python实现基于SVM手写数字识别功能

#!/usr/bin/env python
import numpy as np
import mlpy
import cv2
print 'loading ...'

def getnumc(fn):
 '''返回数字特征'''
 fnimg = cv2.imread(fn) #读取图像
 img=cv2.resize(fnimg,(8,8)) #将图像大小调整为8*8
 alltz=[]
 for now_h in xrange(0,8):
 xtz=[] 
 for now_w in xrange(0,8):
  b = img[now_h,now_w,0]
  g = img[now_h,now_w,1]
  r = img[now_h,now_w,2]
  btz=255-b
  gtz=255-g
  rtz=255-r
  if btz>0 or gtz>0 or rtz>0:
  nowtz=1
  else:
  nowtz=0
  xtz.append(nowtz) 
 alltz+=xtz
 return alltz
 
#读取样本数字
x=[]
y=[]
for numi in xrange(1,10):
 for numij in xrange(1,5):
 fn='nums/'+str(numi)+'-'+str(numij)+'.png'
 x.append(getnumc(fn))
 y.append(numi)
 
x=np.array(x)
y=np.array(y)
svm = mlpy.LibSvm(svm_type='c_svc', kernel_type='poly',gamma=10)
svm.learn(x, y)
print u"训练样本测试："
print svm.pred(x)
print u"未知图像测试："
for iii in xrange (1,10):
 testfn= 'nums/test/'+str(iii)+'-test.png'
 testx=[]
 testx.append(getnumc(testfn))
 print 
 print testfn+":",
 print svm.pred(testx)