from urllib import requestdef download_pics(pic_name):url = 'http://wsbs.zjhz.hrss.gov.cn/captcha.svl'res = request.urlopen(url)get_img = res.read()with open('/Users/luacheng/project/python/image/vcode/%s.jpg' % (pic_name), 'wb') as f:f.write(get_img)if __name__ == '__main__':for i in range(100):pic_name = idownload_pics(pic_name)

from PIL import Image
import numpydef binarization(im):  # 二值化imgry = im.convert('L')imgry = numpy.array(imgry)  # 将图像转化为数组height, width = imgry.shapef = open('1.txt', 'w')for i in range(height):for j in range(width):gray = imgry[i, j]if gray <= 220:  # 阈值设为220imgry[i, j] = 0else:imgry[i, j] = 1f.write(str(imgry[i,j]))  #输出到txt查看f.write('\n')'''plt.figure('')plt.imshow(imgry, cmap='gray')plt.axis('off')plt.show()'''return imgryif __name__ == '__main__':img = Image.open('/Users/luacheng/project/python/image/vcode/1.jpg')binarization(img)

 1 def cutImg(img):  #图像切割
 2     s = 12
 3     w = 40
 4     h = 81
 5     t = 0
 6     cut_img = []
 7     for i in range(4):
 8         pic = img.crop((s + w * i, t, s + w * (i + 1), h))
 9         cut_img.append(pic)
10     return cut_img

 1 import os
 2 from PIL import *
 3 from PIL import Image
 4 import numpy as np
 5 from libsvm.python.svmutil import *
 6 from libsvm.python.svm import *
 7
 8
 9 address = 'D:\python\验证码-sort\\'
10 f = open('train.txt', 'w')
11
12 def get_feature(dir, file):
13     f.write(dir)
14     im = Image.open(address + dir +'\\' + file)
15     imarr = np.array(im)
16     height, width = imarr.shape
17     for i in range(height):
18         for j in range(width):
19             gray = imarr[i,j]
20             if gray <= 150:
21                 imarr[i, j] = 0
22             else:
23                 imarr[i, j] = 255
24     im = Image.fromarray(imarr)
25     count = 0
26     width, height = im.size
27     for i in range(height):
28         c = 0
29         for j in range(width):
30             if im.getpixel((j, i)) == 0: c += 1
31         f.write(' %d:%d'%(count, c))
32         count += 1
33     for i in range(width):
34         c = 0
35         for j in range(height):
36             if im.getpixel((i, j)) == 0: c += 1
37         f.write(' %d:%d'%(count, c))
38         count += 1
39     f.write('\n')
40
41 def train_svm_model():
42     y, x = svm_read_problem('train.txt')
43     model = svm_train(y, x)
44     svm_save_model('model_file', model)
45
46 if __name__ == '__main__':
47     dirs = os.listdir(address)
48     for dir in dirs:
49         files = os.listdir(address + dir)
50         for file in files:
51             get_feature(dir, file)
52     train_svm_model()

1 from libsvm.python.svmutil import *
2 from libsvm.python.svm import *
3 import image_slove
4
5 if __name__ == '__main__':
6     model = svm_load_model('model_file')
7     yt, xt = svm_read_problem('test.txt')
8     p_label, p_acc, p_val = svm_predict(yt, xt, model)