K-means算法应用：图片压缩

##加载数据

from sklearn.datasets import load_sample_image
china = load_sample_image("china.jpg")
print(china.shape)
china

import matplotlib.pyplot as plt
plt.imshow(china)
plt.show()

plt.imshow(china[:,:,0])
plt.show()

plt.imshow(china[:,:,0],plt.cm.gray)
plt.show()

from sklearn .datasets import load_sample_image
from sklearn.cluster import KMeans
import matplotlib.pyplot as plt
import numpy as np

china = load_sample_image("china.jpg")
plt.imshow(china)
plt.show()

image = china[::3,::3]
image.shape

plt.imshow(image)
plt.show()

x=image.reshape(-1,3)

model =KMeans(n_clusters=64)
b = model.fit_predict(x)
a = model.cluster_centers_
a[b]

##压缩图片
import sys
sys.getsizeof(china)

sys.getsizeof(new_image)

import matplotlib.image as img
img.imsave("F://02.jpg",china)
#img.imsave("F://03.jpg",new_image)

结果：