python+selenium滑動式驗證碼解決辦法


python+selenium滑動式驗證碼解決辦法

示例代碼:

# -*- 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

#爬蟲模擬的瀏覽器頭部信息
agent = "Mozilla/5.0 (Windows NT 5.1; rv:33.0) Gecko/20100101 Firefox/33.0"
headers = {
        "User-Agent": agent
        }

# 根據位置對圖片進行合並還原
# filename:圖片
# location_list:圖片位置
#內部兩個圖片處理函數的介紹
#crop函數帶的參數為(起始點的橫坐標,起始點的縱坐標,寬度,高度)
#paste函數的參數為(需要修改的圖片,粘貼的起始點的橫坐標,粘貼的起始點的縱坐標)
def get_merge_image(filename,location_list):
    #打開圖片文件
    im = image.open(filename)
    #創建新的圖片,大小為260*116
    new_im = image.new("RGB", (260,116))
    im_list_upper=[]
    im_list_down=[]
    # 拷貝圖片
    for location in location_list:
        #上面的圖片
        if location["y"]==-58:
            im_list_upper.append(im.crop((abs(location["x"]),58,abs(location["x"])+10,166)))
        #下面的圖片
        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
    #黏貼圖片
    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

#對比RGB值
def is_similar(image1,image2,x,y):
    pass
    #獲取指定位置的RGB值
    pixel1=image1.getpixel((x,y))
    pixel2=image2.getpixel((x,y))
    for i in range(0,3):
        # 如果相差超過50則就認為找到了缺口的位置
        if abs(pixel1[i]-pixel2[i])>=50:
            return False
    return True

#計算缺口的位置
def get_diff_location(image1,image2):
    i=0
    # 兩張原始圖的大小都是相同的260*116
    # 那就通過兩個for循環依次對比每個像素點的RGB值
    # 如果相差超過50則就認為找到了缺口的位置
    for i in range(62,260):#有人可能看不懂這個位置為什么要從62開始看最后一張圖(圖:3)
        for j in range(0,116):
            if is_similar(image1,image2,i,j)==False:
                return  i

#根據缺口的位置模擬x軸移動的軌跡
def get_track(length):
    pass
    list=[]
    #間隔通過隨機范圍函數來獲得,每次移動一步或者兩步
    x=random.randint(1,3)
    #生成軌跡並保存到list內
    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動
    for i in range(length):
        list.append(1)
    return list

#滑動驗證碼破解程序
def main():
    #打開火狐瀏覽器
    driver = webdriver.Firefox()
    #用火狐瀏覽器打開網頁
    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/滑動驗證/img.jpg")#對整個頁面截圖
    imgelement = driver.find_element_by_xpath('/html/body/div[2]/div[2]/div[1]/div/div[2]/div[1]/div/a/div[1]/canvas')  # 定位驗證碼
    location = imgelement.location  # 獲取驗證碼x,y軸坐標
    size = imgelement.size  # 獲取驗證碼的長寬
    rangle = (int(location['x'] ), int(location['y']), int(location['x'] + size['width']),
              int(location['y'] + size['height']))  # 寫成我們需要截取的位置坐標
    i = Image.open("D:/test2/滑動驗證/img.jpg")  # 打開截圖
    i = i.convert('RGB')
    frame1 = i.crop(rangle)  # 使用Image的crop函數,從截圖中再次截取我們需要的區域
    frame1.save('D:/test2/滑動驗證/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/滑動驗證/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]')  # 定位驗證碼
    location = imgelement.location  # 獲取驗證碼x,y軸坐標
    size = imgelement.size  # 獲取驗證碼的長寬
    rangle = (int(location['x'] ), int(location['y']), int(location['x'] + size['width']),
              int(location['y'] + size['height']))  # 寫成我們需要截取的位置坐標
    i = Image.open("D:/test2/滑動驗證/img.jpg")  # 打開截圖
    i = i.convert('RGB')
    frame2 = i.crop(rangle)  # 使用Image的crop函數,從截圖中再次截取我們需要的區域
    frame2.save('D:/test2/滑動驗證/new2.jpg')

    #計算缺口位置
    loc=get_diff_location(frame1, frame2)
    print('-------------')
    print(loc)
    #找到滑動的圓球
    element=driver.find_element_by_xpath('/html/body/div[2]/div[2]/div[1]/div/div[2]/div[2]/div[2]')
    location=element.location
    #獲得滑動圓球的高度
    y=location["y"]
    #鼠標點擊元素並按住不放
    print ("第一步,點擊元素")
    ActionChains(driver).click_and_hold(on_element=element).perform()

    time.sleep(0.15)

    print ("第二步,拖動元素")
    ActionChains(driver).move_to_element_with_offset(to_element=element, xoffset=loc + 30, yoffset=y - 445).perform()
    #釋放鼠標
    ActionChains(driver).release(on_element=element).perform()


    #關閉瀏覽器,為了演示方便,暫時注釋掉.
    #driver.quit()

#主函數入口
if __name__ == "__main__":
    pass
    main()

