Python爬蟲selenium驗證之中文識別點選+圖片驗證碼案例(最新推薦)

更新時間：2025年02月25日 11:47:03 作者：dme.

本文介紹了如何使用Python和Selenium結(jié)合ddddocr庫實現(xiàn)圖片驗證碼的識別和點擊功能,感興趣的朋友一起看看吧

1.獲取圖片

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.打開首頁
driver.get('https://www.geetest.com/adaptive-captcha-demo')
# 2.點擊【文字點選驗證】
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.點擊開始驗證
tag = WebDriverWait(driver, 30, 0.5).until(lambda dv: dv.find_element(
    By.CLASS_NAME,
    'geetest_btn_click'
))
tag.click()
time.sleep(5)
# 要識別的目標(biāo)圖片
target_tag = driver.find_element(
    By.CLASS_NAME,
    'geetest_ques_back'
)
target_tag.screenshot("target.png")
# 識別圖片
bg_tag = driver.find_element(
    By.CLASS_NAME,
    'geetest_bg'
)
bg_tag.screenshot("bg.png")
time.sleep(2000)
driver.close()

2.目標(biāo)識別

截圖每個字符，并基于ddddocr識別。

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.打開首頁
driver.get('https://www.geetest.com/adaptive-captcha-demo')
# 2.點擊【滑動拼圖驗證】
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.點擊開始驗證
tag = WebDriverWait(driver, 30, 0.5).until(lambda dv: dv.find_element(
    By.CLASS_NAME,
    'geetest_btn_click'
))
tag.click()
# 4.等待驗證碼出來
time.sleep(5)
# 5.識別任務(wù)圖片
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("要識別的文字：", target_word_list)
time.sleep(2000)
driver.close()

3.背景坐標(biāo)識別

3.1 ddddocr

能識別，但是發(fā)現(xiàn)默認識別率有點低，想要提升識別率，可以搭建Pytorch環(huán)境對模型進行訓(xùn)練，參考：https://github.com/sml2h3/dddd_trainer

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.打開首頁
driver.get('https://www.geetest.com/adaptive-captcha-demo')
# 2.點擊【滑動拼圖驗證】
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.點擊開始驗證
tag = WebDriverWait(driver, 30, 0.5).until(lambda dv: dv.find_element(
    By.CLASS_NAME,
    'geetest_btn_click'
))
tag.click()
# 4.等待驗證碼出來
time.sleep(5)
# 5.識別任務(wù)圖片
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("要識別的文字：", target_word_list)
# 6.背景圖片
bg_tag = driver.find_element(
    By.CLASS_NAME,
    'geetest_bg'
)
content = bg_tag.screenshot_as_png
# 7.識別背景中的所有文字并獲取坐標(biāo)
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.循環(huán)坐標(biāo)中的每個文字并識別
bg_word_dict = {}
img = Image.open(BytesIO(content))
for box in poses:
    x1, y1, x2, y2 = box
    # 根據(jù)坐標(biāo)獲取每個文字的圖片
    corp = img.crop(box)
    img_byte = BytesIO()
    corp.save(img_byte, 'png')
    # 識別文字
    ocr2 = ddddocr.DdddOcr(show_ad=False)
    word = ocr2.classification(img_byte.getvalue())  # 識別率低
    # 獲取每個字的坐標(biāo)  {"鴨":}
    bg_word_dict[word] = [int((x1 + x2) / 2), int((y1 + y2) / 2)]
print(bg_word_dict)
time.sleep(1000)
driver.close()

3.2 打碼平臺

https://www.chaojiying.com/

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("密碼".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'}

