Python爬虫selenium验证-中文识别点选+图片验证码案例

1.获取图片

python 复制代码
import re
import time
import ddddocr
import requests
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.chrome.service import Service
from selenium.webdriver.support.wait import WebDriverWait
from selenium.webdriver import ActionChains

service = Service("driver/chromedriver.exe")
driver = webdriver.Chrome(service=service)

# 1.打开首页
driver.get('https://www.geetest.com/adaptive-captcha-demo')

# 2.点击【文字点选验证】
tag = WebDriverWait(driver, 30, 0.5).until(lambda dv: dv.find_element(
    By.XPATH,
    '//*[@id="gt-showZh-mobile"]/div/section/div/div[2]/div[1]/div[2]/div[3]/div[4]'
))
tag.click()

# 3.点击开始验证
tag = WebDriverWait(driver, 30, 0.5).until(lambda dv: dv.find_element(
    By.CLASS_NAME,
    'geetest_btn_click'
))
tag.click()

time.sleep(5)

# 要识别的目标图片
target_tag = driver.find_element(
    By.CLASS_NAME,
    'geetest_ques_back'
)
target_tag.screenshot("target.png")

# 识别图片
bg_tag = driver.find_element(
    By.CLASS_NAME,
    'geetest_bg'
)
bg_tag.screenshot("bg.png")

time.sleep(2000)
driver.close()

2.目标识别

截图每个字符,并基于ddddocr识别。

python 复制代码
import re
import time
import ddddocr
import requests
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.chrome.service import Service
from selenium.webdriver.support.wait import WebDriverWait
from selenium.webdriver import ActionChains

service = Service("driver/chromedriver.exe")
driver = webdriver.Chrome(service=service)

# 1.打开首页
driver.get('https://www.geetest.com/adaptive-captcha-demo')

# 2.点击【滑动拼图验证】
tag = WebDriverWait(driver, 30, 0.5).until(lambda dv: dv.find_element(
    By.XPATH,
    '//*[@id="gt-showZh-mobile"]/div/section/div/div[2]/div[1]/div[2]/div[3]/div[4]'
))
tag.click()

# 3.点击开始验证
tag = WebDriverWait(driver, 30, 0.5).until(lambda dv: dv.find_element(
    By.CLASS_NAME,
    'geetest_btn_click'
))
tag.click()

# 4.等待验证码出来
time.sleep(5)

# 5.识别任务图片
target_word_list = []
parent = driver.find_element(By.CLASS_NAME, 'geetest_ques_back')
tag_list = parent.find_elements(By.TAG_NAME, "img")

for tag in tag_list:
    ocr = ddddocr.DdddOcr(show_ad=False)
    word = ocr.classification(tag.screenshot_as_png)
    target_word_list.append(word)

print("要识别的文字:", target_word_list)

time.sleep(2000)
driver.close()

3.背景坐标识别

3.1 ddddocr

能识别,但是发现默认识别率有点低,想要提升识别率,可以搭建Pytorch环境对模型进行训练,参考:https://github.com/sml2h3/dddd_trainer

python 复制代码
import re
import time
import ddddocr
import requests
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.chrome.service import Service
from selenium.webdriver.support.wait import WebDriverWait
from selenium.webdriver import ActionChains
from PIL import Image, ImageDraw
from io import BytesIO

service = Service("driver/chromedriver.exe")
driver = webdriver.Chrome(service=service)

# 1.打开首页
driver.get('https://www.geetest.com/adaptive-captcha-demo')

# 2.点击【滑动拼图验证】
tag = WebDriverWait(driver, 30, 0.5).until(lambda dv: dv.find_element(
    By.XPATH,
    '//*[@id="gt-showZh-mobile"]/div/section/div/div[2]/div[1]/div[2]/div[3]/div[4]'
))
tag.click()

# 3.点击开始验证
tag = WebDriverWait(driver, 30, 0.5).until(lambda dv: dv.find_element(
    By.CLASS_NAME,
    'geetest_btn_click'
))
tag.click()

# 4.等待验证码出来
time.sleep(5)

# 5.识别任务图片
target_word_list = []
parent = driver.find_element(By.CLASS_NAME, 'geetest_ques_back')
tag_list = parent.find_elements(By.TAG_NAME, "img")
for tag in tag_list:
    ocr = ddddocr.DdddOcr(show_ad=False)
    word = ocr.classification(tag.screenshot_as_png)
    target_word_list.append(word)

print("要识别的文字:", target_word_list)

