Lecture 4.1 - Understanding Contours.ipynb

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    "# Contours"
   ]
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      "Number of Contours found = 3\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/shapes.jpg')\n",
    "cv2.imshow('Input Image', image)\n",
    "cv2.waitKey(0)\n",
    "\n",
    "# Grayscale\n",
    "gray = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)\n",
    "\n",
    "# Find Canny edges\n",
    "edged = cv2.Canny(gray, 30, 200)\n",
    "cv2.imshow('Canny Edges', edged)\n",
    "cv2.waitKey(0)\n",
    "\n",
    "# Finding Contours\n",
    "# Use a copy of your image e.g. edged.copy(), since findContours alters the image\n",
    "contours, hierarchy = cv2.findContours(edged, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)\n",
    "cv2.imshow('Canny Edges After Contouring', edged)\n",
    "cv2.waitKey(0)\n",
    "\n",
    "print(\"Number of Contours found = \" + str(len(contours)))\n",
    "\n",
    "# Draw all contours\n",
    "# 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(0)\n",
    "cv2.destroyAllWindows()"
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    "**cv2.findContours(image, Retrieval Mode, Approximation Method)**\n",
    "\n",
    "Returns -> contours, hierarchy\n",
    "\n",
    "**NOTE** In OpenCV 3.X, findContours returns a 3rd argument which is ret (or a boolean indicating if the function was successfully run). \n",
    "\n",
    "If you're using OpenCV 3.X replace line 12 with:\n",
    "\n",
    "_, contours, hierarchy = cv2.findContours(image, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)\n",
    "\n",
    "The variable 'contours' are stored as a numpy array of (x,y) points that form the contour\n",
    "\n",
    "While, 'hierarchy' describes the child-parent relationships between contours (i.e. contours within contours)\n",
    "\n",
    "\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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