text: # --------------------------------------------------------
  # SiamMask
  # Licensed under The MIT License
  # Written by Qiang Wang (wangqiang2015 at ia.ac.cn)
  # --------------------------------------------------------
  import glob
  from tools.test import *
  
  parser = argparse.ArgumentParser(description='PyTorch Tracking Demo')
  
  parser.add_argument('--resume', default='', type=str, required=True,
                      metavar='PATH',help='path to latest checkpoint (default: none)')
  parser.add_argument('--config', dest='config', default='config_davis.json',
                      help='hyper-parameter of SiamMask in json format')
  parser.add_argument('--base_path', default='../../data/tennis', help='datasets')
  args = parser.parse_args()
  
  if __name__ == '__main__':
      # Setup device
      device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
      torch.backends.cudnn.benchmark = True
  
      # Setup Model
      cfg = load_config(args)
      from custom import Custom
      siammask = Custom(anchors=cfg['anchors'])
      if args.resume:
          assert isfile(args.resume), '{} is not a valid file'.format(args.resume)
          siammask = load_pretrain(siammask, args.resume)
  
      siammask.eval().to(device)
  
      # Parse Image file
      img_files = sorted(glob.glob(join(args.base_path, '*.jp*')))
      ims = [cv2.imread(imf) for imf in img_files]
  
      # Select ROI
      cv2.namedWindow("SiamMask", cv2.WND_PROP_FULLSCREEN)
      # cv2.setWindowProperty("SiamMask", cv2.WND_PROP_FULLSCREEN, cv2.WINDOW_FULLSCREEN)
      try:
          init_rect = cv2.selectROI('SiamMask', ims[0], False, False)
          x, y, w, h = init_rect
      except:
          exit()
  
      toc = 0
      for f, im in enumerate(ims):
          tic = cv2.getTickCount()
          if f == 0:  # init
              target_pos = np.array([x + w / 2, y + h / 2])
              target_sz = np.array([w, h])
              state = siamese_init(im, target_pos, target_sz, siammask, cfg['hp'])  # init tracker
          elif f > 0:  # tracking
              state = siamese_track(state, im, mask_enable=True, refine_enable=True)  # track
              location = state['ploygon'].flatten()
              mask = state['mask'] > state['p'].seg_thr
  
              im[:, :, 2] = (mask > 0) * 255 + (mask == 0) * im[:, :, 2]
              cv2.polylines(im, [np.int0(location).reshape((-1, 1, 2))], True, (0, 255, 0), 3)
              cv2.imshow('SiamMask', im)
              key = cv2.waitKey(1)
              if key > 0:
                  break
  
          toc += cv2.getTickCount() - tic
      toc /= cv2.getTickFrequency()
      fps = f / toc
      print('SiamMask Time: {:02.1f}s Speed: {:3.1f}fps (with visulization!)'.format(toc, fps))
  