分水岭分割流程：图像->灰度->二值->距离变换->寻找种子->生成Marker->分水岭变换->输出
参考：

python OpenCV学习笔记（二十九）：图像流域（分水岭）分割算法

import cv2 as cv
import numpy as np


def watershed_demo():
    print(src.shape)
    # 模糊操作
    blur = cv.pyrMeanShiftFiltering(src, 10, 100)
    # 灰度、二值化图像
    gray = cv.cvtColor(blur, cv.COLOR_BGR2GRAY)
    ret, binary = cv.threshold(gray, 0, 255, cv.THRESH_BINARY | cv.THRESH_OTSU)
    cv.imshow("binary", binary)

    # morphology operation
    kernel = cv.getStructuringElement(cv.MORPH_RECT, (3, 3))
    mb = cv.morphologyEx(binary, cv.MORPH_OPEN, kernel, iterations=2)
    sure_bg = cv.morphologyEx(mb, cv.MORPH_CLOSE, kernel, iterations=3)
    cv.imshow("morphology operation", sure_bg)

    # distance transform
    dist = cv.distanceTransform(mb, cv.DIST_L2, 3)
    dist_output = cv.normalize(dist, 0, 1, cv.NORM_MINMAX)
    cv.imshow("distance_t", dist_output*50)

    ret, surface = cv.threshold(dist, dist.max()*0.6, 255, cv.THRESH_BINARY)
    cv.imshow("surface", surface)

    surface_fg = np.uint8(surface)
    unknown = cv.subtract(sure_bg, surface_fg)
    ret, markers = cv.connectedComponents(surface_fg)
    print("ret =", ret)

    # watershed transform
    markers = markers +1
    markers[unknown == 255] = 0
    markers = cv.watershed(src, markers = markers)
    src[markers == -1] = [0, 0, 255]
    cv.imshow("result", src)


print("--------- Hello Python ---------")
src = cv.imread("D:/opencv/coins1.jpg")
# cv.namedWindow("coins", cv.WINDOW_AUTOSIZE)
# cv.imshow("coins", src)
watershed_demo()
cv.waitKey(0)
cv.destroyAllWindows()