template_matching.ipynb

{
 "metadata": {
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.9-final"
  },
  "orig_nbformat": 2,
  "kernelspec": {
   "name": "Python 3.7.9 64-bit",
   "display_name": "Python 3.7.9 64-bit",
   "metadata": {
    "interpreter": {
     "hash": "ad3c5c1a376d0db7bb720492bd9d1a768b4ff58106da778aca420fe1c12bfb49"
    }
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2,
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "from ponyslayer.utils import imshow, imshows, imdraw, imdraws, imdraws_color, immask, immasks, implot\n",
    "import numpy as np\n",
    "import imutils\n",
    "from ponyslayer.unicorn import rotate_image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
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GzkvQgUCgU0Gg1SU1MRDodhtVphs9ngcDgwMDAAtVqN9PR06PV6iMViRKNRBAIBDAwMYGhoKN7tf04oFEIoFIJMJoNEIkFaWhqSk5MhEolARPB6vbBarVCpVEhKSkJSUhIMBgPS09MhFovh9Xov2W2d4wkL70VQUVGBlStXQqlUor29HT/72c9gs9lgt9shFotxzTXX4Prrr0ckEsHHH3+MLVu2oKOjAz6fL96tf2WRSAQ7d+5Eb28vJk6ciLvuugvFxcWYOXMmHn30UX6Hh08++STerV6W4j78X251zz33kMViIbvdTvfff/+o2xplMhn98pe/JL/fTw0NDfx13kQok8lE69evJ47j6MMPP6Qrrrhi1ONTp06lvXv3EhERx3HEcRz19fXxC92xurDFRt4LRKVSoaSkBGlpaZgyZQq/3vEZOp0OpaWlSElJgUAgwJ49e2CxWPgNwRJBKBRCXV0dPvzwQ/T09KCiogITJkxAR0cHOjs7MTw8jMOHDyMYDCI7OxtFRUWQy+WYOnUqP1e5qamJXQe+gOL+F+RyqLy8PHrllVeoqamJ+vv7KRKJkMPh4EfemTNn0vvvv091dXX061//miZPnkwTJ07kT14lQolEIjKZTHTFFVfQqlWraPfu3XTixAl64IEHSCKRkEwmo+zsbCouLqZHH32UhoaGKBwOU39/PzU1NdHLL79Mubm5cT+Oy6XYyHueJBIJxGIxkpOTkZubiyuuuAKxWAzhcBiBQIDfaUClUiE3NxeFhYUQCARob29PuJM4sVgMVqsVVqsV2dnZ0Ol0yMrKgl6vh0qlQigUQn9/P4gIfX198Hq9kMlkMBgMMJlMMJvNkEql8T6MywYL73kQiUSYO3cu5s+fD5PJhLy8PABAXV0dduzYAYfDgdra2svyhoXOzk689NJLSE1NhVQqxY9//GPYbDZ88MEHMJvNOH78OJ5++mkYjUZce+21KC8vj3fLlx0W3vMgEolw9dVX4/vf/z6USiU/U+jUqVN46aWXYLPZLts1nsxmM15//XUolUr86Ec/wne+8x20traitrYWZrMZdXV1aGxs5BcVYOG98Fh4z4FarUZmZiaSkpKQmZkJuVwOjuNgNpsxPDyMrq4uBAIBcByHzMxM6HQ6GI1GdHd3IxgMwmq1guO4eB/GeSEiRCIRhEIh2Gw2NDc3w263IyMjA1OnTsXg4CCsVisCgQDMZjNqa2vhdDoxceJEyGQy2O12fhcI5tywiQnnoLy8HN/97ndRWFiI7OxsZGdno6+vD8899xwOHz4Mh8OBzs5OKJVKrF27FsuXL4fZbMa2bdtgs9nQ29uL3t7ehA8wcHqRgZycHGRlZcFkMmH58uWYMGECPvjgA6xbtw6hUIhf8qeoqAhf+9rXoFar8cYbb2DTpk1s98HzwEbec5CSkoIrr7ySnzRPRPD5fKivr8fHH38M4PRi5TKZDEVFRZgzZw4ikQiamprQ2NgYz9YvOI7j0NXVha6uLkyZMgUPPfQQKisr0draCplMBq/Xi5aWFrS0tEClUmHSpEnIysrCvn37IBKJEIvF2Oh7jlh4zwPHcaitrcXx48fR19eH3t5eAEBRURGuvvpqaDQa2O12rFu3Di0tLeNml3mBQICSkhJ84xvfgMPhwKeffoq2tjb+cbFYjOnTp2PNmjWw2+04ePAgrFZrHDtOTCy85yEajWLv3r145pln4PP5+P1ry8vL8dOf/hQSiQRPPfUU/vSnP/GXjsaL6dOno6ysDBaLBY899tio8EqlUixduhSVlZWor69Hf38/C+85YOH9koRCIZKSkqBUKqHRaOByudDf3w+73Y7BwUFEo1EkJydDLpcjKSkJ4XAYkUgEw8PDGBoaGhdvDSORCAYGBmCxWKBUKpGUlIRAIMBf2x0ZGYHdbodGo4FGo4FWq4Ver4fJZEJGRgb8fj+8Xu9lcS7gUmAnrL4ktVqNVatWYcGCBRgaGkJjYyNcLheamppw6tQpGI1G3HPPPZgyZQr6+vrQ1NQEj8eDkydPorOzM97tXxIpKSmoqKhAeno6Fi5ciJUrV2J4eBg/+clP8Pe//x0mkwkVFRXQ6/W4+eabsXz5cni9XtTU1MBut6O6uhpvvfVWQk7QiJe43+aVCJWamkovv/wyxWIxqq6upilTpox6vLi4mD788EPiOI7Wr19P6enpce85XiUQCGjt2rXkdDrPOjFBqVTSb3/7WxoZGeEnMESjUXrhhRfYHOCvUOxt8xfIzMzkJxzk5OSMekwoFCIvLw8FBQXQ6/Uwm8344IMPUFtbe8kXjhtrenp6sGvXLohEIhgMBixfvhxOpxONjY2IRqNobm7Gtm3bkJqaikmTJkGr1ca75YQU978gY7luvPFGOnjwIHV0dJDb7SaO4/iRVyKR0EMPPUR1dXW0Z88eWrlyJRUUFJDBYCCRSBT33uNZSUlJNHHiRJoxYwa99NJL1NraSq+++irl5uaSQCCg1NRUys/PpxtuuIEOHz5MsViMjbxfsdjIexZnrtGKxWKkpaUhLy8PRqMR4XAYfr8fwWAQHMdBIBDwy7qKxWK43e5LsoNfIjizfWgwGIRIJILJZEJaWhp/0m94eBiDg4NQKpVwuVzw+XzgOA5KpRKhUAjhcJjdwPEFWHjPQq/X4/rrr0dxcTFKS0uhVqsRCASwY8cOHDlyBD09PaN282P+NZ/Phy1btqC1tRVSqRSrVq1CLBZDdXU19u/fD7vdjvXr16O6uhoymQwPP/wwvF4vtm/fjtra2ni3P+bFffgfa1VUVETvv/8+jYyM8LsbOJ1OevDBB0kqlfJviaVSKT3yyCPk9/vp1KlTtGzZsrj3PhZLJBKRRCKh5cuXU2NjI7lcLvrP//xPfnMykUjEb8BmtVrJbDbTqlWr4t73WC828v6TQCDg553m5eVBp9NBIpFgaGgI/f39cDqdsNvtiEQiUKlUyM7OhkajgUAgwMmTJ9Hf34/h4eF4H8aYdGYXBpfLhebmZng8HkgkEpSXl8Pr9aKvrw9+vx9EBIlEwp8IrKiogMfjQV9fH1tC9izYdd5/EovFuOOOO/CNb3wDWq0WeXl5SElJwa5du/DCCy/AZrOhu7sbdrsd06ZNw/e+9z1MnDgR+/btw969e+HxeGA2m+F2u+N9KGNWSkoK8vLykJSUhEWLFqGyshJmsxnPPPMM6urq8MADD+A3v/kN1Go1urq64HQ6cejQITz77LPo6+uLd/tjDht5/0koFCIrKwuzZs2CUqkEESEWi8Fut+PIkSOw2Wz87gZarRZTp07FFVdcgX379vHrNjH/ntvtxvHjx6FUKrFkyRLMmjULycnJSEpKAgD+NReLxSgqKsIVV1yB4eFhqFQqCIVCENG4uFPty2LhPQu3240DBw6gu7sbR48eRSAQgFwux9VXX43S0lKoVCpUV1dj3759OHLkCDsreoE0Njbi9ddfh9FoxKxZs1BUVIScnBzccccdsFgsOHbsGGpra9ntk//EwnsWTqcTb7zxBnbv3o1wOIxgMAitVosVK1bgnnvuwZEjR/DEE0+gqakJoVAIkUgk3i0nPCLCkSNHUF9fj4yMDDz22GP86PuDH/wAXq8XTz31FOrr61l4/2nch1cmk0Gr1UKlUiE5ORkCgQAcx8Hn88HtdkOpVCIjIwM6nY5f/d/j8cDtdrPPt+eIiODxeNDT0wOr1cqfjAqHwwiHw5DL5bBarejp6YFCoYBWq4VIJIJcLo9z52PLuA9vXl4e7r33XuTl5aGoqOhzqxtWVFTg7rvvhlKpRENDA37yk5/A4XDAYrHEqePEFw6H8eGHH6KzsxMej+dzEzeGh4fx5ptv4sCBA6ioqMDq1auh0Wji1O3YNe7DazAYsHTpUkydOhXA6UtGnzVhwgTccMMNkEql+Pjjj/H222+zkybnKRaLob6+HvX19Wd9PBgM4vDhwzh8+DD8fj9uueUWFt6zGJfhlUgkKC0txYQJE1BWVoakpCQQEdrb29Ha2oru7m44HI5RPyOVSjF16lTceOONLLwXWSgUQmNjI/r7+/mvicVilJaW4oYbbsDg4CDq6+vH5KZsl9K4DK9KpcLXv/51rFq1CkqlEqmpqYhGo9i9ezdeeOEFeDweDA4Ofu5nbr/9dlx33XUsvBeZ3W7H73//+1HhlUqlWL58OebOnYvGxkY8/vjjLLzxbiAehEIhP+GA4zh+C0u73Y7Ozs5R12yj0Sh8Ph/UajVkMhlkMlkcOx8fIpEI/zpHo1H4/X74/X6o1WrodDq43W528grjNLyf1d3djffeew+9vb04duzY5y771NXV4emnn4ZarY5Th+OP1+vlPw+3tbXhueeeg9FoxOLFi1FZWRnn7saOcR/evr4+vPnmmzh58iQ4jvvcNcTm5ma0trZ+7kQWc/EQEf/v0NXVhfXr10OtViMlJQVz586Nc3djx7gPr0ajQXFxMQQCAWw2GywWC6RSKXJycpCSkhLv9salcDiM3t5eDA4O8rdMRqNRdnPG/zPuw5ufn48f//jH8Hg82LBhA/7yl7/AYDDggQcewKxZs+Ld3rjkdDrx/PPPY9euXfFuZUwbt+HlOA7RaBRqtRpTpkxBOBzGgQMHIBQKoVAoUFRUhOnTp8e7zXHlzMQPi8UCvV7Pf00gEEAkErGPLv/PuAxvKBTC3r17EQqFkJWVhQULFvAzWwDA5XJh69atbEmbS2zy5MmYPXv2qK9NmDAB8+fPh9FoxJVXXgmhUBin7saecRneYDCIrVu3YufOnZg7dy6uuOKKUeEdGBjA3/72N0gkkjh2Ob4IBALcd999mDZt2qivFxUV4bvf/S4KCgogk8kgEoni1OHYMy7DS0T8tV2/388vJpecnIwJEybwuxx4PB7+Z87M41Wr1QiFQhgaGmKziS4AiUSC1NRUKBQKxGIx9Pb2IhgMwu/3Azh9Z9WZHRY8Hg9sNtuoyQzj2bgM79mIRCIsXrwYWVlZ6Onpweuvv44TJ07wj6tUKtx22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     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "visualize = False\n",
