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Mar 20th, 2019
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  1. import cv2
  2. import numpy as np
  3.  
  4. # If you're wondering why only two dimensions, well this is a grayscale image,
  5. # if we doing a colored image, we'd use
  6. # rectangle = np.zeros((300, 300, 3),np.uint8)
  7.  
  8. # Making a sqare
  9. square = np.zeros((300, 300), np.uint8)
  10. cv2.rectangle(square, (50, 50), (250, 250), 255, -2)
  11. cv2.imshow("Square", square)
  12. cv2.waitKey(0)
  13.  
  14. # Making a ellipse
  15. ellipse = np.zeros((300, 300), np.uint8)
  16. cv2.ellipse(ellipse, (150, 150), (150, 150), 30, 0, 180, 255, -1)
  17. cv2.imshow("Ellipse", ellipse)
  18. cv2.waitKey(0)
  19.  
  20. cv2.destroyAllWindows()
  21.  
  22.  
  23. # Shows only where they intersect
  24. And = cv2.bitwise_and(square, ellipse)
  25. cv2.imshow("AND", And)
  26. cv2.waitKey(0)
  27.  
  28. # Shows where either square or ellipse is
  29. bitwiseOr = cv2.bitwise_or(square, ellipse)
  30. cv2.imshow("OR", bitwiseOr)
  31. cv2.waitKey(0)
  32.  
  33. # Shows where either exist by itself
  34. bitwiseXor = cv2.bitwise_xor(square, ellipse)
  35. cv2.imshow("XOR", bitwiseXor)
  36. cv2.waitKey(0)
  37.  
  38. # Shows everything that isn't part of the square
  39. bitwiseNot_sq = cv2.bitwise_not(square)
  40. cv2.imshow("NOT - square", bitwiseNot_sq)
  41. cv2.waitKey(0)
  42.  
  43. ### Notice the last operation inverts the image totally
  44.  
  45. cv2.destroyAllWindows()
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