                                          blur_type=self.config["type"],
                                          blur_passes=self.config["passes"],
                                          threshold=self.config["threshold"])
              if np.any(sub_crop_offset):
                  mask.set_sub_crop(sub_crop_offset)
              mask = self._crop_to_coverage(mask.mask)
              mask_size = mask.shape[0]
              face_size = self.dummy.shape[0]
              if mask_size != face_size:
                  interp = cv2.INTER_CUBIC if mask_size < face_size else cv2.INTER_AREA
 
</s> remove                 centering = "legacy" if self._alignments.version == 1.0 else "face"
 </s> add                 centering = "legacy" if self._alignments.version == 1.0 else mask.stored_centering </s> remove         retval = "_{}".format(dict_key) if dict_key != "stored_size" else dict_key
 </s> add         retval = "_{}".format(dict_key) if not dict_key.startswith("stored") else dict_key </s> remove         if self._centering == "legacy":
            crop_offset = reference_face.pose.offset["face"] * -1
 </s> add         mask_centering = detected_face.mask[self._args.mask_type].stored_centering
        if self._centering != mask_centering:
            crop_offset = reference_face.pose.offset[mask_centering] * -1 </s> remove                                    centering="face",
 </s> add                                    centering=mask.stored_centering,
                mask.set_sub_crop(sub_crop_offset, centering)
                                          blur_type=self.config["type"],
                                          blur_passes=self.config["passes"],
                                          threshold=self.config["threshold"])
              if np.any(sub_crop_offset):
                mask.set_sub_crop(sub_crop_offset, centering)
              mask = self._crop_to_coverage(mask.mask)
              mask_size = mask.shape[0]
              face_size = self.dummy.shape[0]
              if mask_size != face_size:
                  interp = cv2.INTER_CUBIC if mask_size < face_size else cv2.INTER_AREA
keep keep keep keep replace keep keep keep keep keep
 core mask updates:
  - Add support for different mask centering
  - Update legacy alignments to store mask centering
  - Bugfix: lib.image ImageIO. Ensure unique queues are created (fixes mask tool when Face is input and an output folder is provided) 
plugins/convert/mask/mask_blend.py