95AJpNheHiY3/u93yOO4+PO+c53vsNVV12F7/usX7+eW2+99WwVWQghhBA96KyFmTAMectb3sJv/dZvnfR4kiS84Q1vIAxD7rzzTj7/+c9z66238pGPfGT5nH379vGGN7yBV73qVezatYv3v//9/Nqv/Rrf+MY3zlaxhRBCCNFjlDHGnM0nuPXWW3n/+99PuVw+7v5//ud/5ud+7uc4evQoIyMjAHzuc5/jQx/6ELOzs3iex4c+9CG+9rWv8fDDDy8/7ld+5Vcol8vcdtttz7sM1WqVYrFIpVKhUCickXoJIYQQ4ux6vn+/uzZmZufOnVx66aXLQQZgx44dVKtVHnnkkeVztm/fftzjduzYwc6dO5/z2kEQUK1Wj7sJIYQQ4sLUtTAzNTV1XJABln+empp6znOq1SqtVuuU177lllsoFovLt8nJyTNceiGEEEKcL36qMPMHf/AHKKWe8/b444+frbI+bzfffDOVSmX5dujQoW4XSQghhBBnifPTnPzBD36Qd77znc95ztq1a5/XtUZHR7n77ruPu296enr52NP/ffq+Z59TKBRIp9OnvLbv+/i+/7zKIYQQQoje9lOFmaGhIYaGhs7IE2/bto2Pf/zjzMzMMDw8DMDtt99OoVDg4osvXj7n61//+nGPu/3229m2bdsZKYMQQgghet9ZGzNz8OBBdu3axcGDB0mShF27drFr1y7q9ToAN9xwAxdffDFvf/vbeeCBB/jGN77Bf/yP/5H3vve9y60qv/mbv8nevXv5/d//fR5//HH+/M//nC996Ut84AMfOFvFFkIIIUSPOWtTs9/5znfy+c9//oT7v/3tb/PKV74SgAMHDvBbv/VbfOc73yGbzfKOd7yDT3ziEzjOMw1G3/nOd/jABz7Ao48+ysTEBB/+8Id/YlfXj5Op2UIIIUTveb5/v8/6OjPnAwkzQgghRO8579eZEUIIIYQ4EyTMCCGEEKKnSZgRQgghRE+TMCOEEEKIniZhRgghhBA9TcKMEEIIIXqahBkhhBBC9DQJM0IIIYToaRJmhBBCCNHTJMwIIYQQoqdJmBFCCCFET5MwI4QQQoieJmFGCCGEED1NwowQQgghepqEGSGEEEL0NAkzQgghhOhpEmaEEEII0dMkzAghhBCip0mYEUIIIURPkzAjhBBCiJ4mYUYIIYQQPU3CjBBCCCF6moQZIYQQQvQ0CTNCCCGE6GkSZoQQQgjR0yTMCCGEEKKnSZgRQgghRE+TMCOEEEKIniZhRgghhBA9TcKMEEIIIXqahBkhhBBC9DQJM0IIIYToaU63C3AuGGMAqFarXS6JEEIIIZ6vp/9uP/13/FReFGGmVqsBMDk52eWSCCGEEOKnVavVKBaLpzyuzE+KOxcArTVHjx4ln8+jlOp2cc6YarXK5OQkhw4dolAodLs4L0ryHnSfvAfdJ+9Bd13Ir78xhlqtxvj4OJZ16pExL4qWGcuymJiY6HYxzppCoXDB/QPuNfIedJ+8B90n70F3Xaiv/3O1yDxNBgALIYQQoqdJmBFCCCFET5Mw08N83+ejH/0ovu93uygvWvIedJ+8B90n70F3yev/IhkALIQQQogLl7TMCCGEEKKnSZgRQgghRE+TMCOEEEKIniZhRgghhBA9TcJMD/j4xz/OtddeSyaToVQqnfScgwcP8oY3vIFMJsPw8DC/93u/RxzHx53zne98h6uuugrf91m/fj233nrr2S/8BWz16tUopY67feITnzjunAcffJDrr7+eVCrF5OQkn/zkJ7tU2gvTZz/7WVavXk0qlWLr1q3cfffd3S7SBetjH/vYCf/eN2/evHy83W7z3ve+l4GBAXK5HG9+85uZnp7uYol73/e+9z3e+MY3Mj4+jlKKL3/5y8cdN8bwkY98hLGxMdLpNNu3b2fPnj3HnbOwsMDb3vY2CoUCpVKJd7/73dTr9XNYi3NDwkwPCMOQt7zlLfzWb/3WSY8nScIb3vAGwjDkzjvv5POf/zy33norH/nIR5bP2bdvH294wxt41atexa5du3j/+9/Pr/3ar/GNb3zjXFXjgvTHf/zHHDt2bPn227/928vHqtUqN9xwA6tWreLee+/lU5/6FB/72Mf4H//jf3SxxBeOL37xi9x000189KMf5b777uPyyy9nx44dzMzMdLtoF6wtW7Yc9+/9+9///vKxD3zgA3zlK1/h7//+7/nud7/L0aNHedOb3tTF0va+RqPB5Zdfzmc/+9mTHv/kJz/Jn/7pn/K5z32Ou+66i2w2y44dO2i328vnvO1tb+ORRx7h9ttv56tf/Srf+973eM973nOuqnDuGNEz/uqv/soUi8UT7v/6179uLMsyU1NTy/f9xV/8hSkUCiYIAmOMMb//+79vtmzZctzjbrzxRrNjx46zWuYL2apVq8xnPvOZUx7/8z//c9PX17f8HhhjzIc+9CGzadOmc1C6C99LX/pS8973vnf55yRJzPj4uLnlllu6WKoL10c/+lFz+eWXn/RYuVw2ruuav//7v1++77HHHjOA2blz5zkq4YUNMP/4j/+4/LPW2oyOjppPfepTy/eVy2Xj+775u7/7O2OMMY8++qgBzD333LN8zj//8z8bpZQ5cuTIOSv7uSAtMxeAnTt3cumllzIyMrJ8344dO6hWqzzyyCPL52zfvv24x+3YsYOdO3ee07JeaD7xiU8wMDDAlVdeyac+9anjuvZ27tzJK17xCjzPW75vx44d7N69m8XFxW4U94IRhiH33nvvcf+mLcti+/bt8m/6LNqzZw/j4+OsXbuWt73tbRw8eBCAe++9lyiKjns/Nm/ezMqVK+X9OEv27dvH1NTUca95sVhk69aty6/5zp07KZVKXHPNNcvnbN++HcuyuOuuu855mc+mF8VGkxe6qamp44IMsPzz1NTUc55TrVZptVqk0+lzU9gLyO/8zu9w1VVX0d/fz5133snNN9/MsWPH+PSnPw10XvM1a9Yc95hnvy99fX3nvMwXirm5OZIkOem/6ccff7xLpbqwbd26lVtvvZVNmzZx7Ngx/uiP/ojrr7+ehx9+mKmpKTzPO2FM38jIyPJnkDiznn5dT/Y78OzP/eHh4eOOO45Df3//Bfe+SJjpkj/4gz/gv/7X//qc5zz22GPHDbATZ99P877cdNNNy/dddtlleJ7Hb/zGb3DLLbe8qJcVFxem17/+9cv/f9lll7F161ZWrVrFl770JfkyJLpOwkyXfPCDH+Sd73znc56zdu3a53Wt0dHRE2ZxPD2LYHR0dPm/Pz6zYHp6mkKhIB9Ez3I678vWrVuJ45j9+/ezadOmU77m8Mz7Il6YwcFBbNs+6esrr+25USqV2LhxI08++SSvfe1rCcOQcrl8XOuMvB9nz9Ov6/T0NGNjY8v3T09Pc8UVVyyf8+MD4uM4ZmFh4YJ7XyTMdMnQ0BBDQ0Nn5Frbtm3j4x//ODMzM8tNirfffjuFQoGLL754+Zyvf/3rxz3u9ttvZ9u2bWekDBeK03lfdu3ahWVZy+/Btm3b+MM//EOiKMJ1XaDzmm/atEm6mE6T53lcffXV3HHHHfziL/4iAFpr7rjjDt73vvd1t3AvEvV6naeeeoq3v/3tXH311biuyx133MGb3/xmAHbv3s3BgwflM+YsWbNmDaOjo9xxxx3L4aVarXLXXXctz3zdtm0b5XKZe++9l6uvvhqAb33rW2it2bp1a7eKfnZ0ewSy+MkOHDhg7r//fvNHf/RHJpfLmfvvv9/cf//9plarGWOMiePYXHLJJeaGG24wu3btMrfddpsZGhoyN9988/I19u7dazKZjPm93/s989hjj5nPfvazxrZtc9ttt3WrWj3tzjvvNJ/5zGfMrl27zFNPPWX++q//2gwNDZl//+///fI55XLZjIyMmLe//e3m4YcfNl/4whdMJpMx//2///culvzC8YUvfMH4vm9uvfVW8+ijj5r3vOc9plQqHTerT5w5H/zgB813vvMds2/fPvODH/zAbN++3QwODpqZmRljjDG/+Zu/aVauXGm+9a1vmR/96Edm27ZtZtu2bV0udW+r1WrLn/eA+fSnP23uv/9+c+DAAWOMMZ/4xCdMqVQy//RP/2QefPBB8wu/8AtmzZo1ptVqLV/jda97nbnyyivNXXfdZb7//e+bDRs2mLe+9a3dqtJZI2GmB7zjHe8wwAm3b3/728vn7N+/37z+9a836XTaDA4Omg9+8IMmiqLjrvPtb3/bXHHFFcbzPLN27VrzV3/1V+e2IheQe++912zdutUUi0WTSqXMRRddZP7Lf/kvpt1uH3feAw88YK677jrj+75ZsWKF+cQnPtGlEl+Y/uzP/sysXLnSeJ5nXvrSl5of/vCH3S7SBevGG280Y2NjxvM8s2LFCnPjjTeaJ598cvl4q9Uy/+E//AfT19dnMpmM+aVf+iVz7NixLpa49337298+6Wf/O97xDmNMZ3r2hz/8YTMyMmJ83zevec1rzO7du4+7xvz8vHnrW99qcrmcKRQK5l3vetfyF+ELiTLGmC41CgkhhBBCnDZZZ0YIIYQQPU3CjBBCCCF6moQZIYQQQvQ0CTNCCCGE6GkSZoQQQgjR0yTMCCGEEKKnSZgRQgghRE+TMCOEEEKIniZhRgghhBA9TcKMEEIIIXqahBkhhBBC9DQJM0IIIYToaf9/XH75kHP61RgAAAAASUVORK5CYII=", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "info = info_from_trace(trace)\n", - "latent_labd = info[\"latent_color_space_d\"]\n", - "observed_labd = info[\"observed_color_space_d\"]\n", - "plt.scatter(latent_labd[...,1].reshape(-1), latent_labd[...,2].reshape(-1), alpha=0.4, c=trace.get_retval()[\"latent_rgbd\"][...,:3].reshape(-1,3))\n", - "# plt.scatter(observed_labd[...,1].reshape(-1), observed_labd[...,2].reshape(-1), alpha=0.4)\n", - "plt.xlim(-128, 128)\n", - "plt.ylim(-128, 128)" - ] - }, - { - "cell_type": "code", - "execution_count": 499, + "execution_count": 844, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "[363945 366902 302418 302418 366902 254052 254052 366902 302418 363945\n", - " 171128 171128 43482 302418 171128 254052 363945 366902 190621 366902\n", - " 302418 302418 366902 363945 288074 440761 254052 254052 254052 363945\n", - " 302418 171128 363945 363945 171128 302418 43482 254052 302418 302418\n", - " 43482 302418 254052 302418 254052 295606 302418 288074 295606 254052\n", - " 366902 366902 295606 171128 43482 363945 366902 302418 302418 295606\n", - " 295606 295606 91590 302418 278459 254052 302418 363945 252563 302418\n", - " 366902 440761 254052 366902 366902 302418 302418 91590 302418 302418\n", - " 254052 363945 302418 254052 302418 302418 254052 302418 302418 254052\n", - " 295606 254052 366902 302418 302418 254052 366902 366902 91590 302418]\n", - "3044.147\n" + "[1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115\n", + " 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115\n", + " 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115\n", + " 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115\n", + " 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115\n", + " 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115\n", + " 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115 1115\n", + " 1115 1115]\n", + "4420.2373\n" ] }, { "data": { "text/plain": [ - "Array(3056.1968, dtype=float32)" + "Array(4432.287, dtype=float32)" ] }, - "execution_count": 499, + "execution_count": 844, "metadata": {}, "output_type": "execute_result" } @@ -464,7 +390,7 @@ "source": [ "key = jax.random.split(key, 2)[-1]\n", "N = 1000\n", - "B = 500\n", + "B = 5\n", "keys = jax.random.split(key, N*B)\n", "\n", "# sampled_poses = Pose.concatenate_poses([Pose.sample_gaussian_vmf_pose_vmap(\n", diff --git a/src/b3d/mesh.py b/src/b3d/mesh.py index d83ae273..8bf27da8 100644 --- a/src/b3d/mesh.py +++ b/src/b3d/mesh.py @@ -75,6 +75,27 @@ def voxel_mesh_from_xyz_colors_dimensions(xyz, resolutions, colors): return b3d.mesh.Mesh.squeeze_mesh(meshes) +@jax.jit +def plane_mesh_from_plane_and_dimensions(pose, w, h, color): + vertices = jnp.array( + [ + [-w / 2, -h / 2, 0], + [-w / 2, h / 2, 0], + [w / 2, h / 2, 0], + [w / 2, -h / 2, 0], + ] + ) + vertices = pose.apply(vertices) + faces = jnp.array( + [ + [0, 1, 3], + [3, 1, 2], + ] + ) + vertex_attributes = jnp.ones((len(vertices), 3)) * color + return Mesh(vertices, faces, vertex_attributes) + + @register_pytree_node_class class Mesh: def __init__(self, vertices, faces, vertex_attributes): From 22c8718bdae3baa7eae232c2aacd83549af74844 Mon Sep 17 00:00:00 2001 From: Nishad Gothoskar Date: Thu, 25 Jul 2024 05:15:22 +0000 Subject: [PATCH 13/16] blurring --- notebooks/aug1demos/slam_color_room.ipynb | 454 +++++++++++++++++++++- src/b3d/chisight/dense/dense_model.py | 3 + src/b3d/renderer/renderer_original.py | 14 +- src/b3d/utils.py | 19 + 4 files changed, 468 insertions(+), 22 deletions(-) diff --git a/notebooks/aug1demos/slam_color_room.ipynb b/notebooks/aug1demos/slam_color_room.ipynb index fe6a60a8..5199b1e7 100644 --- a/notebooks/aug1demos/slam_color_room.ipynb +++ b/notebooks/aug1demos/slam_color_room.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 3, + "execution_count": 244, "metadata": {}, "outputs": [], "source": [ @@ -27,7 +27,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 245, "metadata": {}, "outputs": [], "source": [ @@ -36,7 +36,7 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": 246, "metadata": {}, "outputs": [], "source": [ @@ -49,14 +49,23 @@ " [0.0, room_h, room_w, room_h, 1.0, 1.0, 0.0],\n", " ]\n", ")\n", + "epsilon = 0.003\n", "line_segments = jnp.concatenate(\n", " [\n", " line_segments,\n", " line_segments\n", - " + jnp.array([room_w + 0.002, 0.0, room_w + 0.002, 0.0, 0.0, 0.0, 0.0]),\n", + " + jnp.array([room_w + epsilon, 0.0, room_w + epsilon, 0.0, 0.0, 0.0, 0.0]),\n", " line_segments\n", " + jnp.array(\n", - " [room_w * 2.0 + 0.003, 0.0, room_w * 2.0 + 0.003, 0.0, 0.0, 0.0, 0.0]\n", + " [\n", + " (room_w + epsilon) * 2.0,\n", + " 0.0,\n", + " (room_w + epsilon) * 2.0,\n", + " 0.0,\n", + " 0.0,\n", + " 0.0,\n", + " 0.0,\n", + " ]\n", " ),\n", " ],\n", " axis=0,\n", @@ -90,42 +99,457 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 247, "metadata": {}, "outputs": [], "source": [ - "renderer = b3d.RendererOriginal()" + "renderer = b3d.renderer.renderer_original.RendererOriginal()" ] }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 248, "metadata": {}, "outputs": [ { "data": { - "image/jpeg": 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+ "image/png": "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", "text/plain": [ - "" + "" ] }, - "execution_count": 43, + "execution_count": 248, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "camera_pose = Pose.from_translation(jnp.array([0.21, 0.0, 0.21]))\n", - "rgbd = renderer.render_rgbd_from_mesh(world_mesh.transform(camera_pose.inv()))\n", + "gt_camera_pose = Pose.from_translation(jnp.array([0.81, 0.0, 0.21]))\n", + "rgbd = renderer.render_rgbd_from_mesh(world_mesh.transform(gt_camera_pose.inv()))\n", "b3d.viz_rgb(rgbd)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 298, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 298, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import jax\n", + "import jax.numpy as jnp\n", + "from jax.numpy import convolve\n", + "\n", + "\n", + "def gaussian_kernel(size: int, sigma: float) -> jnp.ndarray:\n", + " \"\"\"Creates a 2D Gaussian kernel.\"\"\"\n", + " ax = jnp.arange(-size // 2 + 1.0, size // 2 + 1.0)\n", + " xx, yy = jnp.meshgrid(ax, ax)\n", + " kernel = jnp.exp(-(xx**2 + yy**2) / (2.0 * sigma**2))\n", + " return kernel / jnp.sum(kernel)\n", + "\n", + "\n", + "def apply_gaussian_blur(image: jnp.ndarray, sigma, kernel_size=5) -> jnp.ndarray:\n", + " \"\"\"Applies Gaussian blur to an image.\"\"\"\n", + " kernel = gaussian_kernel(kernel_size, sigma)\n", + " # Convolve the image with the kernel\n", + " blurred_image = jax.scipy.signal.convolve(image, kernel, mode=\"same\")\n", + " return blurred_image\n", + "\n", + "\n", + "apply_gaussian_blur_rgbd = jax.vmap(\n", + " apply_gaussian_blur, in_axes=(-1, None, None), out_axes=-1\n", + ")\n", + "\n", + "kernel_size = 25\n", + "sigma = 1.0\n", + "\n", + "rgbd_blurred = apply_gaussian_blur_rgbd(rgbd, 1.1, kernel_size)\n", + "b3d.viz_rgb(rgbd_blurred)\n", + "\n", + "\n", + "gt_camera_pose1 = Pose.from_translation(jnp.array([0.81, 0.0, 0.21]))\n", + "gt_camera_pose2 = Pose.from_translation(jnp.array([0.84, 0.0, 0.21]))\n", + "\n", + "rgb1 = renderer.render_rgbd_from_mesh(world_mesh.transform(gt_camera_pose1.inv()))[\n", + " ..., :3\n", + "]\n", + "rgb2 = renderer.render_rgbd_from_mesh(world_mesh.transform(gt_camera_pose2.inv()))[\n", + " ..., :3\n", + "]\n", + "b3d.rr_log_rgb(\"image\", rgb1)\n", + "b3d.rr_log_rgb(\"image/2\", rgb2)\n", + "\n", + "rgb1_blurred = apply_gaussian_blur_rgbd(rgb1, 5.1, kernel_size)\n", + "b3d.rr_log_rgb(\"image/blur\", rgb1_blurred)\n", + "\n", + "\n", + "def error_function(rgb1, rgb2, blur):\n", + " rgb1_blurred = apply_gaussian_blur_rgbd(rgb1, blur, kernel_size)\n", + " rgb2_blurred = apply_gaussian_blur_rgbd(rgb2, blur, kernel_size)\n", + " return -jnp.sum((rgb1_blurred - rgb2_blurred) ** 2)\n", + "\n", + "\n", + "error_function_vmap_blur = jax.vmap(error_function, in_axes=(None, None, 0))\n", + "blur_sweep = jnp.linspace(0.00001, 10.5, 100)\n", + "\n", + "score = error_function_vmap_blur(rgb1, rgb2, blur_sweep)\n", + "plt.plot(score)" + ] + }, + { + "cell_type": "code", + "execution_count": 299, "metadata": {}, "outputs": [], + "source": [ + "lower_bound = jnp.array([0.0, 0.0, 0.0, 0.0])\n", + "upper_bound = jnp.array([1.0, 1.0, 1.0, 3.0])\n", + "convert_rgbd_to_color_space = lambda x: x\n", + "convert_color_space_to_rgbd = lambda x: x\n", + "\n", + "\n", + "# convert_rgbd_to_color_space = lambda x: b3d.colors.rgbd_to_labd(x)\n", + "# convert_color_space_to_rgbd = lambda x: b3d.colors.labd_to_rgbd(x)\n", + "def intermediate_likelihood_func(observed_rgbd, latent_rgbd, likelihood_args):\n", + " k = likelihood_args[\"k\"].const\n", + " fx = likelihood_args[\"fx\"]\n", + " fy = likelihood_args[\"fy\"]\n", + "\n", + " outlier_probability_0 = likelihood_args[f\"outlier_probability_0\"]\n", + " lightness_variance_0 = likelihood_args[f\"lightness_variance_0\"]\n", + " color_variance_0 = likelihood_args[f\"color_variance_0\"]\n", + " depth_variance_0 = likelihood_args[f\"depth_variance_0\"]\n", + "\n", + " inlier_variances_0 = jnp.array(\n", + " [lightness_variance_0, color_variance_0, color_variance_0, depth_variance_0]\n", + " )\n", + " outlier_variances = jnp.array([1000000.0, 1000000.0, 1000000.0, 1000000.0])\n", + "\n", + " image_height, image_width = observed_rgbd.shape[:2]\n", + "\n", + " observed_color_space_d = convert_rgbd_to_color_space(observed_rgbd)\n", + " latent_color_space_d = convert_rgbd_to_color_space(latent_rgbd)\n", + "\n", + " blur = likelihood_args[\"blur\"]\n", + " latent_color_space_d = jnp.clip(\n", + " apply_gaussian_blur_rgbd(latent_color_space_d, 10.0 * blur, 10), 0.0, 1.0\n", + " )\n", + "\n", + " observed_color_space_d = jnp.clip(\n", + " apply_gaussian_blur_rgbd(observed_color_space_d, 10.0 * blur, 10), 0.0, 1.0\n", + " )\n", + "\n", + " subset_observed = observed_color_space_d\n", + " subset_observed_rescaled = (subset_observed - lower_bound) / (\n", + " upper_bound - lower_bound\n", + " )\n", + " rendered_values_rescaled = (latent_color_space_d - lower_bound) / (\n", + " upper_bound - lower_bound\n", + " )\n", + "\n", + " scores_inlier = jax.vmap(\n", + " genjax.truncated_normal.logpdf, in_axes=(0, 0, None, None, None)\n", + " )(subset_observed_rescaled, rendered_values_rescaled, inlier_variances_0, 0.0, 