# 6.背景图片
bg_tag = driver.find_element(
    By.CLASS_NAME,
    'geetest_bg'
)
content = bg_tag.screenshot_as_png

# 7.识别背景中的所有文字并获取坐标
ocr = ddddocr.DdddOcr(show_ad=False, det=True)
poses = ocr.detection(content) # [(x1, y1, x2, y2), (x1, y1, x2, y2), x1, y1, x2, y2]

# 8.循环坐标中的每个文字并识别
bg_word_dict = {}
img = Image.open(BytesIO(content))

for box in poses:
    x1, y1, x2, y2 = box
    # 根据坐标获取每个文字的图片
    corp = img.crop(box)
    img_byte = BytesIO()
    corp.save(img_byte, 'png')
    # 识别文字
    ocr2 = ddddocr.DdddOcr(show_ad=False)
    word = ocr2.classification(img_byte.getvalue())  # 识别率低

    # 获取每个字的坐标  {"鸭":}
    bg_word_dict[word] = [int((x1 + x2) / 2), int((y1 + y2) / 2)]

print(bg_word_dict)

time.sleep(1000)
driver.close()

3.2 打码平台

https://www.chaojiying.com/

python 复制代码
import base64
import requests
from hashlib import md5

file_bytes = open('5.jpg', 'rb').read()

res = requests.post(
    url='http://upload.chaojiying.net/Upload/Processing.php',
    data={
        'user': "deng",
        'pass2': md5("密码".encode('utf-8')).hexdigest(),
        'codetype': "9501",
        'file_base64': base64.b64encode(file_bytes)
    },
    headers={
        'Connection': 'Keep-Alive',
        'User-Agent': 'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 5.1; Trident/4.0)',
    }
)

res_dict = res.json()
print(res_dict)
# {'err_no': 0, 'err_str': 'OK', 'pic_id': '1234612060701120002', 'pic_str': '的,86,73|粉,111,38|菜,40,49|香,198,101', 'md5': 'faac71fc832b2ead01ffb4e813f3be60'}

结合极验案例截图+识别:

python 复制代码
import re
import time
import ddddocr
import requests
import base64
import requests
from hashlib import md5
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.chrome.service import Service
from selenium.webdriver.support.wait import WebDriverWait
from selenium.webdriver import ActionChains
from PIL import Image, ImageDraw
from io import BytesIO

service = Service("driver/chromedriver.exe")
driver = webdriver.Chrome(service=service)

# 1.打开首页
driver.get('https://www.geetest.com/adaptive-captcha-demo')

# 2.点击【滑动拼图验证】
tag = WebDriverWait(driver, 30, 0.5).until(lambda dv: dv.find_element(
    By.XPATH,
    '//*[@id="gt-showZh-mobile"]/div/section/div/div[2]/div[1]/div[2]/div[3]/div[4]'
))
tag.click()

# 3.点击开始验证
tag = WebDriverWait(driver, 30, 0.5).until(lambda dv: dv.find_element(
    By.CLASS_NAME,
    'geetest_btn_click'
))
tag.click()

# 4.等待验证码出来
time.sleep(5)

# 5.识别任务图片
target_word_list = []
parent = driver.find_element(By.CLASS_NAME, 'geetest_ques_back')
tag_list = parent.find_elements(By.TAG_NAME, "img")
for tag in tag_list:
    ocr = ddddocr.DdddOcr(show_ad=False)
    word = ocr.classification(tag.screenshot_as_png)
    target_word_list.append(word)

print("要识别的文字:", target_word_list)

# 6.背景图片
bg_tag = driver.find_element(
    By.CLASS_NAME,
    'geetest_bg'
)
content = bg_tag.screenshot_as_png
bg_tag.screenshot("bg.png")

# 7.识别背景中的所有文字并获取坐标
res = requests.post(
    url='http://upload.chaojiying.net/Upload/Processing.php',
    data={
        'user': "deng",
        'pass2': md5("密码".encode('utf-8')).hexdigest(),
        'codetype': "9501",
        'file_base64': base64.b64encode(content)
    },
    headers={
        'Connection': 'Keep-Alive',
        'User-Agent': 'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 5.1; Trident/4.0)',
    }
)

res_dict = res.json()
print(res_dict)

