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# -*- coding: utf-8 -*-# @Author  : matthew# @Software: PyCharmimport cv2import matplotlib.pyplot as pltimport numpy as npdef seg_kmeans_gray():    img = cv2.imread('000129.jpg', cv2.IMREAD_GRAYSCALE)    # 展平    img_flat = img.reshape((img.shape[0] * img.shape[1], 1))    img_flat = np.float32(img_flat)    # 迭代参数    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TermCriteria_MAX_ITER, 20, 0.5)    flags = cv2.KMEANS_RANDOM_CENTERS    # 聚类    compactness, labels, centers = cv2.kmeans(img_flat, 2, None, criteria, 10, flags)    # 显示结果    img_output = labels.reshape((img.shape[0], img.shape[1]))    plt.subplot(121), plt.imshow(img, 'gray'), plt.title('input')    plt.subplot(122), plt.imshow(img_output, 'gray'), plt.title('kmeans')    plt.show()if __name__ == '__main__':    seg_kmeans_gray()

# -*- coding: utf-8 -*-# @Author  : matthew# @Software: PyCharmimport cv2import matplotlib.pyplot as pltimport numpy as npdef seg_kmeans_color():    img = cv2.imread('000129.jpg', cv2.IMREAD_COLOR)    # 变换一下图像通道bgr->rgb，否则很别扭啊    b, g, r = cv2.split(img)    img = cv2.merge([r, g, b])    # 3个通道展平    img_flat = img.reshape((img.shape[0] * img.shape[1], 3))    img_flat = np.float32(img_flat)    # 迭代参数    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TermCriteria_MAX_ITER, 20, 0.5)    flags = cv2.KMEANS_RANDOM_CENTERS    # 聚类    compactness, labels, centers = cv2.kmeans(img_flat, 2, None, criteria, 10, flags)    # 显示结果    img_output = labels.reshape((img.shape[0], img.shape[1]))    plt.subplot(121), plt.imshow(img), plt.title('input')    plt.subplot(122), plt.imshow(img_output, 'gray'), plt.title('kmeans')    plt.show()if __name__ == '__main__':    seg_kmeans_color()

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