          patched_face *= 255.0
          patched_face = np.rint(patched_face,
                                 out=np.empty(patched_face.shape, dtype="uint8"),
                                 casting='unsafe')
          if self._writer_pre_encode is not None:
              patched_face = self._writer_pre_encode(patched_face)
          logger.trace("Patched image: '%s'", predicted["filename"])
          return patched_face
  
      def _get_new_image(self, predicted, frame_size):
          """ Get the new face from the predictor and apply pre-warp manipulations.
  
          Applies any requested adjustments to the raw output of the Faceswap model
 
</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         logger.trace("Patching image: '%s'", predicted["filename"])
        frame_size = (predicted["image"].shape[1], predicted["image"].shape[0])
 </s> add         logger.trace("Patching image: '%s'", predicted.inbound.filename)  # type: ignore
        frame_size = (predicted.inbound.image.shape[1], predicted.inbound.image.shape[0]) </s> remove         logger.trace("new_face shape: %s, predicted_mask shape: %s", new_face.shape,
                     predicted_mask.shape if predicted_mask is not None else None)
        old_face = reference_face.face[..., :3] / 255.0
 </s> add         logger.trace("new_face shape: %s, predicted_mask shape: %s",  # type: ignore
                     new_face.shape, predicted_mask.shape if predicted_mask is not None else None)
        old_face = cast(np.ndarray, reference_face.face)[..., :3] / 255.0 </s> remove     def _pre_warp_adjustments(self, new_face, detected_face, reference_face, predicted_mask):
 </s> add     def _pre_warp_adjustments(self,
                              new_face: np.ndarray,
                              detected_face: "DetectedFace",
                              reference_face: "AlignedFace",
                              predicted_mask: Optional[np.ndarray]) -> np.ndarray: </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)
        if self._writer_pre_encode is None:
            retval: Union[np.ndarray, List[bytes]] = patched_face
        else:
            retval = self._writer_pre_encode(patched_face)
        logger.trace("Patched image: '%s'", predicted.inbound.filename)  # type: ignore
        return retval
          patched_face *= 255.0
          patched_face = np.rint(patched_face,
                                 out=np.empty(patched_face.shape, dtype="uint8"),
                                 casting='unsafe')
        if self._writer_pre_encode is None:
            retval: Union[np.ndarray, List[bytes]] = patched_face
        else:
            retval = self._writer_pre_encode(patched_face)
        logger.trace("Patched image: '%s'", predicted.inbound.filename)  # type: ignore
        return retval
        if self._writer_pre_encode is None:
            retval: Union[np.ndarray, List[bytes]] = patched_face
        else:
            retval = self._writer_pre_encode(patched_face)
        logger.trace("Patched image: '%s'", predicted.inbound.filename)  # type: ignore
        return retval
        if self._writer_pre_encode is None:
            retval: Union[np.ndarray, List[bytes]] = patched_face
        else:
            retval = self._writer_pre_encode(patched_face)
        logger.trace("Patched image: '%s'", predicted.inbound.filename)  # type: ignore
        return retval
        if self._writer_pre_encode is None:
            retval: Union[np.ndarray, List[bytes]] = patched_face
        else:
            retval = self._writer_pre_encode(patched_face)
        logger.trace("Patched image: '%s'", predicted.inbound.filename)  # type: ignore
        return retval
  
      def _get_new_image(self, predicted, frame_size):
          """ Get the new face from the predictor and apply pre-warp manipulations.
  
          Applies any requested adjustments to the raw output of the Faceswap model
keep keep keep keep replace 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 
lib/convert.py