图像分割
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2024-03-25 08:14:04
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1 K-means
opencv官方介绍及使用典例
使用
import numpy as np
import cv2
img = cv2.imread('home.jpg')
Z = img.reshape((-1,3))
# convert to np.float32
Z = np.float32(Z)
# define criteria, number of clusters(K) and apply kmeans()
criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 10, 1.0)
K = 8
ret,label,center=cv2.kmeans(Z,K,None,criteria,10,cv2.KMEANS_RANDOM_CENTERS)
# Now convert back into uint8, and make original image
center = np.uint8(center)
res = center[label.flatten()]
res2 = res.reshape((img.shape))
cv2.imshow('res2',res2)
cv2.waitKey(0)
cv2.destroyAllWindows()
图像金字塔
opencv官方介绍
函数
cv2.pyrUp(), cv2.pyrDown()
Mean shift
pyrMeanShiftFiltering函数
https://blog.csdn.net/qq_18343569/article/details/47834385
分水岭算法
没网,待续
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