python滑塊驗(yàn)證碼的破解實(shí)現(xiàn)

def get_image1(self,driver):
  """
  獲取滑塊驗(yàn)證缺口小圖片
  :param driver:chrome對象
  :return:缺口小圖片
  """
  canvas = driver.find_element_by_xpath("http://div[@id='xy_img']").get_attribute("style")
  image_data=re.findall("data:image/jpg;base64,(.*?)\"\)",canvas)[0]
  # print(image_data)
  binary_image_data=base64.b64decode(image_data,'-_')
  file_like=BytesIO(binary_image_data)
  image=Image.open(file_like)
  return image

def get_image2(self,driver):
  """
  獲取滑塊驗(yàn)證碼背景圖片
  :param driver:chrome對象
  :return:背景圖片
   """
  driver.save_screenshot('yanzhengma.png')
  # 通過圖片元素節(jié)點(diǎn)獲取坐標(biāo)值
  # element = driver.find_element_by_id("bgImg")
  # left = element.location['x']
  # top = element.location['y']
  # right = element.location['x'] + element.size['width']
  # bottom = element.location['y'] + element.size['height']
  # 通過畫圖軟件直接獲取相應(yīng)圖片的坐標(biāo)值
  left=359
  top=238
  right=658
  bottom=437
  # print((left, top, right, bottom))
  im = Image.open('yanzhengma.png')
  im = im.crop((left, top, right, bottom))
  return im

def get_track(self, distance):
  """
  根據(jù)偏移量獲取移動軌跡
  :param distance:偏移量
  :return:移動軌跡
  """
  # 移動軌跡
  track = []
  # 當(dāng)前位移
  current = 0
  # 減速閾值
  mid = distance * 4 / 5
  # 計算間隔
  t = 0.2
  # 初速度
  v = 0

  while current < distance:
    if current < mid:
      # 加速度為正2
      a = 2
    else:
      # 加速度為負(fù)3
      a = -3
    # 初速度v0
    v0 = v
    # 當(dāng)前速度v = v0 + at
    v = v0 + a * t
    # 移動距離x = v0t + 1/2 * a * t^2
    move = v0 * t + 1 / 2 * a * t * t
    # 當(dāng)前位移
    current += move
    # 加入軌跡
    track.append(round(move))
  return track

 def slider_verification_code(self,driver,cnt):
  """
  破解滑塊驗(yàn)證主程序
  :param driver:chrome對象；cnt：已驗(yàn)證次數(shù)
  :return:已驗(yàn)證次數(shù)
  """
  print("出現(xiàn)滑塊驗(yàn)證，驗(yàn)證中")
  # 1、出現(xiàn)滑塊驗(yàn)證，獲取驗(yàn)證小圖片
  picture1 = self.get_image1(driver)
  picture1.save("./picture1.png")
  # 2、獲取有缺口驗(yàn)證圖片
  picture2 = self.get_image2(driver)
  picture2.save("./picture2.png")
  #二值化圖片,進(jìn)行對比，輸出匹配的坐標(biāo)系
  target_rgb=cv2.imread("./picture2.png")
  target_gray=cv2.cvtColor(target_rgb,cv2.COLOR_BGR2GRAY)
  template_rgb=cv2.imread("./picture1.png",0)
  res=cv2.matchTemplate(target_gray,template_rgb,cv2.TM_CCOEFF_NORMED)
  value=cv2.minMaxLoc(res)
  value = value[3][0]
  cnt += 1
  print("需要位移的距離為："+str(value)+",已驗(yàn)證"+str(cnt)+"次")
  #根據(jù)距離獲取位移的軌跡路線
  track=self.get_track(value)
  time.sleep(1)
  ActionChains(driver).click_and_hold(driver.find_element_by_class_name("handler.handler_bg")).perform()
  for x in track:
    ActionChains(driver).move_by_offset(xoffset=x, yoffset=0).perform()
  time.sleep(0.5)
  ActionChains(driver).release().perform()
  return cnt