OpenCV 3 Computer Vision with Python Cookbook

How to do it

You need to complete the following steps:

1. Import the necessary modules:

import cv2import numpy as np

2. Load the left and right rectified images:

left_img = cv2.imread('../data/stereo/left.png')right_img = cv2.imread('../data/stereo/right.png')

3. Compute the disparity map using the stereo block matching algorithm:

stereo_bm = cv2.StereoBM_create(32)dispmap_bm = stereo_bm.compute(cv2.cvtColor(left_img, cv2.COLOR_BGR2GRAY),                                cv2.cvtColor(right_img, cv2.COLOR_BGR2GRAY))

4. Compute the disparity map using the stereo semi-global block matching algorithm:

stereo_sgbm = cv2.StereoSGBM_create(0, 32)dispmap_sgbm = stereo_sgbm.compute(left_img, right_img)

5. Visualize the results:

plt.figure(figsize=(12,10))plt.subplot(221)plt.title('left') ...