1.0)\n", + " scores_outlier = jax.vmap(\n", + " genjax.truncated_normal.logpdf, in_axes=(0, None, None, None, None)\n", + " )(subset_observed_rescaled, 0.5, outlier_variances, 0.0, 1.0)\n", + "\n", + " scores_inlier_merged = scores_inlier[..., :].sum(-1) + jnp.log(\n", + " 1.0 - outlier_probability_0\n", + " )\n", + " scores_outlier_merged = scores_outlier[..., :].sum(-1) + jnp.log(\n", + " outlier_probability_0\n", + " )\n", + "\n", + " pixelwise_score = jnp.logaddexp(scores_inlier_merged, scores_outlier_merged)\n", + " pixelwise_score_full = jnp.zeros((image_height, image_width))\n", + " pixelwise_score_full = pixelwise_score\n", + "\n", + " return {\n", + " \"score\": (\n", + " jax.nn.logsumexp(pixelwise_score_full) - jnp.log(pixelwise_score_full.size)\n", + " )\n", + " * k,\n", + " \"observed_color_space_d\": observed_color_space_d,\n", + " \"latent_color_space_d\": latent_color_space_d,\n", + " \"pixelwise_score\": pixelwise_score_full,\n", + " }\n", + "\n", + "\n", + "import b3d.chisight.dense.dense_model\n", + "\n", + "b3d.reload(b3d.chisight.dense.dense_model)\n", + "model, viz_trace, info_from_trace = (\n", + " b3d.chisight.dense.dense_model.make_dense_multiobject_model(\n", + " renderer, intermediate_likelihood_func\n", + " )\n", + ")\n", + "importance_jit = jax.jit(model.importance)\n", + "\n", + "\n", + "grid1 = b3d.multivmap(b3d.update_choices_get_score, (False, False, False, True))\n", + "grid2 = b3d.multivmap(b3d.update_choices_get_score, (False, False, False, True, True))\n", + "grid3 = b3d.multivmap(\n", + " b3d.update_choices_get_score, (False, False, False, True, True, True)\n", + ")\n", + "grid4 = b3d.multivmap(\n", + " b3d.update_choices_get_score, (False, False, False, True, True, True, True)\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 301, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "242.8693\n" + ] + } + ], + "source": [ + "IDX = 4\n", + "key = jax.random.PRNGKey(0)\n", + "likelikood_args = {\n", + " \"fx\": renderer.fx,\n", + " \"fy\": renderer.fy,\n", + " \"cx\": renderer.cx,\n", + " \"cy\": renderer.cy,\n", + " \"k\": Pytree.const(50),\n", + "}\n", + "\n", + "T = 22\n", + "choicemap = genjax.ChoiceMap.d(\n", + " {\n", + " \"rgbd\": rgbd,\n", + " \"object_pose_0\": Pose.identity(),\n", + " \"camera_pose\": Pose.from_translation(\n", + " gt_camera_pose.pos + jnp.array([0.1, 0.0, -0.01])\n", + " ),\n", + " \"outlier_probability_background\": 0.999,\n", + " }\n", + ")\n", + "\n", + "trace = importance_jit(\n", + " key,\n", + " choicemap,\n", + " (\n", + " {\n", + " \"num_objects\": Pytree.const(1),\n", + " \"meshes\": [world_mesh],\n", + " \"likelihood_args\": likelikood_args,\n", + " },\n", + " ),\n", + ")[0]\n", + "print(trace.get_score())\n", + "viz_trace(trace)" + ] + }, + { + "cell_type": "code", + "execution_count": 302, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[0.01 0.05 0.01 0.05]\n", + "434.41245\n" + ] + } + ], + "source": [ + "outlier_probability_sweep = jnp.linspace(0.01, 0.1, 30)\n", + "color_variance_sweep = jnp.linspace(0.05, 0.1, 15)\n", + "depth_variance_sweep = jnp.linspace(0.05, 0.1, 15)\n", + "blur_sweep = jnp.linspace(0.01, 1.0, 15)\n", + "\n", + "for arguments in [\n", + " # Pytree.const((\"outlier_probability_background\", \"lightness_variance_background\", \"color_variance_background\", \"depth_variance_background\",)),\n", + " Pytree.const(\n", + " (\n", + " \"outlier_probability_0\",\n", + " \"color_variance_0\",\n", + " \"blur\",\n", + " \"depth_variance_0\",\n", + " )\n", + " ),\n", + "]:\n", + " key = jax.random.split(key, 2)[-1]\n", + "\n", + " # arguments = Pytree.const((\"outlier_probability_background\", \"lightness_variance_background\", \"color_variance_background\", \"depth_variance_background\",))\n", + " sweeps = [\n", + " outlier_probability_sweep,\n", + " color_variance_sweep,\n", + " blur_sweep,\n", + " depth_variance_sweep,\n", + " ]\n", + "\n", + " scores = grid4(trace, key, arguments, *sweeps)\n", + " sampled_indices = jax.vmap(jnp.unravel_index, in_axes=(0, None))(\n", + " jax.random.categorical(key, scores.reshape(-1), shape=(1000,)), scores.shape\n", + " )\n", + " sampled_parameters = jnp.vstack(\n", + " [sweep[indices] for indices, sweep in zip(sampled_indices, sweeps)]\n", + " ).T\n", + "\n", + " print(sampled_parameters[0])\n", + " trace = b3d.update_choices(\n", + " trace,\n", + " key,\n", + " arguments,\n", + " # 0.05, 1.0, 0.02, 0.01\n", + " *sampled_parameters[0],\n", + " )\n", + " print(trace.get_score())\n", + " viz_trace(trace)\n", + " info_from_trace(trace)[\"score\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 201, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[512 553 566 594 600 607 635 641 647 648 676 682 689 717] [ 1 2 1 45 7 21 561 88 2 216 35 4 16 1]\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 201, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import jax.random\n", + "\n", + "key = b3d.split_key(key)\n", + "\n", + "gt_translation = trace.get_choices()[\"camera_pose\"].pos\n", + "w = 3.1\n", + "wz = 1.0\n", + "grid = b3d.utils.make_grid_points(\n", + " jnp.array([gt_translation[0] - w, gt_translation[1], gt_translation[2] - wz]),\n", + " jnp.array([gt_translation[0] + w, gt_translation[1], gt_translation[2] + wz]),\n", + " jnp.array([41, 1, 31]),\n", + ")\n", + "poses = Pose.from_translation(grid)\n", + "address = Pytree.const((\"camera_pose\",))\n", + "scores = grid1(trace, key, Pytree.const((\"camera_pose\",)), poses)\n", + "sampled_indices = jax.random.categorical(key, scores, shape=(1000,))\n", + "\n", + "# print(sampled_indices)\n", + "sampled_indices_unique, counts = jnp.unique(sampled_indices, return_counts=True)\n", + "sampled_pose = poses[sampled_indices[0]]\n", + "print(sampled_indices_unique, counts)\n", + "sampled_trace = b3d.update_choices(trace, key, address, sampled_pose)\n", + "viz_trace(sampled_trace)\n", + "\n", + "plt.scatter(grid[sampled_indices, 0], grid[sampled_indices, 2], alpha=0.5)" + ] + }, + { + "cell_type": "code", + "execution_count": 200, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 200, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.scatter(poses.pos[:, 0], poses.pos[:, 2], c=scores)\n", + "plt.colorbar()" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [] }, { diff --git a/src/b3d/chisight/dense/dense_model.py b/src/b3d/chisight/dense/dense_model.py index 16008989..7244ead5 100644 --- a/src/b3d/chisight/dense/dense_model.py +++ b/src/b3d/chisight/dense/dense_model.py @@ -36,6 +36,9 @@ def dense_multiobject_model(args_dict): likelihood_args = args_dict["likelihood_args"] num_objects = args_dict["num_objects"] + blur = genjax.uniform(0.0001, 1.0) @ f"blur" + likelihood_args["blur"] = blur + outlier_probability = ( genjax.uniform(0.0001, 1.0) @ f"outlier_probability_background" ) diff --git a/src/b3d/renderer/renderer_original.py b/src/b3d/renderer/renderer_original.py index 161bd471..c6b1e0c4 100644 --- a/src/b3d/renderer/renderer_original.py +++ b/src/b3d/renderer/renderer_original.py @@ -91,14 +91,14 @@ def interpolate_bwd(self, saved_tensors, diffs): class RendererOriginal(object): def __init__( self, - width=200, - height=200, - fx=150.0, - fy=150.0, - cx=100.0, - cy=100.0, + width=100, + height=100, + fx=75.0, + fy=75.0, + cx=50.0, + cy=50.0, near=0.001, - far=10.0, + far=5.0, ): """ Triangle mesh renderer. diff --git a/src/b3d/utils.py b/src/b3d/utils.py index 27817ee7..36f7d303 100644 --- a/src/b3d/utils.py +++ b/src/b3d/utils.py @@ -807,3 +807,22 @@ def voxel_occupied_occluded_free( in_axes=(0, 0, 0, None, None, None, None, None, None, None), ) ) + + +def make_grid_points(min_vec, max_vec, num_vec): + """ + Generate uniformly spaced translation proposals in a 3D box + Args: + min_x, min_y, min_z: minimum x, y, z values + """ + deltas = jnp.stack( + jnp.meshgrid( + *[ + jnp.linspace(min_vec[i], max_vec[i], num_vec[i]) + for i in range(len(min_vec)) + ], + ), + axis=-1, + ) + deltas = deltas.reshape((-1, len(min_vec)), order="F") + return deltas From f935771c79ab60f341de5a1406d773a3f8a4fd88 Mon Sep 17 00:00:00 2001 From: Nishad Gothoskar Date: Thu, 25 Jul 2024 17:03:25 +0000 Subject: [PATCH 14/16] slam improvements --- notebooks/aug1demos/slam_color_room.ipynb | 452 +++++++++++++++++----- src/b3d/chisight/dense/dense_model.py | 4 +- 2 files changed, 365 insertions(+), 91 deletions(-) diff --git a/notebooks/aug1demos/slam_color_room.ipynb b/notebooks/aug1demos/slam_color_room.ipynb index 5199b1e7..491789ef 100644 --- a/notebooks/aug1demos/slam_color_room.ipynb +++ b/notebooks/aug1demos/slam_color_room.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 244, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -27,7 +27,7 @@ }, { "cell_type": "code", - "execution_count": 245, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -36,7 +36,7 @@ }, { "cell_type": "code", - "execution_count": 246, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -99,7 +99,7 @@ }, { "cell_type": "code", - "execution_count": 247, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -108,7 +108,7 @@ }, { "cell_type": "code", - "execution_count": 248, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -119,7 +119,7 @@ "" ] }, - "execution_count": 248, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -132,22 +132,43 @@ }, { "cell_type": "code", - "execution_count": 298, + "execution_count": 46, "metadata": {}, "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[64148.992 64148.992 64148.992 64148.992 64148.72 64138.473 64074.863\n", + " 63920.66 63702.61 63478.688 63288.047 63135.72 63011.062 62903.82\n", + " 62806.684 62714.773 62625.15 62536.133 62446.81 62356.742 62265.703\n", + " 62173.66 62080.695 61986.92 61892.527 61797.742 61702.78 61607.883\n", + " 61513.266 61419.1 61325.555 61232.727 61140.703 61049.51 60959.19\n", + " 60869.73 60781.117 60693.34 60606.375 60520.21 60434.848 60350.266\n", + " 60266.445 60183.41 60101.15 60019.69 59939.027 59859.17 59780.15\n", + " 59701.96 59624.633 59548.195 59472.65 59398.023 59324.355 59251.65\n", + " 59179.945 59109.266 59039.65 58971.11 58903.688 58837.406 58772.3\n", + " 58708.402 58645.734 58584.324 58524.188 58465.36 58407.85 58351.684\n", + " 58296.863 58243.414 58191.33 58140.625 58091.29 58043.33 57996.734\n", + " 57951.496 57907.61 57865.043 57823.797 57783.844 57745.156 57707.72\n", + " 57671.508 57636.492 57602.637 57569.92 57538.312 57507.79 57478.305\n", + " 57449.836 57422.344 57395.81 57370.195 57345.465 57321.594 57298.555\n", + " 57276.31 57254.836]\n" + ] + }, { "data": { "text/plain": [ - "[]" + "[]" ] }, - "execution_count": 298, + "execution_count": 46, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -174,7 +195,9 @@ " \"\"\"Applies Gaussian blur to an image.\"\"\"\n", " kernel = gaussian_kernel(kernel_size, sigma)\n", " # Convolve the image with the kernel\n", - " blurred_image = jax.scipy.signal.convolve(image, kernel, mode=\"same\")\n", + " blurred_image = jnp.clip(\n", + " jax.scipy.signal.convolve(image, kernel, mode=\"same\"), 0.0, 1.0\n", + " )\n", " return blurred_image\n", "\n", "\n", @@ -189,6 +212,13 @@ "b3d.viz_rgb(rgbd_blurred)\n", "\n", "\n", + "b3d.rr_log_rgb(\"image\", rgb1)\n", + "b3d.rr_log_rgb(\"image/2\", rgb2)\n", + "\n", + "rgb1_blurred = apply_gaussian_blur_rgbd(rgb1, 5.1, kernel_size)\n", + "b3d.rr_log_rgb(\"image/blur\", rgb1_blurred)\n", + "\n", + "\n", "gt_camera_pose1 = Pose.from_translation(jnp.array([0.81, 0.0, 0.21]))\n", "gt_camera_pose2 = Pose.from_translation(jnp.array([0.84, 0.0, 0.21]))\n", "\n", @@ -198,29 +228,141 @@ "rgb2 = renderer.render_rgbd_from_mesh(world_mesh.transform(gt_camera_pose2.inv()))[\n", " ..., :3\n", "]\n", - "b3d.rr_log_rgb(\"image\", rgb1)\n", - "b3d.rr_log_rgb(\"image/2\", rgb2)\n", "\n", - "rgb1_blurred = apply_gaussian_blur_rgbd(rgb1, 5.1, kernel_size)\n", - "b3d.rr_log_rgb(\"image/blur\", rgb1_blurred)\n", "\n", + "def error_function(observed_rgb, latent_rgb, blur):\n", + " observed_rgb_blurred = apply_gaussian_blur_rgbd(observed_rgb, blur, kernel_size)\n", + " latent_rgb_blurred = apply_gaussian_blur_rgbd(latent_rgb, blur, kernel_size)\n", + "\n", + " outlier_prob = 0.01\n", "\n", - "def error_function(rgb1, rgb2, blur):\n", - " rgb1_blurred = apply_gaussian_blur_rgbd(rgb1, blur, kernel_size)\n", - " rgb2_blurred = apply_gaussian_blur_rgbd(rgb2, blur, kernel_size)\n", - " return -jnp.sum((rgb1_blurred - rgb2_blurred) ** 2)\n", + " scores_inlier = genjax.truncated_normal.logpdf(\n", + " observed_rgb_blurred, latent_rgb_blurred, 0.1, 0.0, 1.0\n", + " ) + jnp.log(1.0 - outlier_prob)\n", + " scores_outlier = (\n", + " genjax.truncated_normal.logpdf(observed_rgb_blurred, 0.5, 1000.1, 0.0, 1.0)\n", + " + jnp.log(outlier_prob) * 0.0\n", + " )\n", + "\n", + " scores = jnp.logaddexp(scores_inlier, scores_outlier)\n", + " return scores.sum()\n", "\n", "\n", "error_function_vmap_blur = jax.vmap(error_function, in_axes=(None, None, 0))\n", - "blur_sweep = jnp.linspace(0.00001, 10.5, 100)\n", + "blur_sweep = jnp.linspace(0.000001, 5.5, 100)\n", "\n", - "score = error_function_vmap_blur(rgb1, rgb2, blur_sweep)\n", - "plt.plot(score)" + "scores = error_function_vmap_blur(rgb1, rgb2, blur_sweep)\n", + "print(scores)\n", + "plt.plot(blur_sweep, scores)" ] }, { "cell_type": "code", - "execution_count": 299, + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import functools\n", + "\n", + "import jax\n", + "import jax.numpy as jnp\n", + "\n", + "\n", + "###########\n", + "@functools.partial(\n", + " jnp.vectorize,\n", + " signature=\"(m)->()\",\n", + " excluded=(\n", + " 1,\n", + " 2,\n", + " 3,\n", + " 4,\n", + " 5,\n", + " 6,\n", + " ),\n", + ")\n", + "def per_pixel(\n", + " ij,\n", + " observed_rgb,\n", + " latent_rgb_padded,\n", + " variance,\n", + " outlier_prob: float,\n", + " outlier_volume: float,\n", + " filter_size: int,\n", + "):\n", + " latent_rgb_padded_window = jax.lax.dynamic_slice(\n", + " latent_rgb_padded,\n", + " (ij[0], ij[1], 0),\n", + " (2 * filter_size + 1, 2 * filter_size + 1, 3),\n", + " )\n", + " scores_inlier = genjax.truncated_normal.logpdf(\n", + " observed_rgb, latent_rgb_padded, 0.1, 0.0, 1.0\n", + " )\n", + "\n", + " probabilities = jax.scipy.stats.norm.logpdf(\n", + " distances, loc=0.0, scale=jnp.sqrt(variance)\n", + " ).sum(-1) - jnp.log(observed_xyz.shape[0] * observed_xyz.shape[1])\n", + " return jnp.logaddexp(\n", + " probabilities.max() + jnp.log(1.0 - outlier_prob),\n", + " jnp.log(outlier_prob) - jnp.log(outlier_volume),\n", + " )\n", + "\n", + "\n", + "def threedp3_likelihood_per_pixel_old(\n", + " observed_xyz: jnp.ndarray,\n", + " rendered_xyz: jnp.ndarray,\n", + " variance,\n", + " outlier_prob,\n", + " outlier_volume,\n", + " filter_size,\n", + "):\n", + " rendered_xyz_padded = jax.lax.pad(\n", + " rendered_xyz,\n", + " -100.0,\n", + " (\n", + " (\n", + " filter_size,\n", + " filter_size,\n", + " 0,\n", + " ),\n", + " (\n", + " filter_size,\n", + " filter_size,\n", + " 0,\n", + " ),\n", + " (\n", + " 0,\n", + " 0,\n", + " 0,\n", + " ),\n", + " ),\n", + " )\n", + " jj, ii = jnp.meshgrid(\n", + " jnp.arange(observed_xyz.shape[1]), jnp.arange(observed_xyz.shape[0])\n", + " )\n", + " indices = jnp.stack([ii, jj], axis=-1)\n", + " log_probabilities = gausssian_mixture_vectorize_old(\n", + " indices,\n", + " observed_xyz,\n", + " rendered_xyz_padded,\n", + " variance,\n", + " outlier_prob,\n", + " outlier_volume,\n", + " filter_size,\n", + " )\n", + " return log_probabilities" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -238,60 +380,71 @@ " fy = likelihood_args[\"fy\"]\n", "\n", " outlier_probability_0 = likelihood_args[f\"outlier_probability_0\"]\n", - " lightness_variance_0 = likelihood_args[f\"lightness_variance_0\"]\n", + " # lightness_variance_0 = likelihood_args[f\"lightness_variance_0\"]\n", " color_variance_0 = likelihood_args[f\"color_variance_0\"]\n", - " depth_variance_0 = likelihood_args[f\"depth_variance_0\"]\n", + " # depth_variance_0 = likelihood_args[f\"depth_variance_0\"]\n", "\n", " inlier_variances_0 = jnp.array(\n", - " [lightness_variance_0, color_variance_0, color_variance_0, depth_variance_0]\n", + " [color_variance_0, color_variance_0, color_variance_0, color_variance_0]\n", " )\n", " outlier_variances = jnp.array([1000000.0, 1000000.0, 1000000.0, 1000000.0])\n", "\n", " image_height, image_width = observed_rgbd.shape[:2]\n", "\n", - " observed_color_space_d = convert_rgbd_to_color_space(observed_rgbd)\n", - " latent_color_space_d = convert_rgbd_to_color_space(latent_rgbd)\n", - "\n", " blur = likelihood_args[\"blur\"]\n", - " latent_color_space_d = jnp.clip(\n", - " apply_gaussian_blur_rgbd(latent_color_space_d, 10.0 * blur, 10), 0.0, 1.0\n", + " observed_color_space_d = apply_gaussian_blur_rgbd(\n", + " observed_rgbd[..., :3], blur, kernel_size\n", " )\n", + " latent_color_space_d = apply_gaussian_blur_rgbd(observed_rgb, blur, kernel_size)\n", "\n", - " observed_color_space_d = jnp.clip(\n", - " apply_gaussian_blur_rgbd(observed_color_space_d, 10.0 * blur, 10), 0.0, 1.0\n", - " )\n", + " scores_inlier = genjax.truncated_normal.logpdf(\n", + " observed_color_space_d, latent_color_space_d, color_variance_0, 0.0, 1.0\n", + " ) + jnp.log(1.0 - outlier_probability_0)\n", + " scores_outlier = genjax.truncated_normal.logpdf(\n", + " observed_color_space_d, 0.5, 0.1, 0.0, 1.0\n", + " ) + jnp.log(outlier_probability_0)\n", + " print(scores_inlier.shape)\n", + " print(scores_outlier.shape)\n", "\n", - " subset_observed = observed_color_space_d\n", - " subset_observed_rescaled = (subset_observed - lower_bound) / (\n", - " upper_bound - lower_bound\n", - " )\n", - " rendered_values_rescaled = (latent_color_space_d - lower_bound) / (\n", - " upper_bound - lower_bound\n", - " )\n", + " return {\n", + " \"score\": pixelwise_score.sum(),\n", + " \"observed_color_space_d\": observed_color_space_d,\n", + " \"latent_color_space_d\": latent_color_space_d,\n", + " \"pixelwise_score\": pixelwise_score,\n", + " }\n", "\n", - " scores_inlier = jax.vmap(\n", - " genjax.truncated_normal.logpdf, in_axes=(0, 0, None, None, None)\n", - " )(subset_observed_rescaled, rendered_values_rescaled, inlier_variances_0, 0.0, 1.0)\n", - " scores_outlier = jax.vmap(\n", - " genjax.truncated_normal.logpdf, in_axes=(0, None, None, None, None)\n", - " )(subset_observed_rescaled, 0.5, outlier_variances, 0.0, 1.0)\n", + " # subset_observed = observed_color_space_d\n", + " # subset_observed_rescaled = (subset_observed - lower_bound) / (\n", + " # upper_bound - lower_bound\n", + " # )\n", + " # rendered_values_rescaled = (latent_color_space_d - lower_bound) / (\n", + " # upper_bound - lower_bound\n", + " # )\n", "\n", - " scores_inlier_merged = scores_inlier[..., :].sum(-1) + jnp.log(\n", - " 1.0 - outlier_probability_0\n", - " )\n", - " scores_outlier_merged = scores_outlier[..., :].sum(-1) + jnp.log(\n", - " outlier_probability_0\n", - " )\n", + " # scores_inlier = jax.vmap(\n", + " # genjax.truncated_normal.logpdf, in_axes=(0, 0, None, None, None)\n", + " # )(subset_observed_rescaled, rendered_values_rescaled, inlier_variances_0, 0.0, 1.0)\n", + " # scores_outlier = jax.vmap(\n", + " # genjax.truncated_normal.logpdf, in_axes=(0, None, None, None, None)\n", + " # )(subset_observed_rescaled, 0.5, outlier_variances, 0.0, 1.0)\n", + "\n", + " # scores_inlier_merged = scores_inlier[..., :3].sum(-1) + jnp.log(\n", + " # 1.0 - outlier_probability_0\n", + " # )\n", + " # scores_outlier_merged = scores_outlier[..., :3].sum(-1) + jnp.log(\n", + " # outlier_probability_0\n", + " # )\n", "\n", - " pixelwise_score = jnp.logaddexp(scores_inlier_merged, scores_outlier_merged)\n", - " pixelwise_score_full = jnp.zeros((image_height, image_width))\n", - " pixelwise_score_full = pixelwise_score\n", + " # pixelwise_score = jnp.logaddexp(scores_inlier_merged, scores_outlier_merged)\n", + " # pixelwise_score_full = jnp.zeros((image_height, image_width))\n", + " # pixelwise_score_full = pixelwise_score\n", "\n", " return {\n", - " \"score\": (\n", - " jax.nn.logsumexp(pixelwise_score_full) - jnp.log(pixelwise_score_full.size)\n", - " )\n", - " * k,\n", + " \"score\": pixelwise_score_full.sum(),\n", + " # \"score\": (\n", + " # jax.nn.logsumexp(pixelwise_score_full) - jnp.log(pixelwise_score_full.size)\n", + " # )\n", + " # * k,\n", " \"observed_color_space_d\": observed_color_space_d,\n", " \"latent_color_space_d\": latent_color_space_d,\n", " \"pixelwise_score\": pixelwise_score_full,\n", @@ -321,14 +474,14 @@ }, { "cell_type": "code", - "execution_count": 301, + "execution_count": 32, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "242.8693\n" + "13398.95\n" ] } ], @@ -351,7 +504,8 @@ " \"camera_pose\": Pose.from_translation(\n", " gt_camera_pose.pos + jnp.array([0.1, 0.0, -0.01])\n", " ),\n", - " \"outlier_probability_background\": 0.999,\n", + " # \"outlier_probability_0\": 0.1,\n", + " # \"color_variance_0\": 0.2,\n", " }\n", ")\n", "\n", @@ -372,32 +526,135 @@ }, { "cell_type": "code", - "execution_count": 302, + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[641] [1000]\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import jax.random\n", + "\n", + "key = b3d.split_key(key)\n", + "\n", + "gt_translation = trace.get_choices()[\"camera_pose\"].pos\n", + "w = 3.1\n", + "wz = 1.0\n", + "grid = b3d.utils.make_grid_points(\n", + " jnp.array([gt_translation[0] - w, gt_translation[1], gt_translation[2] - wz]),\n", + " jnp.array([gt_translation[0] + w, gt_translation[1], gt_translation[2] + wz]),\n", + " jnp.array([41, 1, 31]),\n", + ")\n", + "poses = Pose.from_translation(grid)\n", + "address = Pytree.const((\"camera_pose\",))\n", + "scores = grid1(trace, key, Pytree.const((\"camera_pose\",)), poses)\n", + "sampled_indices = jax.random.categorical(key, scores, shape=(1000,))\n", + "\n", + "# print(sampled_indices)\n", + "sampled_indices_unique, counts = jnp.unique(sampled_indices, return_counts=True)\n", + "sampled_pose = poses[sampled_indices[0]]\n", + "print(sampled_indices_unique, counts)\n", + "sampled_trace = b3d.update_choices(trace, key, address, sampled_pose)\n", + "viz_trace(sampled_trace)\n", + "\n", + "plt.scatter(grid[sampled_indices, 0], grid[sampled_indices, 2], alpha=0.5)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plt.scatter(poses.pos[:, 0], poses.pos[:, 2], c=scores)\n", + "plt.colorbar()" + ] + }, + { + "cell_type": "code", + "execution_count": 397, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 397, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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r7f+Fo0RERG2FIcfMRfR0xbj7PKAXwJyNx9GBZwQgIiIywpBjAWY9GADbTlbYn38dG49ckbocIiKidoEhxwJ0dbJF/OheAIAPNp3EzapaiSsiIiKSHkOOhXhuuC+8O9uhsKwKC9POSF0OERGR5BhyLITS2gqzH+oLAFi++xzOFt2UuCIiIiJpMeRYkNF93DC6jwY1dQLv/nCCg5CJiKhDY8ixMO/8oS8UVnLsPF2E7TmFUpdDREQkGYYcC+Pjao9nhvoAAJbsOCttMURERBJiyLFAk4f5QmElx4H8G8g8f13qcoiIiCTBkGOB3NQ2iA3uCgD4LD1P4mqIiIikwZBjoV6I7AEASDlZwCetiIioQ2LIsVC9NCpEBbhBCGDZLt7NISKijochx4K9OKL+bs43mZdRWHZL4mqIiIjaFkOOBRvk44KB3Z1QXafHyp/zpS6HiIioTTHkWLgpI3oCAL7ae57vtCIiog6FIcfCjQlwQw9Xe5TeqkXS/gtSl0NERNRmGHIsnFwuw/O/PGm1fPc51NTpJa6IiIiobTDkdAB/DO4GVwclruhuIfnoFanLISIiahMMOR2ATScrTPrlVQ+fpefxxZ1ERNQhMOR0EE+EecNeYYVT2jKkny6SuhwiIqJWx5DTQTjadcKjg7sD4KseiIioY2DI6UCeHeYLa7kMGXnXcPRSidTlEBERtSqGnA6km5Mtxg/45cWdO3k3h4iILBtDTgfzwi+vevjx2FVcuFYhcTVERESthyGng+njrsYIvy7QC2DZbt7NISIiy2VSyElISEBoaChUKhU0Gg1iY2ORk5NjaM/Pz4dMJmt0WbdunaFfY+1JSUlGx9qxYwcGDhwIpVKJXr16YeXKlQ3qWbx4MXx8fGBjY4OwsDDs37/fxI/fMU355W7O2oMXce1mlcTVEBERtQ6TQk56ejri4uKwd+9epKSkoKamBtHR0SgvLwcAeHl54erVq0bLu+++CwcHBzzwwANG+1qxYoVRv9jYWEPbuXPnMG7cOIwaNQpZWVmYNm0annvuOWzdutXQZ82aNZg+fTpmz56NQ4cOYcCAAYiJiUFhYeFdnI6OIbxHZ9zn6YhbNXp8mXFe6nKIiIhahUzcxcxwRUVF0Gg0SE9PR2RkZKN9goODMXDgQCQmJv56UJkMGzZsMAo2vzVjxgxs2rQJ2dnZhnWPPvooSkpKsGXLFgBAWFgYQkNDsWjRIgCAXq+Hl5cXpk6dijfffLNZ9ZeWlsLR0RE6nQ5qtbpZ21iK5KNXEL/6MJztOmHPm/fDVmEldUlERETN0tzr912NydHpdAAAFxeXRtszMzORlZWFyZMnN2iLi4uDq6srBg8ejOXLlxvNwpuRkYGoqCij/jExMcjIyAAAVFdXIzMz06iPXC5HVFSUoU9jqqqqUFpaarR0VGMD3dHdxQ43KmqwLvOi1OUQERHdcy0OOXq9HtOmTcPQoUPRr1+/RvskJiYiICAAERERRuvfe+89rF27FikpKfjzn/+Ml156CQsXLjS0a7VauLm5GW3j5uaG0tJSVFZWori4GHV1dY320Wq1TdackJAAR0dHw+Ll5WXqx7YY1lZyPD/cFwDwxa481PLFnUREZGFaHHLi4uKQnZ3dYMDwbZWVlVi9enWjd3HefvttDB06FMHBwZgxYwbeeOMNfPTRRy0tpdlmzpwJnU5nWC5e7Nh3MP4S4gUXewUuXq/Ej9lNh0MiIiJz1KKQEx8fj+TkZGzfvh2enp6N9lm/fj0qKirw1FNP3XF/YWFhuHTpEqqq6p/0cXd3R0FBgVGfgoICqNVq2NrawtXVFVZWVo32cXd3b/I4SqUSarXaaOnIbBVWeCrcGwDw2c6zfHEnERFZFJNCjhAC8fHx2LBhA9LS0uDr69tk38TERIwfPx5dunS5436zsrLg7OwMpVIJAAgPD0dqaqpRn5SUFISHhwMAFAoFQkJCjPro9XqkpqYa+lDzPBXuA5tOcmRfLkXG2WtSl0NERHTPWJvSOS4uDqtXr8b3338PlUplGP/i6OgIW1tbQ7/c3Fzs3LkTmzdvbrCPH374AQUFBRgyZAhsbGyQkpKCDz/8EK+99pqhz4svvohFixbhjTfewLPPPou0tDSsXbsWmzZtMvSZPn06nn76aQwaNAiDBw/GggULUF5ejkmTJpl8EjoyF3sFJgzywqqM81i6Mw8RvVylLomIiOjeECYA0OiyYsUKo34zZ84UXl5eoq6ursE+fvzxRxEUFCQcHByEvb29GDBggFi6dGmDvtu3bxdBQUFCoVCIHj16NDiGEEIsXLhQdO/eXSgUCjF48GCxd+9eUz6O0Ol0AoDQ6XQmbWdpLlwrF75vJgvvGcni+OWOfS6IiKj9a+71+67myTF3HXmenP8Vv/oQko9exR+Du+GTCUFSl0NERNSkNpknhyzHlMieAICNR67g0g2+uJOIiMwfQw4BAPp7OmJor86o0wss350vdTlERER3jSGHDG7fzUk6cAG6ihqJqyEiIro7DDlkMLy3KwI81KiorsNX+/jiTiIiMm8MOWQgk8kwJbIHAGDFz+dwq6ZO4oqIiIhajiGHjIy7zwPdnGxRfLMa3x66LHU5RERELcaQQ0Y6Wcnx7LBfX9xZp++wMwwQEZGZY8ihBh4N9YKjbSecKy5HyomCO29ARETUDjHkUAP2Sms8OaT+xZ1L0/niTiIiMk8MOdSopyN8oLCWI+tiCQ7k35C6HCIiIpMx5FCjuqiU+PNATwDA5zvPSlwNERGR6RhyqEnPD/eFTAZsO1mIMwVlUpdDRERkEoYcalKPLg6I6esOAPh8Z57E1RAREZmGIYd+15QR9ZMDfpd1GVrdLYmrISIiaj6GHPpdwd2dMdjHBTV1Aiv2nJO6HCIiomZjyKE7un03Z/XeCyi9xRd3EhGReWDIoTsa5a9Bb40Dyqpq8d99F6Quh4iIqFkYcuiO5HIZnv/lxZ3Lfz6H6lq9xBURERHdGUMONcvDQV3hplaioLQK32fxxZ1ERNT+MeRQsyitrfDs0PoXd36+Mw96vriTiIjaOYYcaraJYd2hUlrjTOFNbM8plLocIiKi38WQQ82mtumEx8K6AwA+4+SARETUzjHkkEkmDfVFJysZ9p+7jkMX+OJOIiJqvxhyyCTujjaIDeoGAPg8nXdziIio/WLIIZO98Mvj5FtPaJFXdFPiaoiIiBrHkEMm6+2mwv19NBACWLabr3ogIqL2iSGHWmTKiJ4AgPWZl1BUViVxNURERA0x5FCLhPo4I7i7E6pr9Vi1J1/qcoiIiBpgyKEWkclkmBJZfzfn//aeR3lVrcQVERERGWPIoRYb09cNvq720FXWYM2Bi1KXQ0REZMSkkJOQkIDQ0FCoVCpoNBrExsYiJyfH0J6fnw+ZTNbosm7dOgDAkSNHMHHiRHh5ecHW1hYBAQH497//bXScHTt2NLoPrVZr1G/x4sXw8fGBjY0NwsLCsH///paeB2oBK7kMzw+vf9Iqcfc51NTxxZ1ERNR+mBRy0tPTERcXh7179yIlJQU1NTWIjo5GeXk5AMDLywtXr141Wt599104ODjggQceAABkZmZCo9Hgq6++wvHjxzFr1izMnDkTixYtanC8nJwco31pNBpD25o1azB9+nTMnj0bhw4dwoABAxATE4PCQr5uoC39aWA3uDoocLmkEpuOXpW6HCIiIgOZEKLFb1osKiqCRqNBeno6IiMjG+0THByMgQMHIjExscn9xMXF4eTJk0hLSwNQfydn1KhRuHHjBpycnBrdJiwsDKGhoYZwpNfr4eXlhalTp+LNN99sVv2lpaVwdHSETqeDWq1u1jbU0KK0M5j/02kEeKix+e/DIJPJpC6JiIgsWHOv33c1Jken0wEAXFxcGm3PzMxEVlYWJk+efMf9NLaPoKAgeHh4YMyYMfj5558N66urq5GZmYmoqCjDOrlcjqioKGRkZDR5nKqqKpSWlhotdPeeGOINO4UVTl4txa4zxVKXQ0REBOAuQo5er8e0adMwdOhQ9OvXr9E+iYmJCAgIQERERJP72bNnD9asWYMXXnjBsM7DwwNLly7FN998g2+++QZeXl4YOXIkDh06BAAoLi5GXV0d3NzcjPbl5ubWYNzObyUkJMDR0dGweHl5mfKRqQlOdgo8Gnr7xZ1nJa6GiIioXotDTlxcHLKzs5GUlNRoe2VlJVavXv27d3Gys7Px8MMPY/bs2YiOjjas9/f3x5QpUxASEoKIiAgsX74cERER+OSTT1paLgBg5syZ0Ol0huXiRT4RdK9MHu4LK7kMP+deQ/ZlndTlEBERtSzkxMfHIzk5Gdu3b4enp2ejfdavX4+Kigo89dRTjbafOHEC999/P1544QW89dZbdzzm4MGDkZubCwBwdXWFlZUVCgoKjPoUFBTA3d29yX0olUqo1Wqjhe6Nbk62eOg+DwDAZzv54k4iIpKeSSFHCIH4+Hhs2LABaWlp8PX1bbJvYmIixo8fjy5dujRoO378OEaNGoWnn34aH3zwQbOOnZWVBQ+P+ouoQqFASEgIUlNTDe16vR6pqakIDw835SPRPfTCL5MDbjp6BRevV0hcDRERdXTWpnSOi4vD6tWr8f3330OlUhnGvzg6OsLW1tbQLzc3Fzt37sTmzZsb7CM7OxujR49GTEwMpk+fbtiHlZWVIRAtWLAAvr6+CAwMxK1bt7Bs2TKkpaXhp59+Muxn+vTpePrppzFo0CAMHjwYCxYsQHl5OSZNmmT6WaB7om9XNSL9umDn6SIs25WHdx9ufKwWERFRWzAp5CxZsgQAMHLkSKP1K1aswDPPPGP4efny5fD09DQaZ3Pb+vXrUVRUhK+++gpfffWVYb23tzfy8/MB1D899eqrr+Ly5cuws7PDfffdh23btmHUqFGG/hMmTEBRURHeeecdaLVaBAUFYcuWLQ0GI1PbejGyB3aeLsKagxfxcpQfXOwVUpdEREQd1F3Nk2PuOE/OvSeEwEOLdiP7cin+fn9vTB/jJ3VJRERkYdpknhyi/yWTyfDSyF4AgOW7z+F6ebXEFRERUUfFkEP33NhAdwR2VeNmVS2W7MiVuhwiIuqgGHLonpPLZXg9xh8AsCrjPK7qKiWuiIiIOiKGHGoVI/y6YLCvC6pr9fg09YzU5RARUQfEkEOtQiaT4Y1f7uasPXgJeUU3Ja6IiIg6GoYcajWDfFwwuo8GdXqBf6WclrocIiLqYBhyqFW9Fl1/Nyf56FW+04qIiNoUQw61qr5d1Rg/oCsA4OOfciSuhoiIOhKGHGp108f4wVouw/acIhzIvy51OURE1EEw5FCr83G1xyOhXgCAeVtOoQNPsk1ERG2IIYfaxN9H94bSWo4D+TewI6dI6nKIiKgDYMihNuHuaINnInwAAPO25kCv590cIiJqXQw51GZeHNETKqU1Tl4tRfKxq1KXQ0REFo4hh9qMs70Cz0f2AAD866cc1NTpJa6IiIgsGUMOtalnh/mis70C+dcqsO7gJanLISIiC8aQQ23KQWmNuFG9AACfpp7BrZo6iSsiIiJLxZBDbe7xId3RzckW2tJb+L+M81KXQ0REFoohh9qc0toKL0f1BgD8Z0cuym7VSFwRERFZIoYcksSfgruhZxd73KiowRe7zkldDhERWSCGHJKEtZXc8PLOxF15uHazSuKKiIjI0jDkkGTG9nNH/26OKK+uw+LtZ6Uuh4iILAxDDklGJpPh9Zj6uzlf7T2PyyWVEldERESWhCGHJDW8tyuG9HBBdZ0e/952WupyiIjIgjDkkKRkMhneGNsHALA+8xLOFt2UuCIiIrIUDDkkuYHdnREV4Aa9AP71E+/mEBHRvcGQQ+3C6zH+kMmATceuIvuyTupyiIjIAjDkULvg765CbFA3AMC8rTkSV0NERJaAIYfajWlRvWEtl2Hn6SLszbsmdTlERGTmGHKo3fDubI9HB3sBAOZtOQUhhMQVERGROWPIoXbl76N7w6aTHIculCD1ZKHU5RARkRljyKF2RaO2wTMRvgCA+T/lQK/n3RwiImoZk0JOQkICQkNDoVKpoNFoEBsbi5ycXweJ5ufnQyaTNbqsW7fO0O/ChQsYN24c7OzsoNFo8Prrr6O2ttboWDt27MDAgQOhVCrRq1cvrFy5skE9ixcvho+PD2xsbBAWFob9+/eb+PGpPfrbiJ5Q2VjjlLYMPxy9InU5RERkpkwKOenp6YiLi8PevXuRkpKCmpoaREdHo7y8HADg5eWFq1evGi3vvvsuHBwc8MADDwAA6urqMG7cOFRXV2PPnj1YtWoVVq5ciXfeecdwnHPnzmHcuHEYNWoUsrKyMG3aNDz33HPYunWroc+aNWswffp0zJ49G4cOHcKAAQMQExODwkJ+xWHuHO064cURPQEA/0o5jZo6vcQVERGROZKJuxjdWVRUBI1Gg/T0dERGRjbaJzg4GAMHDkRiYiIA4Mcff8Qf/vAHXLlyBW5ubgCApUuXYsaMGSgqKoJCocCMGTOwadMmZGdnG/bz6KOPoqSkBFu2bAEAhIWFITQ0FIsWLQIA6PV6eHl5YerUqXjzzTebVX9paSkcHR2h0+mgVqtbehqoFVRU1yJy3g4U36zC/4vthyeGeEtdEhERtRPNvX7f1Zgcna5+0jYXF5dG2zMzM5GVlYXJkycb1mVkZKB///6GgAMAMTExKC0txfHjxw19oqKijPYVExODjIwMAEB1dTUyMzON+sjlckRFRRn6NKaqqgqlpaVGC7VPdgprTB3dCwDwaeoZVFbXSVwRERGZmxaHHL1ej2nTpmHo0KHo169fo30SExMREBCAiIgIwzqtVmsUcAAYftZqtb/bp7S0FJWVlSguLkZdXV2jfW7vozEJCQlwdHQ0LF5eXs3/wNTmHh3shW5Otigsq8KqjHypyyEiIjPT4pATFxeH7OxsJCUlNdpeWVmJ1atXG93FkdrMmTOh0+kMy8WLF6UuiX6H0toKr4zxAwAs2XEWusoaiSsiIiJz0qKQEx8fj+TkZGzfvh2enp6N9lm/fj0qKirw1FNPGa13d3dHQUGB0brbP7u7u/9uH7VaDVtbW7i6usLKyqrRPrf30RilUgm1Wm20UPv2x+Bu6K1xgK6yBl/szJO6HCIiMiMmhRwhBOLj47FhwwakpaXB19e3yb6JiYkYP348unTpYrQ+PDwcx44dM3oKKiUlBWq1Gn379jX0SU1NNdouJSUF4eHhAACFQoGQkBCjPnq9HqmpqYY+ZBms5DK8Gu0PAFj+8zkUlVVJXBEREZkLk0JOXFwcvvrqK6xevRoqlQparRZarRaVlZVG/XJzc7Fz504899xzDfYRHR2Nvn374sknn8SRI0ewdetWvPXWW4iLi4NSqQQAvPjii8jLy8Mbb7yBU6dO4T//+Q/Wrl2LV155xbCf6dOn44svvsCqVatw8uRJ/O1vf0N5eTkmTZrUkvNA7VhMoBsGeDmhoroOi7fnSl0OERGZC2ECAI0uK1asMOo3c+ZM4eXlJerq6hrdT35+vnjggQeEra2tcHV1Fa+++qqoqakx6rN9+3YRFBQkFAqF6NGjR4NjCCHEwoULRffu3YVCoRCDBw8We/fuNeXjCJ1OJwAInU5n0nbU9nafKRLeM5JF739sFhevl0tdDhERSai51++7mifH3HGeHPPy+LK9+Dn3Gv4S4on5fx0gdTlERCSRNpknh6gtvfbL2JxvD13CmYIyiashIqL2jiGHzEZwd2dE93WDXgAf/3Ra6nKIiKidY8ghs/JajD9kMmDLcS2OXCyRuhwiImrHGHLIrPi5qfDH4G4AgI+25khcDRERtWcMOWR2XonyQycrGXbnFmNPbrHU5RARUTvFkENmx8vFDo8N7g4AmLc1Bx34AUEiIvodDDlkluJH94ZtJytkXSxByomCO29AREQdDkMOmaUuKiWeHeYDAJj/Uw7q9LybQ0RExhhyyGy9MLwn1DbWOF1wE99nXZa6HCIiamcYcshsOdp1wosjewIAPtl2GtW1eokrIiKi9oQhh8zapAhfdFEpcfF6JZIOXJC6HCIiakcYcsis2Sqs8PfRvQAAn6bmoqK6VuKKiIiovWDIIbM3IbQ7vFxsUXyzCit+zpe6HCIiaicYcsjsKazlmD7GDwDwWfpZ6CpqJK6IiIjaA4YcsgjjB3SDv5sKpbdq8dnOs1KXQ0RE7QBDDlkEK7kMr0bX381Z8XM+CstuSVwRERFJjSGHLMaYvm4I7u6Eypo6LErLlbocIiKSGEMOWQyZTIbXY/wBAP/dfwEXr1dIXBEREUmJIYcsSkRPVwzv7YqaOoGPf8qRuhwiIpIQQw5ZnDdi+gAAvsu6gszz1yWuhoiIpMKQQxanv6cj/hriCQCYvfE4X95JRNRBMeSQRXpjbB+obKyRfbkUaw5clLocIiKSAEMOWaQuKiVeiap/pPyjradQUlEtcUVERNTWGHLIYj0Z7g0/NwfcqKjBv1JOS10OERG1MYYcslidrOSYMz4QAPDV3vM4caVU4oqIiKgtMeSQRYvo6Ypx/T2gF8CcjcchBAchExF1FAw5ZPH+MS4ANp3k2J9/HRuPXJG6HCIiaiMMOWTxujnZIm5kLwDAh5tPoryqVuKKiIioLTDkUIfwfGQPdHexQ0FpFRZt53utiIg6AoYc6hBsOlnh7T/0BQAs25WHvKKbEldEREStzaSQk5CQgNDQUKhUKmg0GsTGxiInp+H7gTIyMjB69GjY29tDrVYjMjISlZWVAIAdO3ZAJpM1uhw4cAAAkJ+f32j73r17jY6zbt069OnTBzY2Nujfvz82b97c0vNAHUBUgAYj/bugpk7gveQTHIRMRGThTAo56enpiIuLw969e5GSkoKamhpER0ejvLzc0CcjIwNjx45FdHQ09u/fjwMHDiA+Ph5yef2hIiIicPXqVaPlueeeg6+vLwYNGmR0vG3bthn1CwkJMbTt2bMHEydOxOTJk3H48GHExsYiNjYW2dnZd3M+yILJZDK884e+6GQlw46cIqSeLJS6JCIiakUycRf/nC0qKoJGo0F6ejoiIyMBAEOGDMGYMWPw/vvvN2sfNTU16NatG6ZOnYq3334bQP2dHF9fXxw+fBhBQUGNbjdhwgSUl5cjOTnZsG7IkCEICgrC0qVLm3Xs0tJSODo6QqfTQa1WN2sbMn9zfzyFpeln0d3FDj+9EgmbTlZSl0RERCZo7vX7rsbk6HQ6AICLiwsAoLCwEPv27YNGo0FERATc3NwwYsQI7N69u8l9bNy4EdeuXcOkSZMatI0fPx4ajQbDhg3Dxo0bjdoyMjIQFRVltC4mJgYZGRlNHquqqgqlpaVGC3U8U0f3gptaiQvXK7BsV57U5RARUStpccjR6/WYNm0ahg4din79+gEA8vLqLxhz5szB888/jy1btmDgwIG4//77cebMmUb3k5iYiJiYGHh6ehrWOTg44OOPP8a6deuwadMmDBs2DLGxsUZBR6vVws3NzWhfbm5u0Gq1TdackJAAR0dHw+Ll5dXSj09mzF5pjX88GAAAWLz9LK6UVEpcERERtYYWh5y4uDhkZ2cjKSnJsE6v1wMApkyZgkmTJiE4OBiffPIJ/P39sXz58gb7uHTpErZu3YrJkycbrXd1dcX06dMRFhaG0NBQzJ07F0888QQ++uijlpYLAJg5cyZ0Op1huXiRb6fuqMYP6IrBPi6orKnDB5tPSl0OERG1ghaFnPj4eCQnJ2P79u1Gd2A8PDwAAH379jXqHxAQgAsXLjTYz4oVK9C5c2eMHz/+jscMCwtDbu6v85u4u7ujoKDAqE9BQQHc3d2b3IdSqYRarTZaqGOSyWSYMz4Qchmw6ehV7DlbLHVJRER0j5kUcoQQiI+Px4YNG5CWlgZfX1+jdh8fH3Tt2rXBY+WnT5+Gt7d3g32tWLECTz31FDp16nTHY2dlZRlCFACEh4cjNTXVqE9KSgrCw8NN+UjUgfXtqsbjYfW/l+9uPIHaOr3EFRER0b1kbUrnuLg4rF69Gt9//z1UKpVh/IujoyNsbW0hk8nw+uuvY/bs2RgwYACCgoKwatUqnDp1CuvXrzfaV1paGs6dO4fnnnuuwXFWrVoFhUKB4OBgAMC3336L5cuXY9myZYY+L7/8MkaMGIGPP/4Y48aNQ1JSEg4ePIjPP//c5JNAHder0X5IPnoFOQVl+L+95zFpqO+dNyIiIvMgTACg0WXFihVG/RISEoSnp6ews7MT4eHhYteuXQ32NXHiRBEREdHocVauXCkCAgKEnZ2dUKvVYvDgwWLdunUN+q1du1b4+fkJhUIhAgMDxaZNm0z5OEKn0wkAQqfTmbQdWZav954X3jOSRb/ZW0RR2S2pyyEiojto7vX7rubJMXecJ4cAoE4v8PDi3ci+XIpHBnli3l8GSF0SERH9jjaZJ4fIEljJZXh3fP00CGsPXkLWxRJpCyIionuCIYcIQIi3M/40sBsAYPb32dDrO+wNTiIii8GQQ/SLNx/oAwelNY5c0mF95iWpyyEiorvEkEP0C43KBi/f3xsA8M8tp6CrrJG4IiIiuhsMOUS/8XSED3p2sce18mos2HZa6nKIiOguMOQQ/YbCWo454wMBAF9mnEeOtkziioiIqKUYcoj+x/DeXTA20B11eoE5G4+jA8+yQERk1hhyiBoxa1wAlNZyZORdw+ZjTb/ZnoiI2i+GHKJGeLnY4W8jewIAPth0AhXVtRJXREREpmLIIWrCiyN6wtPZFld0t/Cf7WelLoeIiEzEkEPUBJtOVnhrXF8AwOc783D+WrnEFRERkSkYcoh+R0ygG4b3dkV1nR7vJ5+QuhwiIjIBQw7R75DJZJj9UCCs5TJsO1mI7TmFUpdERETNxJBDdAe9NA6YNNQHAPDeDydQVVsnbUFERNQsDDlEzfD3+3uji0qJc8XlWL47X+pyiIioGRhyiJpBZdMJMx/oAwBYmHYGWt0tiSsiIqI7YcghaqY/BndDiLczKqrrkPDjSanLISKiO2DIIWommUyGd8cHQiYDvs+6gv3nrktdEhER/Q6GHCIT9OvmiImDuwMAZm88jjo932tFRNReMeQQmej1aH842nbCyaulWL3vvNTlEBFRExhyiEzkbK/Aa9F+AID5P53G9fJqiSsiIqLGMOQQtcBjYd4I8FBDV1mDj7bmSF0OERE1giGHqAWs5DK893AgACDpwAUcu6STuCIiIvpfDDlELRTq44LYoK4QApi9MRt6DkImImpXGHKI7sLMBwNgr7DCoQsl2HD4stTlEBHRbzDkEN0FN7UNpt7fGwCQ8OMplN2qkbgiIiK6jSGH6C49O9QXPVztUXyzCp+mnpG6HCIi+gVDDtFdUljL8c5DfQEAK37OR25hmcQVERERwJBDdE+M9NcgKsANtXqBd384ASE4CJmISGoMOUT3yDt/6AuFtRy7zhRj6/ECqcshIurwGHKI7pHune3wYmQPAMD7ySdQWV0ncUVERB2bSSEnISEBoaGhUKlU0Gg0iI2NRU5Ow9leMzIyMHr0aNjb20OtViMyMhKVlZWGdh8fH8hkMqNl7ty5Rvs4evQohg8fDhsbG3h5eWHevHkNjrNu3Tr06dMHNjY26N+/PzZv3mzKxyG65/42she6OdnickkllqaflbocIqIOzaSQk56ejri4OOzduxcpKSmoqalBdHQ0ysvLDX0yMjIwduxYREdHY//+/Thw4ADi4+Mhlxsf6r333sPVq1cNy9SpUw1tpaWliI6Ohre3NzIzM/HRRx9hzpw5+Pzzzw199uzZg4kTJ2Ly5Mk4fPgwYmNjERsbi+zs7JaeC6K7ZquwwqxxAQCAJTvO4vgVzoRMRCQVmbiLEZJFRUXQaDRIT09HZGQkAGDIkCEYM2YM3n///Sa38/HxwbRp0zBt2rRG25csWYJZs2ZBq9VCoVAAAN5880189913OHXqFABgwoQJKC8vR3JysmG7IUOGICgoCEuXLm1W/aWlpXB0dIROp4NarW7WNkR3IoTA819mYtvJAvi62mNj/FCobDpJXRYRkcVo7vX7rsbk6HT1/0p1cXEBABQWFmLfvn3QaDSIiIiAm5sbRowYgd27dzfYdu7cuejcuTOCg4Px0Ucfoba21tCWkZGByMhIQ8ABgJiYGOTk5ODGjRuGPlFRUUb7jImJQUZGRpP1VlVVobS01GghutdkMhnm//U+dHOyxbnicsz89hiftiIikkCLQ45er8e0adMwdOhQ9OvXDwCQl5cHAJgzZw6ef/55bNmyBQMHDsT999+PM2d+nSTt73//O5KSkrB9+3ZMmTIFH374Id544w1Du1arhZubm9Hxbv+s1Wp/t8/t9sYkJCTA0dHRsHh5ebX04xP9Lic7BT6dGAxruQzJR69i9f4LUpdERNThtDjkxMXFITs7G0lJSYZ1er0eADBlyhRMmjQJwcHB+OSTT+Dv74/ly5cb+k2fPh0jR47EfffdhxdffBEff/wxFi5ciKqqqrv4KHc2c+ZM6HQ6w3Lx4sVWPR51bCHezpgxtg8A4N0fTnB8DhFRG2tRyImPj0dycjK2b98OT09Pw3oPDw8AQN++fY36BwQE4MKFpv8lGxYWhtraWuTn5wMA3N3dUVBgPM/I7Z/d3d1/t8/t9sYolUqo1Wqjhag1PTfcF1EBGlTX6hG/+jDfbUVE1IZMCjlCCMTHx2PDhg1IS0uDr6+vUbuPjw+6du3a4LHy06dPw9vbu8n9ZmVlQS6XQ6PRAADCw8Oxc+dO1NT8ekFISUmBv78/nJ2dDX1SU1ON9pOSkoLw8HBTPhJRq6ofnzOA43OIiCRgUsiJi4vDV199hdWrV0OlUkGr1UKr1RrmwJHJZHj99dfx6aefYv369cjNzcXbb7+NU6dOYfLkyQDqBwwvWLAAR44cQV5eHr7++mu88soreOKJJwwB5rHHHoNCocDkyZNx/PhxrFmzBv/+978xffp0Qy0vv/wytmzZgo8//hinTp3CnDlzcPDgQcTHx9+rc0N0T3B8DhGRRIQJADS6rFixwqhfQkKC8PT0FHZ2diI8PFzs2rXL0JaZmSnCwsKEo6OjsLGxEQEBAeLDDz8Ut27dMtrHkSNHxLBhw4RSqRTdunUTc+fObVDP2rVrhZ+fn1AoFCIwMFBs2rTJlI8jdDqdACB0Op1J2xG1xGfpucJ7RrLoPWuzOH6Zv3NERC3V3Ov3Xc2TY+44Tw61Jb1e4PkvDyL1VCF8Xe3xw9RhcFBaS10WEZHZaZN5coio+eTy+vE5XR1tcK64HP/g+BwiolbFkEPUhpztFVj42EBYy2XYeOQK/ruf0xgQEbUWhhyiNhbi7Yw3xvoDAOb8cBwnrnDmbSKi1sCQQySB54b1wP196ufPiVt9CDerau+8ERERmYQhh0gCHJ9DRNT6GHKIJFI/PicYVr+Mz0k6wPE5RET3EkMOkYRCvF3wRkz9+JzZGzk+h4joXmLIIZLY88N7YHSf2++34vgcIqJ7hSGHSGJyuQwf/3UAPBxtkMfxOURE9wxDDlE74GyvwCKOzyEiuqcYcojaCY7PISK6txhyiNqR54f3wCj/LhyfQ0R0DzDkELUjcrkMHz8SZBifM2sDx+cQEbUUQw5RO+Nir8DCifXjc77PuoI1HJ9DRNQiDDlE7dAgHxe8/pvxOSevcnwOEZGpGHKI2qkXfhmfU1WrR9zXHJ9DRGQqhhyidorjc4iI7g5DDlE7xvE5REQtx5BD1M4N8nHBa9Ecn0NEZCqGHCIzMCWyB0beHp+z+hDKOT6HiOiOGHKIzIBcLsO/HgmCu9oGeUXleOu7bI7PISK6A4YcIjPhYq/Awl/eb7Xh8GWsPcjxOUREv4chh8iMhP5mfM473x/HKS3H5xARNYUhh8jM/HZ8zktfc3wOEVFTGHKIzAzH5xARNQ9DDpEZ4vgcIqI7Y8ghMlOhPi54NdoPAMfnEBE1hiGHyIy9GNkTI/w4PoeIqDEMOURmrH58zgCOzyEiagRDDpGZ6+ygNBqfs+7gJalLIiJqF0wKOQkJCQgNDYVKpYJGo0FsbCxycnIa9MvIyMDo0aNhb28PtVqNyMhIVFZWAgDy8/MxefJk+Pr6wtbWFj179sTs2bNRXV1t2D4/Px8ymazBsnfvXqPjrFu3Dn369IGNjQ369++PzZs3t+QcEJm9UB8XTB9TPz7n7e+zOT6HiAgmhpz09HTExcVh7969SElJQU1NDaKjo1FeXm7ok5GRgbFjxyI6Ohr79+/HgQMHEB8fD7m8/lCnTp2CXq/HZ599huPHj+OTTz7B0qVL8Y9//KPB8bZt24arV68alpCQEEPbnj17MHHiREyePBmHDx9GbGwsYmNjkZ2d3dJzQWTW/jaiJyJ/GZ8Tx/E5RESQibv4Ar+oqAgajQbp6emIjIwEAAwZMgRjxozB+++/3+z9fPTRR1iyZAny8vIA1N/J8fX1xeHDhxEUFNToNhMmTEB5eTmSk5MN64YMGYKgoCAsXbq0WcctLS2Fo6MjdDod1Gp1s+slaq+u3azCg5/uQkFpFf4Y3A3/emQAZDKZ1GUREd1Tzb1+39WYHJ1OBwBwcXEBABQWFmLfvn3QaDSIiIiAm5sbRowYgd27d99xP7f38Vvjx4+HRqPBsGHDsHHjRqO2jIwMREVFGa2LiYlBRkZGk8epqqpCaWmp0UJkSTo7KLFw4kDIZcCGw5fx1nfZqK3TS10WEZEkWhxy9Ho9pk2bhqFDh6Jfv34AYLgTM2fOHDz//PPYsmULBg4ciPvvvx9nzpxpdD+5ublYuHAhpkyZYljn4OCAjz/+GOvWrcOmTZswbNgwxMbGGgUdrVYLNzc3o325ublBq9U2WXNCQgIcHR0Ni5eXV0s/PlG7NdjXBf8vtj9kMuDrfRfw4leHUFldJ3VZRERtrsUhJy4uDtnZ2UhKSjKs0+vr/8U4ZcoUTJo0CcHBwfjkk0/g7++P5cuXN9jH5cuXMXbsWPz1r3/F888/b1jv6uqK6dOnIywsDKGhoZg7dy6eeOIJfPTRRy0tFwAwc+ZM6HQ6w3LxImeJJcv0WFh3LHl8IBTWcmw7WYDHlu3F9fLqO29IRGRBWhRy4uPjkZycjO3bt8PT09Ow3sPDAwDQt29fo/4BAQG4cOGC0borV65g1KhRiIiIwOeff37HY4aFhSE3N9fws7u7OwoKCoz6FBQUwN3dvcl9KJVKqNVqo4XIUo3t54HVz4XB0bYTDl8owZ+X7MH5a+V33pCIyEKYFHKEEIiPj8eGDRuQlpYGX19fo3YfHx907dq1wWPlp0+fhre3t+Hny5cvY+TIkQgJCcGKFSsMT179nqysLEOIAoDw8HCkpqYa9UlJSUF4eLgpH4nIog3yccE3f4tANydbnCsux5+X7MHRSyVSl0VE1CasTekcFxeH1atX4/vvv4dKpTKMf3F0dIStrS1kMhlef/11zJ49GwMGDEBQUBBWrVqFU6dOYf369QB+DTje3t6YP38+ioqKDPu/fRdm1apVUCgUCA4OBgB8++23WL58OZYtW2bo+/LLL2PEiBH4+OOPMW7cOCQlJeHgwYPNuitE1JH00jhgw0sReGbFAZy4WopHP9+LxY8PxCh/jdSlERG1LmECAI0uK1asMOqXkJAgPD09hZ2dnQgPDxe7du0ytK1YsaLJ/dy2cuVKERAQIOzs7IRarRaDBw8W69ata1DP2rVrhZ+fn1AoFCIwMFBs2rTJlI8jdDqdACB0Op1J2xGZo9LKavHEsr3Ce0ay6DFzk0jaf17qkoiIWqS51++7mifH3HGeHOpoaur0mPHNUXx76DIA4OX7e2NaVG/OpUNE91xRWRWyr+ha5a5xc6/fJn1dRUTmrZOVHB//dQC6Otpi0fZc/Dv1DLS6W/jgj/1gbcVX2RFRy+n1Ascu67A9pxDbTxXiyCUdrOUyHHpnDNQ2nSSpiSGHqIORyWR4LcYfHk42ePu7bKw5eBGFZbew6LGBsFfyTwIRNV/prRrsOl2M7TmF2JFThOKbVUbtfTxUKNDdkizk8Osqfl1FHVjKiQJM/e8h3KrR4z5PRyQ+HYouKqXUZRFROyWEQG7hTaSdKkTaqUJknr+BWv2vMcJBaY1hvVwxuo8GI/27QKO2aZU6mnv9ZshhyKEO7tCFG3hu1UFcL69Gdxc7rHp2MHxd7aUui4jaiVs1dcg4ew1ppwqxPacQl25UGrX37GKPUf4ajO6jwSAfFyisW/+rb4acZmDIIap3rrgcTy/fjwvXK+Bir0Di04MQ3N1Z6rKISCIXr1dgR0793Zo9Z6+hqvbXd+AprOUI79EZo/y7YHQfN3TvbNfm9THkNANDDtGvisqqMHnVARy9pINNJzkWThyIMX3d7rwhEZm9mjo9DubfMASbM4U3jdq7OtpgVB8NRvlrENGrM+wU0o7fY8hpBoYcImPlVbWIX30I23OKIJcB7z3cD08M8b7zhkRkdorKqrAjp/4rqF2ni1FWVWtos5LLENLdGaP61H8N5efm0K6mmuAj5ERkMnulNb54ahBmbah/6uqt77Kh1d3Cq9F+7eoPHBGZ7vYj3rfH1hy9pDNqd7FXYKRfF4zqo0Fk7y5wtJPmiah7iSGHiIxYW8kx98/94eFkgwXbzmDR9lxc1d3C3D/3RyfOpUNkVnSVNdh9phhppwqRfroQxTerjdr7d3PEKP/6YHOfpxOs5Jb1jxmGHCJqQCaTYVqUHzwcbfCPDdn45tAlFJbdwpInQuDAuXSI2rUrJZX46bgWW45rcSD/Bur+5xHv4b1dMaqPBiP9Wu8R7/aCf62IqEkTQrtDo7LBS18fwq4zxZjwWQZWPBNq8X8YicxNXtFNbD1egC3HtThyscSorWcXe4zuo8GoPhoM8m6bR7zbCw485sBjojs6eqkEz648gOKb1ejmZItVzw5GL42D1GURdVhCCJy8WoYtx7XYmq1FTkGZoU0mAwZ5OyMm0B3Rfd0lecS7tfHpqmZgyCFqvvPXyvHMigM4V1wOJ7tOWPbUIAzycZG6LKIOQ68XOHyxBFuPa7ElW4sL1ysMbdZyGcJ7dsbYfu4Y09cNGpVl321lyGkGhhwi01y7WYXJqw4i62IJFNZyfPpoEMb285C6LCKLVVOnx/5z17ElW4utx7UoLPv13VBKazlG+HXB2H7uuL+Pm0U8DdVcDDnNwJBDZLrK6jpM/e9hbDtZAJkMmPNQIJ6O8JG6LCKLcaumDrvPFGPLcS22nSxASUWNoU2ltMboAA3GBrpjhH8XySflkwpDTjMw5BC1TG2dHu9sPI7V+y4AAKaM6IEZMX0gt7DHT4nays2qWmw/VYgtx7XYcaoQ5dV1hjYXewWi+7ohpp87Inp2htLaSsJK2wdOBkhErcbaSo4PYvuhm5MtPtqag8/S86DV3cK8v9zHP8BEzXSjvBopJwuwNVuLXbnFqP7N+6E8HG0QE+iOsf3cMcjbGdaco6pFGHKIqEVkMhniRvWCu9oGM745iu+zrqCorApLnwyB2qbjjA0gMoVWdws/nagfOLzv3HWjOWx8Xe0xtp87xga64z5PR84yfg8w5BDRXflziCe6qJT421eZ2HP2Gh5ZmoGVkwbD3dGyn+4gaq7z18qxJbt+cr7DF0qM2vp6qOuDTT939Na0r/dDWQKOyeGYHKJ7IvuyDpNWHkBRWRU8HG2w6tnB8HNTSV0WUZsTQiCnoKw+2GRrcUpbZtQe4u2MsYHuiAm0zDls2gIHHjcDQw7RvXXxegWeWbEfZ4vKobKxxoyxffDIIK8ONcMqdUxCCBy5pDM86n2uuNzQZiWXYUgPF4zt54Hovm5w44zhd40hpxkYcojuvZKKajy36iAOnr8BAPByscUrUX54OKibxb38jzq2Or3A/nPXsfV4fbC5qrtlaFNYyzG8lyvG9nNHVIAbnO0VElZqeRhymoEhh6h1VNfqsXrfeSzanmt463FvjQNejfZDTKA7xx2Q2aqqrcOes9ewNVuLlBMFuFb+61u97RVWGNVHg7H93DHSX8OX2bYihpxmYMghal0V1bVYuScfS3ecRemtWgBA/26OeC3GH5G9XRl2yCxUVNciPacIW45rkXayEGVVtYY2J7tOiApww9hAdwzr7QqbTpxCoS0w5DQDQw5R29BV1mDZrjwk7j6Hil8mORvs44LXYvwx2Jfvv6L2R1dZg7RTBdiSrUX66SLcqvl1DhuNSmmYw2awrws6cQ6bNseQ0wwMOURtq/hmFZbsOIv/23veMPHZCL8ueC3aH/09HSWujjq64ptVSDlRgB+ztdiTW4za38xh4+Vii7GB7hjbzwPBXk6c3VtiDDnNwJBDJI2rukp8mpqLdQcvGi4kD/Rzx/QxfujNx86pDV0uqcTWX+awOZh/Hb/JNfBzc6h/1LufO/p6qPn1ajvCkNMMDDlE0jp/rRwLtp3Bd1mXIQQglwGxwd0w7X4/zh9CrSav6Ca2HK+fw+boJZ1R232ejoavonp2cZCoQroThpxmYMghah9ytGX4V0oOth4vAABYy2V4dLAXpo7uzTlF6K4JIXDiaqnhjs3pgpuGNpkMCPVxwdhAd0QHusHTmeHaHDDkNANDDlH7cuRiCeb/lINdZ4oBAEprOZ4K98bfRvaCC+cZIRPo9QKHL5Zg6y93bC5crzC0WctliOjlirGB7hjT1w1dVEoJK6WWYMhpBoYcovZpb941zN+aY5hQ0F5hhcnDe+C54b58+Sc1qbDsFnaeLsbO00XYdaYINypqDG02neQY4dcFY/u5Y7S/Gxzt+Htkzpp7/TbpubeEhASEhoZCpVJBo9EgNjYWOTk5DfplZGRg9OjRsLe3h1qtRmRkJCorKw3t169fx+OPPw61Wg0nJydMnjwZN2/eNNrH0aNHMXz4cNjY2MDLywvz5s1rcJx169ahT58+sLGxQf/+/bF582ZTPg4RtVNDenTGuhfDsWJSKAK7qlFeXYdPU88gct52LE0/i8pfHkOnjq26Vo+Ms9cw98dTePDfuzD4g1S8tu4INh65ghsVNVAprfFwUFcseXwgDr09Bp89OQh/DPZkwOlATLqTM3bsWDz66KMIDQ1FbW0t/vGPfyA7OxsnTpyAvb09gPqAM3bsWMycORMPPfQQrK2tceTIETz88MNQKutvCT7wwAO4evUqPvvsM9TU1GDSpEkIDQ3F6tWrAdQnND8/P0RFRWHmzJk4duwYnn32WSxYsAAvvPACAGDPnj2IjIxEQkIC/vCHP2D16tX45z//iUOHDqFfv37N+jy8k0PU/un1AluOa/HxTzk4W1T/PqAuKiWmju6FR0O7871YHcyFaxVIP1OE9JwiZJwtRvn/BN77PB0R2bsLRvh3QZCXE+ewsVBt8nVVUVERNBoN0tPTERkZCQAYMmQIxowZg/fff7/RbU6ePIm+ffviwIEDGDRoEABgy5YtePDBB3Hp0iV07doVS5YswaxZs6DVaqFQ1H8P/+abb+K7777DqVOnAAATJkxAeXk5kpOTDfseMmQIgoKCsHTp0mbVz5BDZD7q9AIbDl/Ggm2ncelG/Z3hbk62eDmqN/4U3A3WvJhZpIrqWuzNu4b0nCLsPFNs9OJLAHB1UCCydxdE+nXBsN6ucHXg+JqOoLnX77t6sYZOV//onYtL/YylhYWF2LdvHx5//HFERETg7Nmz6NOnDz744AMMGzYMQP2dHicnJ0PAAYCoqCjI5XLs27cPf/zjH5GRkYHIyEhDwAGAmJgY/POf/8SNGzfg7OyMjIwMTJ8+3aiemJgYfPfdd03WW1VVhaqqKsPPpaWld/PxiagNWcll+EuIJ8YP6Io1By5gYVouLpdU4o31R7E0/Symj/HDg/08OEmbmRNCIKegDDtPFyH9dBEOnLuB6rpfZxu2lssw0NsZI/y6YIRfF/T1UPO/OTWpxSFHr9dj2rRpGDp0qOHroby8PADAnDlzMH/+fAQFBeHLL7/E/fffj+zsbPTu3RtarRYajca4CGtruLi4QKvVAgC0Wi18fX2N+ri5uRnanJ2dodVqDet+2+f2PhqTkJCAd999t6UfmYjaAYW1HE+G++AvIV74v735+M+Os8grKkf86sPo63EWr8X4YZS/hhO3mZGSimrszi02BJuC0iqjdk9nW4zwq79bE9GzM1QcfE7N1OKQExcXh+zsbOzevduwTq+vT9tTpkzBpEmTAADBwcFITU3F8uXLkZCQcJfl3p2ZM2ca3f0pLS2Fl5eXhBURUUvZKqzwQmRPTBzcHYm7z2HZrnM4cbUUz648iBBvZ7wW7Y/wnp2lLpMaUacXOHKpxBBqjlwsMZpp2KaTHEN6dDYEmx6u9gyt1CItCjnx8fFITk7Gzp074enpaVjv4eEBAOjbt69R/4CAAFy4cAEA4O7ujsLCQqP22tpaXL9+He7u7oY+BQUFRn1u/3ynPrfbG6NUKg2Dn4nIMqhsOmFalB+eDvfB0vSzWLknH5nnb2DiF3vR1dEGIT4uCPVxRoi3M/q4q2HFrzYkUVB6C+mni7DzdBF25xaj5DePdwP1r1C4PWA41MeFb/Ome8KkkCOEwNSpU7Fhwwbs2LGjwVdKPj4+6Nq1a4PHyk+fPo0HHngAABAeHo6SkhJkZmYiJCQEAJCWlga9Xo+wsDBDn1mzZqGmpgadOtXflkxJSYG/vz+cnZ0NfVJTUzFt2jTDcVJSUhAeHm7KRyIiC+Fsr8DMBwPw7DBfLErLxZoDF3FFdwtXjlzBD0euAABUSmsEeztjkLczBvk4I8jLCXaKuxqaSE2orK7D4Qs3kP7L3ZpT2jKjdpWNNYb3dsUIvy4Y3rsLujrZSlQpWTKTnq566aWXsHr1anz//ffw9/c3rHd0dIStbf0v6IIFCzB79mwkJiYiKCgIq1atwvz585GdnY2ePXsCqH+EvKCgAEuXLjU8Qj5o0CDDI+Q6nQ7+/v6Ijo7GjBkzkJ2djWeffRaffPKJ0SPkI0aMwNy5czFu3DgkJSXhww8/5CPkRASg/qmcrAslOHj+Bg7kX8fhCyW4WVVr1MdaLkNgVzUGGe72uHD2WxPV1OmRX1yOU9oynC4oQ462DDkFZbhwvQK/vbrIZMB9nk4Y0dsVI/y7YICnE5+IoxZrlUfIm/pOdMWKFXjmmWcMP8+dOxeLFy/G9evXMWDAAMybN8/wdBVQPxlgfHw8fvjhB8jlcvz5z3/Gp59+CgeHX1+GdvToUcTFxeHAgQNwdXXF1KlTMWPGDKPjrlu3Dm+99Rby8/PRu3dvzJs3Dw8++GBzPw5DDlEHUqcXOKUtxcH8G/XB59x1aEtvNejn09kOId71oWeQjwt6duF4EKB+vqLLJZWGEHM70JwtuomausYvIxqVEsN/+QpqWC9XvpqD7hm+1qEZGHKIOi4h6i/amb/c6TmYfwM5BWX437+IznadfhN6nNGvmyOU1pY9XqSorOrXuzK/hJozBWUNJt67zV5hBT93Ffq4q+DnpoK/mwp+7irOWUOthiGnGRhyiOi3dJU1OHThBjLz64NP1sUSVNXqjfoorOUY4On461dc3V3M9jUBZbdqcLrgplGgOV1Qhmvl1Y32V1jJ0VPjAH83B6NQ083Jlne7qE0x5DQDQw4R/Z7qWj2OX9H98hVX/d2exgKAn5uD4W5PqI8LPJ3b10W/qrYOZwvLkVNQihztr6Hmckllo/1lMsCnsz383Bzg76aCv7sa/u4O8O5sz9ckULvAkNMMDDlEZAohBM4Vl+Pg+Rs4mH8dB8/fQF5ReYN+GpUSoT4u0Kil+7pGiPqvnU5pS5F/rQJ1+sb/1LurbeDnroK/m0N9mHFToZfGAbYKy/5KjswbQ04zMOQQ0d26drMKB8/fMIztyb6sa3IgrpTUNtbo466Gv7vql1BTv5jrV23UsbXJu6uIiDq6zg5KxAS6IyawfiLSWzV1OHKxBIculOBmVc0dtm5dTrYKw9gZjUrZrr5CI2oLDDlERPeQTScrhPXojLAefKUEkdQ4goyIiIgsEkMOERERWSSGHCIiIrJIDDlERERkkRhyiIiIyCIx5BAREZFFYsghIiIii8SQQ0RERBaJIYeIiIgsEkMOERERWSSGHCIiIrJIDDlERERkkRhyiIiIyCJ16LeQCyEAAKWlpRJXQkRERM11+7p9+zrelA4dcsrKygAAXl5eEldCREREpiorK4Ojo2OT7TJxpxhkwfR6Pa5cuQKVSgWZTNbi/ZSWlsLLywsXL16EWq2+hxXS/+K5bjs8122H57rt8Fy3ndY810IIlJWVoWvXrpDLmx5506Hv5Mjlcnh6et6z/anVav5P00Z4rtsOz3Xb4bluOzzXbae1zvXv3cG5jQOPiYiIyCIx5BAREZFFYsi5B5RKJWbPng2lUil1KRaP57rt8Fy3HZ7rtsNz3Xbaw7nu0AOPiYiIyHLxTg4RERFZJIYcIiIiskgMOURERGSRGHKIiIjIIjHkNNPixYvh4+MDGxsbhIWFYf/+/b/bf926dejTpw9sbGzQv39/bN68uY0qNX+mnOsvvvgCw4cPh7OzM5ydnREVFXXH/zb0K1N/r29LSkqCTCZDbGxs6xZoQUw91yUlJYiLi4OHhweUSiX8/Pz4d6SZTD3XCxYsgL+/P2xtbeHl5YVXXnkFt27daqNqzdfOnTvx0EMPoWvXrpDJZPjuu+/uuM2OHTswcOBAKJVK9OrVCytXrmzdIgXdUVJSklAoFGL58uXi+PHj4vnnnxdOTk6ioKCg0f4///yzsLKyEvPmzRMnTpwQb731lujUqZM4duxYG1dufkw914899phYvHixOHz4sDh58qR45plnhKOjo7h06VIbV25+TD3Xt507d05069ZNDB8+XDz88MNtU6yZM/VcV1VViUGDBokHH3xQ7N69W5w7d07s2LFDZGVltXHl5sfUc/31118LpVIpvv76a3Hu3DmxdetW4eHhIV555ZU2rtz8bN68WcyaNUt8++23AoDYsGHD7/bPy8sTdnZ2Yvr06eLEiRNi4cKFwsrKSmzZsqXVamTIaYbBgweLuLg4w891dXWia9euIiEhodH+jzzyiBg3bpzRurCwMDFlypRWrdMSmHqu/1dtba1QqVRi1apVrVWixWjJua6trRURERFi2bJl4umnn2bIaSZTz/WSJUtEjx49RHV1dVuVaDFMPddxcXFi9OjRRuumT58uhg4d2qp1WprmhJw33nhDBAYGGq2bMGGCiImJabW6+HXVHVRXVyMzMxNRUVGGdXK5HFFRUcjIyGh0m4yMDKP+ABATE9Nkf6rXknP9vyoqKlBTUwMXF5fWKtMitPRcv/fee9BoNJg8eXJblGkRWnKuN27ciPDwcMTFxcHNzQ39+vXDhx9+iLq6urYq2yy15FxHREQgMzPT8JVWXl4eNm/ejAcffLBNau5IpLg2dugXdDZHcXEx6urq4ObmZrTezc0Np06danQbrVbbaH+tVttqdVqClpzr/zVjxgx07dq1wf9IZKwl53r37t1ITExEVlZWG1RoOVpyrvPy8pCWlobHH38cmzdvRm5uLl566SXU1NRg9uzZbVG2WWrJuX7sscdQXFyMYcOGQQiB2tpavPjii/jHP/7RFiV3KE1dG0tLS1FZWQlbW9t7fkzeySGLMXfuXCQlJWHDhg2wsbGRuhyLUlZWhieffBJffPEFXF1dpS7H4un1emg0Gnz++ecICQnBhAkTMGvWLCxdulTq0izOjh078OGHH+I///kPDh06hG+//RabNm3C+++/L3VpdA/wTs4duLq6wsrKCgUFBUbrCwoK4O7u3ug27u7uJvWnei0517fNnz8fc+fOxbZt23Dfffe1ZpkWwdRzffbsWeTn5+Ohhx4yrNPr9QAAa2tr5OTkoGfPnq1btJlqye+1h4cHOnXqBCsrK8O6gIAAaLVaVFdXQ6FQtGrN5qol5/rtt9/Gk08+ieeeew4A0L9/f5SXl+OFF17ArFmzIJfzXsC90tS1Ua1Wt8pdHIB3cu5IoVAgJCQEqamphnV6vR6pqakIDw9vdJvw8HCj/gCQkpLSZH+q15JzDQDz5s3D+++/jy1btmDQoEFtUarZM/Vc9+nTB8eOHUNWVpZhGT9+PEaNGoWsrCx4eXm1ZflmpSW/10OHDkVubq4hSALA6dOn4eHhwYDzO1pyrisqKhoEmdvhUvDVjveUJNfGVhvSbEGSkpKEUqkUK1euFCdOnBAvvPCCcHJyElqtVgghxJNPPinefPNNQ/+ff/5ZWFtbi/nz54uTJ0+K2bNn8xHyZjL1XM+dO1coFAqxfv16cfXqVcNSVlYm1UcwG6ae6//Fp6uaz9RzfeHCBaFSqUR8fLzIyckRycnJQqPRiP/3//6fVB/BbJh6rmfPni1UKpX473//K/Ly8sRPP/0kevbsKR555BGpPoLZKCsrE4cPHxaHDx8WAMS//vUvcfjwYXH+/HkhhBBvvvmmePLJJw39bz9C/vrrr4uTJ0+KxYsX8xHy9mLhwoWie/fuQqFQiMGDB4u9e/ca2kaMGCGefvppo/5r164Vfn5+QqFQiMDAQLFp06Y2rth8mXKuvb29BYAGy+zZs9u+cDNk6u/1bzHkmMbUc71nzx4RFhYmlEql6NGjh/jggw9EbW1tG1dtnkw51zU1NWLOnDmiZ8+ewsbGRnh5eYmXXnpJ3Lhxo+0LNzPbt29v9O/v7fP79NNPixEjRjTYJigoSCgUCtGjRw+xYsWKVq1RJgTvxxEREZHl4ZgcIiIiskgMOURERGSRGHKIiIjIIjHkEBERkUViyCEiIiKLxJBDREREFokhh4iIiCwSQw4RERFZJIYcIiIiskgMOURERGSRGHKIiIjIIjHkEBERkUX6/8onAHRNNon4AAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "scores = b3d.enumerate_choices_get_scores(\n", + " trace,\n", + " key,\n", + " Pytree.const((\"blur\",)),\n", + " blur_sweep,\n", + ")\n", + "plt.plot(blur_sweep, scores)" + ] + }, + { + "cell_type": "code", + "execution_count": 33, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "[0.01 0.05 0.01 0.05]\n", - "434.41245\n" + "[0.09706897 0.24285716]\n", + "13398.95\n" ] } ], "source": [ - "outlier_probability_sweep = jnp.linspace(0.01, 0.1, 30)\n", - "color_variance_sweep = jnp.linspace(0.05, 0.1, 15)\n", - "depth_variance_sweep = jnp.linspace(0.05, 0.1, 15)\n", + "outlier_probability_sweep = jnp.linspace(0.001, 0.2, 30)\n", + "color_variance_sweep = jnp.linspace(0.1, 0.3, 15)\n", "blur_sweep = jnp.linspace(0.01, 1.0, 15)\n", "\n", "for arguments in [\n", - " # Pytree.const((\"outlier_probability_background\", \"lightness_variance_background\", \"color_variance_background\", \"depth_variance_background\",)),\n", " Pytree.const(\n", " (\n", - " \"outlier_probability_0\",\n", - " \"color_variance_0\",\n", - " \"blur\",\n", - " \"depth_variance_0\",\n", + " \"outlier_probability_background\",\n", + " \"color_variance_background\",\n", " )\n", " ),\n", "]:\n", @@ -407,11 +664,10 @@ " sweeps = [\n", " outlier_probability_sweep,\n", " color_variance_sweep,\n", - " blur_sweep,\n", - " depth_variance_sweep,\n", + " # blur_sweep,\n", " ]\n", "\n", - " scores = grid4(trace, key, arguments, *sweeps)\n", + " scores = grid2(trace, key, arguments, *sweeps)\n", " sampled_indices = jax.vmap(jnp.unravel_index, in_axes=(0, None))(\n", " jax.random.categorical(key, scores.reshape(-1), shape=(1000,)), scores.shape\n", " )\n", @@ -434,29 +690,22 @@ }, { "cell_type": "code", - "execution_count": 201, + "execution_count": 316, "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "[512 553 566 594 600 607 635 641 647 648 676 682 689 717] [ 1 2 1 45 7 21 561 88 2 216 35 4 16 1]\n" - ] - }, { "data": { "text/plain": [ - "" + "[]" ] }, - "execution_count": 201, + "execution_count": 316, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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8yM/jx4/XhAkTNHLkSJWWlurmm29u1U5CQoISEhJ6pM8AAKD3xXSGJS0tTQ6HQxUVFVHrKyoqlJGRcdFt16xZo1WrVmnbtm2aMGHCRWtHjBihtLQ07d+/P5buAQCAfiqmwOJ0OjV58mQFAoHIunA4rEAgoNzc3Ha3e/TRR7Vy5UqVlJRoypQpl/w9R48e1enTp5WZmRlL9wAAQD8V823NhYWFevrpp7Vp0ybt2bNHixcvVigUUkFBgSRp4cKFWr58eaR+9erVevDBB/XMM88oOztbwWBQwWBQdXV1kqS6ujr9+Mc/1vvvv69Dhw4pEAjo1ltv1ahRo5SXl9dFwwQAAH1ZzNew5Ofn6+TJk1qxYoWCwaBycnJUUlISuRD38OHDstu/zEFPPvmkGhsb9a//+q9R7RQVFemhhx6Sw+HQhx9+qE2bNqmqqkpZWVmaNWuWVq5cyXUqAABAUifmYTFRLPdxAwAAM3TbPCwAAAC9gcACAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYj8ACAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHhxvd0Bk2Uv+32rdYdWze2FngB9z/3P/15bPv7ycf44afUdvH+AjmhuDqv8yBc6HWrUVUlOTfKmKi6ud84xmHIs7NTo169fr+zsbLlcLvl8Pu3YsaPd2qefflo33XSTUlNTlZqaKr/f36resiytWLFCmZmZSkxMlN/v1759+zrTtS7T1g662HoAX8peFh1WJGnLx7x/gI4I7KlQwca/6J6X/q8e/u+Pdc9L/1cFG/+iwJ6KHu+LScfCmAPLli1bVFhYqKKiIpWXl2vixInKy8tTZWVlm/WlpaVasGCB3n77bZWVlcnr9WrWrFk6duxYpObRRx/VE088oQ0bNmj79u1KSkpSXl6e6uvrOz+yy3CpHcGHLtA+3j9A5wX2VKj4jU/1t8paJbviNDQ1UcmuOP2tslbFb3zao6HFtPeyzbIsK5YNfD6fpk6dqnXr1kmSwuGwvF6vlixZomXLll1y+5aWFqWmpmrdunVauHChLMtSVlaW7rnnHt17772SpOrqank8Hm3cuFHz58+/ZJs1NTVyu92qrq5WSkpKLMNpJZYdwJ+HgGgX/hmoPfx5CGituTmsgo1/0d8qa3VNaqLs9i/PKYTDYR3+4qzGeJL1zKKp3f7noZ46FsZy/I5pxI2Njdq5c6f8fv+XDdjt8vv9Kisr61AbZ86cUVNTkwYPHixJOnjwoILBYFSbbrdbPp+v3TYbGhpUU1MTtQDofR0JK7HUAVeS8iNf6NDpkK5KckaFFencsfaqJKcOngqp/MgXvdTD3hVTYDl16pRaWlrk8Xii1ns8HgWDwQ61cf/99ysrKysSUM5vF0ubxcXFcrvdkcXr9cYyDAAAjHM61KimlrASnY42n090OtTUEtbpUGMP98wMPXrJ8apVq7R582a9+uqrcrlcnW5n+fLlqq6ujixHjhzpwl4CANDzrkpyKt5h19nGljafP9vYonjHuTMtV6KYAktaWpocDocqKqIv+qmoqFBGRsZFt12zZo1WrVqlbdu2acKECZH157eLpc2EhASlpKRELQB6X/64rq0DriSTvKnKvipJp0ONCofDUc+Fw+fOrAxPS9Ikb2ov9bB3xRRYnE6nJk+erEAgEFkXDocVCASUm5vb7naPPvqoVq5cqZKSEk2ZMiXqueHDhysjIyOqzZqaGm3fvv2ibXaXjl48xAW3QGsdvZCWC26B1uLi7Lrzhmwlu+J1+Iuzqq1vUnM4rNr6Jh3+4qxSXPFaND27R+ZjMfFYGPOoCwsL9fTTT2vTpk3as2ePFi9erFAopIKCAknSwoULtXz58kj96tWr9eCDD+qZZ55Rdna2gsGggsGg6urqJEk2m01Lly7VI488ov/+7//WRx99pIULFyorK0vz5s3rmlHG6FI7gLACtI/3D9B5N3/Fo+Vzxura9GTV1jfr2BdnVVvfrDGeZC2bM1Y3f8Vz6Ua6iGnv5Zhva5akdevW6bHHHlMwGFROTo6eeOIJ+Xw+SdLMmTOVnZ2tjRs3SpKys7P12WeftWqjqKhIDz30kKRzE8cVFRXpqaeeUlVVlW688Ub98pe/1LXXXtuh/nTlbc3/yJTZ/YC+iJlugc67Uma6jeX43anAYpruCiwAAKD7dNs8LAAAAL2BwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYj8ACAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwXqcCy/r165WdnS2XyyWfz6cdO3a0W/vxxx/rtttuU3Z2tmw2m9auXduq5qGHHpLNZotaxo4d25muAQCAfijmwLJlyxYVFhaqqKhI5eXlmjhxovLy8lRZWdlm/ZkzZzRixAitWrVKGRkZ7bY7btw4nThxIrL8+c9/jrVrAACgn4o5sPz85z/Xd7/7XRUUFOi6667Thg0bNGDAAD3zzDNt1k+dOlWPPfaY5s+fr4SEhHbbjYuLU0ZGRmRJS0trt7ahoUE1NTVRCwAA6L9iCiyNjY3auXOn/H7/lw3Y7fL7/SorK7usjuzbt09ZWVkaMWKEvvWtb+nw4cPt1hYXF8vtdkcWr9d7Wb8bAACYLabAcurUKbW0tMjj8USt93g8CgaDne6Ez+fTxo0bVVJSoieffFIHDx7UTTfdpNra2jbrly9frurq6shy5MiRTv9uAABgvrje7oAkzZkzJ/LzhAkT5PP5NGzYML300ku66667WtUnJCRc9M9LAACgf4npDEtaWpocDocqKiqi1ldUVFz0gtpYDRo0SNdee63279/fZW0CAIC+K6bA4nQ6NXnyZAUCgci6cDisQCCg3NzcLutUXV2dDhw4oMzMzC5rEwAA9F0x/0mosLBQixYt0pQpUzRt2jStXbtWoVBIBQUFkqSFCxdq6NChKi4ulnTuQt1PPvkk8vOxY8f0wQcfaODAgRo1apQk6d5779U3v/lNDRs2TMePH1dRUZEcDocWLFjQVeMEAAB9WMyBJT8/XydPntSKFSsUDAaVk5OjkpKSyIW4hw8flt3+5Ymb48eP66tf/Wrk8Zo1a7RmzRrNmDFDpaWlkqSjR49qwYIFOn36tIYMGaIbb7xR77//voYMGXKZwwMAAP2BzbIsq7c7cblqamrkdrtVXV2tlJSU3u4OAADogFiO33yXEAAAMB6BBQAAGI/AAgAAjEdgAQAAxjNipltTvVD+kR546cvvNPo/t1+j/2fS+F7sEdB31NQ16H+/8YmOfl6vqwe7tGLOdUoZyAzVQF/zyfGTuu2XO1TfLLnipN9+f5quy+r5u3i5S6gd2ct+3+5zh1bN7ZLfAfRXi57Zrj/97ZT+8cPFJunr16Zp0//y9Va3AMRo5LLfq6WN9Q5JB7rgWMhdQpfpYmGlI88DV7JFz2zXOxeEFUmyJL3zt1Na9Mz23ugWgBi1F1YkqeXvz/ckAssFXij/qEvrgCtJTV2D/vS3Uxet+dPfTqmmrqGHegSgMz45frLdsHJey9/regqB5QL/eM1KV9QBV5L//cYnrc6sXMj6ex0Ac932yx1dWtcVCCwAuszRz+u7tA5A76hv7tq6rkBgAdBlrh7s6tI6AL3D1cF7iDta1xUILBf4P7df06V1wJVkxZzrZLtEje3vdQDM9dvvT+vSuq5AYLlAR+dZYT4WoLWUgQn6+rVpF635+rVpzMcCGO66rCFyXKLG8fe6nkJgacOl5llhHhagfZv+l08zrk1rdabFJmkG87AAfcaBVXPbDS1dNQ9LLJg47iKY6RboPGa6BfqH7pzpNpbjN4EFAAD0Cma6BQAA/QqBBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYj8ACAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHidCizr169Xdna2XC6XfD6fduzY0W7txx9/rNtuu03Z2dmy2Wxau3btZbcJAACuLDEHli1btqiwsFBFRUUqLy/XxIkTlZeXp8rKyjbrz5w5oxEjRmjVqlXKyMjokjYBAMCVxWZZlhXLBj6fT1OnTtW6deskSeFwWF6vV0uWLNGyZcsuum12draWLl2qpUuXdlmbklRTUyO3263q6mqlpKTEMhwAANBLYjl+x3SGpbGxUTt37pTf7/+yAbtdfr9fZWVlnepsZ9psaGhQTU1N1AIAAPqvmALLqVOn1NLSIo/HE7Xe4/EoGAx2qgOdabO4uFhutzuyeL3eTv1uAADQN/TJu4SWL1+u6urqyHLkyJHe7hIAAOhGcbEUp6WlyeFwqKKiImp9RUVFuxfUdkebCQkJSkhI6NTvAwAAfU9MZ1icTqcmT56sQCAQWRcOhxUIBJSbm9upDnRHmwAAoH+J6QyLJBUWFmrRokWaMmWKpk2bprVr1yoUCqmgoECStHDhQg0dOlTFxcWSzl1U+8knn0R+PnbsmD744AMNHDhQo0aN6lCbAADgyhZzYMnPz9fJkye1YsUKBYNB5eTkqKSkJHLR7OHDh2W3f3ni5vjx4/rqV78aebxmzRqtWbNGM2bMUGlpaYfaBAAAV7aY52ExEfOwAADQ93TbPCwAAAC9gcACAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8eJ6uwMma24Oq/zIFzodatRVSU5N8qYqLo6MBwC4coTDlo5VnVWosVlJzjgNHZQou93W4/0gsLQjsKdCG989pEOnQ2pqCSveYVf2VUm684Zs3fwVT293DwCAbre/slZv7q7QgZN1qm9ukSvOoZFDBirveo9GpSf3aF8ILG0I7KlQ8Rufqra+SVclOZXodOhsY4v+Vlmr4jc+lSRCCwCgX9tfWatn3z2kz0ONynS7NMCZqDONzdp9vFrHq8+q4IbsHg0t/H3jAs3NYW1895Bq65t0TWqikl3xirPbleyK1zWpiaqtb9Km9w6puTnc210FAKBbhMOW3txdoc9DjRqdPlDJrng57DYlu+I1On2gPg81atvHFQqHrR7rE4HlAuVHvtCh0yFdleSU3R798tjtdl2V5NTBUyGVH/mil3oIAED3OlZ1VgdO1inT7ZLNFn29is1mU6bbpf2VdTpWdbbH+kRgucDpUKOaWsJKdDrafD7R6VBTS1inQ4093DMAAHpGqLFZ9c0tGuBs+8qRRKdDDc0tCjU291ifCCwXuCrJqXiHXWcbW9p8/mxji+Id5860AADQHyU54+SKc+hMO4HkbGOLEuIcSmon0HQHAssFJnlTlX1Vkk6HGhUOR1+nEg6fO7MyPC1Jk7ypvdRDAAC619BBiRo5ZKBOVNfLsqKvU7EsSyeq6zUqfaCGDkrssT4RWC4QF2fXnTdkK9kVr8NfnFVtfZOaw2HV1jfp8BdnleKK16Lp2czHAgDot+x2m/Ku92hwklP7KuuijoX7Kus0OMmpWeM8PTofC7c1t+H8Lcvn52H5PNSoeIddYzzJWjSdeVgAAP3fqPRkFdyQHZmHpaKmXglxDo0f6tascT0/D4vNuvBcTx9UU1Mjt9ut6upqpaSkdFm7zHQLALjSdedMt7EcvznDchFxcXZNG35Vb3cDAIBeY7fb5B08oLe7wTUsAADAfAQWAABgPAILAAAwHoEFAAAYj8ACAACMR2ABAADG61RgWb9+vbKzs+VyueTz+bRjx46L1r/88ssaO3asXC6Xxo8fr9dffz3q+TvvvFM2my1qmT17dme6BgAA+qGYA8uWLVtUWFiooqIilZeXa+LEicrLy1NlZWWb9e+9954WLFigu+66S7t27dK8efM0b9487d69O6pu9uzZOnHiRGR58cUXOzciAADQ78Q8063P59PUqVO1bt06See+ENDr9WrJkiVatmxZq/r8/HyFQiG99tprkXVf+9rXlJOTow0bNkg6d4alqqpKW7du7dQgumumWwAA0H1iOX7HdIalsbFRO3fulN/v/7IBu11+v19lZWVtblNWVhZVL0l5eXmt6ktLS5Wenq4xY8Zo8eLFOn36dLv9aGhoUE1NTdQCAAD6r5gCy6lTp9TS0iKPJ/rL/zwej4LBYJvbBIPBS9bPnj1bzz33nAKBgFavXq133nlHc+bMUUtLS5ttFhcXy+12Rxav1xvLMAAAQB9jxHcJzZ8/P/Lz+PHjNWHCBI0cOVKlpaW6+eabW9UvX75chYWFkcc1NTWEFgAA+rGYzrCkpaXJ4XCooqIian1FRYUyMjLa3CYjIyOmekkaMWKE0tLStH///jafT0hIUEpKStQCAAD6r5gCi9Pp1OTJkxUIBCLrwuGwAoGAcnNz29wmNzc3ql6S3nrrrXbrJeno0aM6ffq0MjMzY+keAADop2K+rbmwsFBPP/20Nm3apD179mjx4sUKhUIqKCiQJC1cuFDLly+P1P/oRz9SSUmJfvazn+nTTz/VQw89pL/+9a/64Q9/KEmqq6vTj3/8Y73//vs6dOiQAoGAbr31Vo0aNUp5eXldNEwAANCXxXwNS35+vk6ePKkVK1YoGAwqJydHJSUlkQtrDx8+LLv9yxw0ffp0vfDCC/rpT3+qBx54QKNHj9bWrVt1/fXXS5IcDoc+/PBDbdq0SVVVVcrKytKsWbO0cuVKJSQkdNEwAQBAXxbzPCwmYh4WAAD6nm6bhwUAAKA3EFgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGI/AAgAAjEdgAQAAxiOwAAAA4xFYAACA8QgsAADAeAQWAABgPAILAAAwHoEFAAAYj8ACAACMR2ABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHgEFgAAYDwCCwAAMB6BBQAAGC+utztgsnDY0rGqswo1NivJGaehgxJlt9t6u1sAAFxxCCzt2F9Zqzd3V+jAyTrVN7fIFefQyCEDlXe9R6PSk3u7ewAAXFE69Seh9evXKzs7Wy6XSz6fTzt27Lho/csvv6yxY8fK5XJp/Pjxev3116OetyxLK1asUGZmphITE+X3+7Vv377OdK1L7K+s1bPvHtLu49UaNCBeI9IGatCAeO0+Xq1n3z2k/ZW1vdY3AACuRDEHli1btqiwsFBFRUUqLy/XxIkTlZeXp8rKyjbr33vvPS1YsEB33XWXdu3apXnz5mnevHnavXt3pObRRx/VE088oQ0bNmj79u1KSkpSXl6e6uvrOz+yTgqHLb25u0Kfhxo1On2gkl3xcthtSnbFa3T6QH0eatS2jysUDls93jcAAK5UNsuyYjry+nw+TZ06VevWrZMkhcNheb1eLVmyRMuWLWtVn5+fr1AopNdeey2y7mtf+5pycnK0YcMGWZalrKws3XPPPbr33nslSdXV1fJ4PNq4caPmz5/fqs2GhgY1NDREHtfU1Mjr9aq6ulopKSmxDKeVI5+f0eNv/U2DBsQr2RXf6vna+iZVnWnS/3fLtfIOHnBZvwsAgCtZTU2N3G53h47fMZ1haWxs1M6dO+X3+79swG6X3+9XWVlZm9uUlZVF1UtSXl5epP7gwYMKBoNRNW63Wz6fr902i4uL5Xa7I4vX641lGBcVamxWfXOLBjjbvrwn0elQQ3OLQo3NXfY7AQDAxcUUWE6dOqWWlhZ5PJ6o9R6PR8FgsM1tgsHgRevP/xtLm8uXL1d1dXVkOXLkSCzDuKgkZ5xccQ6daSeQnG1sUUKcQ0ntBBoAAND1+uRRNyEhQQkJCd3S9tBBiRo5ZKB2H6/WwIQ42Wxf3sZsWZZOVNdr/FC3hg5K7JbfDwAAWovpDEtaWpocDocqKiqi1ldUVCgjI6PNbTIyMi5af/7fWNrsTna7TXnXezQ4yal9lXWqrW9Sczis2vom7aus0+Akp2aN8zAfCwAAPSimwOJ0OjV58mQFAoHIunA4rEAgoNzc3Da3yc3NjaqXpLfeeitSP3z4cGVkZETV1NTUaPv27e222d1GpSer4IZsXZ/lVtWZJh06FVLVmSaNH+pWwQ3ZzMMCAEAPi/lPQoWFhVq0aJGmTJmiadOmae3atQqFQiooKJAkLVy4UEOHDlVxcbEk6Uc/+pFmzJihn/3sZ5o7d642b96sv/71r3rqqackSTabTUuXLtUjjzyi0aNHa/jw4XrwwQeVlZWlefPmdd1IYzQqPVkjZg5kplsAAAwQc2DJz8/XyZMntWLFCgWDQeXk5KikpCRy0ezhw4dlt3954mb69Ol64YUX9NOf/lQPPPCARo8era1bt+r666+P1Nx3330KhUK6++67VVVVpRtvvFElJSVyuVxdMMTOs9tt3LoMAIABYp6HxUSx3McNAADM0G3zsAAAAPQGAgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOMRWAAAgPEILAAAwHh98tuaL3R+7ruamppe7gkAAOio88ftjsxh2y8CS21trSTJ6/X2ck8AAECsamtr5Xa7L1rTL6bmD4fDOn78uJKTk2WznftywpqaGnm9Xh05cqRfTtfP+Po2xte3Mb6+jfGZw7Is1dbWKisrK+p7CNvSL86w2O12XX311W0+l5KSYvwOuxyMr29jfH0b4+vbGJ8ZLnVm5TwuugUAAMYjsAAAAOP128CSkJCgoqIiJSQk9HZXugXj69sYX9/G+Po2xtc39YuLbgEAQP/Wb8+wAACA/oPAAgAAjEdgAQAAxiOwAAAA4xFYAACA8fpUYFm/fr2ys7Plcrnk8/m0Y8eOdmtnzpwpm83Wapk7d26k5s4772z1/OzZs3tiKFH+9Kc/6Zvf/KaysrJks9m0devWS25TWlqqSZMmKSEhQaNGjdLGjRtb1cTyenWnWMf3yiuv6JZbbtGQIUOUkpKi3Nxcvfnmm1E1Dz30UKt9N3bs2G4cRftiHV9paWmb/zeDwWBUXV/df229r2w2m8aNGxepMWn/FRcXa+rUqUpOTlZ6errmzZunvXv3XnK7l19+WWPHjpXL5dL48eP1+uuvRz1vWZZWrFihzMxMJSYmyu/3a9++fd01jDZ1ZmxPP/20brrpJqWmpio1NVV+v7/V/z1TPjs7M76NGze26rvL5YqqMWHfSZ0bX1869sWqzwSWLVu2qLCwUEVFRSovL9fEiROVl5enysrKNutfeeUVnThxIrLs3r1bDodD//Zv/xZVN3v27Ki6F198sSeGEyUUCmnixIlav359h+oPHjyouXPn6hvf+IY++OADLV26VN/5zneiDuqxvl7dKdbx/elPf9Itt9yi119/XTt37tQ3vvENffOb39SuXbui6saNGxe17/785z93R/cvKdbxnbd3796o/qenp0ee68v77z/+4z+ixnXkyBENHjy41XvPlP33zjvv6Ac/+IHef/99vfXWW2pqatKsWbMUCoXa3ea9997TggULdNddd2nXrl2aN2+e5s2bp927d0dqHn30UT3xxBPasGGDtm/frqSkJOXl5am+vr4nhiWpc2MrLS3VggUL9Pbbb6usrExer1ezZs3SsWPHoupM+OzszPikc1PW/2PfP/vss6jnTdh3UufG15eOfTGz+ohp06ZZP/jBDyKPW1parKysLKu4uLhD2z/++ONWcnKyVVdXF1m3aNEi69Zbb+3qrl4WSdarr7560Zr77rvPGjduXNS6/Px8Ky8vL/L4cl+v7tKR8bXluuuusx5++OHI46KiImvixIld17Eu0pHxvf3225Yk64svvmi3pj/tv1dffdWy2WzWoUOHIutM3X+WZVmVlZWWJOudd95pt+b222+35s6dG7XO5/NZ3/ve9yzLsqxwOGxlZGRYjz32WOT5qqoqKyEhwXrxxRe7p+Md0JGxXai5udlKTk62Nm3aFFln4menZXVsfM8++6zldrvbfd7UfWdZndt/feXY1xF94gxLY2Ojdu7cKb/fH1lnt9vl9/tVVlbWoTZ+/etfa/78+UpKSopaX1paqvT0dI0ZM0aLFy/W6dOnu7Tv3aGsrCzqtZCkvLy8yGvRFa+XScLhsGprazV48OCo9fv27VNWVpZGjBihb33rWzp8+HAv9bBzcnJylJmZqVtuuUXvvvtuZH1/23+//vWv5ff7NWzYsKj1pu6/6upqSWr1/+0fXeo9ePDgQQWDwagat9stn8/Xq/uwI2O70JkzZ9TU1NRqGxM/Ozs6vrq6Og0bNkxer1e33nqrPv7448hzpu47qXP7rz8d+/pEYDl16pRaWlrk8Xii1ns8nlZ/92/Ljh07tHv3bn3nO9+JWj979mw999xzCgQCWr16td555x3NmTNHLS0tXdr/rhYMBtt8LWpqanT27NnLfr1Ms2bNGtXV1en222+PrPP5fNq4caNKSkr05JNP6uDBg7rppptUW1vbiz3tmMzMTG3YsEG//e1v9dvf/lZer1czZ85UeXm5pMv//26S48eP64033mj13jN1/4XDYS1dulQ33HCDrr/++nbr2nsPnt8/5/81aR92dGwXuv/++5WVlRV1ADfxs7Oj4xszZoyeeeYZ/e53v9NvfvMbhcNhTZ8+XUePHpVk5r6TOrf/+tuxL663O9ATfv3rX2v8+PGaNm1a1Pr58+dHfh4/frwmTJigkSNHqrS0VDfffHNPdxNteOGFF/Twww/rd7/7XdQ1HnPmzIn8PGHCBPl8Pg0bNkwvvfSS7rrrrt7oaoeNGTNGY8aMiTyePn26Dhw4oMcff1zPP/98L/as623atEmDBg3SvHnzotabuv9+8IMfaPfu3b12PU136szYVq1apc2bN6u0tDTqwlQTPzs7Or7c3Fzl5uZGHk+fPl1f+cpX9Ktf/UorV67s7m52Wmf2X3879vWJMyxpaWlyOByqqKiIWl9RUaGMjIyLbhsKhbR58+YOfQiOGDFCaWlp2r9//2X1t7tlZGS0+VqkpKQoMTHxsl4vk2zevFnf+c539NJLL7U6/X6hQYMG6dprrzV+37Vn2rRpkb73l/1nWZaeeeYZ3XHHHXI6nRetNWH//fCHP9Rrr72mt99+W1dfffVFa9t7D57fP+f/NWUfxjK289asWaNVq1Zp27ZtmjBhwkVre/uzszPjOy8+Pl5f/epXI303bd9JnRtffzz29YnA4nQ6NXnyZAUCgci6cDisQCAQlZTb8vLLL6uhoUHf/va3L/l7jh49qtOnTyszM/Oy+9ydcnNzo14LSXrrrbcir8XlvF6mePHFF1VQUKAXX3wx6na89tTV1enAgQPG77v2fPDBB5G+94f9J527w2H//v0d+sDszf1nWZZ++MMf6tVXX9Uf//hHDR8+/JLbXOo9OHz4cGVkZETV1NTUaPv27T26DzszNuncXTIrV65USUmJpkyZcsn63vrs7Oz4/lFLS4s++uijSN9N2XfS5Y2vPx77+sxdQps3b7YSEhKsjRs3Wp988ol19913W4MGDbKCwaBlWZZ1xx13WMuWLWu13Y033mjl5+e3Wl9bW2vde++9VllZmXXw4EHrD3/4gzVp0iRr9OjRVn19fbeP58K+7Nq1y9q1a5clyfr5z39u7dq1y/rss88sy7KsZcuWWXfccUek/n/+53+sAQMGWD/+8Y+tPXv2WOvXr7ccDodVUlISqbnU62Xy+P7zP//TiouLs9avX2+dOHEislRVVUVq7rnnHqu0tNQ6ePCg9e6771p+v99KS0uzKisrjR/f448/bm3dutXat2+f9dFHH1k/+tGPLLvdbv3hD3+I1PTl/Xfet7/9bcvn87XZpkn7b/HixZbb7bZKS0uj/r+dOXMmUnPh58u7775rxcXFWWvWrLH27NljFRUVWfHx8dZHH30UqVm1apU1aNAg63e/+5314YcfWrfeeqs1fPhw6+zZs0aPbdWqVZbT6bT+67/+K2qb2tpay7LM+uzszPgefvhh680337QOHDhg7dy505o/f77lcrmsjz/+OFJjwr7r7PjO6wvHvlj1mcBiWZb1i1/8wrrmmmssp9NpTZs2zXr//fcjz82YMcNatGhRVP2nn35qSbK2bdvWqq0zZ85Ys2bNsoYMGWLFx8dbw4YNs7773e/2ygHh/G2uFy7nx7No0SJrxowZrbbJycmxnE6nNWLECOvZZ59t1e7FXq+eFOv4ZsyYcdF6yzp3G3dmZqbldDqtoUOHWvn5+db+/ft7dmB/F+v4Vq9ebY0cOdJyuVzW4MGDrZkzZ1p//OMfW7XbV/efZZ27DTQxMdF66qmn2mzTpP3X1tgkRb2n2vp8eemll6xrr73Wcjqd1rhx46zf//73Uc+Hw2HrwQcftDwej5WQkGDdfPPN1t69e3tgRF/qzNiGDRvW5jZFRUWWZZn12dmZ8S1dujTyvvJ4PNY///M/W+Xl5VHtmrDvLKvz/zf7yrEvVjbLsqyuOVcDAADQPfrENSwAAODKRmABAADGI7AAAADjEVgAAIDxCCwAAMB4BBYAAGA8AgsAADAegQUAABiPwAIAAIxHYAEAAMYjsAAAAOP9/z4pUvpj9kC4AAAAAElFTkSuQmCC", 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", "text/plain": [ "
