1.5：基于聚类的“图像分割”实例编写

 1 import numpy as np
 2 import PIL.Image as image
 3 from sklearn.cluster import KMeans
 4  
 5 def loadData(filePath):
 6     f = open(filePath,‘rb‘)
 7     data = []
 8     img = image.open(f)
 9     m,n = img.size
10     for i in range(m):
11         for j in range(n):
12             x,y,z = img.getpixel((i,j))
13             data.append([x/256.0,y/256.0,z/256.0])
14     f.close()
15     return np.mat(data),m,n
16  
17 imgData,row,col = loadData(‘kmeans/bull.jpg‘)
18 label = KMeans(n_clusters=4).fit_predict(imgData)
19  
20 label = label.reshape([row,col])
21 pic_new = image.new("L", (row, col))
22 for i in range(row):
23     for j in range(col):
24         pic_new.putpixel((i,j), int(256/(label[i][j]+1)))
25 pic_new.save("result-bull-4.jpg", "JPEG")