python识别验证码的思路及解决方案
内容摘要
介绍，在爬虫中经常会遇到验证码识别的问题，现在的验证码大多分
文章正文
在本篇内容里小编给大家整理的是一篇关于python识别验证码的思路及解决方案，有需要的朋友们可以参考下。
1、介绍
在爬虫中经常会遇到验证码识别的问题，现在的验证码大多分计算验证码、滑块验证码、识图验证码、语音验证码等四种。本文就是识图验证码，识别的是简单的验证码，要想让识别率更高，识别的更加准确就需要花很多的精力去训练自己的字体库。
识别验证码通常是这几个步骤：
（1）灰度处理
（2）二值化
（3）去除边框（如果有的话）
（4）降噪
（5）切割字符或者倾斜度矫正
（6）训练字体库
（7）识别
这6个步骤中前三个步骤是基本的，4或者5可根据实际情况选择是否需要。
经常用的库有pytesseract(识别库)、OpenCV(高级图像处理库)、imagehash（图片哈希值库）、numpy（开源的、高性能的Python数值计算库）、PIL的 Image，ImageDraw，ImageFile等。博主的Python学习圈子点击即可进入一起交流学习，还有最新的Python资料可以免费下载
2、实例
以某网站登录的验证码识别为例：具体过程和上述的步骤稍有不同。
首先分析一下，验证码是由4个从0到9等10个数字组成的，那么从0到9这个10个数字没有数字只有第一、第二、第三和第四等4个位置。那么计算下来共有40个数字位置，如下：
那么接下来就要对验证码图片进行降噪、分隔得到上面的图片。以这40个图片集作为基础。
对要验证的验证码图片进行降噪、分隔后获取四个类似上面的数字图片、通过和上面的比对就可以知道该验证码是什么了。
以上面验证码2837为例：
1、图片降噪
2、图片分隔
3、图片比对
通过比验证码降噪、分隔后的四个数字图片，和上面的40个数字图片进行哈希值比对，设置一个误差，max_dif：允许最大hash差值，越小越精确，最小为0。
这样四个数字图片通过比较后获取对应是数字，连起来，就是要获取的验证码。
完整代码如下：
#coding=utf-8 import os import re from selenium import webdriver from selenium.webdriver.common.keys import Keys import time from selenium.webdriver.common.action_chains import ActionChains import collections import mongoDbBase import numpy import imagehash from PIL import Image,ImageFile import datetime class finalNews_IE: def __init__(self,strdate,logonUrl,firstUrl,keyword_list,exportPath,codepath,codedir): self.iniDriver() self.db = mongoDbBase.mongoDbBase() self.date = strdate self.firstUrl = firstUrl self.logonUrl = logonUrl self.keyword_list = keyword_list self.exportPath = exportPath self.codedir = codedir self.hash_code_dict ={} for f in range(0,10): for l in range(1,5): file = os.path.join(codedir, "codeLibrarycode" + str(f) + "_"+str(l) + ".png") # print(file) hash = self.get_ImageHash(file) self.hash_code_dict[hash]= str(f) def iniDriver(self): # 通过配置文件获取IEDriverServer.exe路径 IEDriverServer = "C:Program FilesInternet ExplorerIEDriverServer.exe" os.environ["webdriver.ie.driver"] = IEDriverServer self.driver = webdriver.Ie(IEDriverServer) def WriteData(self, message, fileName): fileName = os.path.join(os.getcwd(), self.exportPath + "/" + fileName) with open(fileName, "a") as f: f.write(message) # 获取图片文件的hash值 def get_ImageHash(self,imagefile): hash = None if os.path.exists(imagefile): with open(imagefile, "rb") as fp: hash = imagehash.average_hash(Image.open(fp)) return hash # 点降噪 def clearNoise(self, imageFile, x=0, y=0): if os.path.exists(imageFile): image = Image.open(imageFile) image = image.convert("L") image = numpy.asarray(image) image = (image > 135) * 255 image = Image.fromarray(image).convert("RGB") # save_name = "D:workpython36_crawlVeriycodemode_5590.png" # image.save(save_name) image.save(imageFile) return image #切割验证码 # rownum：切割行数；colnum：切割列数；dstpath：图片文件路径；img_name：要切割的图片文件 def splitimage(self, imagePath,imageFile,rownum=1, colnum=4): img = Image.open(imageFile) w, h = img.size if rownum <= h and colnum <= w: print("Original image info: %sx%s, %s, %s" % (w, h, img.format, img.mode)) print("开始处理图片切割, 请稍候...") s = os.path.split(imageFile) if imagePath == "": dstpath = s[0] fn = s[1].split(".") basename = fn[0] ext = fn[-1] num = 1 rowheight = h // rownum colwidth = w // colnum file_list =[] for r in range(rownum): index = 0 for c in range(colnum): # (left, upper, right, lower) # box = (c * colwidth, r * rowheight, (c + 1) * colwidth, (r + 1) * rowheight) if index < 1: colwid = colwidth + 6 elif index < 2: colwid = colwidth + 1 elif index < 3: colwid = colwidth box = (c * colwid, r * rowheight, (c + 1) * colwid, (r + 1) * rowheight) newfile = os.path.join(imagePath, basename + "_" + str(num) + "." + ext) file_list.append(newfile) img.crop(box).save(newfile, ext) num = num + 1 index += 1 return file_list def compare_image_with_hash(self, image_hash1,image_hash2, max_dif=0): """ max_dif: 允许最大hash差值, 越小越精确,最小为0 推荐使用 """ dif = image_hash1 - image_hash2 # print(dif) if dif < 0: dif = -dif if dif <= max_dif: return True else: return False # 截取验证码图片 def savePicture(self): self.driver.get(self.logonUrl) self.driver.maximize_window() time.sleep(1) self.driver.save_screenshot(self.codedir +"Temp.png") checkcode = self.driver.find_element_by_id("checkcode") location = checkcode.location # 获取验证码x,y轴坐标 size = checkcode.size # 获取验证码的长宽 rangle = (int(location["x"]), int(location["y"]), int(location["x"] + size["width"]), int(location["y"] + size["height"])) # 写成我们需要截取的位置坐标 i = Image.open(self.codedir +"Temp.png") # 打开截图 result = i.crop(rangle) # 使用Image的crop函数，从截图中再次截取我们需要的区域 filename = datetime.datetime.now().strftime("%M%S") filename =self.codedir +"Temp_code.png" result.save(filename) self.clearNoise(filename) file_list = self.splitimage(self.codedir,filename) verycode ="" for f in file_list: imageHash = self.get_ImageHash(f) for h,code in self.hash_code_dict.items(): flag = self.compare_image_with_hash(imageHash,h,0) if flag: # print(code) verycode+=code break print(verycode) self.driver.close() def longon(self): self.driver.get(self.logonUrl) self.driver.maximize_window() time.sleep(1) self.savePicture() accname = self.driver.find_element_by_id("username") # accname = self.driver.find_element_by_id("//input[@id="username"]") accname.send_keys("ctrchina") accpwd = self.driver.find_element_by_id("password") # accpwd.send_keys("123456") code = self.getVerycode() checkcode = self.driver.find_element_by_name("checkcode") checkcode.send_keys(code) submit = self.driver.find_element_by_name("button") submit.click()
实例补充：
# -*- coding: utf-8 -* import sys reload(sys) sys.setdefaultencoding( "utf-8" ) import re import requests import io import os import json from PIL import Image from PIL import ImageEnhance from bs4 import BeautifulSoup import mdata class Student: def __init__(self, user,password): self.user = str(user) self.password = str(password) self.s = requests.Session() def login(self): url = "http://202.118.31.197/ACTIONLOGON.APPPROCESS?mode=4" res = self.s.get(url).text imageUrl = "http://202.118.31.197/"+re.findall("<img src="(.