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 matplotlib.pyplot as plt

2. Load the test images:

img0 = cv2.imread('../data/Lena.png', cv2.IMREAD_GRAYSCALE)img1 = cv2.imread('../data/Lena_rotated.png', cv2.IMREAD_GRAYSCALE)

3. Create the detector, detect keypoints, and computer descriptors:

detector = cv2.ORB_create(100)kps0, fea0 = detector.detectAndCompute(img0, None)kps1, fea1 = detector.detectAndCompute(img1, None)

4. Create the k-nearest neighbor descriptor matcher with k=2, and find matches from left to right and vice versa:

matcher = cv2.BFMatcher_create(cv2.NORM_HAMMING, False)matches01 = matcher.knnMatch(fea0, fea1, k=2)matches10 = matcher.knnMatch(fea1, fea0, k=2)

5. Create ...