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- import cv2
- import numpy as np
- # If you're wondering why only two dimensions, well this is a grayscale image,
- # if we doing a colored image, we'd use
- # rectangle = np.zeros((300, 300, 3),np.uint8)
- # Making a sqare
- square = np.zeros((300, 300), np.uint8)
- cv2.rectangle(square, (50, 50), (250, 250), 255, -2)
- cv2.imshow("Square", square)
- cv2.waitKey(0)
- # Making a ellipse
- ellipse = np.zeros((300, 300), np.uint8)
- cv2.ellipse(ellipse, (150, 150), (150, 150), 30, 0, 180, 255, -1)
- cv2.imshow("Ellipse", ellipse)
- cv2.waitKey(0)
- cv2.destroyAllWindows()
- # Shows only where they intersect
- And = cv2.bitwise_and(square, ellipse)
- cv2.imshow("AND", And)
- cv2.waitKey(0)
- # Shows where either square or ellipse is
- bitwiseOr = cv2.bitwise_or(square, ellipse)
- cv2.imshow("OR", bitwiseOr)
- cv2.waitKey(0)
- # Shows where either exist by itself
- bitwiseXor = cv2.bitwise_xor(square, ellipse)
- cv2.imshow("XOR", bitwiseXor)
- cv2.waitKey(0)
- # Shows everything that isn't part of the square
- bitwiseNot_sq = cv2.bitwise_not(square)
- cv2.imshow("NOT - square", bitwiseNot_sq)
- cv2.waitKey(0)
- ### Notice the last operation inverts the image totally
- cv2.destroyAllWindows()
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