          A list of :class:`~lib.align.DetectedFace` objects. Detected faces can be added
          later with :func:`add_detected_faces`. Default: ``None``
      """
  
      def __init__(self, filename, image, detected_faces=None):
          logger.trace("Initializing %s: (filename: '%s', image shape: %s, detected_faces: %s)",
                       self.__class__.__name__, filename, image.shape, detected_faces)
          self._filename = filename
          self._image = image
          self._image_shape = image.shape
          self._detected_faces = detected_faces
  
 
</s> remove         later with :func:`add_detected_faces`. Default: ``None``
 </s> add         later with :func:`add_detected_faces`. Setting ``None`` will default to an empty list.
        Default: ``None`` </s> remove         self._image = image
        self._image_shape = image.shape
        self._detected_faces = detected_faces
 </s> add         self._image: Optional["np.ndarray"] = image
        self._image_shape = cast(Tuple[int, int, int], image.shape)
        self._detected_faces: List["DetectedFace"] = ([] if detected_faces is None
                                                      else detected_faces) </s> remove     def filename(self):
 </s> add     def filename(self) -> str: </s> remove         logger.trace("Received frame: (filename: '%s', shape: %s", filename, image.shape)
 </s> add         logger.trace("Received frame: (filename: '%s', shape: %s",  # type: ignore
                     filename, image.shape) </s> remove     def __init__(self, size, padding, tk_vars):
        logger.trace("Initializing %s: (size: %s, padding: %s, tk_vars: %s)",
 </s> add     def __init__(self,
                 size: int,
                 padding: int,
                 tk_vars: Dict[Literal["refresh", "busy"], tk.BooleanVar]) -> None:
        logger.trace("Initializing %s: (size: %s, padding: %s, tk_vars: %s)",  # type: ignore
    def __init__(self,
                 filename: str,
                 image: "np.ndarray",
                 detected_faces: Optional[List["DetectedFace"]] = None) -> None:
        logger.trace("Initializing %s: (filename: '%s', image shape: %s, "  # type: ignore
                     "detected_faces: %s)", self.__class__.__name__, filename, image.shape,
                     detected_faces)
          A list of :class:`~lib.align.DetectedFace` objects. Detected faces can be added
          later with :func:`add_detected_faces`. Default: ``None``
      """
  
    def __init__(self,
                 filename: str,
                 image: "np.ndarray",
                 detected_faces: Optional[List["DetectedFace"]] = None) -> None:
        logger.trace("Initializing %s: (filename: '%s', image shape: %s, "  # type: ignore
                     "detected_faces: %s)", self.__class__.__name__, filename, image.shape,
                     detected_faces)
    def __init__(self,
                 filename: str,
                 image: "np.ndarray",
                 detected_faces: Optional[List["DetectedFace"]] = None) -> None:
        logger.trace("Initializing %s: (filename: '%s', image shape: %s, "  # type: ignore
                     "detected_faces: %s)", self.__class__.__name__, filename, image.shape,
                     detected_faces)
    def __init__(self,
                 filename: str,
                 image: "np.ndarray",
                 detected_faces: Optional[List["DetectedFace"]] = None) -> None:
        logger.trace("Initializing %s: (filename: '%s', image shape: %s, "  # type: ignore
                     "detected_faces: %s)", self.__class__.__name__, filename, image.shape,
                     detected_faces)
          self._filename = filename
          self._image = image
          self._image_shape = image.shape
          self._detected_faces = detected_faces
  
keep keep keep keep replace replace replace keep keep keep keep keep
 Bugfix: convert - Gif Writer
  - Fix non-launch error on Gif Writer
  - convert plugins - linting
  - convert/fs_media/preview/queue_manager - typing
  - Change convert items from dict to Dataclass 
plugins/extract/pipeline.py