          self.model = BiSeNet(self.model_path,
                               self.config["allow_growth"],
                               self._exclude_gpus,
                               self.input_size,
                               19)
  
          placeholder = np.zeros((self.batchsize, self.input_size, self.input_size, 3),
                                 dtype="float32")
          self.model.predict(placeholder)
  
 
</s> remove         mean = (0.485, 0.456, 0.406)
        std = (0.229, 0.224, 0.225)
 </s> add         mean = (0.384, 0.314, 0.279) if self._is_faceswap else (0.485, 0.456, 0.406)
        std = (0.324, 0.286, 0.275) if self._is_faceswap else (0.229, 0.224, 0.225) </s> remove         self._segment_indices = self._get_segment_indices()
 </s> add  </s> remove         model_filename = "bisnet_face_parsing_v1.h5"
 </s> add         model_filename = f"bisnet_face_parsing_v{'2' if self._is_faceswap else '1'}.h5"
                             lbls)
          self.model = BiSeNet(self.model_path,
                               self.config["allow_growth"],
                               self._exclude_gpus,
                               self.input_size,
                             lbls)
  
          placeholder = np.zeros((self.batchsize, self.input_size, self.input_size, 3),
                                 dtype="float32")
          self.model.predict(placeholder)
  
keep keep keep keep replace keep keep keep keep keep
 Bisenet-FP - Improved weights for masker (#1210)

* Add option to load faceswap trained weights

* Switch to original weights if fs weights not present

* typofix 
plugins/extract/mask/bisenet_fp.py