def METHOD_NAME(self, bbox_list, MOT_flag):
    kwargs = {'num_workers': 0, 'pin_memory': True}
    if self.frame is not None:
        bbox_loader_class = ResnetDataLoader(bbox_list, self._transform, 
                                            self.frame, self._img_size)
    else:
        raise ValueError("Trying to create ResenetDataLoader without a frame")
    bbox_loader = torch.utils.data.DataLoader(bbox_loader_class, 
                            batch_size=self._b_size, shuffle=False, **kwargs)
    torch.set_grad_enabled(False)
    for idx, imgs in enumerate(bbox_loader):
        v_imgs = imgs.to(self._device)
        output = self._resnet_model(v_imgs)
        if idx == 0:
            app_features = output.data
        else:
            app_features = torch.cat((app_features, output.data), dim=0)
    return app_features.cpu()