Bugfixes:

  - Convert: Fix error when 'learn mask' has been selected
  - Bisenet-FP mask: Correctly store mask for face or head centering

Author: torzdf

plugins/extract/mask/bisenet_fp.py

@@ -49,7 +49,7 @@ def __init__(self, **kwargs) -> None:
         self.batchsize = cfg.batch_size()
 
         self._segment_indices = self._get_segment_indices()
-        self.storage_centering = "head" if cfg.include_hair() else "face"
+        self._storage_centering = "head" if cfg.include_hair() else "face"
         """ Literal["head", "face"] The mask type/storage centering to use """
         # Separate storage for face and head masks
         self._storage_name = f"{self._storage_name}_{self._storage_centering}"

plugins/train/model/_base/inference.py

@@ -272,8 +272,9 @@ def _build(self):
             built = self._build_layers(layers, history, built)
 
         assert len(self._input) == 1
-        assert len(built) == 1
-        retval = keras.Model(inputs=self._input[0], outputs=built[0], name=self._name)
+        assert len(built) in (1, 2)
+        out = built[0] if len(built) == 1 else built
+        retval = keras.Model(inputs=self._input[0], outputs=out, name=self._name)
         logger.debug("Compiled inference model '%s': %s", retval.name, retval)
 
         return retval