1、效果演示
2、如何识别
2.1准备数据集
首先需要使用爬虫,对验证码图片进行采集,尽量每一种类型都要采集到。
2.2图像矫正
接下来对采集的数据进行人工校正
2.3数据清洗
(1)对数据进行进行旋转,达到增加数据量的目的。
(2)对数据进行灰度化处理,将三维图片降为二维。
(3)对图片大小进行resize,可以提高训练速度。
# 图片转换部分,得到x
picture = Picture(path=img_path)
# 图像灰度化处理
temp_img = picture.gray()
# 图像resize
temp_img = temp_img.resize((50, 50), Image.LANCZOS)
# 获取y
word = img_path.split('\\')[-1].split('-')[0]# 结果包装成列表,保证x,y是一个整体,不被打乱
res = [np.array(temp_img),np.array(word)]
# 将结构给全局变量
result_list.append(res)
# 记录完成数量
complete_list.append(img_path)
2.4划分训练集与测试集
一般训练集占数据量的80%,测试集占总数据量的20%,当然也可以根据自己的情况调整比例。
2.5训练模型
这里可以使用CNN神经网络模型进行训练,效果非常不错。
2.6实战测试
下面直接上代码。其中的滑动系数可能需要自行调整,这个变动不会太频繁,可能几个月某度变一次。
__author__ = "detayun"import os
import sys
import time
import base64
import requests
from PIL import Image
from io import BytesIO
sys.path.append(os.path.abspath(os.path.dirname(os.path.abspath(os.path.dirname(__file__)))))
from selenium import webdriver
from selenium.webdriver.support.wait import WebDriverWait
from selenium.webdriver import ActionChains#PIL图片保存为base64编码
def PIL_base64(img, coding='utf-8'):img_format = img.formatif img_format == None:img_format = 'JPEG'format_str = 'JPEG'if 'png' == img_format.lower():format_str = 'PNG'if 'gif' == img_format.lower():format_str = 'gif'if img.mode == "P":img = img.convert('RGB')if img.mode == "RGBA":format_str = 'PNG'img_format = 'PNG'output_buffer = BytesIO()# img.save(output_buffer, format=format_str)img.save(output_buffer, quality=100, format=format_str)byte_data = output_buffer.getvalue()base64_str = 'data:image/' + img_format.lower() + ';base64,' + base64.b64encode(byte_data).decode(coding)return base64_str# 根据链接下载旋转图片
def get_img(url):header = {"Host": "passport.baidu.com","User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:93.0) Gecko/20100101 Firefox/93.0","Accept": "image/avif,image/webp,*/*","Accept-Language": "zh-CN,zh;q=0.8,zh-TW;q=0.7,zh-HK;q=0.5,en-US;q=0.3,en;q=0.2","Accept-Encoding": "gzip, deflate, br","Referer": "https://wappass.baidu.com/","Connection": "keep-alive","Cookie": 'Hm_lvt_3eecc7feff77952670b7c24e952e8773=1666849322,1666919008,1666961940,1667175865; Hm_lpvt_3eecc7feff77952670b7c24e952e8773=1667186488; token="MTY2NzE4NzczNS4yMTEzMjg1OmQwNDNhNmZiZTA4MjlmOGY1YjE0MjA0NmViN2M1NTdkM2MyYWY3NzE="; sessionid=aa6zibdmfbs5cwzh6x62niw7fbqe5pon',"Sec-Fetch-Dest": "image","Sec-Fetch-Mode": "no-cors","Sec-Fetch-Site": "same-site","Pragma": "no-cache","Cache-Control": "no-cache",}response = requests.get(url=url,headers=header)if response.status_code == 200:img = Image.open(BytesIO(response.content))# 将图片转换成base64字符串并返回return PIL_base64(img)# 识别
def shibie(base64_img):url = "http://www.detayun.cn/tool/verify_code_identify/"header = {"Host": "www.detayun.cn","User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:101.0) Gecko/20100101 Firefox/101.0","Accept": "application/json, text/javascript, */*; q=0.01","Accept-Language": "zh-CN,zh;q=0.8,zh-TW;q=0.7,zh-HK;q=0.5,en-US;q=0.3,en;q=0.2","Referer": "http://www.detayun.cn/tool/verifyCodeIdentifyPage/?verify_idf_id=9","Content-Type": "application/x-www-form-urlencoded; charset=UTF-8","X-Requested-With": "XMLHttpRequest","Content-Length": "134652","Origin": "http://www.detayun.cn","Connection": "keep-alive","Cookie": 