OpenCV 3 Computer Vision with Python Cookbook

How to do it...

Use the following steps:

1. Import all necessary modules:

import cv2import numpy as npimport matplotlib.pyplot as plt

2. Load the image as grayscale and display it:

grey = cv2.imread('../data/Lena.png', 0)cv2.imshow('original grey', grey)cv2.waitKey()cv2.destroyAllWindows()

3. Equalize the histogram of the grayscale image:

grey_eq = cv2.equalizeHist(grey)

4. Compute the histogram for the equalized image and show it:

hist, bins = np.histogram(grey_eq, 256, [0, 255])plt.fill_between(range(256), hist, 0)plt.xlabel('pixel value')plt.show()

5. Show the equalized image:

cv2.imshow('equalized grey', grey_eq)cv2.waitKey()cv2.destroyAllWindows()

6. Load the image as BGR and convert it to the HSV color space:

color = cv2.imread('../data/Lena.png') ...