                                          coverage_ratio=self.coverage_ratio,
                                          dtype="float32",
                                          is_aligned=self._image_is_aligned)
                  batch.setdefault("detected_faces", []).append(face)
                  batch.setdefault("feed_faces", []).append(feed_face)
                  batch.setdefault("filename", []).append(item.filename)
                  idx += 1
                  if idx == self.batchsize:
 
</s> remove                                         image=item.get_image_copy(self.color_format),
 </s> add                                         image=image, </s> remove                                     source_is_video=self._frames.is_video))
 </s> add                                     source_is_video=self._frames.is_video,
                                    source_frame_dims=image.shape[:2])) </s> remove 
 </s> add             if "source_frame_dims" not in metadata["source"]:
                logger.error("The faces need to be re-extracted as at least some of them do not "
                             "contain information required to correctly generate masks.")
                logger.error("You can re-extract the face-set by using the Alignments Tool's "
                             "Extract job.")
                break </s> remove     @staticmethod
    def _resize(image, target_size):
 </s> add     @classmethod
    def _resize(cls, image, target_size):
                if not self._image_is_aligned:
                    # Split roi mask from feed face alpha channel
                    roi_mask = feed_face.face[..., 3]
                    feed_face._face = feed_face.face[..., :3]  # pylint:disable=protected-access
                else:
                    # We have to do the warp here as AlignedFace did not perform it
                    roi_mask = transform_image(roi,
                                               feed_face.matrix,
                                               feed_face.size,
                                               padding=feed_face.padding)

                batch.setdefault("roi_masks", []).append(roi_mask)
                                          coverage_ratio=self.coverage_ratio,
                                          dtype="float32",
                                          is_aligned=self._image_is_aligned)
                if not self._image_is_aligned:
                    # Split roi mask from feed face alpha channel
                    roi_mask = feed_face.face[..., 3]
                    feed_face._face = feed_face.face[..., :3]  # pylint:disable=protected-access
                else:
                    # We have to do the warp here as AlignedFace did not perform it
                    roi_mask = transform_image(roi,
                                               feed_face.matrix,
                                               feed_face.size,
                                               padding=feed_face.padding)

                batch.setdefault("roi_masks", []).append(roi_mask)
                  batch.setdefault("detected_faces", []).append(face)
                  batch.setdefault("feed_faces", []).append(feed_face)
                  batch.setdefault("filename", []).append(item.filename)
                  idx += 1
                  if idx == self.batchsize:
keep keep add keep keep keep keep keep
 extract: mask - Delete any mask from outside of frame boundaries 
plugins/extract/mask/_base.py