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 globimport numpy as np

2. Set the pattern size and prepare lists with images:

PATTERN_SIZE = (9, 6)left_imgs = list(sorted(glob.glob('../data/stereo/case1/left*.png')))right_imgs = list(sorted(glob.glob('../data/stereo/case1/right*.png')))assert len(left_imgs) == len(right_imgs)

3. Find the chessboard points:

criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 1e-3)left_pts, right_pts = [], []img_size = Nonefor left_img_path, right_img_path in zip(left_imgs, right_imgs):    left_img = cv2.imread(left_img_path, cv2.IMREAD_GRAYSCALE)    right_img = cv2.imread(right_img_path, cv2.IMREAD_GRAYSCALE)    if img_size is None: img_size = (left_img.shape[1], ...