[python] 使用OpenCV、selenium解决【滑块验证码】

• 弹出滑块验证码后使用selenium元素截图将验证码整个背景图截取出来
  
• 将需要滑动的小图单独截取出来，最好将小图与背景图顶部的像素距离获取到，这样可以将背景图上下多余的边框截取掉
  
• 使用OpenCV将背景图和小图进行灰度处理，并对小图再次进行二值化全局阈值，这样就可以利用OpenCV在背景图中找到小图所在的位置
  
• 用OpenCV获取到相差的距离后利用selenium的鼠标拖动方法进行拖拉至终点。
  

import os
from selenium import webdriver

browser = webdriver.Chrome()
browser.get("https://www.toutiao.com/c/user/token/MS4wLjABAAAA4EKNlqVeNTTuEdWn0VytNS8cdODKTsNNwLTxOnigzZtclro2Kylvway5mTyTUKvz/")
save_path = os.path.join(os.path.expanduser('~'), "Desktop", "background.png")
browser.find_element_by_id("element_id_name").screenshot(save_path)

   

element_object = browser.find_element_by_xpath("xpath_element")
px = element_object.value_of_css_property("top")

import numpy
import cv2

def make_threshold(img):
  """全局阈值
  将图片二值化,去除噪点,让其黑白分明"""
  x = numpy.ones(img.shape, numpy.uint8) * 255
  y = img - x
  result, thresh = cv2.threshold(y, 127, 255, cv2.THRESH_BINARY_INV)
  # 将二值化后的结果返回
  return thresh

class ComputeDistance:
  """获取需要滑动的距离
  将验证码背景大图和需要滑动的小图进行处理,先在大图中找到相似的小图位置,再获取对应的像素偏移量"""
  def __init__(self, Background_path: str, image_to_move: str, offset_top_px: int):
    """
    :param Background_path: 验证码背景大图
    :param image_to_move: 需要滑动的小图
    :param offset_top_px: 小图距离在大图上的顶部边距(像素偏移量)
    """
    self.Background_img = cv2.imread(Background_path)
    self.offset_px = offset_top_px
    self.show_img = show_img
    small_img_data = cv2.imread(image_to_move, cv2.IMREAD_UNCHANGED)
    # 得到一个改变维度为50的乘以值
    scaleX = 50 / small_img_data.shape[1]
    # 使用最近邻插值法缩放，让xy乘以scaleX，得到缩放后shape为50x50的图片
    self.tpl_img = cv2.resize(small_img_data, (0, 0), fx=scaleX, fy=scaleX)
    self.Background_cutting = None
  def tpl_op(self):
    # 将小图转换为灰色
    tpl_gray = cv2.cvtColor(self.tpl_img, cv2.COLOR_BGR2GRAY)
    h, w = tpl_gray.shape
    # 将背景图转换为灰色
    # Background_gray = cv2.cvtColor(self.Background_img, cv2.COLOR_BGR2GRAY)
    Background_gray = cv2.cvtColor(self.Background_cutting, cv2.COLOR_BGR2GRAY)
    # 得到二值化后的小图
    threshold_img = make_threshold(tpl_gray)
    # 将小图与大图进行模板匹配,找到所对应的位置
    result = cv2.matchTemplate(Background_gray, threshold_img, cv2.TM_CCOEFF_NORMED)
    min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)
    # 左上角位置
    top_left = (max_loc[0] - 5, max_loc[1] + self.offset_px)
    # 右下角位置
    bottom_right = (top_left[0] + w, top_left[1] + h)
    # 在源颜色大图中画出小图需要移动到的终点位置
    """rectangle(图片源数据, 左上角, 右下角, 颜色, 画笔厚度)"""
    cv2.rectangle(self.Background_img, top_left, bottom_right, (0, 0, 255), 2)
  def cutting_background(self):
    """切割图片的上下边框"""
    height = self.tpl_img.shape[0]
    # 将大图中上下多余部分去除,如: Background_img[40:110, :]
    self.Background_cutting = self.Background_img[self.offset_px - 10: self.offset_px + height + 10, :]
  def run(self):
    # 如果小图的长度与大图的长度一致则不用将大图进行切割,可以将self.cutting_background()注释掉
    self.cutting_background()
    return self.tpl_op()

if __name__ == '__main__':
  image_path1 = "背景图路径"
  image_path2 = "小图路径"
  distance_px = "像素距离"
  main = ComputeDistance(image_path1, image_path2, distance_px)
  main.run()

