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  1. import cv2
  2. import numpy as np
  3. import matplotlib.pyplot as plt
  4.  
  5. image = cv2.imread('images/scan.jpg')
  6.  
  7. cv2.imshow('Original', image)
  8. cv2.waitKey(0)
  9.  
  10. # Cordinates of the 4 corners of the original image
  11. points_A = np.float32([[320,15], [700,215], [85,610], [530,780]])
  12.  
  13. # Cordinates of the 4 corners of the desired output
  14. # We use a ratio of an A4 Paper 1 : 1.41
  15. points_B = np.float32([[0,0], [420,0], [0,594], [420,594]])
  16.  
  17. # Use the two sets of four points to compute
  18. # the Perspective Transformation matrix, M    
  19. M = cv2.getPerspectiveTransform(points_A, points_B)
  20.  
  21. warped = cv2.warpPerspective(image, M, (420,594))
  22.  
  23. cv2.imshow('warpPerspective', warped)
  24. cv2.waitKey(0)
  25. cv2.destroyAllWindows()
  26.  
  27.  
  28. import cv2
  29. import numpy as np
  30. import matplotlib.pyplot as plt
  31.  
  32. image = cv2.imread('images/ex2.jpg')
  33. rows,cols,ch = image.shape
  34.  
  35. cv2.imshow('Original', image)
  36. cv2.waitKey(0)
  37.  
  38. # Cordinates of the 4 corners of the original image
  39. points_A = np.float32([[320,15], [700,215], [85,610]])
  40.  
  41. # Cordinates of the 4 corners of the desired output
  42. # We use a ratio of an A4 Paper 1 : 1.41
  43. points_B = np.float32([[0,0], [420,0], [0,594]])
  44.  
  45. # Use the two sets of four points to compute
  46. # the Perspective Transformation matrix, M    
  47. M = cv2.getAffineTransform(points_A, points_B)
  48.  
  49. warped = cv2.warpAffine(image, M, (cols, rows))
  50.  
  51. cv2.imshow('warpPerspective', warped)
  52. cv2.waitKey(0)
  53. cv2.destroyAllWindows()
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