結(jié)合極驗案例截圖+識別：

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.打開首頁
driver.get('https://www.geetest.com/adaptive-captcha-demo')
# 2.點擊【滑動拼圖驗證】
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.點擊開始驗證
tag = WebDriverWait(driver, 30, 0.5).until(lambda dv: dv.find_element(
    By.CLASS_NAME,
    'geetest_btn_click'
))
tag.click()
# 4.等待驗證碼出來
time.sleep(5)
# 5.識別任務(wù)圖片
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("要識別的文字：", target_word_list)
# 6.背景圖片
bg_tag = driver.find_element(
    By.CLASS_NAME,
    'geetest_bg'
)
content = bg_tag.screenshot_as_png
bg_tag.screenshot("bg.png")
# 7.識別背景中的所有文字并獲取坐標(biāo)
res = requests.post(
    url='http://upload.chaojiying.net/Upload/Processing.php',
    data={
        'user': "deng",
        'pass2': md5("密碼".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.每個字的坐標(biāo)  {"鴨":(196,85), ...}    target_word_list = ["花","鴨","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.坐標(biāo)點擊

根據(jù)坐標(biāo)，在驗證碼上進行點擊。

ActionChains(driver).move_to_element_with_offset(標(biāo)簽對象, xoffset=x, yoffset=y).click().perform()

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.打開首頁
driver.get('https://www.geetest.com/adaptive-captcha-demo')
# 2.點擊【滑動拼圖驗證】
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.點擊開始驗證
tag = WebDriverWait(driver, 30, 0.5).until(lambda dv: dv.find_element(
    By.CLASS_NAME,
    'geetest_btn_click'
))
tag.click()
# 4.等待驗證碼出來
time.sleep(5)
# 5.識別任務(wù)圖片
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("要識別的文字：", target_word_list)
# 6.背景圖片
bg_tag = driver.find_element(
    By.CLASS_NAME,
    'geetest_bg'
)
content = bg_tag.screenshot_as_png
# bg_tag.screenshot("bg.png")
# 7.識別背景中的所有文字并獲取坐標(biāo)
res = requests.post(
    url='http://upload.chaojiying.net/Upload/Processing.php',
    data={
        'user': "deng",
        'pass2': md5("自己密碼".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.點擊
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.圖片驗證碼

在很多登錄、注冊、頻繁操作等行為時，一般都會加入驗證碼的功能。

如果想要基于代碼實現(xiàn)某些功能，就必須實現(xiàn)：自動識別驗證碼，然后再做其他功能。

6.識別

基于Python的模塊 ddddocr 可以實現(xiàn)對圖片驗證碼的識別。

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 本地識別

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 在線識別

也可以直接請求獲取圖片，然后直接識別：

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)

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

有些平臺的圖片是以base64編碼形式存在，需要處理下在識別。

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/

import requests
import ddddocr
# 獲得圖片驗證碼地址
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']
# 訪問并獲取圖片驗證碼
res = requests.get(captcha_url)
# 識別驗證碼
ocr = ddddocr.DdddOcr(show_ad=False)
code = ocr.classification(res.content)
print(code)
# 登錄認證
res = requests.post(
    url="https://api.ruanwen.la/api/auth/authenticate",
    json={
        "mobile": "手機號",
        "device": "pc",
        "password": "密碼",
        "captcha_token": captcha_token,
        "captcha": code,
        "identity": "advertiser"
    }
)
print(res.json())
# {'success': True, 'message': '驗證成功', 'data': {'token': 'eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpc3MiOiJodHRwczovL2FwaS5ydWFud2VuLmxhL2FwaS9hdXRoL2F1dGhlbnRpY2F0ZSIsImlhdCI6MTcwMTY1MzI2NywiZXhwIjoxNzA1MjUzMjY3LCJuYmYiOjE3MDE2NTMyNjcsImp0aSI6IjQ3bk05ejZyQ0JLV28wOEQiLCJzdWIiOjUzMzEyNTgsInBydiI6IjQxZGY4ODM0ZjFiOThmNzBlZmE2MGFhZWRlZjQyMzQxMzcwMDY5MGMifQ.XxFYMEot-DfjTUcuVuoCjcBqu3djvzJiTeJERaR95co'}, 'status': 200}

到此這篇關(guān)于Python爬蟲selenium驗證-中文識別點選+圖片驗證碼案例的文章就介紹到這了,更多相關(guān)Python selenium驗證內(nèi)容請搜索腳本之家以前的文章或繼續(xù)瀏覽下面的相關(guān)文章希望大家以后多多支持腳本之家！

您可能感興趣的文章: