Method predict

predict.py:80–194

Enhance a video by increasing its frame rate using frame interpolation. Parameters: - mp4 (Path): Path to the video file. - keep_original_duration (bool): Indicator to maintain the original video duration after frame interpolation. - custom_fps (float): Targ

(
        self,
        mp4: Path = Input(description="Upload an mp4 video file."),
        framerate_multiplier: int = Input(
            description="Determines how many intermediate frames to generate between original frames. E.g., a value of 2 will double the frame rate, and 4 will quadruple it, etc.",
            default=2,
            choices=[2, 4, 8, 16, 32],
        ),
        keep_original_duration: bool = Input(
            description="Should the enhanced video retain the original duration? If set to `True`, the model will adjust the frame rate to maintain the video's original duration after adding interpolated frames. If set to `False`, the frame rate will be set based on `custom_fps`.",
            default=True,
        ),
        custom_fps: float = Input(
            description="Set `keep_original_duration` to `False` to use this! Desired frame rate (fps) for the enhanced video. This will only be considered if `keep_original_duration` is set to `False`.",
            default=None,
            ge=1,
            le=240,
        ),
    )

            os.makedirs(out_dir)

    def predict(
        self,
        mp4: Path = Input(description="Upload an mp4 video file."),
        framerate_multiplier: int = Input(
            description="Determines how many intermediate frames to generate between original frames. E.g., a value of 2 will double the frame rate, and 4 will quadruple it, etc.",
            default=2,
            choices=[2, 4, 8, 16, 32],
        ),
        keep_original_duration: bool = Input(
            description="Should the enhanced video retain the original duration? If set to `True`, the model will adjust the frame rate to maintain the video's original duration after adding interpolated frames. If set to `False`, the frame rate will be set based on `custom_fps`.",
            default=True,
        ),
        custom_fps: float = Input(
            description="Set `keep_original_duration` to `False` to use this! Desired frame rate (fps) for the enhanced video. This will only be considered if `keep_original_duration` is set to `False`.",
            default=None,
            ge=1,
            le=240,
        ),
    ) -> Iterator[Path]:
        """
        Enhance a video by increasing its frame rate using frame interpolation.

        Parameters:
        - mp4 (Path): Path to the video file.
        - keep_original_duration (bool): Indicator to maintain the original video duration after frame interpolation.
        - custom_fps (float): Target frame rate for the enhanced video when not maintaining the original duration.
        - framerate_multiplier (int): Multiplier for the number of frames.

        Returns:
        Iterator[Path]: Paths to the generated enhanced video files.
        """

        num_iterations = int(math.log2(framerate_multiplier))
        original_seq_name = os.path.basename(mp4).split(".")[0]

        for enhancing_iteration in tqdm(range(num_iterations), desc="Enhancing iterations"):
            # Opening the video and extracting essential properties
            video = cv2.VideoCapture(str(mp4))
            original_video_fps = video.get(cv2.CAP_PROP_FPS)
            width, height = int(video.get(cv2.CAP_PROP_FRAME_WIDTH)), int(video.get(cv2.CAP_PROP_FRAME_HEIGHT))
            original_num_frames = sum(video.read()[0] for _ in range(int(video.get(cv2.CAP_PROP_FRAME_COUNT))))

            # Informing the user of video details before processing
            print(f"Video Name: {original_seq_name}")
            print(f"Original Frame Rate (FPS): {original_video_fps}")
            print(f"Original Total Number of Frames: {original_num_frames}")

            img_array = []
            # Processing each set of 4 frames for frame rate enhancement
            for t in tqdm(range(0, original_num_frames - 3), desc="Processing frames"):
                video.set(cv2.CAP_PROP_POS_FRAMES, t)
                _, rawFrame0 = video.read()
                _, rawFrame1 = video.read()
                _, rawFrame2 = video.read()
                _, rawFrame3 = video.read()

                # If any frame in the set of 4 is missing, stop processing
                if any(frame is None for frame in [rawFrame0, rawFrame1, rawFrame2, rawFrame3]):