opencv8.py

#!/usr/bin/env python3

import numpy as np
import cv2

# it all comes down to fine tuning of values

def read_rgb_image(image_name, show):
    rgb_image = cv2.imread(image_name)
    if show: 
        cv2.imshow("RGB Image",rgb_image)
    return rgb_image

def convert_rgb_to_gray(rgb_image,show):
    gray_image = cv2.cvtColor(rgb_image, cv2.COLOR_BGR2GRAY)
    if show: 
        cv2.imshow("Gray Image",gray_image)
    return gray_image

def convert_gray_to_binary(gray_image, adaptive, show):
    if adaptive: 
        binary_image = cv2.adaptiveThreshold(gray_image, 
                            255, 
                            cv2.ADAPTIVE_THRESH_GAUSSIAN_C, 
                            cv2.THRESH_BINARY_INV, 115, 2)
    else:
        _,binary_image = cv2.threshold(gray_image,127,255,cv2.THRESH_BINARY_INV)
    if show:
        cv2.imshow("Binary Image", binary_image)
    return binary_image    

def getContours(binary_image):      
    contours, hierarchy = cv2.findContours(binary_image, 
                                              cv2.RETR_TREE, 
                                               cv2.CHAIN_APPROX_SIMPLE)
    return contours

def draw_contours(image, contours, image_name):
    index = -1 #means all contours
    thickness = 2 #thickness of the contour line
    color = (255, 0, 255) #color of the contour line
    cv2.drawContours(image, contours, index, color, thickness)
    cv2.imshow(image_name,image)



def main():
    image_name = "images/shapes.jpg"
    rgb_image = read_rgb_image(image_name, True)
    gray_image= convert_rgb_to_gray(rgb_image,True)
    binary_image = convert_gray_to_binary(gray_image, True, True)
    contours = getContours(binary_image)
    draw_contours(rgb_image, contours,"RGB Contours")

    cv2.waitKey(0)
    cv2.destroyAllWindows()

if __name__ == '__main__':
    main()