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19--blending.py
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19--blending.py
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import cv2
import numpy as np
apple = cv2.imread('apple.jpg')
orange = cv2.imread('orange.jpg')
orange = cv2.resize(orange, (512,512))
print(apple.shape)
print(orange.shape)
apple_orange = np.hstack((apple[:, :256], orange[:, 256:]))
# generate Gaussian pyramid for apple
apple_copy = apple.copy()
gp_apple = [apple_copy]
for i in range(6):
apple_copy = cv2.pyrDown(apple_copy)
gp_apple.append(apple_copy)
# generate Gaussian pyramid for orange
orange_copy = orange.copy()
gp_orange = [orange_copy]
for i in range(6):
orange_copy = cv2.pyrDown(orange_copy)
gp_orange.append(orange_copy)
# generate Laplacian Pyramid for apple
apple_copy = gp_apple[5]
lp_apple = [apple_copy]
for i in range(5, 0, -1):
gaussian_expanded = cv2.pyrUp(gp_apple[i])
laplacian = cv2.subtract(gp_apple[i-1], gaussian_expanded)
lp_apple.append(laplacian)
# generate Laplacian Pyramid for orange
orange_copy = gp_orange[5]
lp_orange = [orange_copy]
for i in range(5, 0, -1):
gaussian_expanded = cv2.pyrUp(gp_orange[i])
laplacian = cv2.subtract(gp_orange[i-1], gaussian_expanded)
lp_orange.append(laplacian)
# Now add left and right halves of images in each level
apple_orange_pyramid = []
n = 0
for apple_lap, orange_lap in zip(lp_apple, lp_orange):
n += 1
cols, rows, ch = apple_lap.shape
laplacian = np.hstack((apple_lap[:, 0:int(cols/2)], orange_lap[:, int(cols/2):]))
apple_orange_pyramid.append(laplacian)
# now reconstruct
apple_orange_reconstruct = apple_orange_pyramid[0]
for i in range(1, 6):
apple_orange_reconstruct = cv2.pyrUp(apple_orange_reconstruct)
apple_orange_reconstruct = cv2.add(apple_orange_pyramid[i], apple_orange_reconstruct)
cv2.imshow("apple", apple)
cv2.imshow("orange", orange)
cv2.imshow("apple_orange", apple_orange)
cv2.imshow("apple_orange_reconstruct", apple_orange_reconstruct)
cv2.waitKey(0)
cv2.destroyAllWindows()