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- import cv2
- import numpy as np
- import matplotlib.pyplot as plt
- image = cv2.imread('images/scan.jpg')
- cv2.imshow('Original', image)
- cv2.waitKey(0)
- # Cordinates of the 4 corners of the original image
- points_A = np.float32([[320,15], [700,215], [85,610], [530,780]])
- # Cordinates of the 4 corners of the desired output
- # We use a ratio of an A4 Paper 1 : 1.41
- points_B = np.float32([[0,0], [420,0], [0,594], [420,594]])
- # Use the two sets of four points to compute
- # the Perspective Transformation matrix, M
- M = cv2.getPerspectiveTransform(points_A, points_B)
- warped = cv2.warpPerspective(image, M, (420,594))
- cv2.imshow('warpPerspective', warped)
- cv2.waitKey(0)
- cv2.destroyAllWindows()
- import cv2
- import numpy as np
- import matplotlib.pyplot as plt
- image = cv2.imread('images/ex2.jpg')
- rows,cols,ch = image.shape
- cv2.imshow('Original', image)
- cv2.waitKey(0)
- # Cordinates of the 4 corners of the original image
- points_A = np.float32([[320,15], [700,215], [85,610]])
- # Cordinates of the 4 corners of the desired output
- # We use a ratio of an A4 Paper 1 : 1.41
- points_B = np.float32([[0,0], [420,0], [0,594]])
- # Use the two sets of four points to compute
- # the Perspective Transformation matrix, M
- M = cv2.getAffineTransform(points_A, points_B)
- warped = cv2.warpAffine(image, M, (cols, rows))
- cv2.imshow('warpPerspective', warped)
- cv2.waitKey(0)
- cv2.destroyAllWindows()
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