def read_frame(self, video_path, bound=None, fps=3):
        """
        Reads frames from a video directory, processes them, and returns a tensor of images.

        Args:
            video_path (str): Path to the directory containing video frames.
            bound (tuple, optional): A tuple specifying the range of frames to read. Defaults to None.
            fps (int, optional): Frames per second to sample from the video. Defaults to 3.

        Returns:
            torch.Tensor: A tensor containing the processed images.
        """
        max_frame = len(os.listdir(video_path))
        images_group = list()
        frame_indices = self.get_index(bound, fps, max_frame, first_idx=1)  # frame_idx starts from 1
        for frame_index in frame_indices:
            img = Image.open(os.path.join(video_path, f'{frame_index:05d}.jpg'))
            images_group.append(img)
        torch_imgs = self.transform(images_group)
        return torch_imgs

        Reads frames from a video directory, processes them, and returns a tensor of images.

        Args:
            video_path (str): Path to the directory containing video frames.
            bound (tuple, optional): A tuple specifying the range of frames to read. Defaults to None.
            fps (int, optional): Frames per second to sample from the video. Defaults to 3.

        Returns:
            torch.Tensor: A tensor containing the processed images.
        
vlmeval/dataset/tamperbench.py