" ] @@ -465,6 +714,33 @@ "output_type": "display_data" } ], + "source": [ + "scores = b3d.enumerate_choices_get_scores(\n", + " trace,\n", + " key,\n", + " Pytree.const((\"blur\",)),\n", + " blur_sweep,\n", + ")\n", + "plt.plot(blur_sweep, scores)" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'b3d' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[1], line 3\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mjax\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mrandom\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m key \u001b[38;5;241m=\u001b[39m \u001b[43mb3d\u001b[49m\u001b[38;5;241m.\u001b[39msplit_key(key)\n\u001b[1;32m 5\u001b[0m gt_translation \u001b[38;5;241m=\u001b[39m trace\u001b[38;5;241m.\u001b[39mget_choices()[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcamera_pose\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;241m.\u001b[39mpos\n\u001b[1;32m 6\u001b[0m w \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m3.1\u001b[39m\n", + "\u001b[0;31mNameError\u001b[0m: name 'b3d' is not defined" + ] + } + ], "source": [ "import jax.random\n", "\n", diff --git a/src/b3d/chisight/dense/dense_model.py b/src/b3d/chisight/dense/dense_model.py index 7244ead5..5bd06a7a 100644 --- a/src/b3d/chisight/dense/dense_model.py +++ b/src/b3d/chisight/dense/dense_model.py @@ -60,9 +60,7 @@ def dense_multiobject_model(args_dict): @ f"object_pose_{i}" ) - outlier_probability = ( - genjax.uniform(0.0001, 1.0) @ f"outlier_probability_{i}" - ) + outlier_probability = genjax.uniform(0.0, 1.0) @ f"outlier_probability_{i}" lightness_variance = genjax.uniform(0.0001, 1.0) @ f"lightness_variance_{i}" color_variance = genjax.uniform(0.0001, 1.0) @ f"color_variance_{i}" depth_variance = genjax.uniform(0.0001, 1.0) @ f"depth_variance_{i}" From 9ab4d8a875a30ed99faf79a35deddfe38c86e7fd Mon Sep 17 00:00:00 2001 From: Nishad Gothoskar Date: Thu, 25 Jul 2024 18:16:15 +0000 Subject: [PATCH 15/16] figure out bug in using non log kernel instead of log kernel gaussian --- notebooks/aug1demos/slam_color_room.ipynb | 447 ++++++++++++++++------ 1 file changed, 329 insertions(+), 118 deletions(-) diff --git a/notebooks/aug1demos/slam_color_room.ipynb b/notebooks/aug1demos/slam_color_room.ipynb index 491789ef..556b2901 100644 --- a/notebooks/aug1demos/slam_color_room.ipynb +++ b/notebooks/aug1demos/slam_color_room.ipynb @@ -132,43 +132,33 @@ }, { "cell_type": "code", - "execution_count": 46, + "execution_count": 77, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "[64148.992 64148.992 64148.992 64148.992 64148.72 64138.473 64074.863\n", - " 63920.66 63702.61 63478.688 63288.047 63135.72 63011.062 62903.82\n", - " 62806.684 62714.773 62625.15 62536.133 62446.81 62356.742 62265.703\n", - " 62173.66 62080.695 61986.92 61892.527 61797.742 61702.78 61607.883\n", - " 61513.266 61419.1 61325.555 61232.727 61140.703 61049.51 60959.19\n", - " 60869.73 60781.117 60693.34 60606.375 60520.21 60434.848 60350.266\n", - " 60266.445 60183.41 60101.15 60019.69 59939.027 59859.17 59780.15\n", - " 59701.96 59624.633 59548.195 59472.65 59398.023 59324.355 59251.65\n", - " 59179.945 59109.266 59039.65 58971.11 58903.688 58837.406 58772.3\n", - " 58708.402 58645.734 58584.324 58524.188 58465.36 58407.85 58351.684\n", - " 58296.863 58243.414 58191.33 58140.625 58091.29 58043.33 57996.734\n", - " 57951.496 57907.61 57865.043 57823.797 57783.844 57745.156 57707.72\n", - " 57671.508 57636.492 57602.637 57569.92 57538.312 57507.79 57478.305\n", - " 57449.836 57422.344 57395.81 57370.195 57345.465 57321.594 57298.555\n", - " 57276.31 57254.836]\n" + "[26975.96 26975.96 26976.023 26991.326 27073.22 27171.703 27243.037\n", + " 27292.375 27326.016 27346.416 27355.047 27353.271 27342.432 27323.75\n", + " 27298.328 27267.105 27230.904 27190.414 27146.22 27098.822 27048.646\n", + " 26996.047 26941.34 26884.781 26826.61 26767.025 26706.215 26644.34\n", + " 26581.562 26518.049 26453.943 26389.422 26324.643 26259.78 26195.002\n", + " 26130.484 26066.398 26002.906 25940.166 25878.316 25817.496 25757.824\n", + " 25699.395 25642.303 25586.62 25532.398 25479.684 25428.506 25378.879\n", + " 25330.814 25284.309 25239.35 25195.922 25153.996 25113.547 25074.54\n", + " 25036.94 25000.709 24965.805 24932.184 24899.805 24868.629 24838.605\n", + " 24809.7 24781.861 24755.057 24729.238 24704.375 24680.422 24657.344\n", + " 24635.105 24613.67 24593.004 24573.078 24553.863 24535.324 24517.434\n", + " 24500.168 24483.5 24467.4 24451.852 24436.828 24422.309 24408.271\n", + " 24394.7 24381.566 24368.863 24356.57 24344.668 24333.145 24321.98\n", + " 24311.162 24300.682 24290.521 24280.666 24271.111 24261.84 24252.844\n", + " 24244.11 24235.633]\n" ] }, { "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 46, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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", 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" ] @@ -191,7 +181,7 @@ " return kernel / jnp.sum(kernel)\n", "\n", "\n", - "def apply_gaussian_blur(image: jnp.ndarray, sigma, kernel_size=5) -> jnp.ndarray:\n", + "def _apply_blur(image: jnp.ndarray, sigma, kernel_size=5) -> jnp.ndarray:\n", " \"\"\"Applies Gaussian blur to an image.\"\"\"\n", " kernel = gaussian_kernel(kernel_size, sigma)\n", " # Convolve the image with the kernel\n", @@ -201,66 +191,82 @@ " return blurred_image\n", "\n", "\n", - "apply_gaussian_blur_rgbd = jax.vmap(\n", - " apply_gaussian_blur, in_axes=(-1, None, None), out_axes=-1\n", - ")\n", - "\n", - "kernel_size = 25\n", - "sigma = 1.0\n", - "\n", - "rgbd_blurred = apply_gaussian_blur_rgbd(rgbd, 1.1, kernel_size)\n", - "b3d.viz_rgb(rgbd_blurred)\n", - "\n", + "apply_blur = jax.vmap(_apply_blur, in_axes=(-1, None, None), out_axes=-1)\n", "\n", - "b3d.rr_log_rgb(\"image\", rgb1)\n", - "b3d.rr_log_rgb(\"image/2\", rgb2)\n", + "observed_camera_pose = Pose.from_translation(jnp.array([0.81, 0.0, 0.21]))\n", + "latent_camera_pose = Pose.from_translation(jnp.array([0.83, 0.0, 0.21]))\n", + "observed_rgb = renderer.render_rgbd_from_mesh(\n", + " world_mesh.transform(observed_camera_pose.inv())\n", + ")[..., :3]\n", + "latent_rgb = renderer.render_rgbd_from_mesh(\n", + " world_mesh.transform(latent_camera_pose.inv())\n", + ")[..., :3]\n", "\n", - "rgb1_blurred = apply_gaussian_blur_rgbd(rgb1, 5.1, kernel_size)\n", - "b3d.rr_log_rgb(\"image/blur\", rgb1_blurred)\n", - "\n", - "\n", - "gt_camera_pose1 = Pose.from_translation(jnp.array([0.81, 0.0, 0.21]))\n", - "gt_camera_pose2 = Pose.from_translation(jnp.array([0.84, 0.0, 0.21]))\n", - "\n", - "rgb1 = renderer.render_rgbd_from_mesh(world_mesh.transform(gt_camera_pose1.inv()))[\n", - " ..., :3\n", - "]\n", - "rgb2 = renderer.render_rgbd_from_mesh(world_mesh.transform(gt_camera_pose2.inv()))[\n", - " ..., :3\n", - "]\n", + "kernel_size = 25\n", "\n", "\n", - "def error_function(observed_rgb, latent_rgb, blur):\n", - " observed_rgb_blurred = apply_gaussian_blur_rgbd(observed_rgb, blur, kernel_size)\n", - " latent_rgb_blurred = apply_gaussian_blur_rgbd(latent_rgb, blur, kernel_size)\n", + "def likelihood(observed_rgb, latent_rgb, blur):\n", + " observed_rgb_blurred = apply_blur(observed_rgb, blur, kernel_size)\n", + " latent_rgb_blurred = apply_blur(latent_rgb, blur, kernel_size)\n", "\n", - " outlier_prob = 0.01\n", + " outlier_prob = 0.001\n", "\n", " scores_inlier = genjax.truncated_normal.logpdf(\n", - " observed_rgb_blurred, latent_rgb_blurred, 0.1, 0.0, 1.0\n", + " observed_rgb_blurred, latent_rgb_blurred, 0.3, 0.0, 1.0\n", " ) + jnp.log(1.0 - outlier_prob)\n", - " scores_outlier = (\n", - " genjax.truncated_normal.logpdf(observed_rgb_blurred, 0.5, 1000.1, 0.0, 1.0)\n", - " + jnp.log(outlier_prob) * 0.0\n", - " )\n", - "\n", + " scores_outlier = genjax.truncated_normal.logpdf(\n", + " observed_rgb_blurred, 0.5, 10.1, 0.0, 1.0\n", + " ) + jnp.log(outlier_prob)\n", " scores = jnp.logaddexp(scores_inlier, scores_outlier)\n", " return scores.sum()\n", "\n", "\n", - "error_function_vmap_blur = jax.vmap(error_function, in_axes=(None, None, 0))\n", - "blur_sweep = jnp.linspace(0.000001, 5.5, 100)\n", + "likelihood_vmap_blur = jax.vmap(likelihood, in_axes=(None, None, 0))\n", + "blur_sweep = jnp.linspace(0.01, 10.5, 100)\n", "\n", - "scores = error_function_vmap_blur(rgb1, rgb2, blur_sweep)\n", + "scores = likelihood_vmap_blur(observed_rgb, latent_rgb, blur_sweep)\n", "print(scores)\n", - "plt.plot(blur_sweep, scores)" + "plt.plot(blur_sweep, scores)\n", + "\n", + "b3d.rr_log_rgb(\"image\", observed_rgb)\n", + "b3d.rr_log_rgb(\n", + " \"image/latent\", apply_blur(latent_rgb, blur_sweep[scores.argmax()], kernel_size)\n", + ")" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 155, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1.4934343\n" + ] + }, + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 155, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "import functools\n", "\n", @@ -268,6 +274,15 @@ "import jax.numpy as jnp\n", "\n", "\n", + "def log_gaussian_kernel(size: int, sigma: float) -> jnp.ndarray:\n", + " \"\"\"Creates a 2D Gaussian kernel.\"\"\"\n", + " ax = jnp.arange(-size // 2 + 1.0, size // 2 + 1.0)\n", + " xx, yy = jnp.meshgrid(ax, ax)\n", + " kernel = -(xx**2 + yy**2) / (2.0 * sigma**2)\n", + " kernel = kernel - jax.nn.logsumexp(kernel)\n", + " return kernel\n", + "\n", + "\n", "###########\n", "@functools.partial(\n", " jnp.vectorize,\n", @@ -277,18 +292,14 @@ " 2,\n", " 3,\n", " 4,\n", - " 5,\n", - " 6,\n", " ),\n", ")\n", "def per_pixel(\n", " ij,\n", " observed_rgb,\n", " latent_rgb_padded,\n", - " variance,\n", - " outlier_prob: float,\n", - " outlier_volume: float,\n", - " filter_size: int,\n", + " log_kernel,\n", + " filter_size,\n", "):\n", " latent_rgb_padded_window = jax.lax.dynamic_slice(\n", " latent_rgb_padded,\n", @@ -296,61 +307,217 @@ " (2 * filter_size + 1, 2 * filter_size + 1, 3),\n", " )\n", " scores_inlier = genjax.truncated_normal.logpdf(\n", - " observed_rgb, latent_rgb_padded, 0.1, 0.0, 1.0\n", - " )\n", + " observed_rgb[ij[0], ij[1], :], latent_rgb_padded_window, 0.1, 0.0, 1.0\n", + " ).sum(-1)\n", + " return jax.nn.logsumexp(scores_inlier + log_kernel)\n", "\n", - " probabilities = jax.scipy.stats.norm.logpdf(\n", - " distances, loc=0.0, scale=jnp.sqrt(variance)\n", - " ).sum(-1) - jnp.log(observed_xyz.shape[0] * observed_xyz.shape[1])\n", - " return jnp.logaddexp(\n", - " probabilities.max() + jnp.log(1.0 - outlier_prob),\n", - " jnp.log(outlier_prob) - jnp.log(outlier_volume),\n", - " )\n", "\n", + "filter_size = 10\n", "\n", - "def threedp3_likelihood_per_pixel_old(\n", - " observed_xyz: jnp.ndarray,\n", - " rendered_xyz: jnp.ndarray,\n", - " variance,\n", - " outlier_prob,\n", - " outlier_volume,\n", - " filter_size,\n", - "):\n", - " rendered_xyz_padded = jax.lax.pad(\n", - " rendered_xyz,\n", - " -100.0,\n", + "\n", + "@jax.jit\n", + "def likelihood_per_pixel(observed_rgb: jnp.ndarray, latent_rgb: jnp.ndarray, blur):\n", + " latent_rgb_padded = jnp.pad(\n", + " latent_rgb,\n", " (\n", - " (\n", - " filter_size,\n", - " filter_size,\n", - " 0,\n", - " ),\n", - " (\n", - " filter_size,\n", - " filter_size,\n", - " 0,\n", - " ),\n", - " (\n", - " 0,\n", - " 0,\n", - " 0,\n", - " ),\n", + " (filter_size, filter_size),\n", + " (filter_size, filter_size),\n", + " (0, 0),\n", " ),\n", + " mode=\"edge\",\n", " )\n", " jj, ii = jnp.meshgrid(\n", - " jnp.arange(observed_xyz.shape[1]), jnp.arange(observed_xyz.shape[0])\n", + " jnp.arange(observed_rgb.shape[1]), jnp.arange(observed_rgb.shape[0])\n", " )\n", " indices = jnp.stack([ii, jj], axis=-1)\n", - " log_probabilities = gausssian_mixture_vectorize_old(\n", + "\n", + " log_kernel = log_gaussian_kernel(2 * filter_size + 1, blur)\n", + "\n", + " log_probabilities = per_pixel(\n", " indices,\n", - " observed_xyz,\n", - " rendered_xyz_padded,\n", - " variance,\n", - " outlier_prob,\n", - " outlier_volume,\n", + " observed_rgb,\n", + " latent_rgb_padded,\n", + " log_kernel,\n", " filter_size,\n", " )\n", - " return log_probabilities" + " return log_probabilities\n", + "\n", + "\n", + "filter_size = 10\n", + "\n", + "\n", + "@jax.jit\n", + "def likelihood(observed_rgb: jnp.ndarray, latent_rgb: jnp.ndarray, blur):\n", + " return likelihood_per_pixel(observed_rgb, latent_rgb, blur).sum()\n", + "\n", + "\n", + "likelihood_vmap_blur = jax.vmap(likelihood, in_axes=(None, None, 0))\n", + "\n", + "observed_camera_pose = Pose.from_translation(jnp.array([0.81, 0.0, 0.21]))\n", + "latent_camera_pose = Pose.from_translation(jnp.array([0.83, 0.0, 0.21]))\n", + "observed_rgb = renderer.render_rgbd_from_mesh(\n", + " world_mesh.transform(observed_camera_pose.inv())\n", + ")[..., :3]\n", + "latent_rgb = renderer.render_rgbd_from_mesh(\n", + " world_mesh.transform(latent_camera_pose.inv())\n", + ")[..., :3]\n", + "\n", + "b3d.rr_log_rgb(\"image\", observed_rgb)\n", + "b3d.rr_log_rgb(\"image/latent\", latent_rgb)\n", + "\n", + "\n", + "b3d.rr_log_depth(\"b\", likelihood_per_pixel(observed_rgb, latent_rgb, 0.01))\n", + "b3d.rr_log_depth(\"b/higher_noise\", likelihood_per_pixel(observed_rgb, latent_rgb, 10.0))\n", + "# b3d.rr_log_depth(\"b/diff\", likelihood_per_pixel(observed_rgb, latent_rgb, 