From 9515773ffe1ca26f2d4effd4b7fe2796c8f244e7 Mon Sep 17 00:00:00 2001 From: "lixin@20200" Date: Sun, 9 Apr 2023 18:58:48 +0800 Subject: [PATCH] update readme & rm outdated demos --- .gitignore | 1 + README.md | 20 +++++-- demo_axis_layer.py | 102 --------------------------------- doc/pose_correction.gif | Bin 0 -> 3113648 bytes scripts/_app.py | 44 -------------- scripts/simple_anatomy_loss.py | 2 +- 6 files changed, 16 insertions(+), 153 deletions(-) delete mode 100644 demo_axis_layer.py create mode 100644 doc/pose_correction.gif delete mode 100644 scripts/_app.py diff --git a/.gitignore b/.gitignore index 1469959..9f7bd9f 100644 --- a/.gitignore +++ b/.gitignore @@ -9,6 +9,7 @@ __pycache__/ build/ dist/ +test/ assets/mano/ assets/mano_v1_2/ assets/mano_layer.svg diff --git a/README.md b/README.md index 3d198c9..1a0f904 100644 --- a/README.md +++ b/README.md @@ -51,7 +51,6 @@ python scripts/simple_app.py --mode axis

- To overcome the first issue, For each joint rotation, we decomposed it as two rotations, one is the rotation from the original MANO basis to our newly defined anatomical consistent basis (this rotation is calculated in MANO's canonical pose and is independent to the pose of the hand), and the other is the rotation from the **unposed** anatomical consistent basis to that of the **posed** hand. @@ -61,18 +60,22 @@ To overcome the second issue, we penalize the rotation in form of the euler angles, which is more robust to the small angle. :eyes: See [manotorch/anatomy_loss.py](manotorch/anatomy_loss.py): `AnatomyConstraintLossEE` for details (EE: euler angle). -:runner: Run: [scripts/simple_anatomy_loss.py](scripts/simple_anatomy_loss.py) +:runner: Run: [scripts/simple_anatomy_loss.py](scripts/simple_anatomy_loss.py) to show the pose correction. ```shell python scripts/simple_anatomy_loss.py ``` +

