          box = np.zeros((output_size, output_size, 1), dtype="float32")
          edge = output_size // 32
          box[edge:-edge, edge:-edge] = 1.0
  
          box = BlurMask(self._config["type"],
                         box, self._config["kernel_size"],
                         self._config["passes"]).blurred
          return box
  
      def run(self,
              detected_face: DetectedFace,
              sub_crop_offset: Optional[np.ndarray],
 
</s> remove         self._thread = MultiThread(self._process,
                                   self._trigger,
                                   self._shutdown,
                                   self._queue_patch_in,
                                   self._samples,
                                   tk_vars,
                                   thread_count=1,
                                   name="patch_thread")
 </s> add         self._thread = Thread(target=self._process,
                              name="patch_thread",
                              args=(self._trigger,
                                    self._shutdown,
                                    self._queue_patch_in,
                                    self._samples,
                                    tk_vars),
                              daemon=True) </s> remove             mask = predicted_mask
 </s> add             mask = self._process_predicted_mask(predicted_mask) </s> remove         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)

 </s> add 
        if self._config["type"] is not None:
            box = BlurMask("gaussian",
                           box,
                           6,
                           is_ratio=True).blurred
          box = np.zeros((output_size, output_size, 1), dtype="float32")
          edge = output_size // 32
          box[edge:-edge, edge:-edge] = 1.0
  
        if self._config["type"] is not None:
            box = BlurMask("gaussian",
                           box,
                           6,
                           is_ratio=True).blurred
        if self._config["type"] is not None:
            box = BlurMask("gaussian",
                           box,
                           6,
                           is_ratio=True).blurred
        if self._config["type"] is not None:
            box = BlurMask("gaussian",
                           box,
                           6,
                           is_ratio=True).blurred
          return box
  
      def run(self,
              detected_face: DetectedFace,
              sub_crop_offset: Optional[np.ndarray],
keep keep keep keep replace replace replace keep keep keep keep keep
 Preview Tool fixes
  - Prevent errors from getting swallowed
  - Correctly handle None mask type
  - Consistent box blending 
plugins/convert/mask/mask_blend.py