segmentation_mask_tests.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import numpy as np\n",
    "import glob\n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "filenames = glob.glob('train/img/**/*.jpg', recursive=True)\n",
    "\n",
    "selected_fnames = np.random.choice(filenames, 3).tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "for img_fname in selected_fnames:\n",
    "    dir_id, img_id = img_fname.split('/')[2:]\n",
    "    label_fname = 'train/inst/' + dir_id + '/' + img_id[:-3] + 'png'\n",
    "    img = cv2.imread(img_fname)[:, :, ::-1]\n",
    "    label = cv2.imread(label_fname)[:, :, ::-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f1b1e116dd8>"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "semantic_mask = label[:, :, 0]\n",
    "instance_idx = label[:, :, 1] * 256 + label[:, :, 2]\n",
    "inst_idx_set = set(instance_idx.flatten())\n",
    "inst_idx_set.remove(0)\n",
    "H, W = label.shape[:2]\n",
    "mask = np.zeros([H, W, len(inst_idx_set)], dtype=semantic_mask.dtype)\n",
    "for i, idx in enumerate(inst_idx_set):\n",
    "    mask[:, :, i] = (instance_idx == idx) * semantic_mask"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f1b1e09d630>"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(instance_idx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "instance_idx = np.array(instance_idx, dtype=\"uint8\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "14.9 ms ± 7.81 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit np.unique(instance_idx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "106 ms ± 1.57 ms per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit set(instance_idx.flatten())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0,  4,  5,  6,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20,\n",
       "       21, 22, 23, 24, 25, 26, 27, 28, 29, 36, 40, 41, 42, 44, 46, 47, 48,\n",
       "       49, 51, 53, 54, 57, 59, 60, 63, 64, 65, 66], dtype=uint16)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.unique(instance_idx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = [np.random.randn(1920, 1080) for _ in range(50)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "16.7 ms ± 7.76 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit -n 100 a[0].nonzero()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "9.04 ms ± 10.4 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit -n 100 np.where(a[0] != 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([   0,    0,    0, ..., 1919, 1919, 1919]),\n",
       " array([   0,    1,    2, ..., 1077, 1078, 1079]))"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[0].nonzero()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "1 not in {2:2, 3:1}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([   0,    0,    0, ..., 1919, 1919, 1919]),\n",
       " array([   0,    1,    2, ..., 1077, 1078, 1079]))"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.where(a[0] != 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "618"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.random.randint(0, 1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "mask = np.transpose(mask, [1, 2, 0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "98 µs ± 32.3 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit np.where(mask[0] != 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "A = torch.tensor(mask)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "87.1 µs ± 326 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit A[0].nonzero()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "torch.nn.functional.interpolate()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "A = torch.tensor(np.array(instance_idx, dtype=\"uint8\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.56 µs ± 5.68 ns per loop (mean ± std. dev. of 7 runs, 1000000 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit A[10:-10, 10:-10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,\n",
       "        3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3,\n",
       "        3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3]),\n",
       " array([1020, 1021, 1022, 1023, 1024, 1025, 1026, 1027, 1028, 1029, 1030,\n",
       "        1031, 1032, 1033, 1034, 1035, 1036, 1037, 1038, 1039, 1040, 1041,\n",
       "        1042, 1043, 1044, 1045, 1046, 1047, 1048, 1049, 1050, 1051, 1052,\n",
       "        1053, 1054, 1055, 1056, 1057, 1058, 1059, 1060, 1061, 1062, 1063,\n",
       "        1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074,\n",
