Added README.md

Author: mehabhalodiya

Contour-Detection/README.md

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+# Contour Detection
+
+Contours can be explained simply as a curve joining all the continuous points (along the boundary), having same color or intensity. The contours are a useful tool for shape analysis and object detection and recognition.
+
+- For better accuracy, use binary images. So before finding contours, apply threshold or canny edge detection.
+
+- Since OpenCV 3.2, `findContours()` no longer modifies the source image but returns a modified image as the first of three return parameters.
+
+- In OpenCV, finding contours is like finding white object from black background. So remember, object to be found should be white and background should be black.
+
+</br>
+
+Let's see how to find contours of a binary image:
+
+```
+def getContours(img,imgContour):
+    contours, hierarchy = cv2.findContours(img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
+```
+
+See, there are three arguments in `cv.findContours()` function, first one is source image, second is contour retrieval mode, third is contour approximation method. And it outputs a modified image, the contours and hierarchy. contours is a Python list of all the contours in the image. Each individual contour is a Numpy array of (x,y) coordinates of boundary points of the object.
+
+</br>
+
+## How to draw the contours?
+
+To draw the contours, `cv.drawContours` function is used. It can also be used to draw any shape provided you have its boundary points. 
+
+Its first argument is source image, second argument is the contours which should be passed as a Python list, third argument is index of contours (useful when drawing individual contour. To draw all contours, pass -1) and remaining arguments are color, thickness etc.
+
+- To draw all the contours in an image:
+```
+cv.drawContours(img, contours, -1, (0,255,0), 3)
+```
+
+- To draw an individual contour, say 4th contour:
+```
+cv.drawContours(img, contours, 3, (0,255,0), 3)
+```
+
+</br>
+
+## Contour Approximation Method
+
+I have used this method in `getContours()` function.
+What does it denote actually?
+
+We know that contours are the boundaries of a shape with same intensity. It stores the (x,y) coordinates of the boundary of a shape. But does it store all the coordinates ? That is specified by this contour approximation method.
+
+If you pass `cv.CHAIN_APPROX_NONE`, all the boundary points are stored. But actually do we need all the points? For eg, you found the contour of a straight line. Do you need all the points on the line to represent that line? No, we need just two end points of that line. This is what `cv.CHAIN_APPROX_SIMPLE` does. It removes all redundant points and compresses the contour, thereby saving memory.
+
+Below image of a rectangle demonstrate this technique. Just draw a circle on all the coordinates in the contour array (drawn in blue color). First image shows points I got with `cv.CHAIN_APPROX_NONE` (734 points) and second image shows the one with `cv.CHAIN_APPROX_SIMPLE` (only 4 points). See, how much memory it saves!!!
+
+</br>
+
+![contour](https://user-images.githubusercontent.com/73488906/111815073-40cbc200-8901-11eb-82ac-a6d21000ae48.jpg)
+
+</br>
+
+Note: In this script, I have used `cv2.CHAIN_APPROX_NONE`.