python selenium 模拟实现滑块验证码
canndy_test.py
import cv2 import numpy as np def matchImg(imgPath1, imgPath2): imgs = [] # 原始图像，用于展示 sou_img1 = cv2.imread(imgPath1) sou_img2 = cv2.imread(imgPath2) # 原始图像，灰度 # 最小阈值100,最大阈值500 img1 = cv2.imread(imgPath1, 0) blur1 = cv2.GaussianBlur(img1, (5, 5), 0) canny1 = cv2.Canny(blur1, 120, 500) cv2.imwrite('temp1.png', canny1) img2 = cv2.imread(imgPath2, 0) blur2 = cv2.GaussianBlur(img2, (5, 5), 0) canny2 = cv2.Canny(blur2, 120, 500) cv2.imwrite('temp2.png', canny2) target = cv2.imread('temp1.png') template = cv2.imread('temp2.png') # 调整显示大小 target_temp = cv2.resize(sou_img1, (250, 250)) target_temp = cv2.copyMakeBorder(target_temp, 5, 5, 5, 5, cv2.BORDER_CONSTANT, value=[255, 255, 255]) template_temp = cv2.resize(sou_img2, (250, 250)) template_temp = cv2.copyMakeBorder(template_temp, 5, 5, 5, 5, cv2.BORDER_CONSTANT, value=[255, 255, 255]) imgs.append(target_temp) imgs.append(template_temp) theight, twidth = template.shape[:2] # 匹配拼图 result = cv2.matchTemplate(target, template, cv2.TM_CCOEFF_NORMED) # 归一化 cv2.normalize(result, result, 0, 1, cv2.NORM_MINMAX, -1) min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result) # 如果不需要看后面的效果，只要返回位置，把下面的注释去掉 return max_loc[0] def fix_img(filename): # 获取滑块的大小 # 1.为了更高的准确率，使用二值图像 img = cv2.imread(filename) gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) _, thresh = cv2.threshold(gray, 127, 255, cv2.THRESH_BINARY) # 2.将轮廓提取出来 contours, _ = cv2.findContours(thresh, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE) # 3.用绿色(0, 255, 0)来画出最小的矩形框架 x, y, w, h = cv2.boundingRect(contours[0]) rect_x = x + w rect_y = y + h # print(x, y, rect_x, rect_y) # x，y是矩阵左上点的坐标，w，h是矩阵的宽和高 rect_img = cv2.rectangle(img, (x, y), (rect_x, rect_y), (0, 255, 0), 1) # 3.根据滑块的高度和宽度进行截图 mixintu = rect_img[y:rect_y, x:rect_x] return mixintu def compute_gap(fadebg, fullbg): # 1.对滑块进行图片处理 tp_img = fix_img(fadebg) # 裁掉透明部分，找出滑块的大小 tp_pic = cv2.cvtColor(cv2.Canny(tp_img, 100, 200), cv2.COLOR_GRAY2BGR) # 2.对背景进行图片处理 bg_pic = cv2.cvtColor(cv2.Canny(cv2.imread(fullbg), 100, 200), cv2.COLOR_GRAY2BGR) # 3.模板匹配matchTemplate res = cv2.matchTemplate(bg_pic, tp_pic, cv2.TM_CCOEFF_NORMED) min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res) # print(min_val, max_val, min_loc, max_loc) # 最小值，最大值，最小值的位置，最大值的位置 # 返回滑块移动距离 return max_loc[0]
webmethod.py
from selenium.webdriver.common.action_chains import ActionChains from selenium.webdriver.common.by import By import time import base64 from canndy_test import compute_gap from selenium import webdriver url = "https://xxxxxxxxxxxx/admin-web/#/login" account = "admin" password = "123456" username_input = '[placeholder="请输入用户名"]' password_input = '[placeholder="请输入密码"]' login_button = '[class="login-submit"]' # 获取谷歌驱动 driver = webdriver.Chrome() # 打开网址 driver.get(url) # 窗口最大化 driver.maximize_window() # 等待元素加载完成 driver.implicitly_wait(20) # 输入账号 driver.find_element(By.CSS_SELECTOR, username_input).send_keys(account) # 输入密码 driver.find_element(By.CSS_SELECTOR, password_input).send_keys(password) # 点击登录 driver.find_element(By.CSS_SELECTOR, login_button).click() time.sleep(4) def skip_code(): """ 滑动滑块 """ time.sleep(3) flag = 1 # 如果没有滑动成功，将一直重新定位并滑动滑块，直到进入系统 while flag: try: # 获取背景图src targetUrl1 = driver.find_elements(By.TAG_NAME, 'img')[1].get_attribute('src') # 定位背景图片元素，并获取该元素src属性值 imgData = base64.b64decode(targetUrl1.split(',')[1]) # 获取的src属性经过base64编码了，所以需要解码 with open('targetUrl.png', 'wb') as file: # 保存到当前目录 file.write(imgData) # 获取拼图src tempUrl2 = driver.find_elements(By.TAG_NAME, 'img')[2].get_attribute('src') imgData = base64.b64decode(tempUrl2.split(',')[1]) with open('tempUrl.png', 'wb') as file: file.write(imgData) # 计算移动距离 move = compute_gap('tempUrl.png', 'targetUrl.png') distance = int(move + 13.5) # 计算出的move会有偏差，所以这里需要反复实验出实际值 # 查找滑动箭头元素 draggable = driver.find_element(By.CSS_SELECTOR, '[class="verify-move-block"]') # 将鼠标悬停在滑动箭头元素上 ActionChains(driver).click_and_hold(draggable).perform() # 拖动 ActionChains(driver).move_by_offset(xoffset=distance, yoffset=0).perform() ActionChains(driver).release().perform() time.sleep(2) except: flag = 0 time.sleep(2) # 关闭浏览器 driver.quit() skip_code()
