python滑块验证码

前言

网上有不少关于滑块验证码的文章，要么就是说了一堆原理断断续续的放一些代码块，要么就是收费!!!都没什么卵用
今天给大家分享一篇Python自动验证滑块验证码的操作!，你只需要复制粘贴就行，原理不细说，一些简要说明在代码备注中

提示：以下是代码正文内容

# -*- coding: utf-8 -*- import numpy as np import random from selenium.webdriver import ActionChains import time from selenium import webdriver from PIL import Image import os from selenium.webdriver.support.ui import WebDriverWait # opencv-python需要安装这个模块 import cv2 class Login(object): """ 腾讯防水墙滑动验证码激活成功教程 使用OpenCV库 成功率大概90%左右：在实际应用中，登录后可判断当前页面是否有登录成功才会出现的信息：比如用户名等。循环 https://open.captcha..com/online.html 激活成功教程 腾讯滑动验证码 腾讯防水墙 python + seleniuum + cv2 """ def __init__(self): # 如果是实际应用中，可在此处账号和密码 self.url = "https://open.captcha..com/online.html" self.driver = webdriver.Chrome() @staticmethod def show(name): cv2.imshow('Show', name) cv2.waitKey(0) cv2.destroyAllWindows() @staticmethod def webdriverwait_send_keys(dri, element, value): """ 显示等待输入 :param dri: driver :param element: :param value: :return: """ WebDriverWait(dri, 10, 5).until(lambda dr: element).send_keys(value) @staticmethod def webdriverwait_click(dri, element): """ 显示等待 click :param dri: driver :param element: :return: """ WebDriverWait(dri, 10, 5).until(lambda dr: element).click() @staticmethod def get_postion(chunk, canves): """ 判断缺口位置 :param chunk: 缺口图片是原图 :param canves: :return: 位置 x, y """ otemp = chunk oblk = canves target = cv2.imread(otemp, 0) template = cv2.imread(oblk, 0) # w, h = target.shape[::-1] temp = 'temp.jpg' targ = 'targ.jpg' cv2.imwrite(temp, template) cv2.imwrite(targ, target) target = cv2.imread(targ) target = cv2.cvtColor(target, cv2.COLOR_BGR2GRAY) target = abs(255 - target) cv2.imwrite(targ, target) target = cv2.imread(targ) template = cv2.imread(temp) result = cv2.matchTemplate(target, template, cv2.TM_CCOEFF_NORMED) x, y = np.unravel_index(result.argmax(), result.shape) return x, y # # 展示圈出来的区域 # cv2.rectangle(template, (y, x), (y + w, x + h), (7, 249, 151), 2) # cv2.imwrite("yuantu.jpg", template) # show(template) @staticmethod def get_track(distance): """ 模拟轨迹 假装是人在操作 :param distance: :return: """ # 初速度 v = 0 # 单位时间为0.2s来统计轨迹，轨迹即0.2内的位移 t = 0.2 # 位移/轨迹列表，列表内的一个元素代表0.2s的位移 tracks = [] # 当前的位移 current = 0 # 到达mid值开始减速 mid = distance * 7 / 8 distance += 10 # 先滑过一点，最后再反着滑动回来 # a = random.randint(1,3) while current < distance: if current < mid: # 加速度越小，单位时间的位移越小,模拟的轨迹就越多越详细 a = random.randint(2, 4) # 加速运动 else: a = -random.randint(3, 5) # 减速运动 # 初速度 v0 = v # 0.2秒时间内的位移 s = v0 * t + 0.5 * a * (t  2) # 当前的位置 current += s # 添加到轨迹列表 tracks.append(round(s)) # 速度已经达到v,该速度作为下次的初速度 v = v0 + a * t # 反着滑动到大概准确位置 for i in range(4): tracks.append(-random.randint(2, 3)) for i in range(4): tracks.append(-random.randint(1, 3)) return tracks @staticmethod def urllib_download(imgurl, imgsavepath): """ 下载图片 :param imgurl: 图片url :param imgsavepath: 存放地址 :return: """ from urllib.request import urlretrieve urlretrieve(imgurl, imgsavepath) def after_quit(self): """ 关闭浏览器 :return: """ self.driver.quit() def login_main(self): # ssl._create_default_https_context = ssl._create_unverified_context driver = self.driver driver.maximize_window() driver.get(self.url) click_keyi_username = driver.find_element_by_xpath("//div[@class='wp-onb-tit']/a[text()='可疑用户']") self.webdriverwait_click(driver, click_keyi_username) login_button = driver.find_element_by_id('code') self.webdriverwait_click(driver, login_button) time.sleep(1) driver.switch_to.frame(driver.find_element_by_id('tcaptcha_iframe')) # switch 到 滑块frame time.sleep(0.5) bk_block = driver.find_element_by_xpath('//img[@id="slideBg"]') # 大图 web_image_width = bk_block.size web_image_width = web_image_width['width'] bk_block_x = bk_block.location['x'] slide_block = driver.find_element_by_xpath('//img[@id="slideBlock"]') # 小滑块 slide_block_x = slide_block.location['x'] bk_block = driver.find_element_by_xpath('//img[@id="slideBg"]').get_attribute('src') # 大图 url slide_block = driver.find_element_by_xpath('//img[@id="slideBlock"]').get_attribute('src') # 小滑块 图片url slid_ing = driver.find_element_by_xpath('//div[@id="tcaptcha_drag_thumb"]') # 滑块 os.makedirs('./image/', exist_ok=True) self.urllib_download(bk_block, './image/bkBlock.png') self.urllib_download(slide_block, './image/slideBlock.png') time.sleep(0.5) img_bkblock = Image.open('./image/bkBlock.png') real_width = img_bkblock.size[0] width_scale = float(real_width) / float(web_image_width) position = self.get_postion('./image/bkBlock.png', './image/slideBlock.png') real_position = position[1] / width_scale real_position = real_position - (slide_block_x - bk_block_x) track_list = self.get_track(real_position + 4) ActionChains(driver).click_and_hold(on_element=slid_ing).perform() # 点击鼠标左键，按住不放 time.sleep(0.2) # print('第二步,拖动元素') for track in track_list: ActionChains(driver).move_by_offset(xoffset=track, yoffset=0).perform() # 鼠标移动到距离当前位置（x,y） time.sleep(0.002) # ActionChains(driver).move_by_offset(xoffset=-random.randint(0, 1), yoffset=0).perform() # 微调，根据实际情况微调 time.sleep(1) # print('第三步,释放鼠标') ActionChains(driver).release(on_element=slid_ing).perform() time.sleep(1) print('登录成功') self.after_quit() if __name__ == '__main__': phone = "" login = Login() login.login_main()