                       predicted["filename"], placeholder.shape)
  
          return placeholder, background
  
      def _pre_warp_adjustments(self, new_face, detected_face, reference_face, predicted_mask):
          """ Run any requested adjustments that can be performed on the raw output from the Faceswap
          model.
  
          Any adjustments that can be performed before warping the face into the final frame are
          performed here.
 
</s> remove         logger.trace("Got filename: '%s'. (placeholders: %s)",
                     predicted["filename"], placeholder.shape)
 </s> add         logger.trace("Got filename: '%s'. (placeholders: %s)",  # type: ignore
                     predicted.inbound.filename, placeholder.shape) </s> remove     def _get_new_image(self, predicted, frame_size):
 </s> add     def _get_new_image(self,
                       predicted: "ConvertItem",
                       frame_size: Tuple[int, int]) -> Tuple[np.ndarray, np.ndarray]: </s> remove     def _get_frame_ranges(self):
 </s> add     def _get_frame_ranges(self) -> Optional[List[Tuple[int, int]]]: </s> remove     def _post_warp_adjustments(self, background, new_image):
 </s> add     def _post_warp_adjustments(self, background: np.ndarray, new_image: np.ndarray) -> np.ndarray: </s> remove         postprocess_items = {}
 </s> add         postprocess_items: Dict[str, Optional[Dict[str, Union[tuple, dict]]]] = {}
    def _pre_warp_adjustments(self,
                              new_face: np.ndarray,
                              detected_face: "DetectedFace",
                              reference_face: "AlignedFace",
                              predicted_mask: Optional[np.ndarray]) -> np.ndarray:
                       predicted["filename"], placeholder.shape)
  
          return placeholder, background
  
    def _pre_warp_adjustments(self,
                              new_face: np.ndarray,
                              detected_face: "DetectedFace",
                              reference_face: "AlignedFace",
                              predicted_mask: Optional[np.ndarray]) -> np.ndarray:
          """ Run any requested adjustments that can be performed on the raw output from the Faceswap
          model.
  
          Any adjustments that can be performed before warping the face into the final frame are
          performed here.
keep keep keep keep 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 
lib/convert.py