opening image files.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "68460c23",
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "5f2572b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f66c2df1",
   "metadata": {},
   "outputs": [],
   "source": [
    "img = cv2.imread('DATA/00-puppy.jpg')\n",
    "while True:\n",
    "    cv2.imshow('puppy',img)\n",
    "    if cv2.waitKey(1) & 0xFF == 27:\n",
    "        break\n",
    "cv2.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "51a05919",
   "metadata": {},
   "outputs": [],
   "source": [
    "# drawing on images\n",
    "blan_img = np.zeros(shape=(512,512,3), dtype=np.int16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "6a022e69",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f6132f20f40>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(blan_img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "de40ab05",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f610effe2b0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# drawing a rectangele\n",
    "\n",
    "a = cv2.rectangle(blan_img,(34,0), (510,150),(0,255,0),thickness=10)\n",
    "plt.imshow(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "bfdcec45",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f6132f1e1f0>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cv2.circle(blan_img,(300,10),50,(0,255,0),10)\n",
    "plt.imshow(blan_img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "1e977d49",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f6132fbfd90>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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cRvx1Xj8FtkQ+FK8x76Nk+GnD48CcOHPKsPunKOXRiEgOUOJKloUO2wywl5NtnKKEGvOuJrJgI9SYdwkZXrCxE7swNbrapLtr8UDJpIh4gRJXMvwYONNhu8EWKfy59ylOjXmnYgs2Mvb3fgMwC3tzTCe9JG4RkUQocQ3UedhGuKc4zFlDn7q8H8XeKXl11OOhdV4PksGLlI9gOwr3dtTlA/4Ge71LRGQAlLgG6lPAJQ7b27EXqj7u28sdBW4gdsHGDOyyqL70Qk2LJUCrw/bh2Hp/EZEBUOIaiEHA+DhznsBW3iWgCVuw8UyMbVOBFdhbHWWcD4jf5ukTRHYlFxFJkBLXQBThXJQB9rCpLx3fo3QAV9NznVfotOGvyNAjr3jd5mcAn3UjEBHJVkpcqXQQ+J/9f/qH2LuQRFcbgk1eK7B3Y8koT6AbSYpISilxDUQdznvwBAO+uV4z8GVsfUd3oSOvh4Hygb1FcrVgCzWcTMG5mEVExIES10DMx/kX8J04r23qozZOFmzEasz7EBm2zutfcU5e/4Aa74pIvylxpVJ98l6qEfgKsdd51WFvlZUxHTa2YbOtiEgKKHF5SCv2DuvR67zysB02HgCK3Q5KRMRlSlz9VYTz+bkjxK+w64cAtnvSGmI35n2UDGnM63SXZB9Q4lYgIpJtlLj661bgIoftPwLeTM1bfwhcSe+NeR8jzacNO7EtoHpTgL0liohIPyScuF544QWmTZvGyJEj8fl8rFy5MmK7MYY777yTESNGMGTIEGpra3nnnXci5hw+fJjZs2dTUlJCWVkZ1157LUeOxCtFyzC+rpEmTo15Q/fzSmvBhlNRSpr3nYh4W8KJ6+jRo4wbN4777rsv5vZ/+Zd/4d577+WXv/wlW7Zs4dRTT2Xy5MkcP348PGf27Nns3r2bDRs2sHbtWl544QVuuOGG/n8VOaoJmI09bei5xrwiIv1lBgAwTz/9dPjzzs5OU1VVZX7yk5+EH2tubjaFhYXmscceM8YY88YbbxjAvPrqq+E5zz77rPH5fOb999/v0/sGAgGD/V2dvFGKoR3T68f7UfP/t8Ncg+F/JTk+h1EEZhUYE2OsBDPUpTgixkVx9s+GNMSkodF9VGPoxPn7VB+p+whgABMIBBLOPUm9xrV3714aGhqora0NP1ZaWsqECROor7e14fX19ZSVlXHhhReG59TW1pKXl8eWLVt6vCZAa2srwWAwYshJH3PytGFvjXm1bEpEskVSE1dDQwMAlZWRLWArKyvD2xoaGqioiCwdGDRoEKeffnp4TrRFixZRWloaHtXV1ckMOys4NeatI4Mb84qIJMgTVYULFy4kEAiEx/79+9MdUkZyasw7HduYd7DbQYmIJFlSE1dVVRUAjY2NEY83NjaGt1VVVdHU1BSxvaOjg8OHD4fnRCssLKSkpCRiSGyhxryxCjamYXvglrock4hIMiU1cZ1zzjlUVVWxcePG8GPBYJAtW7bg9/sB8Pv9NDc3s23btvCcTZs20dnZyYQJE5IZTs5qBr5E7Ma8U7HXvDKqMa+ISCISreZoaWkx27dvN9u3bzeAueeee8z27dvNX//6V2OMMXfffbcpKyszq1atMq+//rqZMWOGOeecc8yxY8fCr/HFL37RfOYznzFbtmwxL774ojnvvPPMVVdd1ecYMqKqcCHOFUm7MNQkOcYERyW22rCTntWGq8EMStV7+zCsddg3nRjWp3ffaGioqjDNHwOoKkw4cT333HMxvwnmzJljjLEl8d/73vdMZWWlKSwsNBMnTjR79uyJeI0PP/zQXHXVVaa4uNiUlJSYq6++2rS0tPQ5hoxIXIUYXo7zP2ZMkmPsxxhM7OR1ouvx4al43zwMHzrsl2MYhqV/32jk+FDiSu/HABKXzxhj8JhgMEhpaWlyX7QUOETv7SY+AM6Ieuwl4FKH17wA2DXw0AaqBHt6cEaMbauBr2Nvo5U0edj7kJ3ey/bjXduOJfNNRRJUDfwVdXFJlyBQCoFAIOG6BU9UFXpWhtSQBIHrcG7MW5TMNzwNfWeJSMro18tAbKZnJuhuBRnz19whem/MW0eSG/Pej3Pp4oukpHO+iOQGJa6BuBvnX8AZtnc7sEdeq7An+UNC67weAPKT8Ubxmuj+K7rRpIj0W4b9as0yw4GfpjuISAex17Ri3Ul5GvZOyr1dmuqTq7peSEQkRZS4BqKVnrcj7u4UoMydUBJxBPgqsdd5TQOWAkP7++JFwBCH7duAvf19cRERJa6BacWW6zmpBSa6EEuCnBrzTgceph+NecuBBXHmvAC8negLi4icpMQ1UE3APoftI4D/QZIuHiVXE7bDRnTBBtgOGwk35v1vwCiH7UeBtxJ5QRGRnpS4BuplYrdk7+52MrZBYDvxG/M6nfmLsAjnooz/1/WCIiIDoMSVDN8H3nfY7gN+S8Ymr8PY5OXUmNdxSVoh8H+BTzjMMdjuvyIiA6TElQxN9Dxk6c4HTMIeeWWoj+i9MW8d8BscGvN+HliI80WxPwJ7BhajiAgocSXPPTiv6fJh7/T4KXfC6Y824AZswUasdV4PEqMjVgFwB86nCDux1R4fJStSEcllSlzJshf4Tpw5o4DPkTHdNGJpBGYRe53XVOw6r+HdH/wUtijDyVrsqVIRkSRQ4kqWTvrWNPbnwOwUxzJAx7GLlKNPG+Zhj7yWYNsR4geewl7jctKOOmWISNIocSXT48B6eh6qdFcI/Ax72jCDBYFrib3OaxrwSDUMWYpzQQbYrvrxjkRFRBKgxJVMTcAV2PVKTsqALwJTUh3QwBzC5tdYjXmn7oflt0NFY5wXmYkWHItIUilxJVsbtj9hvLucXQcsJ+NPG3Zw8sirR8HGGnjgesiPdRrQYCst3019jCKSW5S4kq0T+CHwA+zFIiclwGXA+WR0wcYhuhrzVsdY57UGnroSTv+w24MGe4HsG11PFhFJIiWuVGjDJq53+jD3a8BubGbIYC1+mLUB1kR1fvcBU5+Bh66BoYe7HuzELjZO6m2VRUQsJa5U+l/YRrzxnII9vfh1YHBKI0pcATAO+C0cOx+ufwBWT+t55DVjNTw8B/I/Bn6EkpaIpIwSVyqtBy4HDvRh7lDgIex6sAtSGFNfFWKbAz8LbCFcPdhUCV96EtZO7fmUqWvhyWFQ+SPsxTERkRRQ4kq19djqhiN9mJsPVGHL6v8NKE5hXPHcCfwn8Pf0WKfVXgDfWgarpkc+7gOmH4cHOhNozCsikiAlLjc8C3wZCPRx/qeAW4HXsAlkZIriilaOPUJ8E/ifOBaMHB4GVy+FNVNjd9h4nK5FyiIiSeYzxsQr3M44wWCQ0tIkt1ovxVbA9WjG1+UD4IwBvsdl2IZ/VQk8x2Cvk92M7YX4BMm/fvRV4FTsTSBHkVCFY/7H9vTg9KgKylBh4XXAwSSFKZJU1cBfyeiK3qwWBEohEAhQUuJ4/4keevs1LamwDrgK2yn+n+jb8a4PW7Bxf9fnM7GnHf8V2Nb1mKFne4tY8jj5Q1qMvTeWD3uIlOi5PQOcgPYfw/Vd67imdXv5UGPeJV0h65KXiCSLjrhC4h1xHcLe3yMZeysfexuQGAUOfXaEk/3/gtjOuPFiuwvbXxBsEiul/39t7gOu74qj3ea9x9tg6p8jX7ITe5/Na8+Gg8N7voxI2lRiV9briCs9BnDEpcQVEi9xSVynBeG3X7cdNaKtngbf+A0EM/RmmiLisgEkLhVnSNK0lMB1S2yS6oz6K3baGpvUhnycnthEJHsocUlSHayAmb/ruc7Lh13ntfyrUNmQltBEJEsocUnSdeSfPPJKqDGviEgfKHGFBIEb0x1E9jhYYa9prY21zmst/G5mt96GIiIJUOIKMYB+kSZVsBRmPR67Me+0tbD06qiu8iIifaDE1d2L2HtIHcfebl4G7FiRc2PeZd/SaUORnDSAn3uVw0fLx5bET8e2fZCkyG+D330TpkUdYRns6cTrbrY3kBaRHPEd4FWt45IMNxRYCsyIsW01tqmIquVFcovWcUlG+wi4BpuketxJGViOGvOKSHxKXOKqw8CXsA14uwu1TPwtoM5QIuJEiUtc145tcxh95BVqzPsg6rwlIr1T4pK0aMJe01pLz9OGdcBT2NuDiYhEU+KStPkYmI098uouD3vNawmQ2CVbEckFSlySVi2cPG0YfUux6dhrXoPdDkpEMpoSl6TdQezNJp+JejxUsPEE9tZJIiKgxCUZogNbKr+KngUb07A3ay5IQ1wiknmUuCRjHAK+iS2Vj7XO60nsImYRyW1KXJJRgsAsYq/zmobtvDHM7aBEJKNouYxknOPADV3/noZNWiEzsH9tzUR9kEVylY64JCM1Al/GrvOKNhV72rDC1YhEJFMocUnGagPmYAs2ugt12HgAKHI7KBFJOyUuyWihxry9FWwsB4rdDkpE0kqJSzLeYew1rd4a8z6CGvOK5BIlLvGEeI15l6BKI5FcocQlnhFqzBvrtOFU1JhXJFcocYmnhBrzRp827N6YV/fGFsluSlziOUeA61BjXpFcpcQlnuTUmLcOeBw15hXJVkpc4llOjXmno8a8ItlKiUs87RB2kXKsOymHGvOWuRyTiKSWEpd4XgD4Cr035n0YNeYVySZKXJIVQo15o9d5gT1tuBSt8xLJFkpckjVCjXmjj7zAFmz8DjXmFckGSlySVXprzJvHyca8p7odlIgklRKXZJ1m4FrskVf0Oq9QY14lLxHvSihxLVq0iIsuuojTTjuNiooKLr/8cvbs2RMx5/jx48ybN49hw4ZRXFzMzJkzaWxsjJizb98+6urqKCoqoqKigttvv52Ojo6BfzUiXT4ErqTn/bxC67weRacNRTzLJGDy5Mlm6dKlZteuXWbHjh3msssuMzU1NebIkSPhOXPnzjXV1dVm48aNZuvWreaSSy4xl156aXh7R0eHGTNmjKmtrTXbt28369atM+Xl5WbhwoV9jiMQCBjsNXgNDcdRAWYlmE4wJmqsAjMoA2LU0MjlEQgEEklDxhhjEkpc0ZqamgxgNm/ebIwxprm52eTn55sVK1aE57z55psGMPX19cYYY9atW2fy8vJMQ0NDeM7ixYtNSUmJaW1t7dP7KnFpJDJOBbOansnrRNfjwzIgRg2NXB39SVwDusYVCAQAOP300wHYtm0b7e3t1NbWhueMGjWKmpoa6uvrAaivr+eCCy6gsvJkQ57JkycTDAbZvXt3zPdpbW0lGAxGDJG+OsrJrvLdhRrzPoQa84p4Sb8TV2dnJ7fccguf+9znGDNmDAANDQ0UFBRQVlYWMbeyspKGhobwnO5JK7Q9tC2WRYsWUVpaGh7V1dX9DVty1FFO3s8rVmPe3wCFbgclIv3S78Q1b948du3axfLly5MZT0wLFy4kEAiEx/79+1P+npJ9mrCNeaMLNsDez+sJ1JhXxAv6lbjmz5/P2rVree655zjzzDPDj1dVVdHW1kZzc3PE/MbGRqqqqsJzoqsMQ5+H5kQrLCykpKQkYoj0R/fGvN11b8yrIy+RDJfIBbHOzk4zb948M3LkSPP222/32B4qznjyySfDj7311lsGehZnNDY2hufcf//9pqSkxBw/frxPcag4Q2Ogo5TYBRudYNZ0bU93jBoauTBSXlV44403mtLSUvP888+bAwcOhMfHH38cnjN37lxTU1NjNm3aZLZu3Wr8fr/x+/3h7aFy+EmTJpkdO3aY9evXm+HDh6scXsP1UYgtiTcxxkpUbaih4cZIeeLq7Y2XLl0annPs2DFz0003maFDh5qioiJzxRVXmAMHDkS8znvvvWemTJlihgwZYsrLy82CBQtMe3t7n+NQ4tJI1qjEJq9Y67xWo3VeGhqpHv1JXL6uhOQpwWCQ0tLSdIchWaIQWIEtje+uE1vIcT22sENEki8QCCRct6BehZLzWoFvoMa8Il6hxCWCvRmlU2Pex1DyEskUSlwiXZwa805FjXlFMoUSl0g3HcB19LyTcmid1wNAfhriEpGTlLhEohwEvoY98oquXJqKvZPyMLeDEpEwJS6RGOI15n0QKHM5JhGxlLhEeuHUmHcG8GugwO2gRESJS8RJqDHvMzG2TcWu/1JjXhF3KXGJxNEBXE3vjXkfAAa7HZRIDlPiEumDD4FvYa95xSrYeALdjFLELUpcIn3UDHyJngUboXVeDwPlLsckkosGpTsAES9pwxZsgK0u9HX924ct2MjDLmLucD80kZyhIy6RBDUBs4i9zqsOeAoY7nZQIjlEiUukH45jG/Oujno8tM5rCVDsdlAiOUKJS6SfApxsDxWrMe+jQJHbQYnkACUukQE4hF3n1Vtj3sdQY16RZFPiEhmgeI15l6DGvCLJpMQlkgQHgdk4N+Y93e2gRLKUEpdIkhwBvkrPgg0f9prXQ8BQt4MSyUJKXCJJ9DFwAz1PG4Jd5/UwaswrMlBKXCJJ1oTtsBFdsAH2tOGTqDGvyEAocYmkQDu2t2GsxrzTgF+hxrwi/aXEJZIih7Fd5WOdNpyGbcxb4nZQIllAiUskhT4CvkzvjXl/jdpDiSRKTXZFUqwNW7ABaswrkgw64hJxQSPOjXl/h468RPpKiUvEJceBrxO7MW+ow8Zpbgcl4kFKXCIuCmLbQ60hdmPeR1BjXpF4lLhEXHYIe02rt8a8y9E6LxEnSlwiaeDUmHca8ABqzCvSGyUukTQ5iL3mtQY15hVJhBKXSBq1YBvzxlrnpca8IrEpcYmk2THgenpvzPtr1JhXpDslLpEM4NSYtw7bmFd3UhaxlLhEMkSoMe/KqMe7F2wMcTckkYykxCWSQQ4D19B7Y97HUWNeESUukQzzEfa0YW+NeX+D2kNJblPiEslA7cQu2PBh20M9iDpkS+5S4hLJUE2cLJVXY16Rk5S4RDLYMeI35tU1L8k1SlwiGa6Fk+2hemvMq2pDySVKXCIecAiYSezGvHXYakOt85JcocQl4hGhxryrUGNeyW1KXCIechD4BrELNqZhCzbU21CynRKXiMfEa8y7DHWVl+ymxCXiQU6NeacDD6PThpK9lLhEPCrUmDf6yAvUmFeymxKXiIc5Neadji3YKHI3JJGUU+IS8biPsI15eyvYeBw4ze2gRFJIiUskC3yEXecVq2CjDvgtag8l2UOJSyRLhBrzxlrnFWoPpca8kg2UuESySBNwFbFPG05FjXklOyhxiWSZUGPe6NOGaswr2UKJSyQL9aUx72C3gxJJEiUukSx1kPiNeSvdDkokCZS4RLJYB3AtvRds/AooSENcIgOhxCWS5Q4B38Qeeakxr2QDJS6RHBAEvkLsdV5TUWNe8RYlLpEccRy4gd4b8y5DjXnFG5S4RHJII/BlYjfmnYoa84o3KHGJ5Jg2YA62YKO77h021JhXMpkSl0gOauZkY97odV5TsaXyxS7HJNJXCSWuxYsXM3bsWEpKSigpKcHv9/Pss8+Gtx8/fpx58+YxbNgwiouLmTlzJo2NjRGvsW/fPurq6igqKqKiooLbb7+djo6O5Hw1ItJnh3Fe5/UIag8lGcokYPXq1eaZZ54xb7/9ttmzZ4/5zne+Y/Lz882uXbuMMcbMnTvXVFdXm40bN5qtW7eaSy65xFx66aXh53d0dJgxY8aY2tpas337drNu3TpTXl5uFi5cmEgYJhAIGOz1ZQ0NjQGOCjArwXSCMVFjFZhBGRCjRvaOQCCQ0O9/Y4xJKHHFMnToULNkyRLT3Nxs8vPzzYoVK8Lb3nzzTQOY+vp6Y4wx69atM3l5eaahoSE8Z/HixaakpMS0trb2+T2VuDQ0kjuKwKymZ/I60fV4eQbEqJGdoz+Jq9/XuE6cOMHy5cs5evQofr+fbdu20d7eTm1tbXjOqFGjqKmpob6+HoD6+nouuOACKitPNpqZPHkywWCQ3bt39/pera2tBIPBiCEiyfMx8DViN+adBjwIlLodlEgvEk5cO3fupLi4mMLCQubOncvTTz/N6NGjaWhooKCggLKysoj5lZWVNDQ0ANDQ0BCRtELbQ9t6s2jRIkpLS8Ojuro60bBFJI4jODfm/Q1qzCuZIeHEdf7557Njxw62bNnCjTfeyJw5c3jjjTdSEVvYwoULCQQC4bF///6Uvp9IrnJqzBuqNlRjXkm3hG+IWlBQwLnnngvA+PHjefXVV/npT3/KrFmzaGtro7m5OeKoq7GxkaqqKgCqqqp45ZVXIl4vVHUYmhNLYWEhhYWFiYYqIv0Qasy7BLuuy9f1uK/b51/CrgcTSYcBr+Pq7OyktbWV8ePHk5+fz8aNG8Pb9uzZw759+/D7/QD4/X527txJU1NTeM6GDRsoKSlh9OjRAw1FRJLkEHaRcqzGvKE7KZe5HJNIWCKVHHfccYfZvHmz2bt3r3n99dfNHXfcYXw+n/n9739vjLHl8DU1NWbTpk1m69atxu/3G7/fH35+qBx+0qRJZseOHWb9+vVm+PDhKofX0MjQMRhbEm9ijJVghmVAjBreHikvh7/mmmvMWWedZQoKCszw4cPNxIkTw0nLGGOOHTtmbrrpJjN06FBTVFRkrrjiCnPgwIGI13jvvffMlClTzJAhQ0x5eblZsGCBaW9vTyhoJS4NDfdGBTZ5xVrntRpMfgbEqOHd0Z/E5TPGGDwmGAxSWlqa7jBEckYBtgHvtKjHO4FnsNWITdFPEumDQCBASUlJQs9Rr0IRiasNezPK6Ma8oXVeS4BT3Q5KcpYSl4j0STO22jDWOq+pwGOoMa+4Q4lLRPrsQ5zXeT2C7uclqZfwOi4RyW0dwPVd/55G7HVeV3bNE0kFHXGJSMKasL0NY63zqgOeAsrdDkpyhhKXiPTLUWzyWh31ePeCDdX+SioocYlIvx3BnjaMVbAxA9uYV83aJNmUuERkQEKNeZ+JsW0qsAI15pXkUuISkQHrAK6h5zovH/a04QPoyEuSR4lLRJIi1Jh3NT0LNkJHXmUuxyTZSYlLRJImAHyFnndSDh15LQOGuRyTZB+t4xKRpGol9jovsAUbeWidlwyMjrhEJOmasEde0R024OQ6L3XYkP5S4hKRlGjFuTHvA6gxr/SPEpeIpEwzvTfmnYZtzKvkJYlS4hKRlIrXmPdRdNpQEqPiDBFJOTXmlWTSEZeIuMKpMe9UbMGGSuWlL5S4RMQ1R4Gr6NmYN7TO60G0SFniU+ISEVcdBW6g98a8v