python+selenium滑动式验证码

目录

• python+selenium滑动式验证码:
  • 实列：
  • 破解滑动验证:

python+selenium滑动式验证码:

实列：

# -*- coding:utf-8 -*-
from selenium import webdriver
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.common.action_chains import ActionChains
import PIL.Image as image
from PIL import Image,ImageEnhance
import time,re, random
import requests
try:
    from StringIO import StringIO
except ImportError:
    from io import StringIO

#爬虫模拟的浏览器头部信息
agent = "Mozilla/5.0 (Windows NT 5.1; rv:33.0) Gecko/20100101 Firefox/33.0"
headers = {
        "User-Agent": agent
        }

# 根据位置对图片进行合并还原
# filename:图片
# location_list:图片位置
#内部两个图片处理函数的介绍
#crop函数带的参数为(起始点的横坐标，起始点的纵坐标，宽度，高度）
#paste函数的参数为(需要修改的图片，粘贴的起始点的横坐标，粘贴的起始点的纵坐标）
def get_merge_image(filename,location_list):
    #打开图片文件
    im = image.open(filename)
    #创建新的图片,大小为260*116
    new_im = image.new("RGB", (260,116))
    im_list_upper=[]
    im_list_down=[]
    # 拷贝图片
    for location in location_list:
        #上面的图片
        if location["y"]==-58:
            im_list_upper.append(im.crop((abs(location["x"]),58,abs(location["x"])+10,166)))
        #下面的图片
        if location["y"]==0:
            im_list_down.append(im.crop((abs(location["x"]),0,abs(location["x"])+10,58)))
    new_im = image.new("RGB", (260,116))
    x_offset = 0
    #黏贴图片
    for im in im_list_upper:
        new_im.paste(im, (x_offset,0))
        x_offset += im.size[0]
    x_offset = 0
    for im in im_list_down:
        new_im.paste(im, (x_offset,58))
        x_offset += im.size[0]
    return new_im

#对比RGB值
def is_similar(image1,image2,x,y):
    pass
    #获取指定位置的RGB值
    pixel1=image1.getpixel((x,y))
    pixel2=image2.getpixel((x,y))
    for i in range(0,3):
        # 如果相差超过50则就认为找到了缺口的位置
        if abs(pixel1[i]-pixel2[i])>=50:
            return False
    return True

#计算缺口的位置
def get_diff_location(image1,image2):
    i=0
    # 两张原始图的大小都是相同的260*116
    # 那就通过两个for循环依次对比每个像素点的RGB值
    # 如果相差超过50则就认为找到了缺口的位置
    for i in range(62,260):#有人可能看不懂这个位置为什么要从62开始看最后一张图（图：3）
        for j in range(0,116):
            if is_similar(image1,image2,i,j)==False:
                return  i

#根据缺口的位置模拟x轴移动的轨迹
def get_track(length):
    pass
    list=[]
    #间隔通过随机范围函数来获得,每次移动一步或者两步
    x=random.randint(1,3)
    #生成轨迹并保存到list内
    while length-x>=5:
        list.append(x)
        length=length-x
        x=random.randint(1,3)
    #最后五步都是一步步移动
    for i in range(length):
        list.append(1)
    return list

#滑动验证码破解程序
def main():
    #打开火狐浏览器
    driver = webdriver.Firefox()
    #用火狐浏览器打开网页
    driver.get("https://account.geetest.com/register")
    time.sleep(2)
    driver.find_element_by_xpath('//*[@id="captcha"]/div/div[3]/span[2]').click()
    time.sleep(5)

    driver.get_screenshot_as_file("D:/test2/滑动验证/img.jpg")#对整个页面截图
    imgelement = driver.find_element_by_xpath('/html/body/div[2]/div[2]/div[1]/div/div[2]/div[1]/div/a/div[1]/canvas')  # 定位验证码
    location = imgelement.location  # 获取验证码x,y轴坐标
    size = imgelement.size  # 获取验证码的长宽
    rangle = (int(location['x'] ), int(location['y']), int(location['x'] + size['width']),
              int(location['y'] + size['height']))  # 写成我们需要截取的位置坐标
    i = Image.open("D:/test2/滑动验证/img.jpg")  # 打开截图
    i = i.convert('RGB')
    frame1 = i.crop(rangle)  # 使用Image的crop函数，从截图中再次截取我们需要的区域
    frame1.save('D:/test2/滑动验证/new.jpg')
    driver.find_element_by_xpath('/html/body/div[2]/div[2]/div[1]/div/div[2]/div[2]/div[2]').click()
    time.sleep(4)

