test_haze_detection_parallel_v1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "initial_id",
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "24b0127520ba9c9c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "solve_haze_detection 2x1, 2 pixels: solve_haze_detection 2x1, 2 pixels: 0.0 seconds, 0.0 seconds CPU\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import common\n",
    "\n",
    "from parallel_haze_detection_v1 import detect_haze_parallel_v1\n",
    "\n",
    "common.regression_test()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2dbfb2145679281c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(22, 33, 4)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "solve_haze_detection_v3 33x22, 726 pixels: solve_haze_detection_v3 33x22, 726 pixels: 0.4 seconds, 0.3 seconds CPU\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/hjhawkinsiv/analytical_smoke_detect_2024/parallel_haze_detection_v1.py:85: RuntimeWarning: invalid value encountered in divide\n",
      "  return haze_img / weight_sum\n",
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers). Got range [0.03360216218777628..122.85003547352855].\n"
     ]
    },
    {
     "data": {
      "image/png": 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ch6XluA9LTNFWUbHch6VDzCV0TG19vfy+k5uwuMxT05K5E5qt1yG2IU4fs2GXfwxO/9Bc5iGy5zBlk9z+Fdp/2PmMw3i2jnTbF5wTFod4pwTeITbsND4c+suhWpd/wmHjMKZdNjfs8iXLhct8b/a1Gqfs3a6vTAxx7fKyZgAAcGohYQEAAJ5HwgIAADyPhAUAAHgeCQsAAPA8EhYAAOB5JCwAAMDzSFgAAIDnkbAAAADPI2EBAACeR8ICAAA8j4QFAAB4HgkLAADwPBIWAADgeQnxbkBrqq8Py+eLfXpsl8npfX77nM/vt6854HPJNR2mEHeYqz3sUK1Lau3yHrmMDb/L2LAYx8cY02Ad63MZGw695dJXPocx+XG8faxLb8nYR4fDYftqrSOlsMNO7BTbYL+9LuPD4SNaDk12GpMOHx1OfWXc9oYW4QgLAADwPBIWAADgeSQsAADA80hYAACA55GwAAAAzyNhAQAAnkfCAgAAPI+EBQAAeB4JCwAA8DwSFgAA4HkkLAAAwPNaPWEpKCjQBRdcoJSUFPXq1UsTJkzQtm3bjhuzZMkS+Xy+qEdSUlJrNw0AALRTrZ6wFBYWaubMmVq/fr1ef/111dXV6YorrlBVVdVx41JTU7V///7IY/fu3a3dNAAA0E61+mzNK1eujHq+ZMkS9erVSxs3btTo0aObjfP5fMrIyGjt5gAAgA6g1ROWTyovL5ckde/e/bjlKisr1adPH4XDYZ133nn60Y9+pCFDhjRZtqamRjU1NZHnFRUVkiQTNlYz3PsDbtPT24vPVN5h2c97HvDZD5lgIGgd6wsEHGLt2+xzeI/8DnPT+xzeI2PiM54DPvsDtv6AfWyC3/FAcZx2/4DDNjfU11vH1tU1WMfW19dZx4Z9DvuDw77k9Dlr/zEr4xDs0FVOw9nnsr22cTEEtulJt+FwWLfddpsuueQSDR06tNlygwYN0hNPPKGXX35ZS5cuVTgc1sUXX6y9e/c2Wb6goEBpaWmRR+/evdtqEwAAgAf4jEsaeAK33HKLXnvtNb399ts644wzWhxXV1enc845R/