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 camera matrix and distortion coefficients for our camera, and a photo, that was taken by the same camera:

camera_matrix = np.load('../data/pinhole_calib/camera_mat.npy')dist_coefs = np.load('../data/pinhole_calib/dist_coefs.npy')img = cv2.imread('../data/pinhole_calib/img_00.png')

3. Undistort the image with cv2.undistort—the empty regions will appear in the image:

ud_img = cv2.undistort(img, camera_matrix, dist_coefs)cv2.imshow('undistorted image', ud_img)cv2.waitKey(0)cv2.destroyAllWindows()

4. Eliminate the empty regions by computing the optimal camera matrix and applying it to get the undistorted image without black ...