                              source=dict(alignments_version=self._alignments.version,
                                          original_filename=output,
                                          face_index=face_idx,
                                          source_filename=src_filename,
                                          source_is_video=self._globals.is_video))
  
                  b_image = encode_image(aligned.face, ".png", metadata=meta)
                  _io["saver"].save(output, b_image)
          _io["saver"].close()
  
 
</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                                     source_is_video=self._images.is_video))
 </s> add                                     source_is_video=self._images.is_video,
                                    source_frame_dims=extract_media.image_size)) </s> remove                 center = np.rint(offset + self._head_size / 2).astype("int32")
 </s> add                 center = np.rint(adjusted + self._head_size / 2).astype("int32") </s> remove                 offset -= self.pose.offset["head"]
                offset *= (self._head_size - (self._head_size * _EXTRACT_RATIOS["head"]))
 </s> add                 adjusted = offset - self.pose.offset["head"]
                adjusted *= (self._head_size - (self._head_size * _EXTRACT_RATIOS["head"]))
                                        source_is_video=self._globals.is_video,
                                        source_frame_dims=image.shape[:2]))
                              source=dict(alignments_version=self._alignments.version,
                                          original_filename=output,
                                          face_index=face_idx,
                                          source_filename=src_filename,
                                        source_is_video=self._globals.is_video,
                                        source_frame_dims=image.shape[:2]))
  
                  b_image = encode_image(aligned.face, ".png", metadata=meta)
                  _io["saver"].save(output, b_image)
          _io["saver"].close()
  
keep keep keep keep replace keep keep keep keep keep
 extract: mask - Delete any mask from outside of frame boundaries 
tools/manual/detected_faces.py