     

def handle_distance(distance):
  """将直线距离转为缓慢的轨迹"""
  import random
  slow_distance = []
  while sum(slow_distance) <= distance:
    slow_distance.append(random.randint(-2, 15))
  if sum(slow_distance) != distance:
    slow_distance.append(distance - sum(slow_distance))
  return slow_distance

import time
from random import randint
from selenium.webdriver.common.action_chains import ActionChains

def move_slider(website, slider, track, **kwargs):
  """将滑块移动到终点位置
  :param website: selenium页面对象
  :param slider: selenium页面中滑块元素对象
  :param track: 到终点所需的距离
  """
  name = kwargs.get('name', '滑块')
  try:
    if track[0] > 200:
      return track[0]
    # 点击滑块元素并拖拽
    ActionChains(website).click_and_hold(slider).perform()
    time.sleep(0.15)
    for i in track:
      # 随机上下浮动鼠标
      ActionChains(website).move_by_offset(xoffset=i, yoffset=randint(-2, 2)).perform()
    # 释放元素
    time.sleep(1)
    ActionChains(website).release(slider).perform()
    time.sleep(1)
    # 随机拿开鼠标
    ActionChains(website).move_by_offset(xoffset=randint(200, 300), yoffset=randint(200, 300)).perform()
    print(f'[网页] 拖拽 {name}')
    return True
  except Exception as e:
    print(f'[网页] 拖拽 {name} 失败 {e}')

访问今日头条某博主的主页，直接打开主页的链接会出现验证码。
下面代码 使用pip安装好相关依赖库后可直接运行：

import os
import time
import requests
import cv2
import numpy
from random import randint
from selenium import webdriver
from selenium.webdriver.common.action_chains import ActionChains

def show_image(img_array, name='img', resize_flag=False):
  """展示图片"""
  maxHeight = 540
  maxWidth = 960
  scaleX = maxWidth / img_array.shape[1]
  scaleY = maxHeight / img_array.shape[0]
  scale = min(scaleX, scaleY)
  if resize_flag and scale < 1:
    img_array = cv2.resize(img_array, (0, 0), fx=scale, fy=scale)
  cv2.imshow(name, img_array)
  cv2.waitKey(0)
  cv2.destroyWindow(name)

def make_threshold(img):
  """全局阈值
  将图片二值化,去除噪点,让其黑白分明"""
  x = numpy.ones(img.shape, numpy.uint8) * 255
  y = img - x
  result, thresh = cv2.threshold(y, 127, 255, cv2.THRESH_BINARY_INV)
  # 将二值化后的结果返回
  return thresh

def move_slider(website, slider, track, **kwargs):
  """将滑块移动到终点位置
  :param website: selenium页面对象
  :param slider: selenium页面中滑块元素对象
  :param track: 到终点所需的距离
  """
  name = kwargs.get('name', '滑块')
  try:
    if track[0] > 200:
      return track[0]
    # 点击滑块元素并拖拽
    ActionChains(website).click_and_hold(slider).perform()
    time.sleep(0.15)
    for i in track:
      # 随机上下浮动鼠标
      ActionChains(website).move_by_offset(xoffset=i, yoffset=randint(-2, 2)).perform()
    # 释放元素
    time.sleep(1)
    ActionChains(website).release(slider).perform()
    time.sleep(1)
    # 随机拿开鼠标
    ActionChains(website).move_by_offset(xoffset=randint(200, 300), yoffset=randint(200, 300)).perform()
    print(f'[网页] 拖拽 {name}')
    return True
  except Exception as e:
    print(f'[网页] 拖拽 {name} 失败 {e}')

class ComputeDistance:
  """获取需要滑动的距离
  将验证码背景大图和需要滑动的小图进行处理,先在大图中找到相似的小图位置,再获取对应的像素偏移量"""
  def __init__(self, Background_path: str, image_to_move: str, offset_top_px: int, show_img=False):
    """
    :param Background_path: 验证码背景大图
    :param image_to_move: 需要滑动的小图
    :param offset_top_px: 小图距离在大图上的顶部边距(像素偏移量)
    :param show_img: 是否展示图片
    """
    self.Background_img = cv2.imread(Background_path)
    self.offset_px = offset_top_px
    self.show_img = show_img
    small_img_data = cv2.imread(image_to_move, cv2.IMREAD_UNCHANGED)
    # 得到一个改变维度为50的乘以值
    scaleX = 50 / small_img_data.shape[1]
    # 使用最近邻插值法缩放，让xy乘以scaleX，得到缩放后shape为50x50的图片
    self.tpl_img = cv2.resize(small_img_data, (0, 0), fx=scaleX, fy=scaleX)
    self.Background_cutting = None
  def show(self, img):
    if self.show_img:
      show_image(img)
  def tpl_op(self):
    # 将小图转换为灰色
    tpl_gray = cv2.cvtColor(self.tpl_img, cv2.COLOR_BGR2GRAY)
    h, w = tpl_gray.shape
    # 将背景图转换为灰色
    # Background_gray = cv2.cvtColor(self.Background_img, cv2.COLOR_BGR2GRAY)
    Background_gray = cv2.cvtColor(self.Background_cutting, cv2.COLOR_BGR2GRAY)
    # 得到二值化后的小图
    threshold_img = make_threshold(tpl_gray)
    # 将小图与大图进行模板匹配,找到所对应的位置
    result = cv2.matchTemplate(Background_gray, threshold_img, cv2.TM_CCOEFF_NORMED)
    min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)
    # 左上角位置
    top_left = (max_loc[0] - 5, max_loc[1] + self.offset_px)
    # 右下角位置
    bottom_right = (top_left[0] + w, top_left[1] + h)
    # 在源颜色大图中画出小图需要移动到的终点位置
    """rectangle(图片源数据, 左上角, 右下角, 颜色, 画笔厚度)"""
    cv2.rectangle(self.Background_img, top_left, bottom_right, (0, 0, 255), 2)
    if self.show_img:
      show_image(self.Background_img)
    return top_left
  def cutting_background(self):
    """切割图片的上下边框"""
    height = self.tpl_img.shape[0]
    # 将大图中上下多余部分去除,如: Background_img[40:110, :]
    self.Background_cutting = self.Background_img[self.offset_px - 10: self.offset_px + height + 10, :]
  def run(self):
    # 如果小图的长度与大图的长度一致则不用将大图进行切割,可以将self.cutting_background()注释掉
    self.cutting_background()
    return self.tpl_op()

