极验验证码

 

from selenium import webdriver
from selenium.webdriver import ActionChains
from selenium.webdriver.common.by import By
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.support.wait import WebDriverWait
from PIL import Image
import time

def get_snap():
    driver.save_screenshot('full_snap.png')
    page_snap_obj=Image.open('full_snap.png')
    return page_snap_obj

def get_image():
    img=driver.find_element_by_class_name('geetest_canvas_img')
    time.sleep(2)
    location=img.location
    size=img.size

    left=location['x']
    top=location['y']
    right=left+size['width']
    bottom=top+size['height']

    page_snap_obj=get_snap()
    image_obj=page_snap_obj.crop((left,top,right,bottom))
    # image_obj.show()
    return image_obj

def get_distance(image1,image2):
    start=57
    threhold=60

    for i in range(start,image1.size[0]):
        for j in range(image1.size[1]):
            rgb1=image1.load()[i,j]
            rgb2=image2.load()[i,j]
            res1=abs(rgb1[0]-rgb2[0])
            res2=abs(rgb1[1]-rgb2[1])
            res3=abs(rgb1[2]-rgb2[2])
            # print(res1,res2,res3)
            if not (res1 < threhold and res2 < threhold and res3 < threhold):
                return i-7
    return i-7

def get_tracks(distance):
    distance+=20 #先滑过一点，最后再反着滑动回来
    v=0
    t=0.2
    forward_tracks=[]

    current=0
    mid=distance*3/5
    while current < distance:
        if current < mid:
            a=2
        else:
            a=-3

        s=v*t+0.5*a*(t**2)
        v=v+a*t
        current+=s
        forward_tracks.append(round(s))

    #反着滑动到准确位置
    back_tracks=[-3,-3,-2,-2,-2,-2,-2,-1,-1,-1]  #总共等于-20

    return {'forward_tracks':forward_tracks,'back_tracks':back_tracks}

try:
    # 1、输入账号密码回车
    driver = webdriver.Chrome()
    driver.implicitly_wait(3)
    driver.get('https://passport.cnblogs.com/user/signin')

    username = driver.find_element_by_id('input1')
    pwd = driver.find_element_by_id('input2')
    signin = driver.find_element_by_id('signin')

    username.send_keys('linhaifeng')
    pwd.send_keys('xxxxx')
    signin.click()

    # 2、点击按钮，得到没有缺口的图片
    button = driver.find_element_by_class_name('geetest_radar_tip')
    button.click()

    # 3、获取没有缺口的图片
    image1 = get_image()

    # 4、点击滑动按钮，得到有缺口的图片
    button = driver.find_element_by_class_name('geetest_slider_button')
    button.click()

    # 5、获取有缺口的图片
    image2 = get_image()

    # 6、对比两种图片的像素点，找出位移
    distance = get_distance(image1, image2)

    # 7、模拟人的行为习惯，根据总位移得到行为轨迹
    tracks = get_tracks(distance)
    print(tracks)

    # 8、按照行动轨迹先正向滑动，后反滑动
    button = driver.find_element_by_class_name('geetest_slider_button')
    ActionChains(driver).click_and_hold(button).perform()

    # 开始正向滑动，加速
    for track in tracks['forward_tracks']:
        ActionChains(driver).move_by_offset(xoffset=track, yoffset=0).perform()

    # 停顿了一下，发现滑过了,然后开始反向滑动
    time.sleep(0.5)
    for back_track in tracks['back_tracks']:
        ActionChains(driver).move_by_offset(xoffset=back_track, yoffset=0).perform()

    # 小范围震荡一下，进一步迷惑极验后台，这一步可以极大地提高成功率
    ActionChains(driver).move_by_offset(xoffset=-3, yoffset=0).perform()
    ActionChains(driver).move_by_offset(xoffset=3, yoffset=0).perform()

    # 成功后，睡一下
    time.sleep(0.5)
    ActionChains(driver).release().perform()

    time.sleep(3)  # 睡时间长一点，确定登录成功
finally:
    driver.close()