本文实例讲述了Python实现破解12306图片验证码的方法。分享给大家供大家参考,具体如下:
不知从何时起,12306的登录验证码竟然变成了按字找图,可以说是又提高了一个等次,竟然把图像识别都用上了。不过有些图片,不得不说有些变态,图片的清晰图就更别说了,明显是从网络上的图库中搬过来的。
谁知没多久,网络就惊现破解12306图片验证码的Python代码了,作为一个爱玩爱刺激的网虫,当然要分享一份过来。
代码大致流程:
1、将验证码图片下载下来,然后切图;
2、利用百度识图进行图片分析;
3、再利用正则表达式来取出百度识图的关键字,最后输出。
代码:
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
|
#!/usr/bin/python
# # FileName : fuck12306.py
# # Author : MaoMao Wang <andelf@gmail.com>
# # Created : Mon Mar 16 22:08:41 2015 by ShuYu Wang
# # Copyright : Feather (c) 2015
# # Description : fuck fuck 12306
# # Time-stamp: <2015-03-17 10:57:44 andelf>
from PIL import Image
from PIL import ImageFilter
import urllib
import urllib2
import re
import json
# hack CERTIFICATE_VERIFY_FAILED
# https://github.com/mtschirs/quizduellapi/issues/2
import ssl
if hasattr (ssl, '_create_unverified_context' ):
ssl._create_default_https_context = ssl._create_unverified_context
UA = "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_2) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/41.0.2272.89 Safari/537.36"
pic_url = "https://kyfw.12306.cn/otn/passcodeNew/getPassCodeNew?module=login&rand=sjrand&0.21191171556711197"
def get_img():
resp = urllib.urlopen(pic_url)
raw = resp.read()
with open ( "./tmp.jpg" , 'wb' ) as fp:
fp.write(raw)
return Image. open ( "./tmp.jpg" )
def get_sub_img(im, x, y):
assert 0 < = x < = 3
assert 0 < = y < = 2
WITH = HEIGHT = 68
left = 5 + ( 67 + 5 ) * x
top = 41 + ( 67 + 5 ) * y
right = left + 67
bottom = top + 67
return im.crop((left, top, right, bottom))
def baidu_stu_lookup(im):
url = "http://stu.baidu.com/n/image?fr=html5&needRawImageUrl=true&id=WU_FILE_0&name=233.png&type=image%2Fpng&lastModifiedDate=Mon+Mar+16+2015+20%3A49%3A11+GMT%2B0800+(CST)&size="
im.save( "./query_temp_img.png" )
raw = open ( "./query_temp_img.png" , 'rb' ).read()
url = url + str ( len (raw))
req = urllib2.Request(url, raw, { 'Content-Type' : 'image/png' , 'User-Agent' :UA})
resp = urllib2.urlopen(req)
resp_url = resp.read() # return a pure url
url = "http://stu.baidu.com/n/searchpc?queryImageUrl=" + urllib.quote(resp_url)
req = urllib2.Request(url, headers = { 'User-Agent' :UA})
resp = urllib2.urlopen(req)
html = resp.read()
return baidu_stu_html_extract(html)
def baidu_stu_html_extract(html):
#pattern = re.compile(r'<script type="text/javascript">(.*?)</script>', re.DOTALL | re.MULTILINE)
pattern = re. compile (r "keywords:'(.*?)'" )
matches = pattern.findall(html)
if not matches:
return '[UNKNOWN]'
json_str = matches[ 0 ]
json_str = json_str.replace( '\\x22' , '"' ).replace( '\\\\', ' \\')
#print json_str
result = [item[ 'keyword' ] for item in json.loads(json_str)]
return '|' .join(result) if result else '[UNKNOWN]'
def ocr_question_extract(im):
# git@github.com:madmaze/pytesseract.git
global pytesseract
try :
import pytesseract
except :
print "[ERROR] pytesseract not installed"
return
im = im.crop(( 127 , 3 , 260 , 22 ))
im = pre_ocr_processing(im)
# im.show()
return pytesseract.image_to_string(im, lang = 'chi_sim' ).strip()
def pre_ocr_processing(im):
im = im.convert( "RGB" )
width, height = im.size
white = im. filter (ImageFilter.BLUR). filter (ImageFilter.MaxFilter( 23 ))
grey = im.convert( 'L' )
impix = im.load()
whitepix = white.load()
greypix = grey.load()
for y in range (height):
for x in range (width):
greypix[x,y] = min ( 255 , max ( 255 + impix[x,y][ 0 ] - whitepix[x,y][ 0 ],
255 + impix[x,y][ 1 ] - whitepix[x,y][ 1 ],
255 + impix[x,y][ 2 ] - whitepix[x,y][ 2 ]))
new_im = grey.copy()
binarize(new_im, 150 )
return new_im
def binarize(im, thresh = 120 ):
assert 0 < thresh < 255
assert im.mode = = 'L'
w, h = im.size
for y in xrange ( 0 , h):
for x in xrange ( 0 , w):
if im.getpixel((x,y)) < thresh:
im.putpixel((x,y), 0 )
else :
im.putpixel((x,y), 255 )
if __name__ = = '__main__' :
im = get_img()
#im = Image.open("./tmp.jpg")
print 'OCR Question:' , ocr_question_extract(im)
for y in range ( 2 ):
for x in range ( 4 ):
im2 = get_sub_img(im, x, y)
result = baidu_stu_lookup(im2)
print (y,x), result
|
希望本文所述对大家Python程序设计有所帮助。
原文链接:http://blog.csdn.net/wuxing26jiayou/article/details/78915864