Python 22.opencv 分水岭算法 图像分割

import cv2
import numpy as np

# 分割连在一块的硬币
img = cv2.imread('coins3.png')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# Otsu's二值化
ret, thresh = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU)

# noise removal
kernel = np.ones((3, 3), np.uint8)
opening = cv2.morphologyEx(thresh, cv2.MORPH_OPEN, kernel, iterations=2)

sure_bg = cv2.dilate(opening, kernel, iterations=3)

# 距离变换分割出来
dist_transform = cv2.distanceTransform(opening, cv2.DIST_L2, 5)
ret, sure_fg = cv2.threshold(dist_transform, 0.7 * dist_transform.max(), 255, 0)

# 得到确定是硬币的区域和不确定的区域
sure_fg = np.uint8(sure_fg)
unknown = cv2.subtract(sure_bg, sure_fg)


# Marker labelling
ret, markers = cv2.connectedComponents(sure_fg)

# Add one to all labels so that sure background is not 0, but 1
markers = markers+1

# Now, mark the region of unknown with zero
markers[unknown==255] = 0

markers = cv2.watershed(img,markers)
img[markers == -1] = [255,0,0]


cv2.imshow('img',img)
cv2.waitKey(0)
cv2.destroyAllWindows()