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 precomputed essential matrix:

data = np.load('../data/stereo/case1/stereo.npy').item()E = data['E']

3. Decompose the essential matrix into two possible rotations and translations:

R1, R2, T = cv2.decomposeEssentialMat(E)

4. Print the results:

print('Rotation 1:')print(R1)print('Rotation 2:')print(R2)print('Translation:')print(T)