本文研究的主要是Python验证码识别的相关代码,具体如下。
Talk is cheap, show you the Code!
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import numpy as np
import matplotlib.pyplot as plt
from sklearn.cluster import KMeans
from PIL import Image
#打开图像
im = np.array(Image. open ( 'yzm.png' ))
#得到图像3个维度
h,w,san = im.shape
X = [(h - x,y) for x in range (h) for y in range (w) if im[x][y][ 2 ]< 200 ]
#将X转换成numpy的array类型,方便后续运算操作
X = np.array(X)
n_clusters = 4
k_means = KMeans(init = 'k-means++' ,n_clusters = n_clusters)
k_means.fit(X)
k_means_labels = k_means.labels_
k_means_cluster_centers = k_means.cluster_centers_
k_means_labels_unique = np.unique(k_means_labels)
colors = [ '#4EACC5' , '#FF9C34' , '#4E9A06' , '#FF3300' ]
plt.figure()
plt.hold( True )
for k,col in zip ( range (n_clusters),colors):
my_members = k_means_labels = = k
cluster_center = k_means_cluster_centers[k]
plt.plot(X[my_members, 1 ],X[my_members, 0 ], 'w' ,markerfacecolor = col,marker = '.' )
plt.plot(cluster_center[ 1 ],cluster_center[ 0 ], 'o' ,markerfacecolor = col,markeredgecolor = 'k' ,markersize = 6 )
plt.title( 'KMeans' )
plt.grid( True )
plt.show()
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总结
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原文链接:http://blog.csdn.net/linzch3/article/details/66472901