OpenCV 3 Computer Vision with Python Cookbook

How to do it...

In order to execute this recipe, we will perform the following steps:

1. First, we import all of the modules we need:

import cv2import numpy as np

2. Open an image and find the connected components in it:

img = cv2.imread('../data/BnW.png', cv2.IMREAD_GRAYSCALE)connectivity = 8num_labels, labelmap = cv2.connectedComponents(img, connectivity, cv2.CV_32S)

3. Show the original image with the scaled image with labels:

img = np.hstack((img, labelmap.astype(np.float32)/(num_labels - 1)))cv2.imshow('Connected components', img)cv2.waitKey()cv2.destroyAllWindows()

4. Open another image, find its Otsu mask, and get the connected components with their statistics:

img = cv2.imread('../data/Lena.png', cv2.IMREAD_GRAYSCALE)otsu_thr, otsu_mask ...