       "        1075, 1076, 1077, 1078, 1079]))"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mask[0].nonzero()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([60, 2])"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A[0].nonzero().shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3]"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(map(int, [1., 2, 3]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "14.6 ms ± 221 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit -n 100 torch.unique(A)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "A = torch.randn(40, 1080, 1920)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "214 ms ± 644 µs per loop (mean ± std. dev. of 7 runs, 20 loops each)\n"
     ]
    }
   ],
   "source": [
    "%%timeit -n 20\n",
    "dim = 2\n",
    "flip_idx = torch.tensor(list(range(A.shape[dim])[::-1]))\n",
    "A.index_select(dim, flip_idx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "259 ms ± 1.24 ms per loop (mean ± std. dev. of 7 runs, 20 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit -n 20 A.flip(dim)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A.shape == torch.Size([40, 1080, 1920])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "74.5 ms ± 31.6 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit np.stack(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "74.6 ms ± 233 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)\n"
     ]
    }
   ],
   "source": [
    "%timeit np.array(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1f201a9940>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0, 19}\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1f17201c18>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0, 19}\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1f18b7d5c0>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0, 19}\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1f201b4cc0>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0, 24}\n"
     ]
    }
   ],
   "source": [
    "for i in range(4):\n",
    "    plt.imshow(mask[:, :, i])\n",
    "    plt.show()\n",
    "    print(set(mask[:, :, i].flatten()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "        0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
       "        0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
       "        0.000000e+00, 0.000000e+00, 0.000000e+00, 6.340200e+04,\n",
       "        0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
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       "        0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
       "        0.000000e+00, 8.159000e+03, 0.000000e+00, 0.000000e+00,\n",
       "        0.000000e+00, 1.099000e+03, 0.000000e+00, 0.000000e+00,\n",
       "        0.000000e+00, 1.416000e+03, 1.255000e+03, 0.000000e+00,\n",
       "        0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
       "        0.000000e+00, 0.000000e+00, 1.344000e+03, 0.000000e+00,\n",
       "        1.488000e+03, 4.336000e+03, 0.000000e+00, 2.279000e+03,\n",
       "        0.000000e+00, 3.956000e+03, 0.000000e+00, 0.000000e+00,\n",
       "        0.000000e+00, 1.373000e+03, 0.000000e+00, 0.000000e+00,\n",
       "        7.459000e+03, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
       "        1.360000e+02, 0.000000e+00, 6.030000e+02, 5.000000e+00]),\n",
       " array([  0.        ,   0.55078125,   1.1015625 ,   1.65234375,\n",
       "          2.203125  ,   2.75390625,   3.3046875 ,   3.85546875,\n",
       "          4.40625   ,   4.95703125,   5.5078125 ,   6.05859375,\n",
       "          6.609375  ,   7.16015625,   7.7109375 ,   8.26171875,\n",
       "          8.8125    ,   9.36328125,   9.9140625 ,  10.46484375,\n",
       "         11.015625  ,  11.56640625,  12.1171875 ,  12.66796875,\n",
       "         13.21875   ,  13.76953125,  14.3203125 ,  14.87109375,\n",
       "         15.421875  ,  15.97265625,  16.5234375 ,  17.07421875,\n",
       "         17.625     ,  18.17578125,  18.7265625 ,  19.27734375,\n",
       "         19.828125  ,  20.37890625,  20.9296875 ,  21.48046875,\n",
       "         22.03125   ,  22.58203125,  23.1328125 ,  23.68359375,\n",
       "         24.234375  ,  24.78515625,  25.3359375 ,  25.88671875,\n",
       "         26.4375    ,  26.98828125,  27.5390625 ,  28.08984375,\n",
       "         28.640625  ,  29.19140625,  29.7421875 ,  30.29296875,\n",
       "         30.84375   ,  31.39453125,  31.9453125 ,  32.49609375,\n",
