OpenCV 3 Computer Vision with Python Cookbook

How to do it...

You need to complete the following steps:

1. Import the modules:

import cv2import numpy as np

2. Generate a system of linear equations:

N = 10A = np.random.randn(N,N)while np.linalg.matrix_rank(A) < N:    A = np.random.randn(N,N)x = np.random.randn(N,1)b = A @ x

3. Solve the system of linear equations:

ok, x_est = cv2.solve(A, b)print('Solved:', ok)if ok:    print('Residual:', cv2.norm(b - A @ x_est))    print('Relative error:', cv2.norm(x_est - x) / cv2.norm(x))

4. Construct an over-determined system of linear equations:

N = 10A = np.random.randn(N*2,N)while np.linalg.matrix_rank(A) < N:    A = np.random.randn(N*2,N)x = np.random.randn(N,1)b = A @ x

5. Solve the over-determined system of linear equations:

ok, x_est = cv2.solve(A, b, flags=cv2.DECOMP_NORMAL) ...