n5+br33nsbvd7UEZbevXurS3KqfBapacDlCIvLt0qHb4YuXzhcvvkH/PZHK/x+jrC0vF6XIyz236BdcIQlNqfaEZbaOoc2N7iMaZfPu/hcSBu3IywOsbaJRDgcVsnBEpWXlys1NfW4ZdvsJ6FZs2bp1Vdf1Zo1a2JKViQpGAzq05/+tHbs2NHk66FQSKFQqDWaCQAA2oFWTx+NMZo1a5aWLVumN998U/369Yt5HQ0NDXr//feVmZnZ2s0DAADtUKsfYZk5c6aeeeYZvfzyy0pJSVFJSYkkKS0tTcnJyZKkKVOm6PTTT1dBQYEk6Qc/+IEuuuginXXWWSorK9MDDzyg3bt366abbmrt5gEAgHao1ROWxx57TJI0ZsyYqOVPPvmkpk2bJkkqLi6OOn/jo48+0s0336ySkhJ169ZNI0eO1Nq1a/WpT32qtZsHAADaoTY96fZkqaioUFpaGifdtrheTrptcSwn3bYYJ93GhpNuW46TbmOIdanXIfZknHTLXEIAAMDzSFgAAIDnkbAAAADPI2EBAACeR8ICAAA8j4QFAAB4HgkLAADwvDabSygeAgG/5X1Y7PM2m/rizeXeIi73rAkG7e+lkpCQaB3rd7iHi/HZxzrdTMH6rgaSjP09XFzqDTr0c2LQ/qMoMdHtYyyY4LD/O3zlc7lvTZ3DPU0qK49Yx1ZV2Y+Peod7qSTIYR+O053GjMO+5NLmeP1Hsq03llvBcYQFAAB4HgkLAADwPBIWAADgeSQsAADA80hYAACA55GwAAAAzyNhAQAAnkfCAgAAPI+EBQAAeB4JCwAA8DwSFgAA4HkkLAAAwPNIWAAAgOeRsAAAAM9zm5fdY/x+v3w2U7Y7zMft8zkEO0whHnaZutylzTb9+//5/faxwaD99PIJCYnWscZvv4v4A/axgQSH7xIOc9PHMtX7J7m8R12S7d+jlE72sZIUCtr3tUt/ucRW19Ta1xsO29dbbV+vz+GD1uETyynYGPu+Cjv0s8s+7NLPxuWfkqVwDH3MERYAAOB5JCwAAMDzSFgAAIDntXrCMn/+fPl8vqjH4MGDjxvz4osvavDgwUpKStKwYcO0YsWK1m4WAABox9rkCMuQIUO0f//+yOPtt99utuzatWuVn5+v6dOn67333tOECRM0YcIEbd26tS2aBgAA2qE2SVgSEhKUkZERefTo0aPZsg8//LDGjRunO+64Q+ecc47uvfdenXfeeVq0aFFbNA0AALRDbZKwbN++XVlZWerfv78mT56s4uLiZsuuW7dOubm5Ucvy8vK0bt26ZmNqampUUVER9QAAAB1Xqycs2dnZWrJkiVauXKnHHntMRUVFGjVqlA4fPtxk+ZKSEqWnp0ctS09PV0lJSbN1FBQUKC0tLfLo3bt3q24DAADwllZPWMaPH6/rr79ew4cPV15enlasWKGysjK98MILrVbH3LlzVV5eHnns2bOn1dYNAAC8p83vdNu1a1edffbZ2rFjR5OvZ2RkqLS0NGpZaWmpMjIyml1nKBRSKBRq1XYCAADvavP7sFRWVmrnzp3KzMxs8vWcnBytWrUqatnrr7+unJyctm4aAABoJ1o9YZkzZ44KCwu1a9curV27Vtdcc40CgYDy8/MlSVOmTNHcuXMj5W+99VatXLlSP/nJT/TBBx9o/vz52rBhg2bNmtXaTQMAAO1Uq/8ktHfvXuXn5+vQoUPq2bOnLr30Uq1fv149e/aUJBUXF0dNgnfxxRfrmWee0fe+9z3dfffdGjhwoJYvX66hQ4e2dtMAAEA75TMuU4Z6REVFhdLS0tQttbvVbM0OExDL3w5naw4E7GfVTQwGrWNDifbnHbmcs8RszbGEMltzLNrjbM3/+pf9bSAOOcQeOXrUOrYh7NDP1pFuszU3MFtzi4RNWIc+Oqjy8nKlpqYet2ybn3R7MtXVh+Xzxd7hAb9D0uHwz99tV3IYlC6JksMHh8s0736Hfk5wSLJ8DklHQqJ9vcFE+3/CLsPZhct+1Clk38+dk90+xhKD9u0ON9j/U6p3ia233x98focEzeELWjhO/0jDcUoqww4Ji0us0xcWh893236OpY+Z/BAAAHgeCQsAAPA8EhYAAOB5JCwAAMDzSFgAAIDnkbAAAADPI2EBAACeR8ICAAA8j4QFAAB4HgkLAADwPBIWAADgeSQsAADA80hYAACA55GwAAAAz3Obl91j6sNGNrOfu0yZLofpuP0O1fodgv0+h+nlHaaIb7DvKtU7xAYcYoMO/RwM2u9eSaGgdazLcHaZmj7gUG9iMGAdmxBw+97l8h677MQu+2Fd0P59Cibajy2X2IS6euvY2tpa61iFw9ahDh8dbhz2wwaX7XWKtYyLYVs5wgIAADyPhAUAAHgeCQsAAPA8EhYAAOB5JCwAAMDzSFgAAIDnkbAAAADPI2EBAACeR8ICAAA8j4QFAAB4HgkLAADwvFZPWPr27Sufz9foMXPmzCbLL1mypFHZpKSk1m4WAABox1p98sM///nPamhoiDzfunWrPvvZz+r6669vNiY1NVXbtm2LPPc5zd4GAAA6mlZPWHr27Bn1fOHChRowYIAuu+yyZmN8Pp8yMjJauykAAKCDaPWE5T/V1tZq6dKlmj179nGPmlRWVqpPnz4Kh8M677zz9KMf/UhDhgxptnxNTY1qamoizysqKiRJPr/vpB+dMQ4TkBvZt9VlO+N1AKuhwb6v6uoaTlyoGYGA/ZTpIYfOSvDbxwYD9r/W+h3qtZ4jXlLAodqEgH1sLNPTNxnvsB8mBBwa7rNvd7Defn9IDNq3OSkUtI6tr6+3jjVh+3FZZx0p+Rz2B5fdsM5lTDv0lZz+J7nthy3RpifdLl++XGVlZZo2bVqzZQYNGqQnnnhCL7/8spYuXapwOKyLL75Ye/fubTamoKBAaWlpkUfv3r3boPUAAMArfMb168lx5OXlKTExUa+88kqLY+rq6nTOOecoPz9f9957b5NlmjrC0rt3byV36mp15MHv8C064JBGu9Tr8s0u4PDt3ee3rzchmGgdmxiyPxE7KSnZOrZzJ/t6OznEJifbx7bHIyxJifZjMpTg9r0rFLSPT3DYlxrC9h+9VUdrrWMPflRhHXvoo8PWsZVVR61jjx6tOXGhZtS5HNlx2B9cYuvq7NvsdiTLIR2wTCWMMaqsPqzy8nKlpqYet2yb/SS0e/duvfHGG3rppZdiigsGg/r0pz+tHTt2NFsmFAopFAq5NhEAALQTbfaT0JNPPqlevXrp85//fExxDQ0Nev/995WZmdlGLQMAAO1NmyQs4XBYTz75pKZOnaqEhOiDOFOmTNHcuXMjz3/wgx/oD3/4g/75z39q06ZN+vKXv6zdu3frpptuaoumAQCAdqhNfhJ64403VFxcrK9+9auNXisuLpbf/+886aOPPtLNN9+skpISdevWTSNHjtTatWv1qU99qi2aBgAA2qE2Pen2ZKmoqFBaWhon3bYQJ922HCfdthwn3caGk25bjpNuW64jn3TLXEIAAMDzSFgAAIDnkbAAAADPI2EBAACeR8ICAAA8j4QFAAB4HgkLAADwvDabSyge/JYTxbvcDyVe3Kbydph+3Nj3Vdhh2nOXWJf7IbgMDZf7ofgdvkokutxXxOE+Ow63JJHLrVRc7oUiSQGHzna5D1PAb78P1yXY1xtKtH+PUzvZz+EWdNje1E5B69jaWvv7klQeqbaODTt87tQH7d+jI/a3u1GD0z1cLONiGBYcYQEAAJ5HwgIAADyPhAUAAHgeCQsAAPA8EhYAAOB5JCwAAMDzSFgAAIDnkbAAAADPI2EBAACeR8ICAAA8j4QFAAB4HgkLAADwPBIWAADgeSQsAADA8xLi3YDWFPBJPotZ1x1miJccYn0+++nWTdh+6vKwQ6MDAfsc1yf7NrvEyjRYh4bDDrEO08vLYXsDPvup6UOJ9rGJCfaxNvvtMa7fulzGtMMmK+gSm2DfYQkOnztpidahUtj+343fYYBU19nvS3tKPrKOVSA++0PJwTLr2MrKo9axYcv/SWHT8vHIERYAAOB5JCwAAMDzSFgAAIDnkbAAAADPizlhWbNmja688kplZWXJ5/Np+fLlUa8bY3TPPfcoMzNTycnJys3N1fbt20+43sWLF6tv375KSkpSdna23n333VibBgAAOqiYE5aqqiqNGDFCixcvbvL1+++/X4888ogef/xxvfPOO+rcubPy8vJUXV3d7Dqff/55zZ49W/PmzdOmTZs0YsQI5eXl6cCBA7E2DwAAdEA+Y2K4puiTwT6fli1bpgkTJkj6+OhKVlaWbr/9ds2ZM0eSVF5ervT0dC1ZskSTJk1qcj3Z2dm64IILtGjRIkkfXx7Vu3dvffOb39Rdd93VqHxNTY1qamoizysqKtS7d2+ldk6Tz+J6ML/f4Zcxh+vPXC5dC7jU63AddyBgf2liICFoHZsYSrKOTUqyj+3cuZN9bBeH2E4h69jkRPt+TgrZv7/t9bLmoMNlzU6XJjvE1jfYX27vculq9ZEq61iF66xDuay55drjZc3/Ki9TeXm5UlNTj1u2Vc9hKSoqUklJiXJzcyPL0tLSlJ2drXXr1jUZU1tbq40bN0bF+P1+5ebmNhtTUFCgtLS0yKN3796tuRkAAMBjWjVhKSkpkSSlp6dHLU9PT4+89kkHDx5UQ0NDTDFz585VeXl55LFnz55WaD0AAPCqdnmn21AopFDI/pA5AABoX1r1CEtGRoYkqbS0NGp5aWlp5LVP6tGjhwKBQEwxAADg1NKqCUu/fv2UkZGhVatWRZZVVFTonXfeUU5OTpMxiYmJGjlyZFRMOBzWqlWrmo0BAACnlph/EqqsrNSOHTsiz4uKirR582Z1795dZ555pm677Tbdd999GjhwoPr166fvf//7ysrKilxJJEljx47VNddco1mzZkmSZs+eralTp+r888/XhRdeqIceekhVVVW68cYb3bcQAAC0ezEnLBs2bNDll18eeT579mxJ0tSpU7VkyRJ95zvfUVVVlWbMmKGysjJdeumlWrlyZdSlpTt37tTBgwcjzydOnKgPP/xQ99xzj0pKSnTuuedq5cqVjU7EBQAApyan+7B4RUVFhdLS0tSjazf5fbH/ymVz75Z/B9uHxjKtduNqXdpsH5sYtD9PO+hwH5Zg0H5e+8RE+9iQwz1ckjolW8cmh+zbnORyH5Ykl1j7E+EDCfa/TvscP8EcqlZy0H5f6hKyj/U73EvpSJX9vTbK/nXIOra+1r5el3tl+QP2+9K+Q4etY4MOF4YkOHzOlhyssI49eMj+vjO1dfVWceFwWHsPHDr592EBAABoCyQsAADA80hYAACA55GwAAAAzyNhAQAAnkfCAgAAPI+EBQAAeB4JCwAA8DwSFgAA4HkkLAAAwPNIWAAAgOeRsAAAAM8jYQEAAJ5HwgIAADyPhAUAAHheQrwb0JpMWDI+E3ugTcyxUJ91qPwOwfYtlmTso41TbNg6VuF6+3ob7PPyhro669i6avv31+/QV6bBvq/CDv3s99tvb1IgZB3rsAt+HO+wHwb89vtD0NdgX6/DRtf57N/j+toa69jq6mrr2MSg/b+qgLHvrMQE+9jkpKB1bDBoH9s1pZN17JHKSutYhe0+s8IxdDFHWAAAgOeRsAAAAM8jYQEAAJ5HwgIAADyPhAUAAHgeCQsAAPA8EhYAAOB5JCwAAMDzSFgAAIDnkbAAAADPizlhWbNmja688kplZWXJ5/Np+fLlkdfq6up05513atiwYercubOysrI0ZcoU7du377jrnD9/vnw+X9Rj8ODBMW8MAADomGJOWKqqqjRixAgtXry40WtHjhzRpk2b9P3vf1+bNm3SSy+9pG3btumqq6464XqHDBmi/fv3Rx5vv/12rE0DAAAdVMwzSo0fP17jx49v8rW0tDS9/vrrUcsWLVqkCy+8UMXFxTrzzDObb0hCgjIyMmJtDgAAOAW0+Tks5eXl8vl86tq163HLbd++XVlZWerfv78mT56s4uLiZsvW1NSooqIi6gEAADou+zm7W6C6ulp33nmn8vPzlZqa2my57OxsLVmyRIMGDdL+/fu1YMECjRo1Slu3blVKSkqj8gUFBVqwYEGj5UY+GYsczBj7KeKN5ZTakuRzShft2yyf/ZTpDQ329fp99n1V7xDrDzi8Rw311rGmxqGfw/b9XFfv0GZj31fJSUHrWH/Y/qMoIWDfz5KU6LePT3TYh/3G/n1KcNj9kxyCUzrbv09JwSTr2IQE+46ub7AOlUO1Cjh8RgcD9vX6HT7fa2rt23y02u6zIxzD/9A2O8JSV1enG264QcYYPfbYY8ctO378eF1//fUaPny48vLytGLFCpWVlemFF15osvzcuXNVXl4eeezZs6ctNgEAAHhEmxxhOZas7N69W2+++eZxj640pWvXrjr77LO1Y8eOJl8PhUIKhUKt0VQAANAOtPoRlmPJyvbt2/XGG2/otNNOi3kdlZWV2rlzpzIzM1u7eQAAoB2KOWGprKzU5s2btXnzZklSUVGRNm/erOLiYtXV1emLX/yiNmzYoF//+tdqaGhQSUmJSkpKVFtbG1nH2LFjtWjRosjzOXPmqLCwULt27dLatWt1zTXXKBAIKD8/330LAQBAuxfzT0IbNmzQ5ZdfHnk+e/ZsSdLUqVM1f/58/fa3v5UknXvuuVFxq1ev1pgxYyRJO3fu1MGDByOv7d27V/n5+Tp06JB69uypSy+9VOvXr1fPnj1jbR4AAOiAYk5YxowZc9yralpyxc2uXbuinj/33HOxNgMAAJxCmEsIAAB4HgkLAADwPBIWAADgeSQsAADA80hYAACA55GwAAAAzyNhAQAAnkfCAgAAPK9NJj+MG5/5+BGjcNh+Su1wC26U1xy/sZ8G3G8fKjnU61KtS6wcpmr3ObxHcohtaKizjw3XW8eGw/Zz0wf89ttbU21fb3Ki/XengC9oHStJJmw/Mhsa7OttsPisOibgsD8EE+z7uktyonVsrc++s0Ih