In [38]:

    

# Importing the libraries 
import cv2
import numpy as np
import matplotlib.pyplot as plt


def connected_component_label(path):
    
    # Getting the input image
    img = cv2.imread(path, 0)
    # Converting those pixels with values 1-127 to 0 and others to 1
    img = cv2.threshold(img, 127, 255, cv2.THRESH_BINARY)[1]
    # Applying cv2.connectedComponents() 
    num_labels, labels = cv2.connectedComponents(img)
    
    # Map component labels to hue val, 0-179 is the hue range in OpenCV
    label_hue = np.uint8(179*labels/np.max(labels))
    blank_ch = 255*np.ones_like(label_hue)
    labeled_img = cv2.merge([label_hue, blank_ch, blank_ch])

    # Converting cvt to BGR
    labeled_img = cv2.cvtColor(labeled_img, cv2.COLOR_HSV2BGR)

    # set bg label to black
    labeled_img[label_hue==0] = 0
    
    
    # Showing Original Image
    plt.imshow(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
    plt.axis("off")
    plt.title("Orginal Image")
    plt.show()
    
    #Showing Image after Component Labeling
    plt.imshow(cv2.cvtColor(labeled_img, cv2.COLOR_BGR2RGB))
    plt.axis('off')
    plt.title("Image after Component Labeling")
    plt.show()


    

In [39]:

    

connected_component_label('C:/Users/Yash Joshi/OG_notebooks/face.jpg')


    

In [40]:

    

connected_component_label('C:/Users/Yash Joshi/OG_notebooks/crosses.jpg')


    

In [41]:

    

connected_component_label('C:/Users/Yash Joshi/OG_notebooks/shapes.png')