       "         33.046875  ,  33.59765625,  34.1484375 ,  34.69921875,\n",
       "         35.25      ,  35.80078125,  36.3515625 ,  36.90234375,\n",
       "         37.453125  ,  38.00390625,  38.5546875 ,  39.10546875,\n",
       "         39.65625   ,  40.20703125,  40.7578125 ,  41.30859375,\n",
       "         41.859375  ,  42.41015625,  42.9609375 ,  43.51171875,\n",
       "         44.0625    ,  44.61328125,  45.1640625 ,  45.71484375,\n",
       "         46.265625  ,  46.81640625,  47.3671875 ,  47.91796875,\n",
       "         48.46875   ,  49.01953125,  49.5703125 ,  50.12109375,\n",
       "         50.671875  ,  51.22265625,  51.7734375 ,  52.32421875,\n",
       "         52.875     ,  53.42578125,  53.9765625 ,  54.52734375,\n",
       "         55.078125  ,  55.62890625,  56.1796875 ,  56.73046875,\n",
       "         57.28125   ,  57.83203125,  58.3828125 ,  58.93359375,\n",
       "         59.484375  ,  60.03515625,  60.5859375 ,  61.13671875,\n",
       "         61.6875    ,  62.23828125,  62.7890625 ,  63.33984375,\n",
       "         63.890625  ,  64.44140625,  64.9921875 ,  65.54296875,\n",
       "         66.09375   ,  66.64453125,  67.1953125 ,  67.74609375,\n",
       "         68.296875  ,  68.84765625,  69.3984375 ,  69.94921875,\n",
       "         70.5       ,  71.05078125,  71.6015625 ,  72.15234375,\n",
       "         72.703125  ,  73.25390625,  73.8046875 ,  74.35546875,\n",
       "         74.90625   ,  75.45703125,  76.0078125 ,  76.55859375,\n",
       "         77.109375  ,  77.66015625,  78.2109375 ,  78.76171875,\n",
       "         79.3125    ,  79.86328125,  80.4140625 ,  80.96484375,\n",
       "         81.515625  ,  82.06640625,  82.6171875 ,  83.16796875,\n",
       "         83.71875   ,  84.26953125,  84.8203125 ,  85.37109375,\n",
       "         85.921875  ,  86.47265625,  87.0234375 ,  87.57421875,\n",
       "         88.125     ,  88.67578125,  89.2265625 ,  89.77734375,\n",
       "         90.328125  ,  90.87890625,  91.4296875 ,  91.98046875,\n",
       "         92.53125   ,  93.08203125,  93.6328125 ,  94.18359375,\n",
       "         94.734375  ,  95.28515625,  95.8359375 ,  96.38671875,\n",
       "         96.9375    ,  97.48828125,  98.0390625 ,  98.58984375,\n",
       "         99.140625  ,  99.69140625, 100.2421875 , 100.79296875,\n",
       "        101.34375   , 101.89453125, 102.4453125 , 102.99609375,\n",
       "        103.546875  , 104.09765625, 104.6484375 , 105.19921875,\n",
       "        105.75      , 106.30078125, 106.8515625 , 107.40234375,\n",
       "        107.953125  , 108.50390625, 109.0546875 , 109.60546875,\n",
       "        110.15625   , 110.70703125, 111.2578125 , 111.80859375,\n",
       "        112.359375  , 112.91015625, 113.4609375 , 114.01171875,\n",
       "        114.5625    , 115.11328125, 115.6640625 , 116.21484375,\n",
       "        116.765625  , 117.31640625, 117.8671875 , 118.41796875,\n",
       "        118.96875   , 119.51953125, 120.0703125 , 120.62109375,\n",
       "        121.171875  , 121.72265625, 122.2734375 , 122.82421875,\n",
       "        123.375     , 123.92578125, 124.4765625 , 125.02734375,\n",
       "        125.578125  , 126.12890625, 126.6796875 , 127.23046875,\n",
       "        127.78125   , 128.33203125, 128.8828125 , 129.43359375,\n",
       "        129.984375  , 130.53515625, 131.0859375 , 131.63671875,\n",
       "        132.1875    , 132.73828125, 133.2890625 , 133.83984375,\n",
       "        134.390625  , 134.94140625, 135.4921875 , 136.04296875,\n",
       "        136.59375   , 137.14453125, 137.6953125 , 138.24609375,\n",
       "        138.796875  , 139.34765625, 139.8984375 , 140.44921875,\n",
       "        141.        ]),\n",
       " <a list of 256 Patch objects>)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f1f20283eb8>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(instance_idx.flatten(), bins=256)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "def instanceToDepth(label):\n",
    "    semantic_mask = label[:, :, 0]\n",
    "    instance_idx = label[:, :, 1] * 256 + label[:, :, 2]\n",
    "    inst_idx_set = set(instance_idx.flatten())\n",
    "    inst_idx_set.remove(0)\n",
    "    H, W = label.shape[:2]\n",
    "    mask = np.zeros([H, W, len(inst_idx_set)], dtype=semantic_mask.dtype)\n",
    "    for i, idx in enumerate(inst_idx_set):\n",
    "        mask[:, :, i] = (instance_idx == idx) * semantic_mask"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.7.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}