+ +

+ ### Composing the Hand Based on the Anatomical Consistent Basis, we can also compose the hand from a given euler angles. :eyes: See: [manotorch/axislayer.py](manotorch/axislayer.py): `AxisLayerFK.compose` for details (FK: forward kinematics). -:runner: Run: [scripts/simple_compose.py](scripts/simple_compose.py), It demonstrates how we specify the euler angles of joint on the index finger and compose the hand in a deterministic way. +:runner: Run: [scripts/simple_compose.py](scripts/simple_compose.py), It shows how we specify the euler angles of joint on the index finger and compose the hand in a deterministic way. ```shell # transform order of right hand @@ -212,7 +215,7 @@ random_shape = torch.rand(batch_size, 10) # Generate random pose parameters, including 3 values for global axis-angle rotation random_pose = torch.rand(batch_size, 3 + ncomps) -# The mano_layer's output contains: +# The mano_layer's output contains: """ MANOOutput = namedtuple( "MANOOutput", @@ -234,5 +237,10 @@ mano_output: MANOOutput = mano_layer(random_pose, random_shape) verts = mano_output.verts # (B, 778, 3), root(center_joint) relative joints = mano_output.joints # (B, 21, 3), root relative transforms_abs = mano_output.transforms_abs # (B, 16, 4, 4), root relative -``` -For advance usages, please visit [scripts](./scripts/) for demonstrations. +``` + +### Advanced Usage + +| [Visualize](scripts/simple_app.py) | [Simple Compose](scripts/simple_compose.py) | [Error Correction](scripts/simple_anatomy_loss.py) | +| :--------------------------------: | :-----------------------------------------: | :------------------------------------------------: | +| ![](doc/axis.gif) | ![](doc/simple_compose.gif) | ![](doc/pose_correction.gif) | diff --git a/demo_axis_layer.py b/demo_axis_layer.py deleted file mode 100644 index 6c4a673..0000000 --- a/demo_axis_layer.py +++ /dev/null @@ -1,102 +0,0 @@ -from math import pi - -import numpy as np -import open3d as o3d -import torch -import tqdm - -from manotorch.axislayer import AxisAdaptiveLayer, AxisLayerFK -from manotorch.manolayer import ManoLayer, MANOOutput -from manotorch.utils.visutils import VizContext, create_coord_system_can - - -def main(): - viz_ctx = VizContext(non_block=True) - viz_ctx.init() - geometry_to_viz = dict( - hand_mesh_init=None, - hand_mesh_curr=None, - axis=None, - coord_system_list=None, - ) - - mano_layer = ManoLayer(rot_mode="axisang", - center_idx=9, - mano_assets_root="assets/mano", - use_pca=False, - flat_hand_mean=True) - hand_faces = mano_layer.th_faces # (NF, 3) - - axisIK = AxisLayerFK(mano_assets_root="assets/mano") - - # constructing the initial bending index fingers - global_aa = torch.zeros((1, 1, 3)) - composed_ee = torch.zeros((1, 16, 3)) - composed_ee[:, 1] = torch.tensor([0, 0, pi / 2]).unsqueeze(0) - composed_ee[:, 2] = torch.tensor([0, 0, pi / 2]).unsqueeze(0) - composed_ee[:, 3] = torch.tensor([0, 0, pi / 2]).unsqueeze(0) - composed_aa = axisIK.compose(composed_ee)[:, 1:, :].clone() # (B, 15, 3) - composed_aa.requires_grad_(True) - zero_shape = torch.zeros((1, 10)) - - param = [] - param.append({"params": [composed_aa]}) - optimizer = torch.optim.Adam(param, lr=1e-3) - scheduler = torch.optim.lr_scheduler.StepLR(optimizer, step_size=500, gamma=0.5) - proc_bar = tqdm.tqdm(range(5000)) - - for i, _ in enumerate(proc_bar): - - curr_pose = torch.cat([global_aa, composed_aa], dim=1).reshape(1, -1) - mano_output: MANOOutput = mano_layer(curr_pose, zero_shape) - hand_verts_curr = mano_output.verts - - T_g_p = mano_output.transforms_abs # (B, 16, 4, 4) - T_g_a, R, ee = axisIK(T_g_p) - ee_tmplind_ind = ee[:, 1:4] # (B, 3, 3) - - b_loss = torch.abs(ee_tmplind_ind[:, :, 0]).mean() - u_loss = torch.abs(ee_tmplind_ind[:, :, 1]).mean() - l_loss = torch.abs(ee_tmplind_ind[:, :, 2]).mean() - - loss = b_loss + u_loss + l_loss - proc_bar.set_description(f"b: {b_loss.item():.5f} | " - f"u: {u_loss.item():.5f} | " - f"l: {l_loss.item():.5f} | ") - loss.backward() - optimizer.step() - scheduler.step() - - # ===== draw hand curr >>>>> - if i % 10 == 0: - if geometry_to_viz["coord_system_list"] is not None: - viz_ctx.remove_geometry_list(geometry_to_viz["coord_system_list"]) - - coord_system_list = [] - for i in range(T_g_a.shape[1]): - coord_system_list += create_coord_system_can(scale=1, transf=T_g_a[0, i].detach().cpu().numpy()) - viz_ctx.add_geometry_list(coord_system_list) - geometry_to_viz["coord_system_list"] = coord_system_list - - if geometry_to_viz.get('hand_mesh_curr', None) is None: - o3d_hand_mesh_curr = o3d.geometry.TriangleMesh() - o3d_hand_mesh_curr.triangles = o3d.utility.Vector3iVector(hand_faces.detach().cpu().numpy()) - o3d_hand_mesh_curr.vertices = o3d.utility.Vector3dVector(hand_verts_curr[0].detach().cpu().numpy()) - o3d_hand_mesh_curr.compute_vertex_normals() - o3d_hand_mesh_curr.compute_triangle_normals() - o3d_hand_mesh_curr.paint_uniform_color([0.9, 0.0, 0.0]) - viz_ctx.add_geometry(o3d_hand_mesh_curr) - geometry_to_viz["hand_mesh_curr"] = 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