1.图形验证码识别(准确度不高，在模糊干扰的情况下)
方法一： import tesserocr from PIL import Image image = Image.open('1.jpg') result = tesserocr.image_to_text(image) print(result) 方法二： import tesserocr print(tesserocr.file_to_text('1.jpg'))
因为识别程度不够好，增加额外的处理，转灰度、二值化，处理效果也不是很好，只能处理一些比较清晰的验证码
import tesserocr from PIL import Image image = Image.open('1.jpg') image = image.convert('L') 转化为灰度图像 threshold = 127 设定阈值 table = [] for i in range(256): if i < threshold: table.append(0) else: table.append(1) image = image.point(table,'1') result = tesserocr.image_to_text(image) print(result) image.show()
2.极验滑动验证码的识别
打开网页输入邮箱、密码、点击验证
from selenium import webdriver from selenium.webdriver.support.wait import WebDriverWait from selenium.webdriver.common.by import By from selenium.webdriver.support import expected_conditions as EC import time #输入密码账户点击 email = '408084563@qq.com' password = '123456' url = 'https://auth.geetest.com/login/' browser = webdriver.Chrome() browser.get(url=url) time.sleep(2) email_input = browser.find_element_by_xpath('//input[@type="email"]') email_input.send_keys(email) time.sleep(2) pasword_input = browser.find_element_by_xpath('//input[@type="password"]') pasword_input.send_keys(password) time.sleep(2) button = browser.find_element_by_xpath('//div[@class="geetest_radar_tip"]') button.click() time.sleep(1) #截取网页 from PIL import Image from io import BytesIO screenshot = browser.get_screenshot_as_png() screenshot = Image.open(BytesIO(screenshot)) screenshot.show()
。。。。
import time from io import BytesIO from PIL import Image from selenium import webdriver from selenium.webdriver import ActionChains from selenium.webdriver.common.by import By from selenium.webdriver.support.ui import WebDriverWait from selenium.webdriver.support import expected_conditions as EC EMAIL = 'cqc@cuiqingcai.com' PASSWORD = '11111' BORDER = 6 INIT_LEFT = 60 class CrackGeetest(): def __init__(self): self.url = 'https://account.geetest.com/login' self.browser = webdriver.Chrome() self.wait = WebDriverWait(self.browser, 20) self.email = EMAIL self.password = PASSWORD def __del__(self): self.browser.close() def get_geetest_button(self): """ 获取初始验证按钮 :return: """ button = self.wait.until(EC.element_to_be_clickable((By.CLASS_NAME, 'geetest_radar_tip'))) return button def get_position(self): """ 获取验证码位置 :return: 验证码位置元组 """ img = self.wait.until(EC.presence_of_element_located((By.CLASS_NAME, 'geetest_canvas_img'))) time.sleep(2) location = img.location size = img.size top, bottom, left, right = location['y'], location['y'] + size['height'], location['x'], location['x'] + size[ 'width'] return (top, bottom, left, right) def get_screenshot(self): """ 获取网页截图 :return: 截图对象 """ screenshot = self.browser.get_screenshot_as_png() screenshot = Image.open(BytesIO(screenshot)) return screenshot def get_slider(self): """ 获取滑块 :return: 滑块对象 """ slider = self.wait.until(EC.element_to_be_clickable((By.CLASS_NAME, 'geetest_slider_button'))) return slider def get_geetest_image(self, name='captcha.png'): """ 获取验证码图片 :return: 图片对象 """ top, bottom, left, right = self.get_position() print('验证码位置', top, bottom, left, right) screenshot = self.get_screenshot() captcha = screenshot.crop((left, top, right, bottom)) captcha.save(name) return captcha def open(self): """ 打开网页输入用户名密码 :return: None """ self.browser.get(self.url) email_input = self.browser.find_element_by_xpath('//input[@type="email"]') password_input = self.browser.find_element_by_xpath('//input[@type="password"]') email_input.send_keys(self.email) password_input.send_keys(self.password) def get_gap(self, image1, image2): """ 获取缺口偏移量 :param image1: 不带缺口图片 :param image2: 带缺口图片 :return: """ left = 60 for i in range(left, image1.size[0]): for j in range(image1.size[1]): if not self.is_pixel_equal(image1, image2, i, j): left = i return left return left def is_pixel_equal(self, image1, image2, x, y): """ 判断两个像素是否相同 :param image1: 图片1 :param image2: 图片2 :param x: 位置x :param y: 位置y :return: 像素是否相同 """ # 取两个图片的像素点 pixel1 = image1.load()[x, y] pixel2 = image2.load()[x, y] threshold = 60 if abs(pixel1[0] - pixel2[0]) < threshold and abs(pixel1[1] - pixel2[1]) < threshold and abs( pixel1[2] - pixel2[2]) < threshold: return True else: return False def get_track(self, distance): """ 根据偏移量获取移动轨迹 :param distance: 偏移量 :return: 移动轨迹 """ # 移动轨迹 track = [] # 当前位移 current = 0 # 减速阈值 mid = distance * 4 / 5 # 计算间隔 t = 0.2 # 初速度 v = 0 while current < distance: if current < mid: # 加速度为正2 a = 2 else: # 加速度为负3 a = -3 # 初速度v0 v0 = v # 当前速度v = v0 + at v = v0 + a * t # 移动距离x = v0t + 1/2 * a * t^2 move = v0 * t + 1 / 2 * a * t * t # 当前位移 current += move # 加入轨迹 track.append(round(move)) return track def move_to_gap(self, slider, track): """ 拖动滑块到缺口处 :param slider: 滑块 :param track: 轨迹 :return: """ ActionChains(self.browser).click_and_hold(slider).perform() for x in track: ActionChains(self.browser).move_by_offset(xoffset=x, yoffset=0).perform() time.sleep(0.5) ActionChains(self.browser).release().perform() def login(self): """ 登录 :return: None """ submit = self.wait.until(EC.element_to_be_clickable((By.CLASS_NAME, 'login-btn'))) submit.click() time.sleep(10) print('登录成功') def crack(self): # 输入用户名密码 self.open() # 点击验证按钮 button = self.get_geetest_button() button.click() # 获取验证码图片 image1 = self.get_geetest_image('captcha1.png') # 点按呼出缺口 slider = self.get_slider() slider.click() # 获取带缺口的验证码图片 image2 = self.get_geetest_image('captcha2.png') # 获取缺口位置 gap = self.get_gap(image1, image2) print('缺口位置', gap) # 减去缺口位移 gap -= BORDER # 获取移动轨迹 track = self.get_track(gap) print('滑动轨迹', track) # 拖动滑块 self.move_to_gap(slider, track) success = self.wait.until( EC.text_to_be_present_in_element((By.CLASS_NAME, 'geetest_success_radar_tip_content'), '验证成功')) print(success) # 失败后重试 if not success: self.crack() else: self.login() if __name__ == '__main__': crack = CrackGeetest() crack.crack()