+?)" width="55"",res)[0] im = Image.open(io.BytesIO(self.s.get(imageUrl).content)) enhancer = ImageEnhance.Contrast(im) im = enhancer.enhance(7) x,y = im.size for i in range(y): for j in range(x): if (im.getpixel((j,i))!=(0,0,0)): im.putpixel((j,i),(255,255,255)) num = [6,19,32,45] verifyCode = "" for i in range(4): a = im.crop((num[i],0,num[i]+13,20)) l=[] x,y = a.size for i in range(y): for j in range(x): if (a.getpixel((j,i))==(0,0,0)): l.append(1) else: l.append(0) his=0 chrr=""; for i in mdata.data: r=0; for j in range(260): if(l[j]==mdata.data[i][j]): r+=1 if(r>his): his=r chrr=i verifyCode+=chrr # print "辅助输入验证码完毕:",verifyCode data= { "WebUserNO":str(self.user), "Password":str(self.password), "Agnomen":verifyCode, } url = "http://202.118.31.197/ACTIONLOGON.APPPROCESS?mode=4" t = self.s.post(url,data=data).text if re.findall("images/Logout2",t)==[]: l = "[0,""+re.findall("alert((.+?));",t)[1][1][2:-2]+""]"+" "+self.user+" "+self.password+" " # print l # return "[0,""+re.findall("alert((.+?));",t)[1][1][2:-2]+""]" return [False,l] else: l = "登录成功 "+re.findall("! (.+?) ",t)[0]+" "+self.user+" "+self.password+" " # print l return [True,l] def getInfo(self): imageUrl = "http://202.118.31.197/ACTIONDSPUSERPHOTO.APPPROCESS" data = self.s.get("http://202.118.31.197/ACTIONQUERYBASESTUDENTINFO.APPPROCESS?mode＝3").text #学籍信息 data = BeautifulSoup(data,"lxml") q = data.find_all("table",attrs={"align":"left"}) a = [] for i in q[0]: if type(i)==type(q[0]) : for j in i : if type(j) ==type(i): a.append(j.text) for i in q[1]: if type(i)==type(q[1]) : for j in i : if type(j) ==type(i): a.append(j.text) data = {} for i in range(1,len(a),2): data[a[i-1]]=a[i] # data["照片"] = io.BytesIO(self.s.get(imageUrl).content) return json.dumps(data) def getPic(self): imageUrl = "http://202.118.31.197/ACTIONDSPUSERPHOTO.APPPROCESS" pic = Image.open(io.BytesIO(self.s.get(imageUrl).content)) return pic def getScore(self): score = self.s.get("http://202.118.31.197/ACTIONQUERYSTUDENTSCORE.APPPROCESS").text #成绩单 score = BeautifulSoup(score, "lxml") q = score.find_all(attrs={"height":"36"})[0] point = q.text print point[point.find("平均学分绩点"):] table = score.html.body.table people = table.find_all(attrs={"height" : "36"})[0].string r = table.find_all("table",attrs={"align" : "left"})[0].find_all("tr") subject = [] lesson = [] for i in r[0]: if type(r[0])==type(i): subject.append(i.string) for i in r: k=0 temp = {} for j in i: if type(r[0])==type(j): temp[subject[k]] = j.string k+=1 lesson.append(temp) lesson.pop() lesson.pop(0) return json.dumps(lesson) def logoff(self): return self.s.get("http://202.118.31.197/ACTIONLOGOUT.APPPROCESS").text if __name__ == "__main__": a = Student(20150000,20150000) r = a.login() print r[1] if r[0]: r = json.loads(a.getScore()) for i in r: for j in i: print i[j], print q = json.loads(a.getInfo()) for i in q: print i,q[i] a.getPic().show() a.logoff()
到此这篇关于python识别验证码的思路及解决方案的文章就介绍到这了
代码注释
[!--zhushi--]
作者：喵哥笔记