# 8.每个字的坐标  {"鸭":(196,85), ...}    target_word_list = ["花","鸭","字"]
bg_word_dict = {}
for item in res_dict["pic_str"].split("|"):
    word, x, y = item.split(",")
    bg_word_dict[word] = (x, y)
    
print(bg_word_dict)

time.sleep(1000)
driver.close()

4.坐标点击

根据坐标,在验证码上进行点击。

python 复制代码
ActionChains(driver).move_to_element_with_offset(标签对象, xoffset=x, yoffset=y).click().perform()
python 复制代码
import re
import time
import ddddocr
import requests
import base64
import requests
from hashlib import md5
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.chrome.service import Service
from selenium.webdriver.support.wait import WebDriverWait
from selenium.webdriver import ActionChains
from PIL import Image, ImageDraw
from io import BytesIO

service = Service("driver/chromedriver.exe")
driver = webdriver.Chrome(service=service)

# 1.打开首页
driver.get('https://www.geetest.com/adaptive-captcha-demo')

# 2.点击【滑动拼图验证】
tag = WebDriverWait(driver, 30, 0.5).until(lambda dv: dv.find_element(
    By.XPATH,
    '//*[@id="gt-showZh-mobile"]/div/section/div/div[2]/div[1]/div[2]/div[3]/div[4]'
))
tag.click()

# 3.点击开始验证
tag = WebDriverWait(driver, 30, 0.5).until(lambda dv: dv.find_element(
    By.CLASS_NAME,
    'geetest_btn_click'
))
tag.click()

# 4.等待验证码出来
time.sleep(5)

# 5.识别任务图片
target_word_list = []
parent = driver.find_element(By.CLASS_NAME, 'geetest_ques_back')
tag_list = parent.find_elements(By.TAG_NAME, "img")
for tag in tag_list:
    ocr = ddddocr.DdddOcr(show_ad=False)
    word = ocr.classification(tag.screenshot_as_png)
    target_word_list.append(word)

print("要识别的文字:", target_word_list)

# 6.背景图片
bg_tag = driver.find_element(
    By.CLASS_NAME,
    'geetest_bg'
)
content = bg_tag.screenshot_as_png

# bg_tag.screenshot("bg.png")

# 7.识别背景中的所有文字并获取坐标
res = requests.post(
    url='http://upload.chaojiying.net/Upload/Processing.php',
    data={
        'user': "deng",
        'pass2': md5("自己密码".encode('utf-8')).hexdigest(),
        'codetype': "9501",
        'file_base64': base64.b64encode(content)
    },
    headers={
        'Connection': 'Keep-Alive',
        'User-Agent': 'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 5.1; Trident/4.0)',
    }
)

res_dict = res.json()

bg_word_dict = {}
for item in res_dict["pic_str"].split("|"):
    word, x, y = item.split(",")
    bg_word_dict[word] = (x, y)

print(bg_word_dict)
# target_word_list = ['粉', '菜', '香']
# bg_word_dict = {'粉': ('10', '10'), '菜': ('50', '50'), '香': ('100', '93')}
# 8.点击
for word in target_word_list:
    time.sleep(2)
    group = bg_word_dict.get(word)
    if not group:
        continue
    x, y = group
    x = int(x) - int(bg_tag.size['width'] / 2)
    y = int(y) - int(bg_tag.size['height'] / 2)
    ActionChains(driver).move_to_element_with_offset(bg_tag, xoffset=x, yoffset=y).click().perform()

time.sleep(1000)
driver.close()

5.图片验证码

在很多登录、注册、频繁操作等行为时,一般都会加入验证码的功能。

如果想要基于代码实现某些功能,就必须实现:自动识别验证码,然后再做其他功能。

6.识别

基于Python的模块 ddddocr 可以实现对图片验证码的识别。

复制代码
pip3.11 install ddddocr==1.4.9  -i https://mirrors.aliyun.com/pypi/simple/
pip3.11 install Pillow==9.5.0

pip install ddddocr==1.4.9  -i https://mirrors.aliyun.com/pypi/simple/
pip install Pillow==9.5.0

