1 from sklearn.datasets import load_sample_image from sklearn.cluster import KMeans import matplotlib.pyplot as plt china = load_sample_image( "china.jpg" ) plt.imshow(china) plt.show() print (china.shape)   2 image = china[:: 3 ,:: 3 ]  #行列分別按step為3的距離取 x = image.reshape( - 1 , 3 ) #生成行數自填充，列數為3的二維陣列 plt.imshow(image) plt.show() print (image.shape,x.shape)   n_color = 64 model = KMeans(n_color) labels = model.fit_predict(x) #每個點的顏色分類 color = model.cluster_centers_ #64個聚類中心，顏色值   color[labels] images = image.reshape( 143 , 214 , 3 ) print (images.shape) plt.imshow(images) plt.show()