          self._converter = Converter(output_size=self._samples.predictor.output_size,
                                      coverage_ratio=self._samples.predictor.coverage_ratio,
                                      draw_transparent=False,
                                      pre_encode=None,
                                      arguments=self._generate_converter_arguments(arguments),
                                      configfile=configfile)
          self._shutdown = Event()
  
          self._thread = MultiThread(self._process,
                                     self._trigger,
 
</s> remove             mask = predicted_mask
 </s> add             mask = predicted_mask[..., None] </s> remove         raw_mask = np.expand_dims(raw_mask, axis=-1) if raw_mask.ndim != 3 else raw_mask
        mask = np.expand_dims(mask, axis=-1) if mask.ndim != 3 else mask
 </s> add  </s> remove             mask = np.ones_like(self.dummy[:, :, 1], dtype="uint8") * 255
 </s> add             mask = np.ones_like(self.dummy[:, :, 1], dtype="float32")[..., None]
                                    arguments=self._generate_converter_arguments(arguments,
                                                                                 available_masks),
          self._converter = Converter(output_size=self._samples.predictor.output_size,
                                      coverage_ratio=self._samples.predictor.coverage_ratio,
                                      draw_transparent=False,
                                      pre_encode=None,
                                    arguments=self._generate_converter_arguments(arguments,
                                                                                 available_masks),
                                      configfile=configfile)
          self._shutdown = Event()
  
          self._thread = MultiThread(self._process,
                                     self._trigger,
keep keep keep keep replace keep keep keep keep keep
 Convert - bugfixes
- Default mask to an available mask in Preview tool
- Correctly output predicted mask 
tools/preview.py