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:
#!/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
PS:这里再为大家提供2款非常方便的正则表达式工具供大家参考使用:
JavaScript正则表达式在线测试工具:
http://tools.jb51.net/regex/javascript
正则表达式在线生成工具:
http://tools.jb51.net/regex/create_reg
更多关于Python相关内容可查看本站专题:《Python正则表达式用法总结》、《Python数据结构与算法教程》、《Python函数使用技巧总结》、《Python字符串操作技巧汇总》、《Python入门与进阶经典教程》及《Python文件与目录操作技巧汇总》
希望本文所述对大家Python程序设计有所帮助。
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