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35 lines
1.0 KiB
35 lines
1.0 KiB
6 months ago
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import numpy as np
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import cv2
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from matplotlib import pyplot as plt
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img = cv2.imread('basil.jpg')
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gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
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ret, thresh = cv2.threshold(gray,0,255,cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)
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# noise removal
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kernel = np.ones((3,3),np.uint8)
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opening = cv2.morphologyEx(thresh,cv2.MORPH_OPEN,kernel, iterations = 2)
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# sure background area
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sure_bg = cv2.dilate(opening,kernel,iterations=3)
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# Finding sure foreground area
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dist_transform = cv2.distanceTransform(opening,cv2.DIST_L2,5)
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ret, sure_fg = cv2.threshold(dist_transform,0.7*dist_transform.max(),255,0)
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# Finding unknown region
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sure_fg = np.uint8(sure_fg)
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unknown = cv2.subtract(sure_bg,sure_fg)
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# Marker labelling
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ret, markers = cv2.connectedComponents(sure_fg)
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# Add one to all labels so that sure background is not 0, but 1
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markers = markers+1
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# Now, mark the region of unknown with zero
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markers[unknown==255] = 0
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markers = cv2.watershed(img,markers)
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img[markers == -1] = [255,0,0]
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plt.imshow(img)
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plt.show()
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