class TodayNews(object):
  def __init__(self):
    self.url = "https://www.toutiao.com/c/user/token/" \
           "MS4wLjABAAAA4EKNlqVeNTTuEdWn0VytNS8cdODKTsNNwLTxOnigzZtclro2Kylvway5mTyTUKvz/"
    self.process_folder = os.path.join(os.path.expanduser('~'), "Desktop", "today_news")
    self.background_path = os.path.join(self.process_folder, "background.png")
    self.small_path = os.path.join(self.process_folder, "small.png")
    self.small_px = None
    self.xpath = {}
    self.browser = None
  def check_file_exist(self):
    """检查流程目录是否存在"""
    if not os.path.isdir(self.process_folder):
      os.mkdir(self.process_folder)
  def start_browser(self):
    """启动浏览器"""
    self.browser = webdriver.Chrome()
    self.browser.maximize_window()
  def close_browser(self):
    self.browser.quit()
  def wait_element_loaded(self, xpath: str, timeout=10, close_browser=True):
    """等待页面元素加载完成
    :param xpath: xpath表达式
    :param timeout: 最长等待超时时间
    :param close_browser: 元素等待超时后是否关闭浏览器
    :return: Boolean
    """
    now_time = int(time.time())
    while int(time.time()) - now_time < timeout:
      # noinspection PyBroadException
      try:
        element = self.browser.find_element_by_xpath(xpath)
        if element:
          return True
        time.sleep(1)
      except Exception:
        pass
    else:
      if close_browser:
        self.close_browser()
      # print("查找页面元素失败，如果不存在网络问题请尝试修改xpath表达式")
      return False
  def add_page_element(self):
    self.xpath['background_img'] = '//div[@role="dialog"]/div[2]/img[1]'
    self.xpath['small_img'] = '//div[@role="dialog"]/div[2]/img[2]'
    self.xpath['slider_button'] = '//div[@id="secsdk-captcha-drag-wrapper"]/div[2]'
  def process_main(self):
    """处理页面内容"""
    self.browser.get(self.url)
    for _ in range(10):
      if self.wait_element_loaded(self.xpath['background_img'], timeout=5, close_browser=False):
        time.sleep(1)
        # 截图
        self.browser.find_element_by_xpath(self.xpath['background_img']).screenshot(self.background_path)
        small_img = self.browser.find_element_by_xpath(self.xpath['small_img'])
        # 获取小图片的URL链接
        small_url = small_img.get_attribute("src")
        # 获取小图片距离背景图顶部的像素距离
        self.small_px = small_img.value_of_css_property("top").replace("px", "").split(".")[0]
        response = requests.get(small_url)
        if response.ok:
          with open(self.small_path, "wb") as file:
            file.write(response.content)
        time.sleep(1)
        # 如果没滑动成功则刷新页面重试
        if not self.process_slider():
          self.browser.refresh()
          continue
      else:
        break
  @staticmethod
  def handle_distance(distance):
    """将直线距离转为缓慢的轨迹"""
    import random
    slow_distance = []
    while sum(slow_distance) <= distance:
      slow_distance.append(random.randint(-2, 15))
    if sum(slow_distance) != distance:
      slow_distance.append(distance - sum(slow_distance))
    return slow_distance
  def process_slider(self):
    """处理滑块验证码"""
    distance_obj = ComputeDistance(self.background_path, self.small_path, int(self.small_px), show_img=False)
    # 获取移动所需的距离
    distance = distance_obj.run()
    track = self.handle_distance(distance[0])
    track.append(-2)
    slider_element = self.browser.find_element_by_xpath(self.xpath['slider_button'])
    move_slider(self.browser, slider_element, track)
    time.sleep(2)
    # 如果滑动完成则返回True
    if not self.wait_element_loaded(self.xpath['slider_button'], timeout=2, close_browser=False):
      return True
    else:
      return False
  def run(self):
    self.check_file_exist()
    self.start_browser()
    self.add_page_element()
    self.process_main()
    # self.close_browser()

if __name__ == '__main__':
  main = TodayNews()
  main.run()