漫水填充：也就是用一定顏色填充聯通區域，通過設定可連通畫素的上下限以及連通方式來達到不同的填充效果;

程式說明依舊以註釋的形式寫出，在Python例程的基礎上修改為隨機顏色填充：

#decoding:utf-8

import numpy as np
import cv2
import random

help_message = '''USAGE: floodfill.py [<image>]

Click on the image to set seed point

Keys:
  f     - toggle floating range
  c     - toggle 4/8 connectivity
  ESC   - exit
'''

if __name__ == '__main__':
    import sys
    try: fn = sys.argv[1]
    except: fn = 'E:/lena.jpg'
    print help_message

    img = cv2.imread(fn, True)
    h, w = img.shape[:2]#得到影象的高和寬
    mask = np.zeros((h+2, w+2), np.uint8)#掩碼單通道8位元，長和寬都比輸入影象多兩個畫素點，滿水填充不會超出掩碼的非零邊緣
    seed_pt = None
    fixed_range = True
    connectivity = 4

    def update(dummy=None):
        if seed_pt is None:
            cv2.imshow('floodfill', img)
            return
        flooded = img.copy()#以副本的形式進行填充，這樣每次
        mask[:] = 0#掩碼初始為全0
        lo = cv2.getTrackbarPos('lo', 'floodfill')#觀察點畫素鄰域負差最大值（也就是與選定畫素多少差值內的歸為同一區域）
        hi = cv2.getTrackbarPos('hi', 'floodfill')#觀察點畫素鄰域正差最大值
        flags = connectivity#低位位元包含連通值, 4 (預設) 或 8
        if fixed_range:
            flags |= cv2.FLOODFILL_FIXED_RANGE #考慮當前象素與種子象素之間的差（高位元也可以為0）
        #以白色進行漫水填充
        cv2.floodFill(flooded, mask, seed_pt, (random.randint(0,255), random.randint(0,255), random.randint(0,255)), (lo,)*3, (hi,)*3, flags)
        
        cv2.circle(flooded, seed_pt, 2, (0, 0, 255), -1)#選定基準點用紅色圓點標出
        cv2.imshow('floodfill', flooded)

    def onmouse(event, x, y, flags, param):#滑鼠響應函式
        global seed_pt
        if flags & cv2.EVENT_FLAG_LBUTTON:#滑鼠左鍵響應，選擇漫水填充基準點
            seed_pt = x, y
            update()

    update()
    cv2.setMouseCallback('floodfill', onmouse)
    cv2.createTrackbar('lo', 'floodfill', 20, 255, update)
    cv2.createTrackbar('hi', 'floodfill', 20, 255, update)

    while True:
        ch = 0xFF & cv2.waitKey()
        if ch == 27:
            break
        if ch == ord('f'):
            fixed_range = not fixed_range #選定時flags的高位位元位0，也就是鄰域的選定為當前畫素與相鄰畫素的的差，這樣的效果就是聯通區域會很大
            print 'using %s range' % ('floating', 'fixed')[fixed_range]
            update()
        if ch == ord('c'):
            connectivity = 12-connectivity #選擇4方向或則8方向種子擴散
            print 'connectivity =', connectivity
            update()
    cv2.destroyAllWindows()