    driver.get_screenshot_as_file("D:/test2/滑动验证/img.jpg")
    imgelement = driver.find_element_by_xpath('/html/body/div[2]/div[2]/div[1]/div/div[2]/div[1]/div/a/div[1]/div/canvas[2]')  # 定位验证码
    location = imgelement.location  # 获取验证码x,y轴坐标
    size = imgelement.size  # 获取验证码的长宽
    rangle = (int(location['x'] ), int(location['y']), int(location['x'] + size['width']),
              int(location['y'] + size['height']))  # 写成我们需要截取的位置坐标
    i = Image.open("D:/test2/滑动验证/img.jpg")  # 打开截图
    i = i.convert('RGB')
    frame2 = i.crop(rangle)  # 使用Image的crop函数，从截图中再次截取我们需要的区域
    frame2.save('D:/test2/滑动验证/new2.jpg')

    #计算缺口位置
    loc=get_diff_location(frame1, frame2)
    print('-------------')
    print(loc)
    #找到滑动的圆球
    element=driver.find_element_by_xpath('/html/body/div[2]/div[2]/div[1]/div/div[2]/div[2]/div[2]')
    location=element.location
    #获得滑动圆球的高度
    y=location["y"]
    #鼠标点击元素并按住不放
    print ("第一步,点击元素")
    ActionChains(driver).click_and_hold(on_element=element).perform()

    time.sleep(0.15)

    print ("第二步，拖动元素")
    ActionChains(driver).move_to_element_with_offset(to_element=element, xoffset=loc + 30, yoffset=y - 445).perform()
    #释放鼠标
    ActionChains(driver).release(on_element=element).perform()


    #关闭浏览器,为了演示方便,暂时注释掉.
    #driver.quit()

#主函数入口
if __name__ == "__main__":
    pass
    main()

破解滑动验证:

from selenium import webdriver
from selenium.webdriver.support.ui import WebDriverWait # 等待元素加载的
from selenium.webdriver.common.action_chains import ActionChains  #拖拽
from selenium.webdriver.support import expected_conditions as EC
from selenium.common.exceptions import TimeoutException, NoSuchElementException
from selenium.webdriver.common.by import By
from PIL import Image
import requests
import re
import random
from io import BytesIO
import time


def merge_image(image_file,location_list):
    """
     拼接图片
    """
    im = Image.open(image_file)
    im.save('code.jpg')
    new_im = Image.new('RGB',(260,116))
    # 把无序的图片 切成52张小图片
    im_list_upper = []
    im_list_down = []
    # print(location_list)
    for location in location_list:
        # print(location['y'])
        if location['y'] == -58: # 上半边
            im_list_upper.append(im.crop((abs(location['x']),58,abs(location['x'])+10,116)))
        if location['y'] == 0:  # 下半边
            im_list_down.append(im.crop((abs(location['x']),0,abs(location['x'])+10,58)))

    x_offset = 0
    for im in im_list_upper:
        new_im.paste(im,(x_offset,0))  # 把小图片放到 新的空白图片上
        x_offset += im.size[0]

    x_offset = 0
    for im in im_list_down:
        new_im.paste(im,(x_offset,58))
        x_offset += im.size[0]
    #new_im.show()
    return new_im

def get_image(driver,div_path):
    '''
    下载无序的图片  然后进行拼接 获得完整的图片
    :param driver:
    :param div_path:
    :return:
    '''
    background_images = driver.find_elements_by_xpath(div_path)
    location_list = []
    for background_image in background_images:
        location = {}
        result = re.findall('background-image: url("(.*?)"); background-position: (.*?)px (.*?)px;',background_image.get_attribute('style'))
        # print(result)
        location['x'] = int(result[0][1])
        location['y'] = int(result[0][2])

        image_url = result[0][0]
        location_list.append(location)
    image_url = image_url.replace('webp','jpg')
    # '替换url http://static.geetest.com/pictures/gt/579066de6/579066de6.webp'
    image_result = requests.get(image_url).content
    image_file = BytesIO(image_result) # 是一张无序的图片
    image = merge_image(image_file,location_list)

    return image


def get_track(distance):

    # 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=[]
    tracks_back=[]
    # 当前的位移
    current=0
    # 到达mid值开始减速
    mid=distance * 7/8
    print("distance",distance)
    global random_int
    random_int=8
    distance += random_int # 先滑过一点，最后再反着滑动回来