    "template_original = cv2.imread(\"Start3.png\")\n",
    "template_original = cv2.cvtColor(template_original, cv2.COLOR_BGR2GRAY)\n",
    "template_original = cv2.Canny(template_original, 50, 200)\n",
    "(tH, tW) = template_original.shape[:2]\n",
    "imshow(template_original)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "(18170042.0, (424, 13), 1.0)\n"
     ]
    },
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "image = cv2.imread(\"Picture1.png\")\n",
    "gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n",
    "found = None\n",
    "for rotation in range(0, 359, 5):\n",
    "    resized = image\n",
    "    template = rotate_image(template_original, rotation)\n",
    "    # resized = rotate_image(image, rotation)\n",
    "    r = gray.shape[1] / float(resized.shape[1])\n",
    "    if resized.shape[0] < tH or resized.shape[1] < tW: # if the resized image is smaller than the template, then break from the loop\n",
    "        break\n",
    "    # detect edges in the resized, grayscale image and apply template\n",
    "\t# matching to find the template in the image\n",
    "    edged = cv2.Canny(resized, 50, 200)\n",
    "    result = cv2.matchTemplate(edged, template, cv2.TM_CCOEFF)\n",
    "    (_, maxVal, _, maxLoc) = cv2.minMaxLoc(result)\n",
    "    # print(maxVal)\n",
    "    if visualize:\n",
    "        clone = np.dstack([edged, edged, edged])\n",
    "        cv2.rectangle(clone, (maxLoc[0], maxLoc[1]), (maxLoc[0] + tW, maxLoc[1] + tH), (0, 0, 255), 2)\n",
    "        cv2.imshow(\"Template\", template)\n",
    "        cv2.imshow(\"Visualize\", clone)\n",
    "        cv2.waitKey(10)\n",
    "\t# if we have found a new maximum correlation value, then update\n",
    "\t# the bookkeeping variable\n",
    "    if found is None or maxVal > found[0]:\n",
    "        found = (maxVal, maxLoc, r)\n",
    "# unpack the bookkeeping variable and compute the (x, y) coordinates\n",
    "# of the bounding box based on the resized ratio\n",
    "(_, maxLoc, r) = found\n",
    "print(found)\n",
    "(startX, startY) = (int(maxLoc[0] * r), int(maxLoc[1] * r))\n",
    "(endX, endY) = (int((maxLoc[0] + tW) * r), int((maxLoc[1] + tH) * r))\n",
    "# draw a bounding box around the detected result and display the image\n",
    "cv2.rectangle(image, (startX, startY), (endX, endY), (0, 0, 255), 2)\n",
    "imshow(image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ]
}