Add the option of the legacy general use weights without training on portrait seg data.

app.py

@@ -45,7 +45,8 @@ usage_to_weights_file = {
     'DIS': 'BiRefNet-DIS5K',
     'HRSOD': 'BiRefNet-HRSOD',
     'COD': 'BiRefNet-COD',
-    'DIS-TR_TEs': 'BiRefNet-DIS5K-TR_TEs'
+    'DIS-TR_TEs': 'BiRefNet-DIS5K-TR_TEs',
+    'General-legacy': 'BiRefNet-legacy'
 }
 
 birefnet = AutoModelForImageSegmentation.from_pretrained('/'.join(('zhengpeng7', usage_to_weights_file['General'])), trust_remote_code=True)
@@ -59,7 +60,7 @@ def predict(
     resolution: str,
     weights_file: Optional[str]
 ) -> Tuple[np.ndarray, np.ndarray]:
-    global birefnet
+    # global birefnet
     # Load BiRefNet with chosen weights
     _weights_file = '/'.join(('zhengpeng7', usage_to_weights_file[weights_file] if weights_file is not None else usage_to_weights_file['General']))
     print('Using weights:', _weights_file)