1.简介
2.代码
import numpy as np
import PIL.Image as image
from sklearn.cluster import KMeans
def loadData(filePath):
f = open(filePath,'rb')
data = []
img = image.open(f)
m,n = img.size
for i in range(m):
for j in range(n):
x,y,z = img.getpixel((i,j))
data.append([x/256.0,y/256.0,z/256.0])
f.close()
return np.mat(data),m,n
imgData,row,col = loadData('kmeans/bull.jpg')
label = KMeans(n_clusters=4).fit_predict(imgData)
label = label.reshape([row,col])
pic_new = image.new("L", (row, col))
for i in range(row):
for j in range(col):
pic_new.putpixel((i,j), int(256/(label[i][j]+1)))
pic_new.save("result-bull-4.jpg", "JPEG")
3.测试效果
图-1
图-2 n_c=4
图-3 n_c=6
图-4 n_c=auto
2020-06-19