0.01) - likelihood_per_pixel(observed_rgb, latent_rgb, 1.0))\n", + "\n", + "blur_sweep = jnp.linspace(0.01, 10.5, 100)\n", + "scores = likelihood_vmap_blur(observed_rgb, latent_rgb, blur_sweep)\n", + "print(blur_sweep[scores.argmax()])\n", + "plt.plot(blur_sweep, scores)" + ] + }, + { + "cell_type": "code", + "execution_count": 144, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "15.189407\n" + ] + }, + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "latent_rgb_padded = jnp.pad(\n", + " latent_rgb,\n", + " (\n", + " (filter_size, filter_size),\n", + " (filter_size, filter_size),\n", + " (0, 0),\n", + " ),\n", + " mode=\"edge\",\n", + ")\n", + "jj, ii = jnp.meshgrid(\n", + " jnp.arange(observed_rgb.shape[1]), jnp.arange(observed_rgb.shape[0])\n", + ")\n", + "indices = jnp.stack([ii, jj], axis=-1)\n", + "ij = jnp.array([54, 65])\n", + "\n", + "\n", + "latent_rgb_padded_window = jax.lax.dynamic_slice(\n", + " latent_rgb_padded,\n", + " (ij[0], ij[1], 0),\n", + " (2 * filter_size + 1, 2 * filter_size + 1, 3),\n", + ")\n", + "scores_inlier = genjax.truncated_normal.logpdf(\n", + " observed_rgb[ij[0], ij[1], :], latent_rgb_padded_window, 0.03, 0.0, 1.0\n", + ").sum(-1)\n", + "plt.imshow(latent_rgb_padded_window)\n", + "plt.matshow(scores_inlier)\n", + "plt.colorbar()\n", + "\n", + "blur = 0.01\n", + "log_kernel = gaussian_kernel(2 * filter_size + 1, blur)\n", + "averaged_prob = jax.nn.logsumexp(jax.nn.logsumexp(scores_inlier + log_kernel))\n", + "averaged_prob = jax.nn.logsumexp(jax.nn.logsumexp(scores_inlier + log_kernel))\n", + "print(averaged_prob)" + ] + }, + { + "cell_type": "code", + "execution_count": 148, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 148, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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dqk2bNunP/uzPouW1DRs2aOnSpdHg83UIOgBgA2HDobCJjQSjObempkbHjh1TY2OjAoGAysvL1d7eHt1c0NPTE5PZPPTQQ3I4HHrooYf06aef6pJLLtHSpUv1D//wDwmP6TASzYksEgqF5HK5dItu0wTHxFRPBwDO84UxpA69pL6+voTWTy7k3N95a/7f7XJOGf3feQOnh7R5wf9JypzGEpkOANhAsrZM2x1BBwBswDB5l2mDG34CABCLTAcAbCAsh8knh1JeAwAkKGKYW5eJ2GpL2PAorwEALEOmAwA2wOOqAQCWOfcwNjPnp4P0CI0AgHGBTAcAbCAVt8FJBYIOANhApqzppMcsAQDjApkOANhARCbvvZYmGwkIOgBgA4bJ3WsGQQcAkKhMucs0azoAAMuQ6QCADWTK7jWCDgDYAOU1AACSjEwHAGwgU+69RtABABugvAYAQJKR6QCADWRKpkPQAQAbyJSgQ3kNAGAZMh0AsIFMyXQIOgBgA4bMbXs2kjeVMUXQAQAbyJRMhzUdAIBlyHQAwAbIdEZp48aNcjgcMW327NnJHgYAxpVzQcdMSwdjkulce+21ev31178aZAIJFQBgjILOhAkT5PF4xuKtAWBcorxmwocffqji4mLNmjVLd955p3p6eobtOzAwoFAoFNMAINMYhsN0SwdJDzqVlZXaunWr2tvbtXnzZnV3d2vBggU6depU3P7Nzc1yuVzRVlJSkuwpAQBsIulBZ8mSJfrbv/1bzZ07V9XV1dq5c6dOnjyp559/Pm7/9evXq6+vL9p6e3uTPSUAsL1zz9Mx09LBmK/wT5s2TVdddZUOHToU9+dOp1NOp3OspwEAtsaaTpKcPn1ahw8fVlFR0VgPBQCwuaQHnfvuu0+7du3Sxx9/rN27d+u73/2usrOztWLFimQPBQDjRqZsJEh6ee2TTz7RihUrdOLECV1yySW6+eabtWfPHl1yySXJHgoAxo1MKa8lPeg899xzyX5LAMA4wa0CAMAGzJbIMra8BgAYOcNkeY2gAwBImCHJMPEktnR5iBvP0wEAWIZMBwBsICKHHCbuKsAdCQAACcuUjQSU1wAAliHTAQAbiBgOOfhyKADACoZhcvdammxfo7wGALAMmQ4A2ECmbCQg6ACADWRK0KG8BgCwDJkOANgAu9cAAJZh9xoAAElGpgMANnA20zGzkSCJkxlDBB0AsIFM2b1G0AEAGzBk7pk4aZLosKYDALAOmQ4A2ADlNQCAdTKkvkZ5DQBgGYIOANjBl+W10TaNsrzW2tqq0tJS5ebmqrKyUnv37r1g/5MnT6q+vl5FRUVyOp266qqrtHPnzoTHo7wGADaQijsSbN++XT6fT21tbaqsrFRLS4uqq6t18OBBFRYWntd/cHBQf/VXf6XCwkL9x3/8h6ZPn67f/e53mjZtWsJjEnQAYBwJhUIxr51Op5xOZ9y+mzZt0urVq1VXVydJamtr0yuvvKItW7bowQcfPK//li1b9Pvf/167d+/WxIkTJUmlpaUjmh/lNQCwATOltT/e+VZSUiKXyxVtzc3NcccbHBxUV1eXvF5v9FhWVpa8Xq86OzvjnvOf//mfqqqqUn19vdxut+bMmaPHHntM4XA44d+TTAcA7MDEukz0fEm9vb3Ky8uLHh4uyzl+/LjC4bDcbnfMcbfbrQMHDsQ956OPPtIbb7yhO++8Uzt37tShQ4d09913a2hoSE1NTQlNk6ADAONIXl5eTNBJpkgkosLCQv3iF79Qdna2Kioq9Omnn+pnP/sZQQcA0onVGwkKCgqUnZ2tYDAYczwYDMrj8cQ9p6ioSBMnTlR2dnb02De/+U0FAgENDg4qJyfna8dlTQcA7MBIQhuBnJwcVVRUyO/3R49FIhH5/X5VVVXFPeemm27SoUOHFIlEosd++9vfqqioKKGAIxF0ACBj+Xw+PfXUU/rVr36lDz74QGvWrFF/f390N9vKlSu1fv36aP81a9bo97//ve6991799re/1SuvvKLHHntM9fX1CY9JeQ0AbCAV916rqanRsWPH1NjYqEAgoPLycrW3t0c3F/T09Cgr66vcpKSkRK+++qrWrVunuXPnavr06br33nv1wAMPJDwmQQcA7CIF909raGhQQ0ND3J91dHScd6yqqkp79uwZ9XgEHQCwgUy5yzRrOgAAy5DpAIAdZMijDQg6AGALji+bmfPtj/IaAMAyZDoAYAeU1wAAlsmQoEN5DQBgGTIdALCDJD3awO4IOgBgA6l4XHUqUF4DAFiGTAcA7CBDNhIQdADADjJkTYfyGgDAMmQ6AGADDuNsM3N+OiDoAIAdsKYDALAMazoAACQXmQ4A2AHlNQCAZTIk6FBeAwBYhkwHAOwgQzIdgg7GjVeP7B/VedXF5UmdBzAq7F4DACC5yHQAwAa4IwEAwDoZsqYz4vLaW2+9paVLl6q4uFgOh0M7duyI+blhGGpsbFRRUZEmTZokr9erDz/8MFnzBQCksREHnf7+fpWVlam1tTXuz5944gn9/Oc/V1tbm9555x1ddNFFqq6u1pkzZ0xPFgCQ3kZcXluyZImWLFkS92eGYailpUUPPfSQbrvtNknSs88+K7fbrR07duiOO+4wN1sAGKccMrmmk7SZjK2k7l7r7u5WIBCQ1+uNHnO5XKqsrFRnZ2fccwYGBhQKhWIaAGB8SmrQCQQCkiS32x1z3O12R3/2p5qbm+VyuaKtpKQkmVMCgPRw7ns6ZloaSPn3dNavX6++vr5o6+3tTfWUAMB6RhJaGkjqlmmPxyNJCgaDKioqih4PBoMqLy+Pe47T6ZTT6UzmNAAg/bBleuRmzpwpj8cjv98fPRYKhfTOO++oqqoqmUMBANLQiDOd06dP69ChQ9HX3d3d2r9/v/Lz8zVjxgytXbtWP/nJT3TllVdq5syZ2rBhg4qLi7Vs2bJkzhsAxhXuSDCMd999VwsXLoy+9vl8kqTa2lpt3bpV999/v/r7+/XDH/5QJ0+e1M0336z29nbl5uYmb9YAMN5kSHltxEHnlltukWEM/9s5HA498sgjeuSRR0xNDBgp7hYN2B/3XgMAOyDTAQBYJVPWdFL+PR0AQOYg0wEAO8iQJ4cSdADADjJkTYfyGgDAMmQ6AGADmbKRgKADAHaQIeU1gg4A2IHJTCddgg5rOgAAy5DpAIAdUF4DAFgmQ4IO5TUAgGXIdADABjJlyzSZDgDAMgQdAIBlKK8BgB1kyEYCgg4A2ABrOgAAJBmZDgDYRZpkK2YQdADADjJkTYfyGgDAMmQ6AGADmbKRgKADAHaQIeU1gg4A2ECmZDqs6QAALEPQAQA7MJLQRqG1tVWlpaXKzc1VZWWl9u7dm9B5zz33nBwOh5YtWzai8Qg6AGAHKQg627dvl8/nU1NTk/bt26eysjJVV1fr6NGjFzzv448/1n333acFCxaMeEyCDgBkqE2bNmn16tWqq6vTNddco7a2Nk2ePFlbtmwZ9pxwOKw777xTDz/8sGbNmjXiMQk6AGAD5zYSmGmSFAqFYtrAwEDc8QYHB9XV1SWv1xs9lpWVJa/Xq87OzmHn+cgjj6iwsFCrVq0a1e9J0AEAO0hSea2kpEQulyvampub4w53/PhxhcNhud3umONut1uBQCDuOW+//baefvppPfXUU6P+NdkyDQDjSG9vr/Ly8qKvnU5nUt731KlT+v73v6+nnnpKBQUFo34fgg4A2EGSvhyal5cXE3SGU1BQoOzsbAWDwZjjwWBQHo/nvP6HDx/Wxx9/rKVLl0aPRSIRSdKECRN08OBBXX755V87LuU1ALCBZK3pJConJ0cVFRXy+/3RY5FIRH6/X1VVVef1nz17tv77v/9b+/fvj7a//uu/1sKFC7V//36VlJQkNC6ZDgBkKJ/Pp9raWs2bN0/z589XS0uL+vv7VVdXJ0lauXKlpk+frubmZuXm5mrOnDkx50+bNk2Szjt+IQQdALCDFNx7raamRseOHVNjY6MCgYDKy8vV3t4e3VzQ09OjrKzkFsQIOgBgA6m691pDQ4MaGhri/qyjo+OC527dunXE47GmAwCwDJkOANgBjzYAAFiGoAMAsIrjy2bm/HTAmg4AwDJkOgBgB5TXAABW4XHVAAAkGZkOANgB5TUAgKXSJHCYQXkNAGAZMh0AsIFM2UhA0AEAO8iQNR3KawAAy5DpAIANUF4DAFiH8hoAAMlFpgMANkB5DQBgnQwprxF0AMAOMiTosKYDALAMmQ4A2ABrOgAA61Bei++tt97S0qVLVVxcLIfDoR07dsT8/K677pLD4YhpixcvTtZ8AQBpbMSZTn9/v8rKyvR3f/d3uv322+P2Wbx4sZ555pnoa6fTOfoZAkAGcBiGHMbo0xUz51ppxEFnyZIlWrJkyQX7OJ1OeTyehN5vYGBAAwMD0dehUGikUwKA9Ed5bfQ6OjpUWFioq6++WmvWrNGJEyeG7dvc3CyXyxVtJSUlYzElAIANJD3oLF68WM8++6z8fr8ef/xx7dq1S0uWLFE4HI7bf/369err64u23t7eZE8JAGzv3O41My0dJH332h133BH983XXXae5c+fq8ssvV0dHh2699dbz+judTtZ8AIDyWnLMmjVLBQUFOnTo0FgPBQCwuTH/ns4nn3yiEydOqKioaKyHAoC0xZdDh3H69OmYrKW7u1v79+9Xfn6+8vPz9fDDD2v58uXyeDw6fPiw7r//fl1xxRWqrq5O6sQBYFzJkPLaiIPOu+++q4ULF0Zf+3w+SVJtba02b96s9957T7/61a908uRJFRcXa9GiRXr00UdZtwEAjDzo3HLLLTIu8CWkV1991dSEACATUV4DAFiH8hoAwErpkq2YwfN0AACWIdMBADswjLPNzPlpgKADADaQKRsJKK8BACxDpgMAdsDuNQCAVRyRs83M+emA8hoAwDJkOgBgB5TXAABWYfcaAABJRqYDAHbAl0MBAFahvAYAQJKR6QCAHbB7DQBglUwprxF0AMAOMmQjAWs6AADLkOkAgA1QXgMAWCdDNhJQXgMAWIZMBwBsgPIaAMA6EeNsM3N+GqC8BgCwDJkOANhBhmwkIOgAgA04ZHJNJ2kzGVuU1wAAliHTAQA7yJDb4BB0AMAGMmXLNOU1ALADIwltFFpbW1VaWqrc3FxVVlZq7969w/Z96qmntGDBAl188cW6+OKL5fV6L9g/HoIOAGSo7du3y+fzqampSfv27VNZWZmqq6t19OjRuP07Ojq0YsUKvfnmm+rs7FRJSYkWLVqkTz/9NOExCToAYAMOwzDdJCkUCsW0gYGBYcfctGmTVq9erbq6Ol1zzTVqa2vT5MmTtWXLlrj9//3f/1133323ysvLNXv2bP3yl79UJBKR3+9P+Pck6ACAHUSS0CSVlJTI5XJFW3Nzc9zhBgcH1dXVJa/XGz2WlZUlr9erzs7OhKb8+eefa2hoSPn5+Qn/mmwkAIBxpLe3V3l5edHXTqczbr/jx48rHA7L7XbHHHe73Tpw4EBCYz3wwAMqLi6OCVxfh6ADADbwxyWy0Z4vSXl5eTFBZ6z89Kc/1XPPPaeOjg7l5uYmfB5BBwDswOLb4BQUFCg7O1vBYDDmeDAYlMfjueC5//iP/6if/vSnev311zV37twRjcuaDgBkoJycHFVUVMRsAji3KaCqqmrY85544gk9+uijam9v17x580Y8LpkOANhBCu5I4PP5VFtbq3nz5mn+/PlqaWlRf3+/6urqJEkrV67U9OnTo5sRHn/8cTU2Nmrbtm0qLS1VIBCQJE2ZMkVTpkxJaEyCDgDYQCruSFBTU6Njx46psbFRgUBA5eXlam9vj24u6OnpUVbWVwWxzZs3a3BwUH/zN38T8z5NTU3auHFjQmMSdAAggzU0NKihoSHuzzo6OmJef/zxx6bHI+gAgB1ww08AgFUckbPNzPnpgN1rAADLkOkAgB1QXgMAWMbiL4emCkEHAGwgWbfBsTvWdAAAliHTAQA7YE0HAGAZQ9Fn4oz6/DRAeQ0AYBkyHQCwgUzZSEDQAQA7MGRyTSdpMxlTlNcAAJYh0wEAO2D3GgDAMhFJDpPnpwHKawAAy5DpAIANsHsNAGCdDFnTobwGALDMiIJOc3Ozrr/+ek2dOlWFhYVatmyZDh48GNPnzJkzqq+v1ze+8Q1NmTJFy5cvVzAYTOqkAWDcOZfpmGlpYERBZ9euXaqvr9eePXv02muvaWhoSIsWLVJ/f3+0z7p16/Sb3/xGL7zwgnbt2qUjR47o9ttvT/rEAWBcyZCgM6I1nfb29pjXW7duVWFhobq6uvQXf/EX6uvr09NPP61t27bpL//yLyVJzzzzjL75zW9qz549uuGGG857z4GBAQ0MDERfh0Kh0fweAJDe2DL99fr6+iRJ+fn5kqSuri4NDQ3J6/VG+8yePVszZsxQZ2dn3Pdobm6Wy+WKtpKSEjNTAgDY2KiDTiQS0dq1a3XTTTdpzpw5kqRAIKCcnBxNmzYtpq/b7VYgEIj7PuvXr1dfX1+09fb2jnZKAJC2zm2ZNtPSwai3TNfX1+v999/X22+/bWoCTqdTTqfT1HsAQNpjy/TwGhoa9PLLL+vNN9/UpZdeGj3u8Xg0ODiokydPxvQPBoPyeDymJgoASH8jCjqGYaihoUEvvvii3njjDc2cOTPm5xUVFZo4caL8fn/02MGDB9XT06OqqqrkzBgAxqOIYb6lgRGV1+rr67Vt2za99NJLmjp1anSdxuVyadKkSXK5XFq1apV8Pp/y8/OVl5ene+65R1VVVXF3rgEAvpQh5bURBZ3NmzdLkm655ZaY488884zuuusuSdI///M/KysrS8uXL9fAwICqq6v15JNPJjyG8eWF+0JDafNQIgCZ5QsNSfrq7yskbkRBJ5ELnJubq9bWVrW2to5qQqdOnZIkva2dozofAKxy6tQpuVyuJL2b2S94pkcAtN0NP4uLi9Xb26upU6fK4Yj9plQoFFJJSYl6e3uVl5eXohnaE9dmeFyb4XFthneha2MYhk6dOqXi4uLkDUh5LTWysrJidsTFk5eXx38gw+DaDI9rMzyuzfCGuzbJy3Ayi+2CDgBkpIghUyWy8bh7DQAwRozI2Wbm/DSQVs/TcTqdampq4g4GcXBthse1GR7XZnhcm7HhMNjzBwApEwqF5HK55C1ZowlZow9wX0QG9HrvZvX19dl6fY7yGgDYAWs6AADLZMiW6bRa0wEApDcyHQCwA0MmM52kzWRMEXQAwA4orwEAkFxkOgBgB5GIJBNf8Iykx5dDCToAYAeU1wAASC4yHQCwgwzJdAg6AGAHGXJHAsprAADLkOkAgA0YRkSGiccTmDnXSgQdALADwzBXIkuTNR3KawAAy5DpAIAdGCY3EqRJpkPQAQA7iEQkx/h/XDVBBwDsIEMyHdZ0AACWIdMBABswIhEZJsprbJkGACSO8hoAAMlFpgMAdhAxJMf4z3QIOgBgB4YhUw9xS5OgQ3kNAGAZMh0AsAEjYsgwUV4z0iTTIegAgB0YEZkrr6XHlmnKawCQwVpbW1VaWqrc3FxVVlZq7969F+z/wgsvaPbs2crNzdV1112nnTt3jmg8gg4A2IARMUy3kdq+fbt8Pp+ampq0b98+lZWVqbq6WkePHo3bf/fu3VqxYoVWrVql//qv/9KyZcu0bNkyvf/++wmP6TDSpRAIAONQKBSSy+XSLbpNExwTR/0+XxhD6tBL6uvrU15eXkLnVFZW6vrrr9e//du/SZIikYhKSkp0zz336MEHHzyvf01Njfr7+/Xyyy9Hj91www0qLy9XW1tbQmOS6QCADXyhIX1hmGgaknQ2iP1xGxgYiDve4OCgurq65PV6o8eysrLk9XrV2dkZ95zOzs6Y/pJUXV09bP942EgAACmUk5Mjj8ejtwMjWxuJZ8qUKSopKYk51tTUpI0bN57X9/jx4wqHw3K73THH3W63Dhw4EPf9A4FA3P6BQCDhORJ0ACCFcnNz1d3drcHBQdPvZRiGHA5HzDGn02n6fZOJoAMAKZabm6vc3FxLxywoKFB2draCwWDM8WAwKI/HE/ccj8czov7xsKYDABkoJydHFRUV8vv90WORSER+v19VVVVxz6mqqorpL0mvvfbasP3jIdMBgAzl8/lUW1urefPmaf78+WppaVF/f7/q6uokSStXrtT06dPV3NwsSbr33nv1rW99S//0T/+k73znO3ruuef07rvv6he/+EXCYxJ0ACBD1dTU6NixY2psbFQgEFB5ebna29ujmwV6enqUlfVVQezGG2/Utm3b9NBDD+nHP/6xrrzySu3YsUNz5sxJeEy+pwMAsAxrOgAAyxB0AACWIegAACxD0AEAWIagAwCwDEEHAGAZgg4AwDIEHQCAZQg6AADLEHQAAJYh6AAALPP/ActA3YMaJBBRAAAAAElFTkSuQmCC", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.matshow(log_kernel)\n", + "plt.colorbar()" + ] + }, + { + "cell_type": "code", + "execution_count": 133, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-1656.8243\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 133, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "print(\n", + " genjax.truncated_normal.logpdf(\n", + " jnp.array([1.0, 1.0, 0.0]), jnp.array([0.0, 0.0, 1.0]), 0.03, 0.0, 1.0\n", + " ).sum(-1)\n", + ")\n", + "\n", + "log_kernel = gaussian_kernel(2 * filter_size + 1, blur)\n", + "plt.matshow(log_kernel)" ] }, { @@ -360,6 +527,50 @@ "outputs": [], "source": [] }, + { + "cell_type": "code", + "execution_count": 130, + "metadata": {}, + "outputs": [], + "source": [ + "b3d.rr_log_depth(\"b\", likelihood_per_pixel(observed_rgb, latent_rgb, 0.01))\n", + "b3d.rr_log_depth(\"b/higher_noise\", likelihood_per_pixel(observed_rgb, latent_rgb, 10.0))\n", + "# b3d.rr_log_depth(\"b/diff\", likelihood_per_pixel(observed_rgb, latent_rgb, 0.01) - likelihood_per_pixel(observed_rgb, latent_rgb, 1.0))" + ] + }, + { + "cell_type": "code", + "execution_count": 127, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-2696.628\n", + "0.9999998\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "blur = 10.0\n", + "kernel = log_gaussian_kernel(2 * filter_size + 1, blur)\n", + "print(kernel.sum())\n", + "plt.matshow(jnp.exp(kernel))\n", + "plt.colorbar()\n", + "print(jnp.exp(kernel).sum())" + ] + }, { "cell_type": "code", "execution_count": 16, From 5e0c35c25037027f3c8d30c26ccdd340bd2fd9c4 Mon Sep 17 00:00:00 2001 From: Nishad Gothoskar Date: Thu, 25 Jul 2024 20:04:38 +0000 Subject: [PATCH 16/16] blur parameter inference working --- notebooks/aug1demos/slam_color_room.ipynb | 469 +++++++++++++--------- src/b3d/chisight/dense/dense_model.py | 16 +- 2 files changed, 283 insertions(+), 202 deletions(-) diff --git a/notebooks/aug1demos/slam_color_room.ipynb b/notebooks/aug1demos/slam_color_room.ipynb index 556b2901..ef674d59 100644 --- a/notebooks/aug1demos/slam_color_room.ipynb +++ b/notebooks/aug1demos/slam_color_room.ipynb @@ -27,7 +27,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 180, "metadata": {}, "outputs": [], "source": [ @@ -36,7 +36,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 156, "metadata": {}, "outputs": [], "source": [ @@ -99,7 +99,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 157, "metadata": {}, "outputs": [], "source": [ @@ -108,157 +108,296 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 271, + "metadata": {}, + "outputs": [], + "source": [ + "import functools\n", + "\n", + "import jax\n", + "import jax.numpy as jnp\n", + "\n", + "\n", + "def log_gaussian_kernel(size: int, sigma: float) -> jnp.ndarray:\n", + " \"\"\"Creates a 2D Gaussian kernel.