Python实现连通域标记算法

import matplotlib.pyplot as plt
import numpy as np
path = r"coin.png"
img = plt.imread(path).astype(float)
img = np.mean(img, axis=2)
th = 0.513    # climb(img, 0.1, 0, 0.01)
b = img>th

def drawImg(im1, im2, c1='gray', c2='gray'):
    fig = plt.figure()
    ax = fig.add_subplot(121)
    plt.imshow(im1, cmap=c1)
    plt.axis('off')
    ax = fig.add_subplot(122)
    plt.imshow(im2, cmap=c2)
    plt.axis('off')
    plt.show()

drawImg(img, b)

from itertools import product
def getIndDct(img):
    # 元素个数
    m,n = img.shape
    # 编号矩阵
    indMat = np.arange(m*n).reshape([m,n])
    dct = {}
    for i,j in product(range(m), range(n)):
        if img[i,j] == 0:
            continue
        ind = indMat[i,j]
        dct[ind] = []
        if i>1 and img[i-1,j]!=0:
            dct[ind].append(indMat[i-1,j])
        if i+1<m and img[i+1, j]!=0:
            dct[ind].append(indMat[i+1,j])
        if j > 1 and img[i,j-1]!=0:
            dct[ind].append(indMat[i, j-1])
        if j+1 < n and img[i, j+1] != 0:
            dct[ind].append(indMat[i, j+1])
    return dct

from copy import deepcopy
def mergeKey(dct, key):
    keys = [key]
    st, ed = 0, 1
    while len(keys)>0:
        for i in range(st, ed):
            k = keys[i]
            if k in dct:
                keys += dct[k]
                del dct[k]
        if ed == len(keys):
            break
        st, ed = ed, len(keys)
    return keys

def uniqueDct(dct):
    uDct = deepcopy(dct)
    for k in dct:
        if k in uDct:
            uDct[k] = list(set(mergeKey(uDct, k)))
    return [list(set([k]+v)) for k,v in uDct.items()]

def cds(img):
    dct = getIndDct(img)
    lst = uniqueDct(dct)
    arr = img.reshape(-1)*0
    for i,L in enumerate(lst, 1):
        arr[L] = i
    return arr.reshape(img.shape)

from scipy.ndimage import binary_erosion

b = img>0.4
bb = binary_erosion(b, np.ones([5,5]))
c = cds(bb)
drawImg(img, c, 'gray', 'jet')