    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(2,5)  # 加速运动
        else:
            a = -random.randint(2,5) # 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
        if round(s)>0:
            tracks.append(round(s))
        else:
            tracks_back.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

        print("tracks:",tracks)
        print("tracks_back:",tracks_back)
        print("current:",current)

    # 反着滑动到大概准确位置

    tracks_back.append(distance-current)
    tracks_back.extend([-2,-5,-8,])

    return tracks,tracks_back


def get_distance(image1,image2):
    '''
       拿到滑动验证码需要移动的距离
      :param image1:没有缺口的图片对象
      :param image2:带缺口的图片对象
      :return:需要移动的距离
      '''
    # print('size', image1.size)

    threshold = 50
    for i in range(0,image1.size[0]):  # 260
        for j in range(0,image1.size[1]):  # 160
            pixel1 = image1.getpixel((i,j))
            pixel2 = image2.getpixel((i,j))
            res_R = abs(pixel1[0]-pixel2[0]) # 计算RGB差
            res_G = abs(pixel1[1] - pixel2[1])  # 计算RGB差
            res_B = abs(pixel1[2] - pixel2[2])  # 计算RGB差
            if res_R > threshold and res_G > threshold and res_B > threshold:
                return i  # 需要移动的距离


def main_check_code(driver,element):
    """
    拖动识别验证码
    :param driver:
    :param element:
    :return:
    """

    login_btn = driver.find_element_by_class_name('js-login')
    login_btn.click()

    element = WebDriverWait(driver, 30, 0.5).until(EC.element_to_be_clickable((By.CLASS_NAME, 'gt_guide_tip')))
    slide_btn = driver.find_element_by_class_name('gt_guide_tip')
    slide_btn.click()



    image1 = get_image(driver, '//div[@class="gt_cut_bg gt_show"]/div')
    image2 = get_image(driver, '//div[@class="gt_cut_fullbg gt_show"]/div')
    # 图片上 缺口的位置的x坐标

    # 2 对比两张图片的所有RBG像素点，得到不一样像素点的x值，即要移动的距离
    l = get_distance(image1, image2)
    print('l=',l)

    # 3 获得移动轨迹
    track_list = get_track(l)
    print('第一步,点击滑动按钮')
    element = WebDriverWait(driver, 30, 0.5).until(EC.element_to_be_clickable((By.CLASS_NAME, 'gt_slider_knob')))
    ActionChains(driver).click_and_hold(on_element=element).perform()  # 点击鼠标左键，按住不放
    import time
    time.sleep(0.4)
    print('第二步,拖动元素')
    for track in track_list[0]:
         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(0.4)
    for track in track_list[1]:
          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(0.1)
    import time
    time.sleep(0.6)
    # ActionChains(driver).move_by_offset(xoffset=2, yoffset=0).perform()  # 鼠标移动到距离当前位置（x,y）
    # ActionChains(driver).move_by_offset(xoffset=8, yoffset=0).perform()  # 鼠标移动到距离当前位置（x,y）
    # ActionChains(driver).move_by_offset(xoffset=2, yoffset=0).perform()  # 鼠标移动到距离当前位置（x,y）
    print('第三步,释放鼠标')
    ActionChains(driver).release(on_element=element).perform()
    time.sleep(1)

def main_check_slider(driver):
    """
    检查滑动按钮是否加载
    :param driver:
    :return:
    """
    while True:
        try :
            driver.get('https://www.huxiu.com/')
            element = WebDriverWait(driver, 30, 0.5).until(EC.element_to_be_clickable((By.CLASS_NAME, 'js-login')))
            if element:
                return element
        except TimeoutException as e:
            print('超时错误，继续')
            time.sleep(5)

if __name__ == '__main__':

    try:
        count = 3  # 最多识别3次
        driver = webdriver.Chrome()
        while count > 0:
            # 等待滑动按钮加载完成
            element = main_check_slider(driver)
            main_check_code(driver,element)
            try:
                success_element = (By.CSS_SELECTOR, '.gt_success')
                # 得到成功标志
                success_images = WebDriverWait(driver,3).until(EC.presence_of_element_located(success_element))
                if success_images:
                    print('成功识别！！！！！！')
                    count = 0
                    import sys
                    sys.exit()
            except Exception as e:
                print('识别错误，继续')
                count -= 1
                time.sleep(1)
        else:
            print('too many attempt check code ')
            exit('退出程序')
    finally:
        driver.close()