019 - Contours.ipynb

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      "Number of contours after contouring: 5\n"
     ]
    }
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   "source": [
    "import cv2\n",
    "import numpy as np\n",
    "\n",
    "#Let's Load a simple image with 3 black squares\n",
    "image = cv2.imread(\"images/test.png\")\n",
    "cv2.imshow(\"Input image\",image)\n",
    "cv2.waitKey()\n",
    "\n",
    "#GrayScale\n",
    "gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)\n",
    "\n",
    "#Find the edges\n",
    "edged=cv2.Canny(gray,30,200)\n",
    "cv2.imshow(\"Canny edges\",edged)\n",
    "cv2.waitKey()\n",
    "\n",
    "#Find contours. Use a copy of your image, since finContours alters the image\n",
    "_, contours, hierarchy = cv2.findContours(edged.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)\n",
    "cv2.imshow(\"Canny edges after contouring\",edged)\n",
    "cv2.waitKey()\n",
    "\n",
    "print(\"Number of contours after contouring: \"+str(len(contours)))\n",
    "\n",
    "#Draw all contours. Use -1 as the 3rd parameter to draw all\n",
    "cv2.drawContours(image,contours,-1,(0,255,0),3)\n",
    "\n",
    "cv2.imshow(\"Contours\", image)\n",
    "cv2.waitKey()\n",
    "cv2.destroyAllWindows()"
   ]
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   "source": [
    "**cv2.findContours(Image,Retrieval Mode, Approximation Method)**\n",
    "\n",
    "Returns->contours,hierarchy\n",
    "\n",
    "**Note** In OpenCV 3.X, findCountours return a 3rd argument wich is ret (or a boolean indicating if the function was successfully run).\n",
    "\n",
    "The variable 'countours' are stored as a numpy array of (x,y) points that form the contour\n",
    "\n",
    "While, 'hirarchy' describes the chlid-parent relationships between contours (i.e. contours within contours)\n",
    "\n",
    "**Approximation Methods**\n",
    "\n",
    "Using cv2.CHAIN_APPROX_NONE stores all the boundary points. But we don't necessarily need all bounding points. If the points form a straight line, we only need the start and ending points of that line.\n",
    "\n",
    "Using cv2.CHAIN_APPROX_SIMPLE instead only provides these start and end points of bounding contours, thus resulting in much more efficent storage of contour information."
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