0btocSZEpeIuK4JNeaV/lPiEpG06ACupvfGvL9CR14SmxKXiKTNh8C3iN2Ydxr2yEs3o5RoSlwiklbNwJfpvTHvw0C5yzFJZtM6LhFJuzZswQaoMa/EpyMuEckIjZxszBt92rAO+B3qsCGWEpeIZIxW4Bv0XOeVh+2w8QBQ7HZQknGUuEQkowSwjXnXELsx76OoMW+uU+ISkYzzIfaaVm+NeR9Dpw1zmRKXiGSkUGPe6FL5ULXhA6i6LFcpcYlIxmoCZmNPG6oxr4QocYlIRjuCbcwbvc4rdCflB4GhbgclaaXEJSIZ72NOnjbsrTFvgdtBSdoocYmIJzg15q1DjXlziRKXiHiGU2Pe6djGvIPdDkpcp8QlIp4Saswbq2BjGvAEasyb7ZS4RMRzmoEvEbsx71TsNS815s1eSlwi4kmhxryx1nlNBx5C67yylRKXiHhWIzCL2KcNQ415h7sdlKScEpeIeNpxnBvzLgFOczsoSSklLhHxvCBwHc6NeYvcDkpSRolLRLLCIXpvzFuHGvNmEyUuEckaHdgjr1XELth4AMhPQ1ySXEpcIpJVDgJfJ/adlKdhCzZOdzsoSSolLhHJOkeArxJ7ndc0YClqzOtlSlwikpWcGvNOBx5GjXm9SolLRLJWE7bDRnTBBtgOG2rM601KXCKS1dqJ35h3iNtByYAocYlI1juMTV5OjXlL3A5K+k2JS0Rywkf03pi3DvgNaszrFUpcIpIz4jXmfRA15vUCJS4RySmhxryx1nlNRY15vUCJS0RyznHsIuXo04ZqzOsNSlwikpOCwLXEXuc1DXgEVRtmKiUuEclZh4CZxG7MOxVYjhrzZiIlLhHJaR2cPPJSY15vUOISkZx3COfGvE+hxryZRIlLRARowVYbxlrnNRV4CDXmzRRKXCIiXY5xsjFv9JHXDGxjXp02TD8lLhGRbuI15n0SNeZNNyUuEZEo7cC36L0x7wOoVD6dBpS47r77bnw+H7fcckv4sePHjzNv3jyGDRtGcXExM2fOpLGxMeJ5+/bto66ujqKiIioqKrj99tvp6OgYSCgiIknl1Jh3KvA4WqScLv1OXK+++ir3338/Y8eOjXj81ltvZc2aNaxYsYLNmzfzwQcfcOWVV4a3nzhxgrq6Otra2vjTn/7Eww8/zLJly7jzzjv7/1WIiKTAR9h1Xr0VbPwWtYdKC9MPLS0t5rzzzjMbNmwwX/jCF8zNN99sjDGmubnZ5OfnmxUrVoTnvvnmmwYw9fX1xhhj1q1bZ/Ly8kxDQ0N4zuLFi01JSYlpbW3t0/sHAgGD/SNIQ0NDI+WjAswqMJ1gTNS4JAPi8/IIBAIJ56B+HXHNmzePuro6amtrIx7ftm0b7e3tEY+PGjWKmpoa6uvrAaivr+eCCy6gsvLk5c3JkycTDAbZvXt3zPdrbW0lGAxGDBERtzQBXyX2Oq8foWIBtyW8v5cvX85rr73GokWLemxraGigoKCAsrKyiMcrKytpaGgIz+metELbQ9tiWbRoEaWlpeFRXV2daNgiIgNyDJhNz9OG36Vnr0NJrYQS1/79+7n55pt55JFHGDx4cKpi6mHhwoUEAoHw2L9/v2vvLSIS0gJcB/iBPwATgNjniSSVEkpc27Zto6mpic9+9rMMGjSIQYMGsXnzZu69914GDRpEZWUlbW1tNDc3RzyvsbGRqqoqAKqqqnpUGYY+D82JVlhYSElJScQQEUmHg8DLwGTgFeBoesPJSQklrokTJ7Jz50527NgRHhdeeCGzZ88O/zs/P5+NGzeGn7Nnzx727duH3+8HwO/3s3PnTpqamsJzNmzYQElJCaNHj07SlyUiklo6PZhGCZdzROleVWiMMXPnzjU1NTVm06ZNZuvWrcbv9xu/3x/e3tHRYcaMGWMmTZpkduzYYdavX2+GDx9uFi5c2Of3VFWhhoaGRnaM/lQVDiLJ/v3f/528vDxmzpxJa2srkydP5he/+EV4+ymnnMLatWu58cYb8fv9nHrqqcyZM4cf/vCHyQ5FRESykM8YY9IdRKKCwSClpaXpDkNERAYoEAgkXLeg5QciIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpSlwiIuIpCSWu73//+/h8vogxatSo8Pbjx48zb948hg0bRnFxMTNnzqSxsTHiNfbt20ddXR1FRUVUVFRw++2309HRkZyvRkREst6gRJ/w6U9/mj/84Q8nX2DQyZe49dZbeeaZZ1ixYgWlpaXMnz+fK6+8kpdeegmAEydOUFdXR1VVFX/60584cOAA3/zmN8nPz+ef//mfk/DliIhI1jMJuOuuu8y4ceNibmtubjb5+flmxYoV4cfefPNNA5j6+npjjDHr1q0zeXl5pqGhITxn8eLFpqSkxLS2tvY5jkAgYAANDQ0NDY+PQCCQSBoyxhiT8DWud955h5EjR/KJT3yC2bNns2/fPgC2bdtGe3s7tbW14bmjRo2ipqaG+vp6AOrr67nggguorKwMz5k8eTLBYJDdu3f3+p6tra0Eg8GIISIiuSmhxDVhwgSWLVvG+vXrWbx4MXv37uXzn/88LS0tNDQ0UFBQQFlZWcRzKisraWhoAKChoSEiaYW2h7b1ZtGiRZSWloZHdXV1ImGLiEgWSega15QpU8L/Hjt2LBMmTOCss87iiSeeYMiQIUkPLmThwoXcdttt