'Hm_lvt_3eecc7feff77952670b7c24e952e8773=1688628385,1688694584,1688743439,1688889515; _ga_CD35DZJ728=GS1.1.1677340409.5.1.1677340416.0.0.0; _ga=GA1.1.1572230966.1677226494; token="MTY4ODg5MzEwOC42MTI2NDk3OjY0ZTk0YWI1NTg3MWFmMDhkOTg3ZmIxZGQxMGIwYzIwZjBlNTRhODE="; sessionid=m8k9lxbpc3pzx2nbuylrj9llft7yqir6; Hm_lpvt_3eecc7feff77952670b7c24e952e8773=1688889515',"Pragma": "no-cache","Cache-Control": "no-cache",}data = {'verify_idf_id':'16','img_base64':base64_img,'words':'',}response = requests.post(url=url,headers=header,data=data)if response.json()['code'] == 401:print('请登录识别账号,更新代码中的Cookie。登录地址:http://www.detayun.cn/account/loginPage/')returnreturn int(str(response.json()['data']['res_str']).replace('顺时针旋转','').replace('度',''))if __name__ == '__main__':options = webdriver.ChromeOptions()driver = webdriver.Chrome(executable_path='.\webdriver\chromedriver.exe', options=options)# 访问百度首页driver.get('https://wappass.baidu.com/static/captcha/tuxing.html?&ak=c27bbc89afca0463650ac9bde68ebe06&backurl=https%3A%2F%2Fwww.baidu.com%2Fs%3Fcl%3D3%26tn%3Dbaidutop10%26fr%3Dtop1000%26wd%3D%25E6%25B6%2588%25E9%2598%25B2%25E6%2588%2598%25E5%25A3%25AB%25E8%25BF%259E%25E5%25A4%259C%25E7%25AD%2591%25E5%259D%259D%25E5%25BA%2594%25E5%25AF%25B9%25E6%25B4%25AA%25E5%25B3%25B0%25E8%25BF%2587%25E5%25A2%2583%26rsv_idx%3D2%26rsv_dl%3Dfyb_n_homepage%26hisfilter%3D1&logid=8309940529500911554&signature=4bce59041938b160b7c24423bde0b518×tamp=1624535702')# 等待滑块出现WebDriverWait(driver, 10).until(lambda x: x.find_element_by_xpath('//div[@class="passMod_slide-btn "]'))yzm_button = driver.find_element_by_xpath('//div[@class="passMod_slide-btn "]')time.sleep(1)move_x = 100# 等待验证码出现WebDriverWait(driver, 10).until(lambda x: x.find_element_by_xpath('//img[@class="passMod_spin-background"]'))img_src = driver.find_element_by_xpath('//img[@class="passMod_spin-background"]').get_attribute('src')# 下载图片并转化为base64img_base64 = get_img(img_src)# 识别图片旋转角度move_x = shibie(img_base64)# 通过旋转角度 * 滑动系数 = 滑动距离move_x = move_x * 0.66# 开始滑动action = ActionChains(driver)action.click_and_hold(yzm_button).perform() # 鼠标左键按下不放action.move_by_offset(move_x, 0).perform()action.release().perform() # 释放鼠标time.sleep(2)# 第二次滑动# 等待滑块出现WebDriverWait(driver, 10).until(lambda x: x.find_element_by_xpath('//div[@class="passMod_slide-btn "]'))yzm_button = driver.find_element_by_xpath('//div[@class="passMod_slide-btn "]')time.sleep(1)move_x = 100# 等待验证码出现WebDriverWait(driver, 10).until(lambda x: x.find_element_by_xpath('//img[@class="passMod_spin-background"]'))img_src = driver.find_element_by_xpath('//img[@class="passMod_spin-background"]').get_attribute('src')# 下载图片并转化为base64img_base64 = get_img(img_src)# 识别图片旋转角度move_x = shibie(img_base64)# 通过旋转角度 * 滑动系数 = 滑动距离move_x = move_x * 0.66# 开始滑动action = ActionChains(driver)action.click_and_hold(yzm_button).perform() # 鼠标左键按下不放action.move_by_offset(move_x, 0).perform()action.release().perform() # 释放鼠标