第六章实验2

import numpy as np
from sklearn.cluster import KMeans
import matplotlib.pyplot as plt
from PIL import Image

im = Image.open('media/gyy1.jpeg') #此处照片换自己的路径
image = np.array(im).astype(np.float32) / 255.0
image = image[:,:, :3]  # Ensure we have 3 channels (RGB)
image_v = image.reshape(-1, 3)         # Flatten the image to a 2D array of pixels and color values
kmeans = KMeans(n_clusters=10, random_state=0)

N = image_v.shape[0]
idx = np.random.randint(0, N, size=int(N * 0.7))   # Use 70% of the data for training
image_v_train = image_v[idx]
kmeans.fit(image_v_train)
image_v_pred = kmeans.predict(image_v)
image_v_pred = image_v_pred.reshape(image.shape[:2]) # Reshape back to the original image dimensions
plt.imshow(image_v_pred)
plt.show() 
plt.imshow(image)
plt.show()