Python OpenCV学习笔记之：分水岭算法分割图像

为什么80%的码农都做不了架构师？>>>   

# -*- coding: utf-8 -*- """ 图像分水岭分割图像 分水岭算法可以参考：http://baike.baidu.com/item/%E5%88%86%E6%B0%B4%E5%B2%AD%E7%AE%97%E6%B3%95 """import numpy as np import cv2 from matplotlib import pyplot as pltimg = cv2.imread('../../../datas/images/apple.jpg') gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) ret, thresh = cv2.threshold(gray,0,255,cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)# 降噪处理 kernel = np.ones((3,3),np.uint8) opening = cv2.morphologyEx(thresh,cv2.MORPH_OPEN,kernel, iterations = 2)# 确定背景 sure_bg = cv2.dilate(opening,kernel,iterations=3)# 查找前景 dist_transform = cv2.distanceTransform(opening,cv2.DIST_L2,5) ret, sure_fg = cv2.threshold(dist_transform,0.7*dist_transform.max(),255,0)# 查找未确定区域 sure_fg = np.uint8(sure_fg) unknown = cv2.subtract(sure_bg,sure_fg)# 标注 ret, markers = cv2.connectedComponents(sure_fg) markers = markers+1# 将未确定区域置为0 markers[unknown==255] = 0# 执行分水岭 markers = cv2.watershed(img,markers) img[markers == -1] = [255,0,0]cv2.imshow("img",img)cv2.waitKey() cv2.destroyAllWindows()

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