登录163邮箱的滑块验证

登录163网易邮箱取数功能，查阅了很多博客的代码都不太稳定或者已失效，下面是经过修改的一个方案，成功率大概在90%以上

def get_verify(self, name='处理滑块移动'):max_distance = self.handle_picture()reality_distance = int((max_distance - 64) / 1.45)sleep(0.5)track_list = self.handle_tracks(reality_distance)# 获取滑块元素slider_handle = self.driver.find_element(By.XPATH, '//*[@class="yidun_slider"]')ActionChains(self.driver).click_and_hold(slider_handle).perform()for i in track_list:ActionChains(self.driver).move_by_offset(i, 0).perform()sleep(1)ActionChains(self.driver).release().perform()def handle_picture(self):bg_img = re.findall(r'alt="验证码背景".*?src="(.*?)"', self.driver.page_source)[0]hk_img = re.findall(r'alt="验证码滑块".*?src="(.*?)"', self.driver.page_source)[0]with open('./bg_img.jpg', 'wb') as f:f.write(requests.get(bg_img).content)f.close()with open('./hk_img.png', 'wb') as f:f.write(requests.get(hk_img).content)f.close()# 读取背景图片和缺口图片bg_img = cv2.imread('./bg_img.jpg')  # 背景图片tp_img = cv2.imread('./hk_img.png')  # 缺口图片# 识别图片边缘bg_edge = cv2.Canny(bg_img, 100, 200)tp_edge = cv2.Canny(tp_img, 100, 200)# 转换图片格式bg_pic = cv2.cvtColor(bg_edge, cv2.COLOR_GRAY2RGB)tp_pic = cv2.cvtColor(tp_edge, cv2.COLOR_GRAY2RGB)# 缺口匹配res = cv2.matchTemplate(bg_pic, tp_pic, cv2.TM_CCOEFF_NORMED)min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)  # 寻找最优匹配x = max_loc[0]  # 滑块在验证图片的x坐标（左边）# 绘制方框th, tw = tp_pic.shape[:2]tl = max_loc  # 左上角点的坐标br = (tl[0] + tw, tl[1] + th)  # 右下角点的坐标cv2.rectangle(bg_img, tl, br, (0, 0, 255), 2)  # 绘制矩形# cv2.imwrite(r'C:\test\out.jpg', bg_img)  # 保存在本地return int(br[0])@staticmethod
def handle_tracks(distance):t = 0.1speed = 0current = 0mid = 3 / 5 * distancetrack_list = []while current < distance:if current < mid:# a = random.choice([1, 2, 3])a = 3else:# a = random.choice([-1, -2, -3])a = -4move_track = speed * t + 0.5 * a * t ** 2track_list.append(round(move_track))speed = speed + a * tcurrent += move_track# 模拟人类来回移动了一小段end_track = [1, 0] * 10 + [0] * 10 + [-1, 0] * 10track_list.extend(end_track)offset = sum(track_list) - distance# 由于四舍五入带来的误差,这里需要补回来if offset > 0:track_list.extend(offset * [-1, 0])elif offset < 0:track_list.extend(offset * [1, 0])return track_list