+/e4rsF+eyuqak9cqBnhBvt9uK7efl+qqbVvc11D2D7WckjGUiNHWAAAgOeRsAAAAM8jYQEAAJ5HwgIAADyPhAUAAHgeCQsAAPA8EhYAAOB5JCwAAMDzSFgAAIDnkbAAAADPI2EBAACeR8ICAAA8j4QFAAB4HgkLAADwvIR4N6A1hcNGxhf79NjG2E/V7jDLu1O9YfmsYwP2oZJLX4Xtpy439jPTy/jtg43PPqevdxgcYYd+rm+wn5re59DmoH21CiXaD0q/P8m+Ykl+X9A6NuAwPlz2Q4ddSX6H97i2zr7i6pp669iEgH0/JwQc9gef/ZtUF3bo55o669gj1bXWsXUN9p+VDZaDMmxaHscRFgAA4HkkLAAAwPNIWAAAgOfFnLCsWbNGV155pbKysuTz+bR8+fKo16dNmyafzxf1GDdu3AnXu3jxYvXt21dJSUnKzs7Wu+++G2vTAABABxVzwlJVVaURI0Zo8eLFzZYZN26c9u/fH3k8++yzx13n888/r9mzZ2vevHnatGmTRowYoby8PB04cCDW5gEAgA4o5quExo8fr/Hjxx+3TCgUUkZGRovX+eCDD+rmm2/WjTfeKEl6/PHH9bvf/U5PPPGE7rrrrlibCAAAOpg2OYflrbfeUq9evTRo0CDdcsstOnToULNla2trtXHjRuXm5v67UX6/cnNztW7duiZjampqVFFREfUAAAAdV6snLOPGjdOvfvUrrVq1Sj/+8Y9VWFio8ePHq6GZ67sPHjyohoYGpaenRy1PT09XSUlJkzEFBQVKS0uLPHr37t3amwEAADyk1W8cN2nSpMjfw4YN0/DhwzVgwAC99dZbGjt2bKvUMXfuXM2ePTvyvKKigqQFAIAOrM0va+7fv7969OihHTt2NPl6jx49FAgEVFpaGrW8tLS02fNgQqGQUlNTox4AAKDjavOEZe/evTp06JAyMzObfD0xMVEjR47UqlWrIsvC4bBWrVqlnJyctm4eAABoB2JOWCorK7V582Zt3rxZklRUVKTNmzeruLhYlZWVuuOOO7R+/Xrt2rVLq1at0tVXX62zzjpLeXl5kXWMHTtWixYtijyfPXu2/vu//1tPPfWU/v73v+uWW25RVVVV5KohAABwaov5HJYNGzbo8ssvjzw/di7J1KlT9dhjj2nLli166qmnVFZWpqysLF1xxRW69957FQqFIjE7d+7UwYMHI88nTpyoDz/8UPfcc49KSkp07rnnauXKlY1OxAUAAKcmn3GaqtgbKioqlJaWpq4pXa1m14zXbM0+v/1MoC6ziLrMMOsya2rQITbgEBsKJtrXm2A/k2+8ZmsOJNjPTtspyb6vUrvYz5p8WrfO1rGdO7nN1hwK2r/HSQn24zI56DAzts8+1i/7GZcPO9xCovpIlXVsl07249IfsI8tPnDYOrZO9vth2G8fW3LQvs17Sz6yjj1SbTfDdNiE9VH5RyovLz/h+aitfpVQPPlkd1KOw0ztkkPi4JLsOMXa7wty2Fqnf8JymKq9od5+WnsXtfHJg9Xg0M8uw9nvcEZcMGhfsdO4klSX2PQtF1rCOCR4DQ4fPAGHTy1/2H57K4/UWsc2OOwQCQn2scZn949Uko7W2X92HHGIbXD4Unm02v49qm/m9iMtEQ7bjclYDhgw+SEAAPA8EhYAAOB5JCwAAMDzSFgAAIDnkbAAAADPI2EBAACeR8ICAAA8j4QFAAB4HgkLAADwPBIWAADgeSQsAADA80hYAACA55GwAAAAzyNhAQAAnpcQ7wa0poDfJ7/PYpp6l9npHWJjmFW7EZvNPMYfp1iHULl0dNiloy2nTHet17i8wfZNVn1DvXVsbZ3995/KqlrrWIe3SJJUl9TgULd95cEE+/7yGfs2m/o669iaI/axyQkB69iwz/5f1dEa+zFdddQ+9iOHMV1bbz+uqo7a19tQbz+u7D+jWx7HERYAAOB5JCwAAMDzSFgAAIDnkbAAAADPI2EBAACeR8ICAAA8j4QFAAB4HgkLAADwPBIWAADgeSQsAADA82JOWNasWaMrr7xSWVlZ8vl8Wr58edTrPp+vyccDDzzQ7Drnz5/fqPzgwYNj3hgAANAxxZywVFVVacSIEVq8eHGTr+/fvz/q8cQTT8jn8+m666477nqHDBkSFff222/H2jQAANBBxTyj1Pjx4zV+/PhmX8/IyIh6/vLLL+vyyy9X//79j9+QhIRGsQAAAFIbn8NSWlqq3/3ud5o+ffoJy27fvl1ZWVnq37+/Jk+erOLi4mbL1tTUqKKiIuoBAAA6Lvs5u1vgqaeeUkpKiq699trjlsvOztaSJUs0aNAg7d+/XwsWLNCoUaO0detWpaSkNCpfUFCgBQsWNFru8318Dk2s/LazYktym9nevuLYt7J1OHSV1XvzH8HWofYTxEs+4/YOW9frEOv3ObxLDttb31BnHVtbZ7/FfsevXS7D0u8QW58QsI41xv49bqhrsI5V2H6DOycErWN9Pod/VWH77a2ttY+trKqxjq2us//UqnV4f8MO48pvuSPF8onTpkdYnnjiCU2ePFlJSUnHLTd+/Hhdf/31Gj58uPLy8rRixQqVlZXphRdeaLL83LlzVV5eHnns2bOnLZoPAAA8os2OsPzxj3/Utm3b9Pzzz8cc27VrV5199tnasWNHk6+HQiGFQiHXJgIAgHaizY6w/PKXv9TIkSM1YsSImGMrKyu1c+dOZWZmtkHLAABAexNzwlJZWanNmzdr8+bNkqSioiJt3rw56iTZiooKvfjii7rpppuaXMfYsWO1aNGiyPM5c+aosLBQu3bt0tq1a3XNNdcoEAgoPz8/1uYBAIAOKOafhDZs2KDLL7888nz27NmSpKlTp2rJkiWSpOeee07GmGYTjp07d+rgwYOR53v37lV+fr4OHTqknj176tJLL9X69evVs2fPWJsHAAA6IJ9xOd3cIyoqKpSWlqaeXbvJ74v9V65w2L4LHEKdzvS3PSNbkgIB+18CExxi/Q6Xc/gcLsfwWYyJ1qjXaceK0/sbCNjXGwzaX/WSHEq0jk1yiJWk5CT7+E4OscG4XSXkcN1cvf2VL9062fdVZ4d+PnLEvs079//LOra07Ih1bLyuEqqrt4+1HZJhY/RRRZnKy8uVmpp63LLMJQQAADyPhAUAAHgeCQsAAPA8EhYAAOB5JCwAAMDzSFgAAIDnkbAAAADPI2EBAACe12aTH8aDMXY36zJut/hy4FCvw43FXLa2weGGVcbhLnsuN8pz2WK/cajXqckO/exyL0iXehvsN7i2ts461uc0NtziXWquT7D/+DXhcFxi/cY+ttbhpmSJDuNDLjdSq7W/gVtdvUOsw43jXG7+VtdgHyvLz8pYPq84wgIAADyPhAUAAHgeCQsAAPA8EhYAAOB5JCwAAMDzSFgAAIDnkbAAAADPI2EBAACeR8ICAAA8j4QFAAB4HgkLAADwPBIWAADgeSQsAADA80hYAACA59nPb+5BO4t3KTU1Nd7NAAAALVBRUaG0tLQWleUICwAA8DwSFgAA4HkkLAAAwPNiSlgKCgp0wQUXKCUlRb169dKECRO0bdu2qDLV1dWaOXOmTjvtNHXp0kXXXXedSktLj7teY4zuueceZWZmKjk5Wbm5udq+fXvsWwMAADqkmBKWwsJCzZw5U+vXr9frr7+uuro6XXHFFaqqqoqU+fa3v61XXnlFL774ogoLC7Vv3z5de+21x13v/fffr0ceeUSPP/643nnnHXXu3Fl5eXmqrq622yoAANCh+Iwxxjb4ww8/VK9evVRYWKjRo0ervLxcPXv21DPPPKMvfvGLkqQPPvhA55xzjtatW6eLLrqo0TqMMcrKytLtt9+uOXPmSJLKy8uVnp6uJUuWaNKkSSdsx7GzjMvLy7lKCACAdiKW/99O57CUl5dLkrp37y5J2rhxo+rq6pSbmxspM3jwYJ155plat25dk+soKipSSUlJVExaWpqys7ObjampqVFFRUXUAwAAdFzWCUs4HNZtt92mSy65REOHDpUklZSUKDExUV27do0qm56erpKSkibXc2x5enp6i2MKCgqUlpYWefTu3dt2MwAAQDtgnbDMnDlTW7du1XPPPdea7WmRuXPnqry8PPLYs2fPSW8DAAA4eawSllmzZunVV1/V6tWrdcYZZ0SWZ2RkqLa2VmVlZVHlS0tLlZGR0eS6ji3/5JVEx4sJhUJKTU2NegAAgI4rpoTFGKNZs2Zp2bJlevPNN9WvX7+o10eOHKlgMKhVq1ZFlm3btk3FxcXKyclpcp39+vVTRkZGVExFRYXeeeedZmMAAMCpJaaEZebMmVq6dKmeeeYZpaSkqKSkRCUlJTp69Kikj0+WnT59umbPnq3Vq1dr48aNuvHGG5WTkxN1hdDgwYO1bNkySZLP59Ntt92m++67T7/97W/1/vvva8qUKcrKytKECRNab0sBAEC7FdPkh4899pgkacyYMVHLn3zySU2bNk2S9NOf/lR+v1/XXXedampqlJeXp0cffTSq/LZt2yJXGEnSd77zHVVVVWnGjBkqKyvTpZdeqpUrVyopKclikwAAQEfjdB8Wr+A+LAAAtD8n7T4sAAAAJwMJCwAA8DwSFgAA4HkkLAAAwPNIWAAAgOeRsAAAAM8jYQEAAJ5HwgIAADyPhAUAAHgeCQsAAPA8EhYAAOB5JCwAAMDzSFgAAIDnkbAAAADPS4h3A1qDMUbSx9NUAwCA9uHY/+1j/8ePp0MkLIcPH5Yk9e7dO84tAQAAsTp8+LDS0tKOW8ZnWpLWeFw4HNa+ffuUkpIin8/X6PWKigr17t1be/bsUWpqahxa2H7QVy1HX7UcfRUb+qvl6KuW82JfGWN0+PBhZWVlye8//lkqHeIIi9/v1xlnnHHCcqmpqZ55k7yOvmo5+qrl6KvY0F8tR1+1nNf66kRHVo7hpFsAAOB5JCwAAMDzTomEJRQKad68eQqFQvFuiufRVy1HX7UcfRUb+qvl6KuWa+991SFOugUAAB3bKXGEBQAAtG8kLAAAwPNIWAAAgOeRsAAAAM8jYQEAAJ7X4ROWxYsXq2/fvkpKSlJ2drbefffdeDfJk+bPny+fzxf1GDx4cLyb5Qlr1qzRlVdeqaysLPl8Pi1fvjzqdWOM7rnnHmVmZio5OVm5ubnavn17fBobZyfqq2nTpjUaZ+PGjYtPY+OsoKBAF1xwgVJSUtSrVy9NmDBB27ZtiypTXV2tmTNn6rTTTlOXLl103XXXqbS0NE4tjp+W9NWYMWMaja2vf/3rcWpx/Dz22GMaPnx45G62OTk5eu211yKvt+cx1aETlueff16zZ8/WvHnztGnTJo0YMUJ5eXk6cOBAvJvmSUOGDNH+/fsjj7fffjveTfKEqqoqjRgxQosXL27y9fvvv1+PPPKIHn/8cb3zzjvq3Lmz8vLyVF1dfZJbGn8n6itJGjduXNQ4e/bZZ09iC72jsLBQM2fO1Pr16/X666+rrq5OV1xxhaqqqiJlvv3tb+uVV17Riy++qMLCQu3bt0/XXnttHFsdHy3pK0m6+eabo8bW/fffH6cWx88ZZ5yhhQsXauPGjdqwYYM+85nP6Oqrr9Zf//pXSe18TJkO7MILLzQzZ86MPG9oaDBZWVmmoKAgjq3ypnnz5pkRI0bEuxmeJ8ksW7Ys8jwcDpuMjAzzwAMPRJaVlZWZUChknn322Ti00Ds+2VfGGDN16lRz9dVXx6U9XnfgwAEjyRQWFhpjPh5HwWDQvPjii5Eyf//7340ks27dung10xM+2VfGGHPZZZeZW2+9NX6N8rBu3bqZ//mf/2n3Y6rDHmGpra3Vxo0blZubG1nm9/uVm5urdevWxbFl3rV9+3ZlZWWpf//+mjx5soqLi+PdJM8rKipSSUlJ1DhLS0tTdnY246wZb731lnr16qVBgwbplltu0aFDh+LdJE8oLy+XJHXv3l2StHHjRtXV1UWNrcGDB+vMM8885cfWJ/vqmF//+tfq0aOHhg4dqrlz5+rIkSPxaJ5nNDQ06LnnnlNVVZVycnLa/ZjqELM1N+XgwYNqaGhQenp61PL09HR98MEHcWqVd2VnZ2vJkiUaNGiQ9u/frwULFmjUqFHaunWrUlJS4t08zyopKZGkJsfZsdfwb+PGjdO1116rfv36aefOnbr77rs1fvx4rVu3ToFAIN7Ni5twOKzbbrtNl1xyiYYOHSrp47GVmJiorl27RpU91cdWU30lSV/60pfUp08fZWVlacuWLbrzzju1bds2vfTSS3FsbXy8//77ysnJUXV1tbp06aJly5bpU5/6lDZv3tyux1SHTVgQm/Hjx0f+Hj58uLKzs9WnTx+98MILmj59ehxbho5k0qRJkb+HDRum4cOHa8CAAXrrrbc0duzYOLYsvmbOnKmtW7dy3lgLNNdXM2bMiPw9bNgwZWZmauzYsdq5c6cGDBhwspsZV4MGDdLmzZtVXl6u3/zmN5o6daoKCwvj3SxnHfYnoR49eigQCDQ6+7m0tFQZGRlxalX70bVrV5199tnasWNHvJviacfGEuPMTv/+/dWjR49TepzNmjVLr776qlavXq0zzjgjsjwjI0O1tbUqKyuLKn8qj63m+qop2dnZknRKjq3ExESdddZZGjlypAoKCjRixAg9/PDD7X5MddiEJTExUSNHjtSqVasiy8LhsFatWqWcnJw4tqx9qKys1M6dO5WZmRnvpnhav379lJGRETXOKioq9M477zDOWmDv3r06dOjQKTnOjDGaNWuWli1bpjfffFP9+vWLen3kyJEKBoNRY2vbtm0qLi4+5cbWifqqKZs3b5akU3JsfVI4HFZNTU37H1PxPuu3LT333HMmFAqZJUuWmL/97W9mxowZpmvXrqakpCTeTfOc22+/3bz11lumqKjI/OlPfzK5ubmmR48e5sCBA/FuWtwdPnzYvPfee+a9994zksyDDz5o3nvvPbN7925jjDELFy40Xbt2NS+//LLZsmWLufrqq02/fv3M0aNH49zyk+94fXX48GEzZ84cs27dOlNUVGTeeOMNc95555mBAwea6urqeDf9pLvllltMWlqaeeutt8z+/fsjjyNHjkTKfP3rXzdnnnmmefPNN82GDRtMTk6OycnJiWOr4+NEfbVjxw7zgx/8wGzYsMEUFRWZl19+2fTv39+MHj06zi0/+e666y5TWFhoioqKzJYtW8xdd91lfD6f+cMf/mCMad9jqkMnLMYY87Of/cyceeaZJjEx0Vx44YVm/fr18W6SJ02cONFkZmaaxMREc/rpp5uJEyeaHTt2xLtZnrB69WojqdFj6tSpxpiPL23+/ve/b9LT000oFDJjx44127Zti2+j4+R4fXXkyBFzxRVXmJ49e5pgMGj69Oljbr755lP2C0RT/STJPPnkk5EyR48eNd/4xjdMt27dTKdOncw111xj9u/fH79Gx8mJ+qq4uNiMHj3adO/e3YRCIXPWWWeZO+64w5SXl8e34XHw1a9+1fTp08ckJiaanj17mrFjx0aSFWPa95jyGWPMyTueAwAAELsOew4LAADoOEhYAACA55GwAAAAzyNhAQAAnkfCAgAAPI+EBQAAeB4JCwAA8DwSFgAA4HkkLAAAwPNIWAAAgOeRsAAAAM/7f3s1q2Byqbx5AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def low_resolution_haze_detection_v1():\n",
    "    subsample = 12\n",
    "    url0 = \"https://thumbnails-v2.createlab.org/thumbnail?root=https%3A%2F%2Fbreathecam.org%2F%23v%3D4654%2C2127%2C4915%2C2322%2Cpts%26t%3D1015.36%26ps%3D0%26bt%3D20240519140924%26et%3D20240519140924%26startDwell%3D0%26endDwell%3D0%26d%3D2024-05-19%26s%3Dclairton4%26fps%3D9&width=400&height=300&format=png&fps=9&tileFormat=mp4&startDwell=0&endDwell=0&fromScreenshot&minimalUI\"\n",
    "    im0 = common.read_image_from_url(url0, subsample=subsample) / 255.0\n",
    "    print(im0.shape)\n",
    "    plt.title(\"Input: no smoke\")\n",
    "    plt.imshow(im0 * 255.0)\n",
    "    plt.show()\n",
    "    url1 = \"https://thumbnails-v2.createlab.org/thumbnail?root=https%3A%2F%2Fbreathecam.org%2F%23v%3D4654%2C2127%2C4915%2C2322%2Cpts%26t%3D984.02%26ps%3D0%26bt%3D20240519135036%26et%3D20240519135036%26startDwell%3D0%26endDwell%3D0%26d%3D2024-05-19%26s%3Dclairton4%26fps%3D9&width=400&height=300&format=png&fps=9&tileFormat=mp4&startDwell=0&endDwell=0&fromScreenshot&minimalUI\"\n",
    "    im1 = common.read_image_from_url(url1, subsample=subsample) / 255.0\n",
    "    plt.title(\"Input: with smoke\")\n",
    "    plt.imshow(im1 * 255.0)\n",
    "    plt.show()\n",
    "    haze_image = detect_haze_parallel_v1(im0, im1)\n",
    "    plt.title(\"Output: Smoke\")\n",
    "    plt.imshow(haze_image * 255.0)\n",
    "    plt.show()\n",
    "\n",
    "low_resolution_haze_detection_v1()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "bd763256",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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