25-Connected_components.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <div style=\"direction:rtl;text-align:right;font-family:B Lotus, B Nazanin, Tahoma\">برچسب زنی اجزای متصل و پیوسته</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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kYSkwQuJsQxHJqrosBT4CnFSlbwzwirvvB7yS/Bwz6wkMBg5Mvma8mWX9lus33XRTo/fRunVrrrjiijREIyIBe4Qcy2HclIbFhNbAFXm3KCESerUWVu7+DxLnraTqDzyafPwoMCClf4q7b3P3j4GFQJ80xVon3bp1S9tMU/fu3WnRokVa9iUiwci1HMbelp4ZKzPobqAUJpJVDT14vYO7rwBIftw92b8nsCRlu6XJvp2Y2QVmNsvMZjUwhmqdfPLJdO3aNS376tevX9r2JSKhEtocxskR6JamswL7RaBrCO5JKFJA0n1WYHU/wdVemMXdJ7h7b3fvna43b9KkCf369UvX7gAYOHBgWvcnIqEWaA6jCYnCKp0G5tXJ3yKh19AF+M/NrJO7rzCzTsDKZP9SoEvKdp2B5Y0JsD7Kyso47rjjat1u7ty5zJ8/n+OPP54OHTrsctvvfve7/PznP09ThJIrPvzwQ6ZMmRJoDKtXrw70/fNcKHMYZUDfOhRC78RhvsPxEei4ixkpM/huFH6ehss3SG5Z+F94anKwMawp0Bzm7rU2oBvwbsrntwFjko/HAL9JPj4QeAcoBfYGPgKiddi/p6MdcMABvnnzZq/Jhg0b/G9/+5t37drVAf/e977n8+bN84qKihpfM2vWLG/VqlVa4lNTU6vUZtUl/6SjkSM5jG+Ys6nU8bLq2/pS5/+Kna7J7b8XceaVOOW7eM3MEqdV4N9rNbW8azXmgzokjMnAChL3ZV8KnA+0I3EmzYfJj21Ttr8WWAR8AJxcx6SXlkH+/ve/r7Y4isfjvmHDBh8yZMhOrykqKvJ77rlnlwXZoEGDAv8GqqnlYctKYUUO5TAeLHLi1RRJsdJEUTUksvNrinDuKUoUZNW9Nl7qDKrmdWpqao1qDS6sspT4Gj3Adu3a+T/+8Y9qC6Np06Z5+/btPRKpPrmUlJT4gQce6AsWLKj29XfeeadHo9HAv4lqannWsjZjlQs5jHY4/yjZuTDyMmdqsdMeJ1LDa0twDjRnfg2vv7PIiQb+/VZTy6uW94VV7969dyqIVqxY4aeeeqq3adOmTvvo2rWrX3LJJTvNXq1YscLLysoC/yaqqeVZU2GV2nrbzjNOy0udUyNO6zruoyvOJdGdlxOXlzplgX+/1dTyquV9YfXb3/72q0KovLzcP/30Uz/qqKMatK+LLrrI165d+9X+tmzZ4oMHDw78m5judvbZZ3vLli0Dj0OtYJsKq9R2V8oy4PZS55NS5yhr2L4uijprUpYGN5c6g/NvOfCss/EWLYOPQ60wW035IG/Owz3yyCO/enz77bfzjW98g9dff71B+xo/fjw9evTg5ZdfBhKXcTjssMPSEmeYnHrqqUyePJnWrXXfC5HAfTuZjt3hjhj03Aave8P2NT4GB2yDl+OJ/TU1OCxv0v1XTjoFHn0SWimFSYjkxU9ahw4daNGiBe+88w7f+ta3uOmmmxp18+R4PM7KlSsZPHgwp59+Ol988QWdO3emSZMmaYw6eGZGv379ePTRR2nXrl3Q4YgUrg4krpD+jkOf7XBTI2+eHCdxAYmzy+GH5fCFw56WuE5WHjGDE/vBxEegrVKYhEReFFbHH388jz32GKeffjqzZs1i69atadnv6tWrmT59OgMGDGDjxo106tQpLfsNm9NOO40HH3yQaDT7t0QTERLXo3o0liiCZjmkJ4XBamB6HAZsh00OnfLvKuxmcGp/GP8gKIVJGOTFHTqffvpp4vH4jmMd0u5f//oX//nPf4jH4xnZfxgcf/zxHH300bz66qtBhyIZZPb1L9ZM/bxIAzwdT8wyZepb8i+H/1Qk3iNPHXscHHk0vKYUltdS/zQIawbLixmrWCyW8V8S2XiPILVq1YpnnnmGE044IehQJEN69+7NO++8w/vvv8/MmTM58MADgw5JdoiR+d8S2XiPALVuDU88Dcd9J+hIJFO+ZTCnBN4vgTdLoGdIJ2DzorCS9Gjfvj2PP/64iqs8deGFF3LwwQez//77c/jhh3PxxRdTVJQXk9YiAOy2Gzz0OBynFJaXfhKFb0Zg/wj0jsDF0XAuu6mwkko6duzIlClT6Nu3b9ChSIadf/75dO/ePegwRNKqYyd4bDIcoxSW986PQvcQzlqpsJKdtG/fnqlTp2rmKs9Fo1FuuummoMMQSbv2u8ETz8DxSmF5LQrcFMIpKxVWUq127drxxBNP8N3vfjfoUCRNJkyYsNMZs507d6ZZs2YBRSSSOe3bJ5YFv6MUljcmxuDLlOMEzRJXEQlbBlNhJTXq0KED48aN03E4eWLOnDk8//zzlfq+/e1vc/LJJwcUkUhmdegIt98NSmH5YY7D81XObP22wckhq2RCFo6Ezf77789dd91FSUlJ0KFII23dupW///3vO/XfdNNNKp4lb3XfH35zFyiF5b6twKtVCiszuLEoXAexq7CSXYpGo1x44YX8+te/zrsrzxei6dOn89FHH1Xqa9u2LbvvvntAEYlkVlER/HgU/PxWUArLfdNjsKhKcdXOIEwZTIWV1CoSiXDppZdy6623amYjxy1fvpyHH364Ul/Hjh0ZOXJkQBGJZF40ChddmiiulMJy23LgkVjlvg7AyBB9X1VYSZ2NHj2au+66i+Li4qBDkUaobjnwkEMOoXnz5tkPRiRLzOCCCxPLgkphue3v1SwHftMgLBlMhZXUWTQaZdSoUdx+++00bdo06HCkgebMmcOLL75Yqe/UU0+lV69eAUUkkh1FRfDjn8CvbocmSmE5a47DjCqzVqdG4NCQXNNKhZXUSzQa5eKLL+ZXv/qVDmjPUZs2bWLJkiWV+qLRKFdeeWVAEYlkT7QIRv0Ubv6VDmjPVZuApQ6pd5krMrgiJMuBKqykQS666CJ++MMfBh2GNNDNN9+80zWtunXrxl577RVQRCLZYwY/GQ0Dzwg6EmmomysSZwmm6moQhgymwkoaJBKJMHbsWA444ICgQ5EGWL58Offee2+lvoMPPpjTTjstoIhEsisahTHXQw+lsJy0HLivynLgNyPwg2gg4VRSa2FlZg+Z2Uozezel70YzW2Zmc5KtX8pzV5vZQjP7wMxOzFTgErwDDjiAZ599VsVVDqqoqOCjjz4iFqucmS677DIikfz6e0s5TGrS4wD4w3To8Y2gI5H6qgA+cqjwyv2XRYOfMarL+z8CnFRN/13u3ivZ/gxgZj2BwcCBydeMN7MQ1I+SKT169FBxlaMefPBBFi1aVKmvVatW9OnTJ6CIMuYRlMOkBvv1gD9Mg/2VwnLOgzFYVKWwamXQJ+CD2GstrNz9H8CaOu6vPzDF3be5+8fAQiDvsrRU1qNHD6ZPn67iKseUl5dz8803V+pr164d559/PqWlpQFFlX7KYbIrZomi6g/TtSyYa8pJHGuVqr3B+VEIMoM1ZsbsIjObm5xmb5Ps2xNIPd1oabJP8pyWBXPTJ598wpdfflmpb+jQobRr1y6giLJKOUy+0uMA+MOzcICWBXPKpw5bqsxaDYlCkBmsoYXV/cC+QC9gBXBHsr+6CTivpg8zu8DMZpnZrAbGICGzY1lw//33DzoUqaPXX399p2taRaNRTjwx7w8tUg6Tney3P0yZlvgoueF1hxerXDA0CpwY4AJ+gword//c3WPuHgcm8vVU+VKgS8qmnUkcvF/dPia4e293792QGCScevTowZlnnolZSK7UJrvk7sydOxdPuSBMNBqlX79+u3hV7lMOk+rsWBYceEbisYSfA/Mc4lWuaXVygEewN+itzaxTyqcDgR1n2zwHDDazUjPbG9gPeLNxIUquue666/jpT3+q+wrmiPHjx/PFF19U6jv66KM55JBDAooo85TDZFeuug5GXaT7CuaK8RXwRZW+YyJwSEDFcV0utzAZeAPoYWZLzex84DdmNs/M5gLHA5cBuPt7wFPAfOCvwGh3j9Wwa8lTZWVl3HnnnYwaNUozVzngs88+Y/z48ZX6OnbsyIgRIwKKKL2Uw6S+mjSBW++EH4/SzFUu+IxEcZWqo8GIgJYDa63H3f3sarp/v4vtfwn8sjFBSe6LRqPcdtttFBUVcddddwUdjtTivffeY8uWLZXuAfn9738fM6u0TJiLlMOkIYqK4Je/SdywedydQUcjtZnvsNmhWUoh/L1I4qDJbGewoK+jJXmstLSUX/7yl1xyySVaFgy56dOnM3fu3Ep9Xbt25YwzdM8PKVxlZXDDz2H0JYl7DEp4TY/D3CoVVFeDHwZQ5aiwkoxq0qQJd9xxBxdeeGHeXdE7n8RiMW655ZZKfU2bNmXkyJE0a9YsoKhEgtekKfzqdrhgFCiFhVcM+FWV5cBmBj+JQrYzmP6bSMbtWBY84ogjgg5FdmHJkiUsXbq0Ut+RRx5JkyZNAopIJByKiuCW26CPUlioLXFYWmXW6sgIZDuDqbCSrCgpKeHmm29m9913DzoUqcGcOXP485//XKmvrKyMSy65JKCIRMKjtBSuvwl22y3oSKQmcxxeiEHqYaGlwMVZXsZVYSVZc8IJJ/DUU0/Rvn37oEORGvz6178mHv/6anuRSITBgwezzz77BBiVSDgcdwJMegraKYWF1m9ikHq90KjB4Ajsk8WzO1VYSVb17