6.1 本地识别

python 复制代码
import ddddocr

ocr = ddddocr.DdddOcr(show_ad=False)
with open("img/v1.jpg", mode='rb') as f:
    body = f.read()
code = ocr.classification(body)
print(code)

6.2 在线识别

也可以直接请求获取图片,然后直接识别:

python 复制代码
import ddddocr
import requests

res = requests.get(url="https://console.zbox.filez.com/captcha/create/reg?_t=1701511836608")

ocr = ddddocr.DdddOcr(show_ad=False)
code = ocr.classification(res.content)
print(code)
python 复制代码
import ddddocr
import requests


res = requests.get(
    url=f"https://api.ruanwen.la/api/auth/captcha?captcha_token=n5A6VXIsMiI4MTKoco0VigkZbByJbDahhRHGNJmS"
)

ocr = ddddocr.DdddOcr(show_ad=False)
code = ocr.classification(res.content)
print(code)

6.3 base64

有些平台的图片是以base64编码形式存在,需要处理下在识别。

python 复制代码
import base64
import ddddocr

content = base64.b64decode("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")

# with open('x.png', mode='wb') as f:
#     f.write(content)

ocr = ddddocr.DdddOcr(show_ad=False)
code = ocr.classification(content)
print(code)

7.案例:x文街

https://i.ruanwen.la/

python 复制代码
import requests
import ddddocr

# 获得图片验证码地址
res = requests.post(url="https://api.ruanwen.la/api/auth/captcha/generate")
res_dict = res.json()

captcha_token = res_dict['data']['captcha_token']
captcha_url = res_dict['data']['src']

# 访问并获取图片验证码
res = requests.get(captcha_url)

# 识别验证码
ocr = ddddocr.DdddOcr(show_ad=False)
code = ocr.classification(res.content)
print(code)

# 登录认证
res = requests.post(
    url="https://api.ruanwen.la/api/auth/authenticate",
    json={
        "mobile": "手机号",
        "device": "pc",
        "password": "密码",
        "captcha_token": captcha_token,
        "captcha": code,
        "identity": "advertiser"
    }
)

print(res.json())
# {'success': True, 'message': '验证成功', 'data': {'token': 'eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpc3MiOiJodHRwczovL2FwaS5ydWFud2VuLmxhL2FwaS9hdXRoL2F1dGhlbnRpY2F0ZSIsImlhdCI6MTcwMTY1MzI2NywiZXhwIjoxNzA1MjUzMjY3LCJuYmYiOjE3MDE2NTMyNjcsImp0aSI6IjQ3bk05ejZyQ0JLV28wOEQiLCJzdWIiOjUzMzEyNTgsInBydiI6IjQxZGY4ODM0ZjFiOThmNzBlZmE2MGFhZWRlZjQyMzQxMzcwMDY5MGMifQ.XxFYMEot-DfjTUcuVuoCjcBqu3djvzJiTeJERaR95co'}, 'status': 200}
相关推荐
孟健11 小时前
Karpathy 用 200 行纯 Python 从零实现 GPT:代码逐行解析
python
码路飞13 小时前
写了个 AI 聊天页面,被 5 种流式格式折腾了一整天 😭
javascript·python
曲幽16 小时前
FastAPI压力测试实战:Locust模拟真实用户并发及优化建议
python·fastapi·web·locust·asyncio·test·uvicorn·workers
敏编程20 小时前
一天一个Python库:jsonschema - JSON 数据验证利器
python
前端付豪20 小时前
LangChain记忆:通过Memory记住上次的对话细节
人工智能·python·langchain
databook20 小时前
ManimCE v0.20.1 发布:LaTeX 渲染修复与动画稳定性提升
python·动效
花酒锄作田1 天前
使用 pkgutil 实现动态插件系统
python
前端付豪2 天前
LangChain链 写一篇完美推文?用SequencialChain链接不同的组件
人工智能·python·langchain
曲幽2 天前
FastAPI实战:打造本地文生图接口,ollama+diffusers让AI绘画更听话
python·fastapi·web·cors·diffusers·lcm·ollama·dreamshaper8·txt2img
老赵全栈实战2 天前
Pydantic配置管理最佳实践(一)
python