4c+DwaCSl4hIjhpQOXxZWRmf/OQneffdd6mqqqKtrY3m5uaIOY2NjVRVVQFQVVXVo8ow9HloTiyFhYWUlJREDBERyU0DSlxHjhzhL3/5CyNGjGD8+PHk5+ezcePG8PY9e/awb98+/H4/AH6/n507d9LU1BSes2HDBkpKShg9evRAQhERkVyRSCXHggULzPPPP2/27t1rXnrpJVNbW2vKy8tNU1OTMcaYuXPnmpqaGrNp0yazdetW4/f7jd/vDz+/o6PDjBkzxkyaNMns2LHDrF+/3gwfPtwsXLgwoYoSVRVqaGhoZMfoT1VhQolr1qxZZsSIEaagoMCcccYZZtasWebdd98Nbz927Ji56aabzNChQ01RUZG54oorzIEDByJe47333jNTpkwxQ4YMMeXl5WbBggWmvb09oaCVuDQ0NDSyY/QncfmMMQaPCQaDlJaWpjsMEREZoEAgkHDdgid7FXow14qISAz9+X3uycT14YcfpjsEERFJgpaWloSfk3Cvwkxw+umnA7Zhr04ZxhZa67Z//34tH4hB+8eZ9o8z7R9nfdk/xhhaWloYOXJkwq/vycSVl2cPFEtLS/VNE4fWvTnT/nGm/eNM+8dZvP3T3wMPT54qFBGR3KXEJSIinuLJxFVYWMhdd91FYWFhukPJWNpHzrR/nGn/ONP+cZbq/ePJdVwiIpK7PHnEJSIiuUuJS0REPEWJS0REPEWJS0REPMWTieu+++7j7LPPZvDgwUyYMIFXXnkl3SG54oUXXmDatGmMHDkSn8/HypUrI7YbY7jzzjsZMWIEQ4YMoba2lnfeeSdizuHDh5k9ezYlJSWUlZVx7bXXcuTIERe/itRZtGgRF110EaeddhoVFRVcfvnl7NmzJ2LO8ePHmTdvHsOGDaO4uJiZM2f2uLnpvn37qKuro6ioiIqKCm6//XY6Ojrc/FJSYvHixYwdOza8KNTv9/Pss8+Gt+fyvonl7rvvxufzccstt4Qfy+V99P3vfx+fzxcxRo0aFd7u6r5JuJ98mi1fvtwUFBSYhx56yOzevdtcf/31pqyszDQ2NqY7tJRbt26d+e53v2ueeuopA5inn346Yvvdd99tSktLzcqVK82f//xnM336dHPOOeeYY8eOhed88YtfNOPGjTMvv/yy+eMf/2jOPfdcc9VVV7n8laTG5MmTzdKlS82uXbvMjh07zGWXXWZqamrMkSNHwnPmzp1rqqurzcaNG83WrVvNJZdcYi699NLw9tA942pra8327dvNunXrTHl5ecL3jMtEq1evNs8884x5++23zZ49e8x3vvMdk5+fb3bt2mWMye19E+2VV14xZ599thk7dqy5+eabw4/n8j666667zKc//Wlz4MCB8Dh48GB4u5v7xnOJ6+KLLzbz5s0Lf37ixAkzcuRIs2jRojRG5b7oxNXZ2WmqqqrMT37yk/Bjzc3NprCw0Dz22GPGGGPeeOMNA5hXX301POfZZ581Pp/PvP/++67F7pampiYDmM2bNxtj7P7Iz883K1asCM958803DWDq6+uNMfaPg7y8PNPQ0BCes3jxYlNSUmJaW1vd/QJcMHToULNkyRLtm25aWlrMeeedZzZs2GC+8IUvhBNXru+ju+66y4wbNy7mNrf3jadOFba1tbFt2zZqa2vDj+Xl5VFbW0t9fX0aI0u/vXv30tDQELFvSktLmTBhQnjf1NfXU1ZWxoUXXhieU1tbS15eHlu2bHE95lQLBALAyabM27Zto729PWIfjRo1ipqamoh9dMEFF1BZWRmeM3nyZILBILt373Yx+tQ6ceIEy5cv5+jRo/j9fu2bbubNm0ddXV3EvgB9/wC88847jBw5kk984hPMnj2bffv2Ae7vG0812T106BAnTpyI+MIBKisreeutt9IUVWZoaGgAiLlvQtsaGhqoqKiI2D5o0CBOP/308Jxs0dnZyS233MLnPvc5xowZA9ivv6CggLKysoi50fso1j4MbfO6nTt34vf7OX78OMXFxTz99NOMHj2aHTt25Py+AVi+fDmvvfYar776ao9tuf79M2HCBJYtW8b555/PgQMH+MEPfsDnP/95du3a5fq+8VTiEumrefPmsWvXLl588cV0h5JRzj//fHbs2EEgEODJJ59kzpw5bN68Od1hZYT9+/dz8803s2HDBgYPHpzucDLOlClTwv8eO3YsEyZM4KyzzuKJJ55gyJAhrsbiqVOF5eXlnHLKKT0qVRobG6mqqkpTVJkh9PU77Zuqqiqampoitnd0dHD48OGs2n/z589n7dq1PPfcc5x55pnhx6uqqmhra6O5uTlifvQ+irUPQ9u8rqCggHPPPZfx48ezaNEixo0bx09/+lPtG+zprqamJj772c8yaNAgBg0axObNm7n33nsZNGgQlZWVOb+PuisrK+OTn/wk7777ruvfP55KXAUFBYwfP56NGzeGH+vs7GTjxo34/f40RpZ+55xzDlVVVRH7JhgMsmXLlvC+8fv9NDc3s23btvCcTZs20dnZyYQJE1yPOdmMMcyfP5+nn36aTZs2cc4550RsHz9+PPn5+RH7aM+ePezbty9iH+3cuTMiwW/YsIGSkhJGjx7tzhfios7OTlpbW7VvgIkTJ7Jz50527NgRHhdeeCGzZ88O/zvX91F3R44c4S9/+QsjRoxw//sn4dKSNFu+fLkpLCw0y5YtM2+88Ya54YYbTFlZWUSlSrZqaWkx27dvN9u3bzeAueeee8z27dvNX//6V2OMLYcvKyszq1atMq+//rqZMWNGzHL4z3zmM2bLli3mxRdfNOedd17WlMPfeOONprS01Dz//PMRJbsff/xxeM7cuXNNTU2N2bRpk9m6davx+/3G7/eHt4dKdidNmmR27Nhh1q9fb4YPH54V5cx33HGH2bx5s9m7d695/fXXzR133GF8Pp/5/e9/b4zJ7X3Tm+5Vhcbk9j5asGCBef75583evXvNSy+9ZGpra015eblpamoyxri7bzyXuIwx5mc/+5mpqakxBQUF5uKLLzYvv/xyukNyxXPPPWeAHmPOnDnGGFsS/73vfc9UVlaawsJCM3HiRLNnz56I1/jwww/NVVddZYqLi01JSYm5+uqrTUtLSxq+muSLtW8As3Tp0vCcY8eOmZtuuskMHTrUFBUVmSuuuMIcOHAg4nXee+89M2XKFDNkyBBTXl5uFixYYNrb213+apLvmmuuMWeddZYpKCgww4cPNxMnTgwnLWNye9/0Jjpx5fI+mjVrlhkxYoQpKCgwZ5xxhpk1a5Z59913w9vd3De6rYmIiHiKp65xiYiIKHGJiIinKHGJiIinKHGJiIinKHGJiIinKHGJiIinKHGJiIinKHGJiIinKHGJiIinKHGJiIinKHGJiIinKHGJiIin/H8C8GXPKL6eEQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cv2.line(blan_img,(400,400),(50,50),(255,0,0), 5)\n",
    "plt.imshow(blan_img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "b81fee33",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f610cca5cd0>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "font = cv2.FONT_HERSHEY_SIMPLEX\n",
    "cv2.putText(blan_img,'hello',(10,500),font,4,(255,255,255),3,cv2.LINE_AA)\n",
    "plt.imshow(blan_img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "684c0a35",
   "metadata": {},
   "outputs": [],
   "source": [
    "blank_img = np.zeros(shape=(512,512,3),dtype=np.int16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "be447945",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f610cc6b0a0>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(blank_img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "19f4bc85",
   "metadata": {},
   "outputs": [],
   "source": [
    "# adding custom polygon\n",
    "vertices = np.array([[100,300],[200,200], [400,400],[200,400]],dtype=np.int32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "0c01accf",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[100, 300],\n",
       "       [200, 200],\n",
       "       [400, 400],\n",
       "       [200, 400]], dtype=int32)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vertices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "f7ee5792",
   "metadata": {},
   "outputs": [],
   "source": [
    "pts = vertices.reshape((-1,1,2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "6281c490",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4, 2)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vertices.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "374c78d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4, 1, 2)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pts.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "3da8200c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f610c7e7970>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cv2.polylines(blank_img,[pts],isClosed=True,color=(255,0,0),thickness=5)\n",
