Opencv Python版学习笔记（二）漫水填充

漫水填充：也就是用一定颜色填充联通区域，通过设置可连通像素的上下限以及连通方式来达到不同的填充效果;

程序说明依旧以注释的形式写出，在Python例程的基础上修改为随机颜色填充：

#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]#得到图像的高和宽
    mask = np.zeros((h+2, w+2), np.uint8)#掩码单通道8比特，长和宽都比输入图像多两个像素点，满水填充不会超出掩码的非零边缘
    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()#以副本的形式进行填充，这样每次
        mask[:] = 0#掩码初始为全0
        lo = cv2.getTrackbarPos('lo', 'floodfill')#观察点像素邻域负差最大值（也就是与选定像素多少差值内的归为同一区域）
        hi = cv2.getTrackbarPos('hi', 'floodfill')#观察点像素邻域正差最大值
        flags = connectivity#低位比特包含连通值, 4 (缺省) 或 8
        if fixed_range:
            flags |= cv2.FLOODFILL_FIXED_RANGE #考虑当前象素与种子象素之间的差（高比特也可以为0）
        #以白色进行漫水填充
        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)#选定基准点用红色圆点标出
        cv2.imshow('floodfill', flooded)

    def onmouse(event, x, y, flags, param):#鼠标响应函数
        global seed_pt
        if flags & cv2.EVENT_FLAG_LBUTTON:#鼠标左键响应，选择漫水填充基准点
            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 #选定时flags的高位比特位0，也就是邻域的选定为当前像素与相邻像素的的差，这样的效果就是联通区域会很大
            print 'using %s range' % ('floating', 'fixed')[fixed_range]
            update()
        if ch == ord('c'):
            connectivity = 12-connectivity #选择4方向或则8方向种子扩散
            print 'connectivity =', connectivity
            update()
    cv2.destroyAllWindows()