结果

代码

# -*- coding: utf-8 -*-
 # ====================0．导入库=======================
 import numpy as np
 import cv2
 # ===================1．图像预处理=======================
 img = cv2.imread('cat.jpg')
 data = img.reshape((-1,3))
 data = np.float32(data)
 # =================2．使用K均值聚类模块=====================
 criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 10, 1.0)
 K = 2
 ret,label,center=cv2.kmeans(data,K,None,criteria,10,cv2.KMEANS_RANDOM_CENTERS)
 # ====================3．打印的实现============================
 print("距离：",ret)
 print("标签：\n",label)
 print("分类中心点：\n",center)
 # ================4．像素值替换及结果展示=======================
 center = np.uint8(center)
 res1 = center[label.flatten()]
 res2 = res1.reshape((img.shape))
 cv2.imshow("original",img)
 cv2.imshow("result",res2)
 cv2.waitKey()
 cv2.destroyAllWindows()