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eastmountyxz · web-flow · commit 52e40dc9f3a6 · 2021-05-18T16:26:34.000+08:00
diff --git a/blog40-ImageSegmentation/blog40-06-kmeans(best).py b/blog40-ImageSegmentation/blog40-06-kmeans(best).py
@@ -0,0 +1,77 @@
+# coding: utf-8
+# 2021-05-17 Eastmount CSDN
+import cv2
+import numpy as np
+import matplotlib.pyplot as plt
+
+#读取原始图像
+img = cv2.imread('scenery.png') 
+print(img.shape)
+
+#图像二维像素转换为一维
+data = img.reshape((-1,3))
+data = np.float32(data)
+
+#定义中心 (type,max_iter,epsilon)
+criteria = (cv2.TERM_CRITERIA_EPS +
+            cv2.TERM_CRITERIA_MAX_ITER, 10, 1.0)
+
+#设置标签
+flags = cv2.KMEANS_RANDOM_CENTERS
+
+#K-Means聚类 聚集成2类
+compactness, labels2, centers2 = cv2.kmeans(data, 2, None, criteria, 10, flags)
+
+#K-Means聚类 聚集成4类
+compactness, labels4, centers4 = cv2.kmeans(data, 4, None, criteria, 10, flags)
+
+#K-Means聚类 聚集成8类
+compactness, labels8, centers8 = cv2.kmeans(data, 8, None, criteria, 10, flags)
+
+#K-Means聚类 聚集成16类
+compactness, labels16, centers16 = cv2.kmeans(data, 16, None, criteria, 10, flags)
+
+#K-Means聚类 聚集成64类
+compactness, labels64, centers64 = cv2.kmeans(data, 64, None, criteria, 10, flags)
+
+#图像转换回uint8二维类型
+centers2 = np.uint8(centers2)
+res = centers2[labels2.flatten()]
+dst2 = res.reshape((img.shape))
+
+centers4 = np.uint8(centers4)
+res = centers4[labels4.flatten()]
+dst4 = res.reshape((img.shape))
+
+centers8 = np.uint8(centers8)
+res = centers8[labels8.flatten()]
+dst8 = res.reshape((img.shape))
+
+centers16 = np.uint8(centers16)
+res = centers16[labels16.flatten()]
+dst16 = res.reshape((img.shape))
+
+centers64 = np.uint8(centers64)
+res = centers64[labels64.flatten()]
+dst64 = res.reshape((img.shape))
+
+#图像转换为RGB显示
+img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+dst2 = cv2.cvtColor(dst2, cv2.COLOR_BGR2RGB)
+dst4 = cv2.cvtColor(dst4, cv2.COLOR_BGR2RGB)
+dst8 = cv2.cvtColor(dst8, cv2.COLOR_BGR2RGB)
+dst16 = cv2.cvtColor(dst16, cv2.COLOR_BGR2RGB)
+dst64 = cv2.cvtColor(dst64, cv2.COLOR_BGR2RGB)
+
+#用来正常显示中文标签
+plt.rcParams['font.sans-serif']=['SimHei']
+
+#显示图像
+titles = [u'原始图像', u'聚类图像 K=2', u'聚类图像 K=4',
+          u'聚类图像 K=8', u'聚类图像 K=16',  u'聚类图像 K=64']  
+images = [img, dst2, dst4, dst8, dst16, dst64]  
+for i in range(6):  
+   plt.subplot(2,3,i+1), plt.imshow(images[i], 'gray'), 
+   plt.title(titles[i])  
+   plt.xticks([]),plt.yticks([])  
+plt.show()
