编写kmeans图像分割代码

好的，以下是一个基于Python的K-means图像分割代码：

import numpy as np
import cv2

def kmeans_image_segmentation(image, k=3):
    # 转换图像数据类型，从[0, 255]变为[0, 1]
    image = image.astype(np.float32) / 255.

    # 改变图像形状以方便聚类
    pixels = image.reshape((-1, 3))

    # 设置K-means参数
    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 50, 0.1)
    flags = cv2.KMEANS_RANDOM_CENTERS

    # 运行K-means算法
    _, labels, centers = cv2.kmeans(pixels, k, None, criteria, 10, flags)

    # 重新构造图像
    segmented_image = centers[labels.flatten()]
    segmented_image = segmented_image.reshape(image.shape)

    # 返回分割后的图像
    return segmented_image

# 示例
image = cv2.imread('input_image.jpg')
segmented_image = kmeans_image_segmentation(image)
cv2.imshow('Input Image', image)
cv2.imshow('Segmented Image', segmented_image)
cv2.waitKey(0)

希望这个代码能够帮助到你！