Python实现滑块验证

python中安装好selenium包 pip install selenium
点击下载chrome的webdriver： http://chromedriver.storage.googleapis.com/index.html，目前只有32位的。
1.驱动下载完成，解压
2.将解压后文件chromedriver.exe复制到python的Scripts安装目录下（我的：E:\Python\Python36-32\Scripts），并且添加到path环境变量
3.将目录chrome的安装目录添加到path环境变量。（我的：C:\Program Files (x86)\Google\Chrome\Application\chrome.exe）
4.运行下面代码：成功打开百度即为成功：（别拉到cmd里直接运行，各种报错，我是在VS终端下调试成功的）
from selenium import webdriver
driver = webdriver.Chrome()
　　driver.get(‘http://www.baidu.com')

然后是详细代码：(代码转自奥哥)

seleclass.py主入口文件

# -*- coding: utf-8 -*-
import json
import time
from selenium import webdriver
from selenium.webdriver.common.action_chains import ActionChains
from image_diff import Diff


class SeleClass:
    def __init__(self, url, username, password):
        self.url = url
        self.wdc_option = webdriver.ChromeOptions()
        self.wdc_option.add_argument('--headless')
        self.wdc_option.add_argument('--disable-gpu')
        self.wdc = webdriver.Chrome(options=self.wdc_option)
        self.wdc.implicitly_wait(10)
        self.wdc.get(self.url)
        self.wdc.maximize_window()
        self.input(username, password)

    def input(self, username, password):
        self.wdc.find_element_by_id('login-username').send_keys(username)
        self.wdc.find_element_by_id('login-passwd').send_keys(password)
        self.mouseLogin()

    def mouseLogin(self):
        ActionChains(self.wdc).move_to_element(self.wdc.find_elements_by_class_name('btn-login')[0]).perform()
        ActionChains(self.wdc).click().perform()
        self.mouseMove(Diff(**self.getBase64Data()).hOption())
        self.isLogin()

    def doScript(self, script):
        for _ in range(10):
            try:
                if len(self.wdc.execute_script(script)) < 3000:
                    print('错误数据大小：%s' % len(self.wdc.execute_script(script)), end='\t')
                    raise BaseException()
                return self.wdc.execute_script(script)
            except:
                time.sleep(1)
        raise BaseException('拉取数据超时')

    def mouseMove(self, long):
        print('鼠标移动位移为：%s' % long)
        ActionChains(self.wdc).click_and_hold(
            self.wdc.find_elements_by_class_name('geetest_slider_button')[0]).perform()
        ActionChains(self.wdc).move_by_offset(long, 0).perform()
        time.sleep(1)
        ActionChains(self.wdc).release().perform()

    def getBase64Data(self):
        bg = self.doScript("return $('.geetest_canvas_bg')[0].toDataURL('image/png')")[22::]
        full = self.doScript("return $('.geetest_canvas_fullbg')[0].toDataURL('image/png')")[22::]
        slice = self.doScript("return $('.geetest_canvas_slice')[0].toDataURL('image/png')")[22::]
        print('真实数据大小：', len(bg), len(full), len(slice))
        return {
            'b1': bg,
            'b2': full,
            'b3': slice
        }

    def isLogin(self):
        for _ in range(10):
            if self.wdc.get_cookie('DedeUserID'):
                self.wdc.get('https://space.bilibili.com/' + self.wdc.get_cookie('DedeUserID')['value'])
                print('登陆成功：%s' % self.wdc.find_element_by_id('h-name').text)
                return
            else:
                time.sleep(1)
        raise BaseException('页面跳转超时')

    def __del__(self):
        time.sleep(2)
        self.wdc.close()


if __name__ == '__main__':
    s = SeleClass('https://passport.bilibili.com/login', 'username', 'password')

image_diff.py图片处理文件

from skimage.measure import compare_ssim
import argparse
import imutils
import cv2
import numpy as np
from base64 import b64decode


class Diff:
    def __init__(self, b1, b2, b3):
        self.imageA = cv2.imdecode(np.frombuffer(b64decode(b1), np.uint8), cv2.COLOR_RGB2BGR)
        self.imageB = cv2.imdecode(np.frombuffer(b64decode(b2), np.uint8), cv2.COLOR_RGB2BGR)
        self.imageC = cv2.imdecode(np.frombuffer(b64decode(b3), np.uint8), cv2.COLOR_RGB2BGR)

    def show(self):
        cv2.imshow('imga', self.imageA)
        cv2.imshow('imgb', self.imageB)
        cv2.imshow('imgc', self.imageC)
        if chr(cv2.waitKey(0)) == 'q':
            cv2.destroyAllWindows()

    def hOption(self):
        grayA = cv2.cvtColor(self.imageA, cv2.COLOR_BGR2GRAY)
        grayB = cv2.cvtColor(self.imageB, cv2.COLOR_BGR2GRAY)
        grayC = cv2.cvtColor(self.imageC, cv2.COLOR_BGR2GRAY)
        npArr_3 = np.array(grayC)
        return self.diff(grayA, grayB, npArr_3)

    def diff(self, grayA, grayB, npArr_3):
        (score, diff) = compare_ssim(grayA, grayB, full=True)
        diff = (diff * 255).astype("uint8")
        print('图片相似度为：%s' % score)
        return self.tf(diff, npArr_3)

    def tf(self, diff, npArr_3):
        thresh = cv2.threshold(diff, 0, 255,
                               cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU)[1]
        cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
                                cv2.CHAIN_APPROX_SIMPLE)
        cnts = cnts[1] if imutils.is_cv3() else cnts[0]

        img3_t = cv2.threshold(npArr_3, 0, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]

        cnts_3 = cv2.findContours(img3_t.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
        cnts_3 = cnts_3[1] if imutils.is_cv3() else cnts_3[0]
        return self.getBr(cnts, cnts_3)

    def getBr(self, cnts, cnts_3):
        x1, y1, w1, h1 = cv2.boundingRect(cnts[-1])
        cv2.rectangle(self.imageA, (x1, y1), (x1 + w1, y1 + h1), (0, 0, 255), 1)
        cv2.rectangle(self.imageB, (x1, y1), (x1 + w1, y1 + h1), (0, 0, 255), 1)
        x2, y2, w2, h2 = cv2.boundingRect(cnts_3[-1])
        cv2.rectangle(self.imageC, (x2, y2), (x2 + w2, y2 + h2), (0, 0, 255), 1)
        cv2.rectangle(self.imageC, (x2, y2), (x2 + w2, y2 + h2), (0, 0, 255), 1)
        return x1 - x2