      def _crop_source_faces(self):
          """ Extract the source faces from the source frames, along with their filenames and the
          transformation matrix used to extract the faces. """
          logger.debug("Updating source faces")
          self._faces = {}
          for image in self.source:
              detected_face = image["detected_faces"][0]
              src_img = image["image"]
              detected_face.load_aligned(src_img, size=self._size, centering=self._centering)
              matrix = detected_face.aligned.matrix
              self._faces.setdefault("filenames",
                                     []).append(os.path.splitext(image["filename"])[0])
              self._faces.setdefault("matrix", []).append(matrix)
              self._faces.setdefault("src", []).append(transform_image(src_img,
 
</s> remove             self._faces.setdefault("filenames",
                                   []).append(os.path.splitext(image["filename"])[0])
            self._faces.setdefault("matrix", []).append(matrix)
            self._faces.setdefault("src", []).append(transform_image(src_img,
                                                                     matrix,
                                                                     self._size,
                                                                     self._padding))
 </s> add             self._faces.filenames.append(os.path.splitext(item.inbound.filename)[0])
            self._faces.matrix.append(matrix)
            self._faces.src.append(transform_image(src_img, matrix, self._size, self._padding)) </s> remove     def _crop_source_faces(self):
 </s> add     def _crop_source_faces(self) -> None: </s> remove                      {k: len(v) for k, v in self._faces.items()})
 </s> add                      {k: len(v) for k, v in self._faces.__dict__.items()}) </s> remove     def _crop_destination_faces(self):
 </s> add     def _crop_destination_faces(self) -> None: </s> remove         self._faces["dst"] = []
        destination = self.destination if self.destination else [np.ones_like(src["image"])
 </s> add         self._faces.dst = []
        destination = self.destination if self.destination else [np.ones_like(src.inbound.image)
        self._faces = _Faces()  # Init new class
        for item in self.source:
            detected_face = item.inbound.detected_faces[0]
            src_img = item.inbound.image
            detected_face.load_aligned(src_img,
                                       size=self._size,
                                       centering=cast("CenteringType", self._centering))
      def _crop_source_faces(self):
          """ Extract the source faces from the source frames, along with their filenames and the
          transformation matrix used to extract the faces. """
          logger.debug("Updating source faces")
        self._faces = _Faces()  # Init new class
        for item in self.source:
            detected_face = item.inbound.detected_faces[0]
            src_img = item.inbound.image
            detected_face.load_aligned(src_img,
                                       size=self._size,
                                       centering=cast("CenteringType", self._centering))
        self._faces = _Faces()  # Init new class
        for item in self.source:
            detected_face = item.inbound.detected_faces[0]
            src_img = item.inbound.image
            detected_face.load_aligned(src_img,
                                       size=self._size,
                                       centering=cast("CenteringType", self._centering))
        self._faces = _Faces()  # Init new class
        for item in self.source:
            detected_face = item.inbound.detected_faces[0]
            src_img = item.inbound.image
            detected_face.load_aligned(src_img,
                                       size=self._size,
                                       centering=cast("CenteringType", self._centering))
        self._faces = _Faces()  # Init new class
        for item in self.source:
            detected_face = item.inbound.detected_faces[0]
            src_img = item.inbound.image
            detected_face.load_aligned(src_img,
                                       size=self._size,
                                       centering=cast("CenteringType", self._centering))
        self._faces = _Faces()  # Init new class
        for item in self.source:
            detected_face = item.inbound.detected_faces[0]
            src_img = item.inbound.image
            detected_face.load_aligned(src_img,
                                       size=self._size,
                                       centering=cast("CenteringType", self._centering))
              matrix = detected_face.aligned.matrix
              self._faces.setdefault("filenames",
                                     []).append(os.path.splitext(image["filename"])[0])
              self._faces.setdefault("matrix", []).append(matrix)
              self._faces.setdefault("src", []).append(transform_image(src_img,
keep keep keep keep replace 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 
tools/preview/preview.py