duXp59+WjNXIbVhwwbefvvtSn3du3fX90uExKUXjukLTzwF+pEIpw0Ob1dZDtwvAh2yGIMKK8m64447jsmTJ9OhQzb/q0tdrFq1aqdb3ABce+21AUQjEj5mcOzx8MiTsLtSWOisYudb3ABcncXlQBVWEojvfOc7TJkyRcuCITRt2jTWrVtXqa9bt26UlZUFFJFI+Bx3Ajw2BZTCwmd6DNZWmbXqZpCtDKbCSgJz3HHHMXXqVC0zhczbb7/N888/X6nvwAMP5LzzzgsoIpFwOqYvPDkVdlMKC5W3Hf5cZdbqQIPzsnQldhVWEqhjjz2W3/3ud0GHISlisRh//OMfK/WZGWPGjKFFixYBRSUSPmZw1DFwzwNBRyKpYsCzVW5EFTG4KgrZyGAqrCRwxx57LKeddpruKxgib7zxBu+++26lvg4dOtCmTZuAIhIJJzM4+ljo9wPdVzBM3ojDvCqzVh0MspHBVFhJ4Nq2bcukSZPo169f0KFI0rJly5g0aVKlvubNm3PNNdcEFJFIeLVtBw9NghOVwkJjGTCpyjWtmpOdg9hVWEkotGzZkieeeIIBAwYEHYokPffcczvdgPmcc87hoIMOCigikfBq2Qoefhx+oBQWGs/HK9+A2QzOjSaOt8okFVYSGq1ateLBBx+kf//+QYciJG5xU/VYqxYtWrDHHnsEFJFIuLVqDeMnwqlKYaHwqcMfqywHNgf2VGElhaRdu3Y89thjnHrqqUGHUvA2b97MhAkT2LJlS6X+G2+8MZiARHJAu/bw4GNwslJY4DYDE2KwOWXaygxuyPByoAorCR0tC4bHq6++ulNh1b59e7p27RpQRCLh17IlPPyElgXD4NU4bKnS1x7IZAZTYSWh1LJlSy6//HKaN28edCgFbevWrYwfP75S33777cegQYN0FqfILrRsCRdfBkphwdoG3F/l0gv7R2BQFDKVwVRYSWgdc8wx3HvvvZSWlgYdSsGKx+O8//77lW7MDHDllVfStGnTgKISyQ3fPgbuvBdKlMICEwfej0OsypXYryiCTGUwFVYSakOGDGHChAn6JR6gadOm8dZbb1XqKy0t5dBDDw0oIpHcYAZnnwf3TYAmSmGBmRaHt6oUVqXAoRmassribQklbD7++GPefvvtoMOo1UEHHcSIESO47777gg6lIG3bto1bbrmFadOmfdXXvHlzRo8ezaxZs9i6dWuA0Ukh+2QxzHmr1s0C1/NAGDoCfqcUFohtwK8qYGrx1xdxbWFwYRHMKod0ZzCrep2aIJhZ8EGISI0OOuggZs+eTUlJyU797733XkN3O9vdezc6uBBQDhMJt4MNZpZAacoslTscvB3ea+BPr7tXO+dV61KgmXUxs7+Z2QIze8/MLkn2tzWzl8zsw+THNimvudrMFprZB2Z2YsNCFpGwmD9/Pk888cRO/cccc0wA0dSd8peIQKJ4eqLKldgBjs7EAVHuvssGdAIOSz5uAfwX6An8BhiT7B8D/Dr5uCfwDuw6uu8AAB9KSURBVIklzL2BRUC0lvdwNTW1cLcDDjjAN27c6Knefvttb9euXUP3Oau2/NPYRhbyl3KYmlputAMM31CKe9nX7a0SvF0D91dTPqi1VnP3Fe7+VvLxRmABsCfQH3g0udmjwI4rdvQHprj7Nnf/GFgI9KntfUQk3JYtW8a6desq9fXq1YsTTjghoIhqp/wlIjssc9hQpe/QCJyQ5lmreu3OzLoBhwL/ATq4+wpIJC9g9+RmewJLUl62NNknIjls48aN3HLLLTv1H3fccUSj0QAiqh/lL5HCthG4pYKdlgP7RiCdGazOhZWZNQemApe6e9Wir9Km1fT5ThuZXWBms8xsVl1jEJFgTZ48mfnz51fqGzhwIEVF4T7BON35K7lP5TCRHPNkDOZX+YkeGE3vJRLqVFiZWTGJpPSEu+845/pzM+uUfL4TsDLZvxTokvLyzsDyqvt09wnu3jtfzgoSKQTr1q3js88+q9TXunVrBg0aFFBEtctE/gLlMJFctA74rEph1Ro4K43LgXU5K9CA3wML3P3OlKeeA4YlHw8D/pjSP9jMSs1sb2A/4M30hSwiQRo7dmylz8vKyvjRj35EmzZtanhFcJS/RKSqGyoqf97E4EdFkLYMVoezXY4mMRU+F5iTbP2AdsArwIfJj21TXnMtibNpPgBO1hk1amr503r06OFLliypdHZgLBbz7t2713df2TgrMOP5SzlMTS23Wg/DP61ydmBFKd7d6refGvNBphObkpKaWv61O+64w+PxeKXi6uqrr67vfjJeWCmHqampVdfuKMJjKcVVvBS/Olq/fdSUD3TldRGpt/bt27No0SJatmwJQHl5OT179mThwoX12Y2uvC4igWgPLCyFVsnTVbY7HLQdPqzHT7LXcOX1cJ/KIyKhtGbNGi644AJGjRpFWVkZjzzyCB9//HHQYYmI1MkaYGQ5/KQIyoBHYvBRmv480oyViDRY69atKSkpYeXKlbVvvDPNWIlIoFoDJXx9WnB9aMZKRNKu6pXYRURySSYyWCZuPygiIiJSkFRYiYiIiKSJCisRERGRNFFhJSIiIpImKqxERERE0kSFlYiIiEiaqLASERERSRMVViIiIiJposJKREREJE1UWImIiIikiQorERERkTRRYSUiIiKSJiqsRERERNJEhZWIiIhImqiwEhEREUkTFVYiIiIiaaLCSkRERCRNai2szKyLmf3NzBaY2Xtmdkmy/0YzW2Zmc5KtX8prrjazhWb2gZmdmMkBiOSL1q1bc8ghh3zVmjZtGnRIOU/5SyR7WtOKb3LwV60pTYIOKRjuvssGdAIOSz5uAfwX6AncCPysmu17Au8ApcDewCIgWst7uJpaobZIJOJt27b1adOmeapx48Z5ixYtAo8vg21WbfmnsY0s5C/lMLVCbxEi3pY2Po0pHmfzV+1ubvcWNA88vky1mvJBrTNW7r7C3d9KPt4ILAD23MVL+gNT3H2bu38MLAT61PY+IoWoa9euXHXVVSxatIgBAwZUeu7CCy/kgw8+YPTo0bRt2zagCHOb8pdIZnVlL67kchbyLv05FUv5dyEX8D7vMJqRtKVN0KFmTz3/+usGfAq0JPEX32JgLvAQ0Ca5zb3AeSmv+T1wRjX7ugCYlWyBV57Zaocffrj/+9//9lmzZvmLL77oXbp0CTwmtey3kpISP+KII3zmzJleF3/605/8sMMO80gkEnjsaWwZn7HKVP4q5BxmHO4lvOElzPRiZjgohxViK6HEj6CPz+Sf7mzZZYuz2Z/jGT+MXh7BAo89Xa3GXFOPpNQcmA2cnvy8AxAlcZzWL4GHkv33sXNi+mEt+w78C5SNdvjhh/vHH39c6Rfm7NmzVVwVWDviiCP86aef9ng8Xqeiaocvv/zSJ02a5N27dw98DGlqWSusyGD+KqQcliiqPvYy/KtWwiyHzoHHppa9dgR9/Gme8Bibai2qUtsW1vhjPOjd2TfwMaSjNaqwAoqBGcDlNTzfDXg3+fhq4OqU52YARxZ6UurVq5cvXry42l+YM2fO9L322ivwGNUy25o1a+YXXXSRL1mypO7VVDXmzZvnI0aM8Gg0GviYGtmyUliR4fxVKDnM6OWlVYqqMtxLiXsJbzooh+V7a0YzH81IX8rCehVUVWev5vKmj2CoR8ntHFZjPqhDwjDgMeC3Vfo7pTy+jMRxCQAHUvngz48o8IPXe/fu7Z988skuf1m++eabKq7yuJ199tn+wQcf1HuWqibl5eU+b948P/744wMfWyNaNg5ez3j+8gLIYUZvL2XxTkVV5Zmr/7iKq/xt53CWv8+ces9S1dS2s97nMcuP59jAx9bQVmM+qEPCODq5k7nAnGTrB0wC5iX7n6NyorqWxNk0HwAnF3JSOvzww2ucqapq1qxZWhbMo1ZcXOzdu3f3SZMm+fr16+v0f6C+li9f7uPHj/c99tgjF4+/ykZhlfH85Xmew4zDq52pqr64muU65ip/WjHF3p19/DF+7+v4LC0FVdW2jEV+H7/1PejkEXIrh9WYDzKd2Ao5KfXq1avWmaqqZs+erZmrPGiRSMTHjh3r27Ztq9f3v6G2bNniw4cPz7XiKqsHr2eyheBrmZFmHFrrTNXOy4KzXDNXud8iRPx6rvatrPU4mzNSVKUuD25mlQ/jvJwqrmrMB0EnpHxNSnVZ/qvJzJkzvWvXroGPQa3+rWXLlj5w4ECfN29e1oqqHTZu3Oivv/66f//73/eSkpLAvxZ1aCqsQtwSM1V1L6oqz1zpmKtcbS1o4QP4gc9lpm9lbUYLqqptIyv9NV7x73OClxD+HFZjPgg6IeVjUurdu3edl/9qMmvWLM1c5VAzM+/cubM/8sgjjfq+p0MsFvOf//zn3qlTp8C/LrU0FVYhbYljquq2/FdzcTXTtSyYO80w78ye/jATMj5DVVurYKP/ghu8Ex0D/7rsqtWYD4JOSPmWlBqy/FeTt956S8VVDrSOHTv6Lbfc4hs2bEjL9z0d4vG4L1++3K+77jpv1qxZ4F+jGpoKqxA245AGz1TtvCw42zVzFf7WkQ5+Czf5ej4PvKja0WJs8mUs8mu5ypvRNPCvUXWtxnwQdELKp6QUjUb9tttuq+vvvjp56aWXAh+XWvUtEon4ySef7P/85z/T+j1Pp3g87s8884z37ds38K9XNU2FVeha1Iv4TaOLqtRWzIshGJdadS1CxE/i+/4PXgpNQVVdgfU0T3hfjgn861W11ZgPgk5I+ZKUSkpK/Prrr/ft27fX9XdenWzYsMGHDh2aawcl533r1auXv/TSS1k/jqqh1q9f788++2zYzjpVYRWqVuJRrvNStqW1sCplvUcY4uTQQcmF0HrxTX+J57N+HFVD2zo+82d5yruE6GK0NeaDoBNSPiSlHWeApesaRVV9+eWXfu6557pZ/twKIBebmXnTpk392muv9Y8++igj3+tMe+utt/yiiy7y0tLSwL+eqLAKUYt4lOu9lFhai6qvi6stHuFcJ49uZ5KLzcCb0tSv5SpfxHuhnaWqqcXZ7LP5l1/ET7yU4HNYjfkg6ISU60kpEon4zTffnPaZqqp2nE4f9HgLufXv399XrFjhsVgso9/rTNu+fbsvXLjQ+/TpE/TXVIVVKFrEi7gp7TNVOxdXmz3KsBCMt3DbaZziy/nIK9gYeJHUmLaNdb6Qd70PvQP9etaUDyJIg5WUlHDdddcxZswYiouLM/peTZo0Ydy4cQwbNgwzy+h7SfWGDx9Ox44diURy+8emuLiYfffdlzPPPDPoUCRwJUS5jihjMEoy+k5GU4oYR4RhJC6IL9k2gqF0oiNRokGH0igllLAv+3AmpwcdSrWKgg4gV0WjUa666ipuvPHGrBU6LVq04P777ycWi/Hkk08Sj8ez8r4iko+iRLmKIm7AsvQ3ttGSYsZTTow4TwLKYZJ/cvtP74CYGTfccANjx47N+uxRkyZNmDhxIkOGDMnq+4pIPjGKGEsR12etqPr6nZtSzAQiKIdJflJhVU8lJSXccMMNXHXVVRQVBTPhV1ZWxj333MOIESO0LJhFt99+O7FYLOgw0mLNmjU88MADQYchgSihiLFEuQojs4cw1MRoQjHjiDICLQtmz+38lgoqgg4jLVazhgd4MOgwqqXCqh6Ki4sZM2YMY8eOpaQks8cj1KZFixbce++9DBkyJOeP+ckVixcvZsuWLUGHkRbr169n2bJlQYchWVdMlDFEGYtRGmgkRkuKuIcI56FfRdmxmE/YQp7kMDawjHDmMP1vriMz47rrrgtk+a8mTZs2ZcKECVoWzJLly5dz9913Bx1GWtx8881s3bo16DAkq4wirg1k+a8mRjMtC2bRclYwjvtxPOhQGsVxbuYWtrIt6FCqFY6frpArLi7mxhtvZMyYMUSj4TqborS0lHvvvZcRI0YEHUrec3fGjx/PihUrgg6lUd566y2mT58edBiSVcUUcWPy7L9wnbNklFHMPUT5UdCh5D3HGc/vWMFnQYfSKG8xh2d5LugwaqTCqhbFxcVcc801XHfddYEv/9WkefPmjBs3jqFDh2pZMMNWrlzJqlWrgg6jUZYvX8769euDDkOyppgoVxPl2sCX/2pitKCIu5MzV8phmbSSL1jN6qDDaDDHWcFnrGdD0KHUSP+Da7Fj+S/sBUvz5s2ZMGEC5513XtCh5LVYLMYNN9wQdBiNcv311wcdgmRRYvlvLBbyaxcZzZPLgsphmRQjxg38IqeXA8fy86BD2KVwVwsB22uvvXJqFqi0tJT77ruP888/P+hQ8tqLL77IP/7xj6DDaJBPP/2UdevWBR2GZM1eRBga+qJqh8Sy4H1EUQ7LpBd5mX/yetBhNMinLGEta4MOY5dyo2IIQJcuXZg6dSrdunULOpR6ad68Oddccw2tWrUKOpS8tXnzZpYuXRp0GPUWj8d57LHHWLx4cdChSFZ0oYRniLB30IHUi9GcKFcDLYMOJW9tZgtLWZZzs1YxYkziSRbzSdCh7JIl73MVbBCJmwuHxl577cX06dM57LDDgg6lwZ5//nnOOeccNm7cGHQoeWn//fdnwYIFOTObCbB27Vq6devGhg2hOTZhtrv3DjqIdAhbDoO9KGEaxmFYDl4nynHivEA55wDKYZmwP92Zz9s5dXubNaxlb77BhpAcX+Xu1f5w5c5vhSzp2rUrU6dOzemiCuCUU05h0qRJtG3bNuhQ8tKGDRv48MMPgw6jXt599122b98edBiScV2TM1WH52RRBWAYEfpRzCRAOSwTNrCRD1kUdBj18i7vsZ3w57BaCyszKzOzN83sHTN7z8xuSva3NbOXzOzD5Mc2Ka+52swWmtkHZnZiJgeQTnvttRdTp06ld+/c/yPazOjfvz8PPfQQrVu3DjqcvPPZZ5/x4IMP5syV2Ldu3crdd99dcNeuKqT8lbBXsqj6VtCBNJoRIUp/ivk9oByWbp/xOQ/ycM5cif1LtnI397GV8OewWpcCLXE1zGbuvsnMioHXgEuA04E17n6rmY0B2rj7VWbWE5gM9AH2AF4G9nf3Gn8DhWEavVOnTrzwwgsceuihQYeSds8//zxnnXUWX375ZdCh5JXS0lIWL15Mx44dgw6lVjNnzqRPnz5Bh1FVxpcCs5G/ku8TeA6DTpTwPMahOTtTVZ2vlwXPApTD0qmUUj5mAZ0Ifw57k1n8P44NOoxKGrwU6Ambkp8WJ5sD/YFHk/2PAgOSj/sDU9x9m7t/DCwkkaRCbffdd8/LogrguOOOo7Q0nNevyWWxWIy33nor6DDqZNasWUGHEIhCyV8Axm55V1TBjmXBvhDSa3Dlshgx3uLtoMOolePMIjdyLdTxGCszi5rZHGAl8JK7/wfo4O4rAJIfd09uviewJOXlS5N9InmloqKCcePGsWnTpto3DtDatWu57777gg4jMMpfItWroIJ7uJ9NbA46lF1ayzru43dBh1FndSqs3D3m7r2AzkAfMztoF5tX9+fSTtPkZnaBmc0ys1D8Kb106VJeeeWVoMNIu3g8ztNPP61lwAyZMWMGs2fPDjqMXZo2bRrvvfde0GEEJhP5C8KXw5xlxHkl506hr40TI8YzaBkwM2bwMrMIeQ7jj8xnQdBh1Fm9zgp093XA34GTgM/NrBNA8uPK5GZLgS4pL+sMLK9mXxPcvXdYTrdevXo1Z555Ji+//HLQoaTVQw89xKhRo9i2LZw3q8wHb7zxRtAh1KiiooKZM2cGHUYopDN/JfcXqhwGqynnLOLk1x+IMR6mglEQ0hvu5oM3+E9oC/JyypkZ8sKvqrqcFbibmbVOPm4CfBd4H3gOGJbcbBjwx+Tj54DBZlZqZnsD+wFvpjvwTFi7di1nn302M2bMCDqURnN3Jk6cyGWXXaaiKsMmTpzIZ5+F86amW7du5Q9/+EPQYQSmkPJXwlrKOZsYfw06kEZz4lQwgQouQ0VVZk3kYT7n86DDqNZWtvIUU4MOo17qMmPVCfibmc0FZpI4RuF54Fbge2b2IfC95Oe4+3vAU8B84K/A6NrOqAmTVatWMWTIkJyfuZo8eTIXX3xx6I//yQcfffRRaIuXZ555hi1btgQdRpAKKn8lrKKcocR4KbSzEHURZwoVXAIoh2XaxyxmCs8EHUa1nuFZtpBbOUxXXq9Bp06d+O9//0vz5s2DDqXe1q1bxxlnnJGXx4yF1aBBg3jkkUcoKysLOpSvrF69mgEDBvDaa68FHUpNdOX1jOpEKf/FyL0c5qylnDPzblkzzAZxBg8zgSaEJ4etYjWnMzi09zXUldfraeXKlVx55ZU599f+6tWrGTp0qIqqLPvTn/7E5s3hOrNm2bJlYS6qJONWUsFVeMjP+KrKWUU5w1RUZdmf+DObQ/Z/ZRnLQ1tU7YoKqxrEYjHuv/9+rrrqqpw5Rmn9+vUMHz6cP/3pT0GHUnC2bdvG448/HnQYlTz88MNBhyCBihFjPBWMwXPgatUAzjrKGU4c5bBs28Y2Hmdy0GFU8giTgg6hQVRY1WL8+PFceumlVFSE+7L/69atY/DgwTz//PNBh1KQYrEYkyZNYsWKFUGHAsCCBQt49tlngw5DQiDGfVRwGU550KHskicPvI/zQtChFKQYMR5nMssJRw6bz/s8m6MFtgqrWsTjcSZOnMjFF18c2mXBHQfc//WvuX8mUC6bPXt2KL4H8XicKVOmsHjx4qBDkVBwYkykgotDuyzofEE5Q4nnwdmMuWw2bzMjBCc9xIgxhadZzCeBxtFQOni9HkaPHs1tt91GkyZNgg7lK+vWrWPIkCGaqQqJAw88kL/85S+BxrB161aOPPJIVq9eHWgcdaCD17MsymiK+A1G06BD+Upi+W8IcZTDwuBAevJnpgcaw1a28m2OZzVrAo2jNjUdvK7Cqh7MjJEjR3LPPfdQVFQUdDisX7+ewYMHh2KWRL4Whv8bYV+6TlJhlXVGlJEUMQ6jOOhgkkXV2ZqpCpkiQpDDCH8Oq6mwCv6rl0N2XHTT3bnrrrsCnblatWoVw4cPV1EVQjlS1EhBSiwLglPEnYHOXCWW/4arqAqhXChqwkzHWNVTLBZjwoQJXHHFFYEdc7V27VpGjBjBCy/oIE8Rqa8YMSZQwZWBHXOVOFB9BHH+HMj7i2SSZqwawN257777iMViWV8WXL9+Peecc45mqkSkEZwY9wEVFHFPVpcFv17+y/1bh4lURzNWjTBx4kRGjx7N1q3ZuUbMqlWrOPvss1VUiUhaxHiQCi7C+TIr75dY/jtHRZXkNRVWjRCLxZg4cSI/+9nPMr4suGbNGoYPHx74GWcikk9iyUsxXJHxZUFndXL5TzlM8puWAhspdVlw3LhxFBenf0r9yy+/5JxzzmHGDP2VJyLptmNZMEYRd2OUZOAdtlDOuZqpkoKgGas02bEsmInb37z22mu8+uqrad+viMgOiZmrizJy+5s4rxFHOUwKgwqrNNlxS5MFCxakdb8zZszg3HPPzdpxXCJSqGLEmIST3hwWYwblnAs5cr9CkcZSYZVGW7du5cwzz+Tdd99Ny/5efvllhgwZwhdffJGW/YmI7NpWyjmLOPMafVsTx4nxEuUMAValJzyRHKDCKs0WLlzIwIEDmT9/fqP288orrzBo0CAVVSKSVc5CyjkdZ36DiyvHifMK5QwGlMOksKiwyoCFCxfSv3//Bs9czZgxg0GDBrFmTbjvkyQi+SlRXA3AaVgOizMjWVQph0nhUWGVITtmrubNm1ev17300ksMHTo0F26gKyJ5bMfMVZy657DE8t+LlDMUUA6TwqTCKoMWLlzI6aefXueZqx3LfytXrsxwZCIitUsUVwOJ826ty4KJ5b//0/KfFDwVVhm2Y+aqtuLqr3/9K4MGDWLt2rVZikxEpHbOIsoZWOuyYGL5bxCgHCaFTYVVFixcuJABAwYwd+7cap+fMWMGw4YN0/KfiITS1zNX71TznBPjr1r+E9nB3XfZgDLgTeAd4D3gpmT/jcAyYE6y9Ut5zdXAQuAD4MQ6vIcXQtt333193rx5nurll1/2Nm3aBB6bmloAbVZtuaGxjSzkr0LKYca+XsJcLyXuZbiXEvdiXnJQDlMrvFZTPrBkUqiRmRnQzN03mVkx8BpwCXASsMndb6+yfU9gMtAH2AN4Gdjf3WO7eI9dB5FH9t13X2677TaKiopYs2YNl19+uc7+k0I12917Z/INspG/kq8rmBxm7EsRt5G4I9oayrkcnf0nhcjdrbr+Wu8V6InKa1Py0+Jk21US6Q9McfdtwMdmtpBEknqjXhHnqUWLFnH66acHHYZIQVD+Sr/EMVfKYSI1qdMxVmYWNbM5wErgJXf/T/Kpi8xsrpk9ZGZtkn17AktSXr402SciknXKXyKSTXUqrNw95u69gM5AHzM7CLgf2BfoBawA7khuXt3U2E5/IZrZBWY2y8xmNShyEZE6yET+AuUwEalevc4KdPd1wN+Bk9z982TCigMTSUyXQ+IvvC4pL+sMLK9mXxPcvXemj7EQEYH05q/k/pTDRGQntRZWZrabmbVOPm4CfBd438w6pWw2EL66yMlzwGAzKzWzvYH9SJyVIyKSVcpfIpJttR68DnQCHjWzKIlC7Cl3f97MJplZLxLT5IuBkQDu/p6ZPQXMByqA0bWdUSMikiHKXyKSVbVebiErQRTQqcoi8pWMX24hW5TDRApPTZdb0JXXRURERNJEhZWIiIhImqiwEhEREUkTFVYiIiIiaaLCSkRERCRNVFiJiIiIpIkKKxEREZE0UWElIiIikiYqrERERETSRIWViIiISJqosBIRERFJExVWIiIiImmiwkpEREQkTVRYiYiIiKSJCisRERGRNFFhJSIiIpImKqxERERE0qQo6ACSVgGbkx8LQXs01nxUSGOFxo+3a7oCCYFNwAdBB5El+n+evzTWuqsxf5m7N2K/6WNms9y9d9BxZIPGmp8KaaxQeOPdlUL6WhTSWKGwxquxpoeWAkVERETSRIWViIiISJqEqbCaEHQAWaSx5qdCGisU3nh3pZC+FoU0Viis8WqsaRCaY6xEREREcl2YZqxEREREclrghZWZnWRmH5jZQjMbE3Q8jWVmD5nZSjN7N6WvrZm9ZGYfJj+2SXnu6uTYPzCzE4OJumHMrIuZ/c3MFpjZe2Z2SbI/X8dbZmZvmtk7yfHelOzPy/ECmFnUzN42s+eTn+ftWBsi3/IXKIcl+/NuvMpfWRyruwfWgCiwCNgHKAHeAXoGGVMaxnQscBjwbkrfb4AxycdjgF8nH/dMjrkU2Dv5tYgGPYZ6jLUTcFjycQvgv8kx5et4DWiefFwM/Ac4Il/HmxzD5cCTwPPJz/N2rA342uRd/kqOSzksD8er/JW9/8dBz1j1ARa6+0fuvh2YAvQPOKZGcfd/AGuqdPcHHk0+fhQYkNI/xd23ufvHwEISX5Oc4O4r3P2t5OONwAJgT/J3vO7um5KfFiebk6fjNbPOwCnAgyndeTnWBsq7/AXKYeRpDlP+ArI01qALqz2BJSmfL0325ZsO7r4CEj/IwO7J/rwZv5l1Aw4l8VdQ3o43ObU8B1gJvOTu+Tze3wJXAvGUvnwda0MU0pjz/vteCDlM+Ss7Yw26sLJq+grpNMW8GL+ZNQemApe6+4ZdbVpNX06N191j7t4L6Az0MbODdrF5zo7XzE4FVrr77Lq+pJq+nBhrIxTimKvKi69BoeQw5a+aX1JNX4PHGnRhtRTokvJ5Z2B5QLFk0udm1gkg+XFlsj/nx29mxSQS0hPuPi3Znbfj3cHd1wF/B04iP8d7FHCamS0mscT1HTN7nPwca0MV0pjz9vteiDlM+SuzYw26sJoJ7Gdme5tZCTAYeC7gmDLhOWBY8vEw4I8p/YPNrNTM9gb2A94MIL4GMTMDfg8scPc7U57K1/HuZmatk4+bAN8F3icPx+vuV7t7Z3fvRuLn8v/c/TzycKyNUCj5C/L0+15IOUz5K4v5KwRH7fcjcSbGIuDaoONJw3gmAyuAchJV8PlAO+AV4MPkx7Yp21+bHPsHwMlBx1/PsR5NYrp0LjAn2frl8Xi/CbydHO+7wNhkf16ON2UMx/H1WTV5PdYGfG3yKn8lx6QclofjVf7K3lh15XURERGRNAl6KVBEREQkb6iwEhEREUkTFVYiIiIiaaLCSkRERCRNVFiJiIiIpIkKKxEREZE0UWElIiIikiYqrERERETS5P8D+HXxL4y3gA8AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 720x576 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import cv2\n",
