              "detected_face: %s, sub_crop_offset: %s, centering: '%s', predicted_mask: %s",
              detected_face, sub_crop_offset, centering, predicted_mask is not None)
          mask = self._get_mask(detected_face, predicted_mask, centering, sub_crop_offset)
          raw_mask = mask.copy()
          if not self.skip and self._do_erode:
              mask = self._erode(mask)
          logger.trace(  # type: ignore
              "mask shape: %s, raw_mask shape: %s", mask.shape, raw_mask.shape)
          return mask, raw_mask
  
 
</s> remove         logger.trace(  # type: ignore
            "detected_face: %s, sub_crop_offset: %s, centering: '%s', predicted_mask: %s",
            detected_face, sub_crop_offset, centering, predicted_mask is not None)
 </s> add         logger.trace("Performing mask adjustment: (detected_face: %s, "  # type: ignore
                     "sub_crop_offset: %s, centering: '%s', predicted_mask: %s",
                     detected_face, sub_crop_offset, centering, predicted_mask is not None) </s> remove                   detected_face: "DetectedFace",
 </s> add                   detected_face: DetectedFace, </s> remove         new_face = self._adjustments["box"].run(new_face)
 </s> add  </s> remove             mask = detected_face.mask[self.mask_type]
            mask.set_blur_and_threshold(blur_kernel=self.config["kernel_size"],
                                        blur_type=self.config["type"],
                                        blur_passes=self.config["passes"],
                                        threshold=self.config["threshold"])
            if sub_crop_offset is not None and 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
                mask = cv2.resize(mask,
                                  self.dummy.shape[:2],
                                  interpolation=interp)[..., None]
            mask = mask.astype("float32") / 255.0
 </s> add             mask = self._get_stored_mask(detected_face, centering, sub_crop_offset)

        if self._config.get("type") is not None and self._do_erode:
              "detected_face: %s, sub_crop_offset: %s, centering: '%s', predicted_mask: %s",
              detected_face, sub_crop_offset, centering, predicted_mask is not None)
          mask = self._get_mask(detected_face, predicted_mask, centering, sub_crop_offset)
          raw_mask = mask.copy()
        if self._config.get("type") is not None and self._do_erode:
              mask = self._erode(mask)
          logger.trace(  # type: ignore
              "mask shape: %s, raw_mask shape: %s", mask.shape, raw_mask.shape)
          return mask, raw_mask
  
keep keep keep keep replace keep keep keep keep keep
 convert: remove box blend plugin 
plugins/convert/mask/mask_blend.py