    "plt.imshow(blank_img)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "f701a3ca",
   "metadata": {},
   "outputs": [],
   "source": [
    "# drawing images using mouse\n",
    "# using callbacks\n",
    "\n",
    "img = np.zeros((512,512,3),np.int8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "c52649b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "def draw_circle(event,x,y,flags,param):\n",
    "    if event == cv2.EVENT_LBUTTONDOWN:\n",
    "        cv2.circle(img,(x,y),100, (0,255,0), -1)\n",
    "\n",
    "cv2.namedWindow(winname='mouse')\n",
    "cv2.setMouseCallback('mouse',draw_circle)\n",
    "\n",
    "\n",
    "while True:\n",
    "    cv2.imshow('mouse',img)\n",
    "    if cv2.waitKey(20) & 0xFF == 27:\n",
    "        break\n",
    "cv2.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "14b9089b",
   "metadata": {},
   "outputs": [],
   "source": [
    "def draw_circle(event,x,y,flags,param):\n",
    "    if event == cv2.EVENT_LBUTTONDOWN:\n",
    "        cv2.circle(img,(x,y),100, (0,255,0), -1)\n",
    "    elif event == cv2.EVENT_RBUTTONDOWN:\n",
    "        cv2.circle(img,(x,y),100, (0,255,0), -1)\n",
    "        \n",
    "\n",
    "cv2.namedWindow(winname='mouse')\n",
    "cv2.setMouseCallback('mouse',draw_circle)\n",
    "\n",
    "\n",
    "while True:\n",
    "    cv2.imshow('mouse',img)\n",
    "    if cv2.waitKey(20) & 0xFF == 27:\n",
    "        break\n",
    "cv2.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "d005cf01",
   "metadata": {},
   "outputs": [],
   "source": [
    "drawing = False\n",
    "ix,iy = -1,-1\n",
    "def draw_rectangle(event,x,y,flags,param):\n",
    "    global ix,iy,drawing\n",
    "    if event == cv2.EVENT_LBUTTONDOWN:\n",
    "        drawing = True\n",
    "        ix,iy = x,y\n",
    "    elif event == cv2.EVENT_MOUSEMOVE:\n",
    "        if drawing:\n",
    "            cv2.rectangle(img,(ix,iy),(x,y), (255,0,0), 5)\n",
    "    \n",
    "    elif event == cv2.EVENT_LBUTTONUP:\n",
    "        drawing = False\n",
    "        cv2.rectangle(img,(ix,iy),(x,y), (255,0,0), 5)\n",
    "        \n",
    "    \n",
    "\n",
    "cv2.namedWindow(winname='mouse')\n",
    "cv2.setMouseCallback('mouse',draw_rectangle)\n",
    "\n",
    "\n",
    "while True:\n",
    "    cv2.imshow('mouse',img)\n",
    "    if cv2.waitKey(20) & 0xFF == 27:\n",
    "        break\n",
    "cv2.destroyAllWindows()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "59d25b0b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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