破解滑動驗證

from selenium import webdriver
from selenium.webdriver.support.ui import WebDriverWait # 等待元素加載的
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):
    """
     拼接圖片
    """
    im = Image.open(image_file)
    im.save('code.jpg')
    new_im = Image.new('RGB',(260,116))
    # 把無序的圖片 切成52張小圖片
    im_list_upper = []
    im_list_down = []
    # print(location_list)
    for location in location_list:
        # print(location['y'])
        if location['y'] == -58: # 上半邊
            im_list_upper.append(im.crop((abs(location['x']),58,abs(location['x'])+10,116)))
        if location['y'] == 0:  # 下半邊
            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))  # 把小圖片放到 新的空白圖片上
        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):
    '''
    下載無序的圖片  然后進行拼接 獲得完整的圖片
    :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')
    # '替換url http://static.geetest.com/pictures/gt/579066de6/579066de6.webp'
    image_result = requests.get(image_url).content
    image_file = BytesIO(image_result) # 是一張無序的圖片
    image = merge_image(image_file,location_list)

    return image


def get_track(distance):

    # 初速度
    v=0
    # 單位時間為0.2s來統計軌跡,軌跡即0.2內的位移
    t=0.2
    # 位移/軌跡列表,列表內的一個元素代表0.2s的位移
    tracks=[]
    tracks_back=[]
    # 當前的位移
    current=0
    # 到達mid值開始減速
    mid=distance * 7/8
    print("distance",distance)
    global random_int
    random_int=8
    distance += random_int # 先滑過一點,最后再反着滑動回來

    while current < distance:
        if current < mid:
            # 加速度越小,單位時間的位移越小,模擬的軌跡就越多越詳細
            a = random.randint(2,5)  # 加速運動
        else:
            a = -random.randint(2,5) # 減速運動
        # 初速度
        v0 = v
        # 0.2秒時間內的位移
        s = v0*t+0.5*a*(t**2)
        # 當前的位置
        current += s
        # 添加到軌跡列表
        if round(s)>0:
            tracks.append(round(s))
        else:
            tracks_back.append(round(s))


        # 速度已經達到v,該速度作為下次的初速度
        v= v0+a*t

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

    # 反着滑動到大概准確位置

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

    return tracks,tracks_back


def get_distance(image1,image2):
    '''
       拿到滑動驗證碼需要移動的距離
      :param image1:沒有缺口的圖片對象
      :param image2:帶缺口的圖片對象
      :return:需要移動的距離
      '''
    # 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]) # 計算RGB差
            res_G = abs(pixel1[1] - pixel2[1])  # 計算RGB差
            res_B = abs(pixel1[2] - pixel2[2])  # 計算RGB差
            if res_R > threshold and res_G > threshold and res_B > threshold:
                return i  # 需要移動的距離


def main_check_code(driver,element):
    """
    拖動識別驗證碼
    :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')
    # 圖片上 缺口的位置的x坐標

    # 2 對比兩張圖片的所有RBG像素點,得到不一樣像素點的x值,即要移動的距離
    l = get_distance(image1, image2)
    print('l=',l)

    # 3 獲得移動軌跡
    track_list = get_track(l)
    print('第一步,點擊滑動按鈕')
    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()  # 點擊鼠標左鍵,按住不放
    import time
    time.sleep(0.4)
    print('第二步,拖動元素')
    for track in track_list[0]:
         ActionChains(driver).move_by_offset(xoffset=track, yoffset=0).perform()  # 鼠標移動到距離當前位置(x,y)
    #time.sleep(0.4)
    for track in track_list[1]:
          ActionChains(driver).move_by_offset(xoffset=track, yoffset=0).perform()  # 鼠標移動到距離當前位置(x,y)
          time.sleep(0.1)
    import time
    time.sleep(0.6)
    # ActionChains(driver).move_by_offset(xoffset=2, yoffset=0).perform()  # 鼠標移動到距離當前位置(x,y)
    # ActionChains(driver).move_by_offset(xoffset=8, yoffset=0).perform()  # 鼠標移動到距離當前位置(x,y)
    # ActionChains(driver).move_by_offset(xoffset=2, yoffset=0).perform()  # 鼠標移動到距離當前位置(x,y)
    print('第三步,釋放鼠標')
    ActionChains(driver).release(on_element=element).perform()
    time.sleep(1)

def main_check_slider(driver):
    """
    檢查滑動按鈕是否加載
    :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('超時錯誤,繼續')
            time.sleep(5)

if __name__ == '__main__':

    try:
        count = 3  # 最多識別3次
        driver = webdriver.Chrome()
        while count > 0:
            # 等待滑動按鈕加載完成
            element = main_check_slider(driver)
            main_check_code(driver,element)
            try:
                success_element = (By.CSS_SELECTOR, '.gt_success')
                # 得到成功標志
                success_images = WebDriverWait(driver,3).until(EC.presence_of_element_located(success_element))
                if success_images:
                    print('成功識別!!!!!!')
                    count = 0
                    import sys
                    sys.exit()
            except Exception as e:
                print('識別錯誤,繼續')
                count -= 1
                time.sleep(1)
        else:
            print('too many attempt check code ')
            exit('退出程序')
    finally:
        driver.close()

 

另一參考博客: https://blog.csdn.net/yinanmo5569/article/details/81712731


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