OpenCV 3 Computer Vision with Python Cookbook

How to do it...

1. Import the modules we need:

import cv2import numpy as np

2. Implement a function which finds the intersection point of two lines:

def intersect(l1, l2):    delta = np.array([l1[1] - l1[0], l2[1] - l2[0]]).astype(np.float32)        delta = 1 / delta    delta[:, 0] *= -1        b = np.matmul(delta, np.array([l1[0], l2[0]]).transpose())    b = np.diagonal(b).astype(np.float32)            res = cv2.solve(delta, b)    return res[0], tuple(res[1].astype(np.int32).reshape((2)))

3. Define a function which un-warps the perspective distortions by calculating the correspondence between four pairs of distorted and un-distorted points:

def rectify(image, corners, out_size):    rect = np.zeros((4, 2), dtype = "float32")    rect[0] = corners[0]    rect[1] = corners[1] rect[2] = corners[2] ...