    "\n",
    "img = cv2.imread(\"images/shapes.png\", 0)\n",
    "_, img = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY)\n",
    "num_labels, labels = cv2.connectedComponents(img)\n",
    "\n",
    "# Map component labels to hue val, 0-179 is the hue range in OpenCV\n",
    "label_hue = np.uint8(179*labels/np.max(labels))\n",
    "blank = np.ones_like(img) * 255\n",
    "labeled_img = cv2.merge([label_hue, blank, blank])\n",
    "\n",
    "# Converting cvt to BGR\n",
    "labeled_img = cv2.cvtColor(labeled_img, cv2.COLOR_HSV2BGR)\n",
    "\n",
    "# set bg label to black\n",
    "labeled_img[label_hue==0] = 0\n",
    "\n",
    "\n",
    "plt.figure(figsize=[10,8])\n",
    "plt.subplot(121);plt.imshow(img, cmap='gray');plt.title(\"Original\");\n",
    "plt.subplot(122);plt.imshow(labeled_img, cmap='gray');plt.title(\"labeled image\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x576 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import cv2\n",
    "\n",
    "img = cv2.imread(\"images/small-connected-test.png\", 0)\n",
    "_, img = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY)\n",
    "_, labels_with_4_connectivity = cv2.connectedComponents(img, connectivity=4)\n",
    "_, labels_with_8_connectivity = cv2.connectedComponents(img, connectivity=8)\n",
    "\n",
    "label_hue4 = np.uint8(179*labels_with_4_connectivity/np.max(labels_with_4_connectivity))\n",
    "label_hue8 = np.uint8(179*labels_with_8_connectivity/np.max(labels_with_8_connectivity))\n",
    "\n",
    "blank = np.ones_like(img) * 255\n",
    "labeled_img4 = cv2.merge([label_hue4, blank, blank])\n",
    "labeled_img8 = cv2.merge([label_hue8, blank, blank])\n",
    "\n",
    "# Converting cvt to BGR\n",
    "labeled_img4 = cv2.cvtColor(labeled_img4, cv2.COLOR_HSV2BGR)\n",
    "labeled_img8 = cv2.cvtColor(labeled_img8, cv2.COLOR_HSV2BGR)\n",
    "\n",
    "# set bg label to black\n",
    "labeled_img4[label_hue4==0] = 0\n",
    "labeled_img8[label_hue8==0] = 0\n",
    "\n",
    "plt.figure(figsize=[10,8])\n",
    "plt.subplot(131);plt.imshow(img, cmap='gray');plt.title(\"Original\");\n",
    "plt.subplot(132);plt.imshow(labeled_img4, cmap='gray');plt.title(\"labeled image with 4 connectivity\");\n",
    "plt.subplot(133);plt.imshow(labeled_img8, cmap='gray');plt.title(\"labeled image with 8 connectivity\");"
   ]
  }
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