\"\"\"\n", + " ax = jnp.arange(-size // 2 + 1.0, size // 2 + 1.0)\n", + " xx, yy = jnp.meshgrid(ax, ax)\n", + " kernel = -(xx**2 + yy**2) / (2.0 * sigma**2)\n", + " kernel = kernel - jax.nn.logsumexp(kernel)\n", + " return kernel\n", + "\n", + "\n", + "@jax.jit\n", + "def intermediate_likelihood_func(observed_rgbd, latent_rgbd, likelihood_args):\n", + " k = likelihood_args[\"k\"].const\n", + " color_variance = likelihood_args[\"color_variance_0\"]\n", + " depth_variance = likelihood_args[\"depth_variance_0\"]\n", + " blur = likelihood_args[\"blur\"]\n", + " outlier_probability = likelihood_args[\"outlier_probability_0\"]\n", + "\n", + " ###########\n", + " @functools.partial(\n", + " jnp.vectorize,\n", + " signature=\"(m)->()\",\n", + " excluded=(\n", + " 1,\n", + " 2,\n", + " 3,\n", + " 4,\n", + " ),\n", + " )\n", + " def per_pixel(\n", + " ij,\n", + " observed_rgbd,\n", + " latent_rgbd_padded,\n", + " log_kernel,\n", + " filter_size,\n", + " ):\n", + " latent_rgb_padded_window = jax.lax.dynamic_slice(\n", + " latent_rgbd_padded,\n", + " (ij[0], ij[1], 0),\n", + " (2 * filter_size + 1, 2 * filter_size + 1, 4),\n", + " )\n", + " scores_inlier = genjax.truncated_normal.logpdf(\n", + " observed_rgbd[ij[0], ij[1], :],\n", + " latent_rgb_padded_window,\n", + " jnp.array([color_variance, color_variance, color_variance, depth_variance]),\n", + " 0.0,\n", + " 1.0,\n", + " ).sum(-1)\n", + " return jax.nn.logsumexp(scores_inlier + log_kernel)\n", + "\n", + " filter_size = 10\n", + "\n", + " @jax.jit\n", + " def likelihood_per_pixel(\n", + " observed_rgbd: jnp.ndarray, latent_rgbd: jnp.ndarray, blur\n", + " ):\n", + " latent_rgbd_padded = jnp.pad(\n", + " latent_rgbd,\n", + " (\n", + " (filter_size, filter_size),\n", + " (filter_size, filter_size),\n", + " (0, 0),\n", + " ),\n", + " mode=\"edge\",\n", + " )\n", + " jj, ii = jnp.meshgrid(\n", + " jnp.arange(observed_rgbd.shape[1]), jnp.arange(observed_rgbd.shape[0])\n", + " )\n", + " indices = jnp.stack([ii, jj], axis=-1)\n", + "\n", + " log_kernel = log_gaussian_kernel(2 * filter_size + 1, blur)\n", + "\n", + " log_probabilities = per_pixel(\n", + " indices,\n", + " observed_rgbd,\n", + " latent_rgbd_padded,\n", + " log_kernel,\n", + " filter_size,\n", + " )\n", + " return log_probabilities\n", + "\n", + " pixelwise_score = likelihood_per_pixel(\n", + " observed_rgbd, latent_rgbd, likelihood_args[\"blur\"]\n", + " )\n", + " return {\n", + " \"score\": pixelwise_score.mean() * k,\n", + " \"observed_color_space_d\": observed_rgbd,\n", + " \"latent_color_space_d\": latent_rgbd,\n", + " \"pixelwise_score\": pixelwise_score,\n", + " }\n", + "\n", + "\n", + "import b3d.chisight.dense.dense_model\n", + "\n", + "b3d.reload(b3d.chisight.dense.dense_model)\n", + "model, viz_trace, info_from_trace = (\n", + " b3d.chisight.dense.dense_model.make_dense_multiobject_model(\n", + " renderer, intermediate_likelihood_func\n", + " )\n", + ")\n", + "importance_jit = jax.jit(model.importance)\n", + "\n", + "\n", + "grid3 = b3d.multivmap(\n", + " b3d.update_choices_get_score, (False, False, False, True, True, True)\n", + ")\n", + "grid4 = b3d.multivmap(\n", + " b3d.update_choices_get_score, (False, False, False, True, True, True, True)\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 277, "metadata": {}, "outputs": [ { - "data": { - "image/jpeg": 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- "image/png": "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", - "text/plain": [ - "" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + "748.9908\n" + ] } ], "source": [ + "IDX = 4\n", + "likelikood_args = {\n", + " \"fx\": renderer.fx,\n", + " \"fy\": renderer.fy,\n", + " \"cx\": renderer.cx,\n", + " \"cy\": renderer.cy,\n", + " \"k\": Pytree.const(100),\n", + "}\n", + "\n", "gt_camera_pose = Pose.from_translation(jnp.array([0.81, 0.0, 0.21]))\n", "rgbd = renderer.render_rgbd_from_mesh(world_mesh.transform(gt_camera_pose.inv()))\n", - "b3d.viz_rgb(rgbd)" + "\n", + "latent_camera_pose = Pose.from_translation(jnp.array([0.84, 0.0, 0.21]))\n", + "choicemap = genjax.ChoiceMap.d(\n", + " {\n", + " \"rgbd\": rgbd,\n", + " \"camera_pose\": latent_camera_pose,\n", + " \"object_pose_0\": Pose.identity(),\n", + " \"color_variance_0\": 0.1,\n", + " \"depth_variance_0\": 0.1,\n", + " }\n", + ")\n", + "\n", + "key = jax.random.PRNGKey(0)\n", + "trace = importance_jit(\n", + " key,\n", + " choicemap,\n", + " (\n", + " {\n", + " \"num_objects\": Pytree.const(1),\n", + " \"meshes\": [world_mesh],\n", + " \"likelihood_args\": likelikood_args,\n", + " },\n", + " ),\n", + ")[0]\n", + "print(trace.get_score())\n", + "viz_trace(trace)\n", + "info = info_from_trace(trace)" ] }, { "cell_type": "code", - "execution_count": 77, + "execution_count": 281, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "[26975.96 26975.96 26976.023 26991.326 27073.22 27171.703 27243.037\n", - " 27292.375 27326.016 27346.416 27355.047 27353.271 27342.432 27323.75\n", - " 27298.328 27267.105 27230.904 27190.414 27146.22 27098.822 27048.646\n", - " 26996.047 26941.34 26884.781 26826.61 26767.025 26706.215 26644.34\n", - " 26581.562 26518.049 26453.943 26389.422 26324.643 26259.78 26195.002\n", - " 26130.484 26066.398 26002.906 25940.166 25878.316 25817.496 25757.824\n", - " 25699.395 25642.303 25586.62 25532.398 25479.684 25428.506 25378.879\n", - " 25330.814 25284.309 25239.35 25195.922 25153.996 25113.547 25074.54\n", - " 25036.94 25000.709 24965.805 24932.184 24899.805 24868.629 24838.605\n", - " 24809.7 24781.861 24755.057 24729.238 24704.375 24680.422 24657.344\n", - " 24635.105 24613.67 24593.004 24573.078 24553.863 24535.324 24517.434\n", - " 24500.168 24483.5 24467.4 24451.852 24436.828 24422.309 24408.271\n", - " 24394.7 24381.566 24368.863 24356.57 24344.668 24333.145 24321.98\n", - " 24311.162 24300.682 24290.521 24280.666 24271.111 24261.84 24252.844\n", - " 24244.11 24235.633]\n" + "[0.05 0.05 2.6389472]\n", + "1020.5025\n" ] }, { "data": { - "image/png": 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", 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" + "Array(1037.1581, dtype=float32)" ] }, + "execution_count": 281, "metadata": {}, - "output_type": "display_data" + "output_type": "execute_result" } ], "source": [ - "import jax\n", - "import jax.numpy as jnp\n", - "from jax.numpy import convolve\n", - "\n", - "\n", - "def gaussian_kernel(size: int, sigma: float) -> jnp.ndarray:\n", - " \"\"\"Creates a 2D Gaussian kernel.\"\"\"\n", - " ax = jnp.arange(-size // 2 + 1.0, size // 2 + 1.0)\n", - " xx, yy = jnp.meshgrid(ax, ax)\n", - " kernel = jnp.exp(-(xx**2 + yy**2) / (2.0 * sigma**2))\n", - " return kernel / jnp.sum(kernel)\n", - "\n", + "# outlier_probability_sweep = jnp.linspace(0.001, 0.2, 30)\n", + "color_variance_sweep = jnp.linspace(0.05, 0.3, 20)\n", + "depth_variance_sweep = jnp.linspace(0.05, 0.3, 15)\n", + "blur_sweep = jnp.linspace(0.01, 10.0, 20)\n", "\n", - "def _apply_blur(image: jnp.ndarray, sigma, kernel_size=5) -> jnp.ndarray:\n", - " \"\"\"Applies Gaussian blur to an image.\"\"\"\n", - " kernel = gaussian_kernel(kernel_size, sigma)\n", - " # Convolve the image with the kernel\n", - " blurred_image = jnp.clip(\n", - " jax.scipy.signal.convolve(image, kernel, mode=\"same\"), 0.0, 1.0\n", + "arguments = Pytree.const(\n", + " (\n", + " \"color_variance_0\",\n", + " \"depth_variance_0\",\n", + " \"blur\",\n", " )\n", - " return blurred_image\n", - "\n", - "\n", - "apply_blur = jax.vmap(_apply_blur, in_axes=(-1, None, None), out_axes=-1)\n", - "\n", - "observed_camera_pose = Pose.from_translation(jnp.array([0.81, 0.0, 0.21]))\n", - "latent_camera_pose = Pose.from_translation(jnp.array([0.83, 0.0, 0.21]))\n", - "observed_rgb = renderer.render_rgbd_from_mesh(\n", - " world_mesh.transform(observed_camera_pose.inv())\n", - ")[..., :3]\n", - "latent_rgb = renderer.render_rgbd_from_mesh(\n", - " world_mesh.transform(latent_camera_pose.inv())\n", - ")[..., :3]\n", - "\n", - "kernel_size = 25\n", - "\n", + ")\n", + "sweeps = [\n", + " color_variance_sweep,\n", + " depth_variance_sweep,\n", + " blur_sweep,\n", + "]\n", "\n", - "def likelihood(observed_rgb, latent_rgb, blur):\n", - " observed_rgb_blurred = apply_blur(observed_rgb, blur, kernel_size)\n", - " latent_rgb_blurred = apply_blur(latent_rgb, blur, kernel_size)\n", + "key = jax.random.split(key, 2)[-1]\n", "\n", - " outlier_prob = 0.001\n", - "\n", - " scores_inlier = genjax.truncated_normal.logpdf(\n", - " observed_rgb_blurred, latent_rgb_blurred, 0.3, 0.0, 1.0\n", - " ) + jnp.log(1.0 - outlier_prob)\n", - " scores_outlier = genjax.truncated_normal.logpdf(\n", - " observed_rgb_blurred, 0.5, 10.1, 0.0, 1.0\n", - " ) + jnp.log(outlier_prob)\n", - " scores = jnp.logaddexp(scores_inlier, scores_outlier)\n", - " return scores.sum()\n", + "# arguments = Pytree.const((\"outlier_probability_background\", \"lightness_variance_background\", \"color_variance_background\", \"depth_variance_background\",))\n", "\n", + "scores = grid3(trace, key, arguments, *sweeps)\n", + "sampled_indices = jax.vmap(jnp.unravel_index, in_axes=(0, None))(\n", + " jax.random.categorical(key, scores.reshape(-1), shape=(1000,)), scores.shape\n", + ")\n", + "sampled_parameters = jnp.vstack(\n", + " [sweep[indices] for indices, sweep in zip(sampled_indices, sweeps)]\n", + ").T\n", "\n", - "likelihood_vmap_blur = jax.vmap(likelihood, in_axes=(None, None, 0))\n", - "blur_sweep = jnp.linspace(0.01, 10.5, 100)\n", + "print(sampled_parameters[0])\n", + "trace = b3d.update_choices(\n", + " trace,\n", + " key,\n", + " arguments,\n", + " # 0.05, 1.0, 0.02, 0.01\n", + " *sampled_parameters[0],\n", + ")\n", + "print(trace.get_score())\n", + "viz_trace(trace)\n", + "info_from_trace(trace)[\"score\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 286, + "metadata": {}, + "outputs": [], + "source": [ + "import jax.random\n", "\n", - "scores = likelihood_vmap_blur(observed_rgb, latent_rgb, blur_sweep)\n", - "print(scores)\n", - "plt.plot(blur_sweep, scores)\n", + "key = b3d.split_key(key)\n", "\n", - "b3d.rr_log_rgb(\"image\", observed_rgb)\n", - "b3d.rr_log_rgb(\n", - " \"image/latent\", apply_blur(latent_rgb, blur_sweep[scores.argmax()], kernel_size)\n", - ")" + "gt_translation = trace.get_choices()[\"camera_pose\"].pos\n", + "w = 2.5\n", + "wz = 3.0\n", + "grid = b3d.utils.make_grid_points(\n", + " jnp.array([gt_translation[0] - w, gt_translation[1], gt_translation[2] - wz]),\n", + " jnp.array([gt_translation[0] + w, gt_translation[1], gt_translation[2] + wz]),\n", + " jnp.array([41, 1, 31]),\n", + ")\n", + "poses = Pose.from_translation(grid)\n", + "address = Pytree.const((\"camera_pose\",))\n", + "scores = grid1(trace, key, Pytree.const((\"camera_pose\",)), poses)" ] }, { "cell_type": "code", - "execution_count": 155, + "execution_count": 287, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "1.4934343\n" + "[635 643 651] [165 249 586]\n" ] }, { "data": { "text/plain": [ - "[]" + "" ] }, - "execution_count": 155, + "execution_count": 287, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -268,91 +407,46 @@ } ], "source": [ - "import functools\n", - "\n", - "import jax\n", - "import jax.numpy as jnp\n", - "\n", - "\n", - "def log_gaussian_kernel(size: int, sigma: float) -> jnp.ndarray:\n", - " \"\"\"Creates a 2D Gaussian kernel.\"\"\"\n", - " ax = jnp.arange(-size // 2 + 1.0, size // 2 + 1.0)\n", - " xx, yy = jnp.meshgrid(ax, ax)\n", - " kernel = -(xx**2 + yy**2) / (2.0 * sigma**2)\n", - " kernel = kernel - jax.nn.logsumexp(kernel)\n", - " return kernel\n", - "\n", - "\n", - "###########\n", - "@functools.partial(\n", - " jnp.vectorize,\n", - " signature=\"(m)->()\",\n", - " excluded=(\n", - " 1,\n", - " 2,\n", - " 3,\n", - " 4,\n", - " ),\n", - ")\n", - "def per_pixel(\n", - " ij,\n", - " observed_rgb,\n", - " latent_rgb_padded,\n", - " log_kernel,\n", - " filter_size,\n", - "):\n", - " latent_rgb_padded_window = jax.lax.dynamic_slice(\n", - " latent_rgb_padded,\n", - " (ij[0], ij[1], 0),\n", - " (2 * filter_size + 1, 2 * filter_size + 1, 3),\n", - " )\n", - " scores_inlier = genjax.truncated_normal.logpdf(\n", - " observed_rgb[ij[0], ij[1], :], latent_rgb_padded_window, 0.1, 0.0, 1.0\n", - " ).sum(-1)\n", - " return jax.nn.logsumexp(scores_inlier + log_kernel)\n", - "\n", - "\n", - "filter_size = 10\n", + "sampled_indices = jax.random.categorical(key, scores * 0.2, shape=(1000,))\n", "\n", + "sampled_indices_unique, counts = jnp.unique(sampled_indices, return_counts=True)\n", + "sampled_pose = poses[sampled_indices[0]]\n", + "print(sampled_indices_unique, counts)\n", + "sampled_trace = b3d.update_choices(trace, key, address, sampled_pose)\n", + "viz_trace(sampled_trace)\n", "\n", - "@jax.jit\n", - "def likelihood_per_pixel(observed_rgb: jnp.ndarray, latent_rgb: jnp.ndarray, blur):\n", - " latent_rgb_padded = jnp.pad(\n", - " latent_rgb,\n", - " (\n", - " (filter_size, filter_size),\n", - " (filter_size, filter_size),\n", - " (0, 0),\n", - " ),\n", - " mode=\"edge\",\n", - " )\n", - " jj, ii = jnp.meshgrid(\n", - " jnp.arange(observed_rgb.shape[1]), jnp.arange(observed_rgb.shape[0])\n", - " )\n", - " indices = jnp.stack([ii, jj], axis=-1)\n", - "\n", - " log_kernel = log_gaussian_kernel(2 * filter_size + 1, blur)\n", - "\n", - " log_probabilities = per_pixel(\n", - " indices,\n", - " observed_rgb,\n", - " latent_rgb_padded,\n", - " log_kernel,\n", - " filter_size,\n", - " )\n", - " return log_probabilities\n", - "\n", - "\n", - "filter_size = 10\n", - "\n", - "\n", - "@jax.jit\n", - "def likelihood(observed_rgb: jnp.ndarray, latent_rgb: jnp.ndarray, blur):\n", - " return likelihood_per_pixel(observed_rgb, latent_rgb, blur).sum()\n", - "\n", - "\n", - "likelihood_vmap_blur = jax.vmap(likelihood, in_axes=(None, None, 0))\n", - "\n", + "plt.scatter(grid[sampled_indices, 0], grid[sampled_indices, 2], alpha=0.5)" + ] + }, + { + "cell_type": "code", + "execution_count": 204, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Array([ 0.01 , 0.5357895, 1.061579 , 1.5873685, 2.113158 ,\n", + " 2.6389472, 3.164737 , 3.6905265, 4.2163157, 4.7421055,\n", + " 5.2678947, 5.7936845, 6.3194737, 6.8452635, 7.371053 ,\n", + " 7.8968425, 8.422632 , 8.9484215, 9.474211 , 10. ], dtype=float32)" + ] + }, + "execution_count": 204, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "blur_sweep" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ "observed_camera_pose = Pose.from_translation(jnp.array([0.81, 0.0, 0.21]))\n", "latent_camera_pose = Pose.from_translation(jnp.array([0.83, 0.0, 0.21]))\n", "observed_rgb = renderer.render_rgbd_from_mesh(\n", @@ -365,15 +459,16 @@ "b3d.rr_log_rgb(\"image\", observed_rgb)\n", "b3d.rr_log_rgb(\"image/latent\", latent_rgb)\n", "\n", - "\n", - "b3d.rr_log_depth(\"b\", likelihood_per_pixel(observed_rgb, latent_rgb, 0.01))\n", - "b3d.rr_log_depth(\"b/higher_noise\", likelihood_per_pixel(observed_rgb, latent_rgb, 10.0))\n", - "# b3d.rr_log_depth(\"b/diff\", likelihood_per_pixel(observed_rgb, latent_rgb, 0.01) - likelihood_per_pixel(observed_rgb, latent_rgb, 1.0))\n", - "\n", - "blur_sweep = jnp.linspace(0.01, 10.5, 100)\n", - "scores = likelihood_vmap_blur(observed_rgb, latent_rgb, blur_sweep)\n", - "print(blur_sweep[scores.argmax()])\n", - "plt.plot(blur_sweep, scores)" + "scores = likelihood_vmap_blur(observed_rgb, latent_rgb, {\"blur\": blur_sweep})\n", + "print(scores)\n", + "# b3d.rr_log_depth(\"b\", likelihood_per_pixel(observed_rgb, latent_rgb, 0.01))\n", + "# b3d.rr_log_depth(\"b/higher_noise\", likelihood_per_pixel(observed_rgb, latent_rgb, 10.0))\n", + "# # b3d.rr_log_depth(\"b/diff\", likelihood_per_pixel(observed_rgb, latent_rgb, 0.01) - likelihood_per_pixel(observed_rgb, latent_rgb, 1.0))\n", + "\n", + "# blur_sweep = jnp.linspace(0.01, 10.5, 100)\n", + "# scores = likelihood_vmap_blur(observed_rgb, latent_rgb, blur_sweep)\n", + "# print(blur_sweep[scores.argmax()])\n", + "# plt.plot(blur_sweep, scores)" ] }, { diff --git a/src/b3d/chisight/dense/dense_model.py b/src/b3d/chisight/dense/dense_model.py index 5bd06a7a..138c4d66 100644 --- a/src/b3d/chisight/dense/dense_model.py +++ b/src/b3d/chisight/dense/dense_model.py @@ -36,23 +36,9 @@ def dense_multiobject_model(args_dict): likelihood_args = args_dict["likelihood_args"] num_objects = args_dict["num_objects"] - blur = genjax.uniform(0.0001, 1.0) @ f"blur" + blur = genjax.uniform(0.0001, 100.0) @ "blur" likelihood_args["blur"] = blur - outlier_probability = ( - genjax.uniform(0.0001, 1.0) @ f"outlier_probability_background" - ) - lightness_variance = ( - genjax.uniform(0.0001, 1.0) @ f"lightness_variance_background" - ) - color_variance = genjax.uniform(0.0001, 1.0) @ f"color_variance_background" - depth_variance = genjax.uniform(0.0001, 1.0) @ f"depth_variance_background" - - likelihood_args[f"outlier_probability_background"] = outlier_probability - likelihood_args[f"lightness_variance_background"] = lightness_variance - likelihood_args[f"color_variance_background"] = color_variance - likelihood_args[f"depth_variance_background"] = depth_variance - all_poses = [] for i in range(num_objects.const): object_pose = (