Upgrade the weights loading method to avoid duplicated loading.

app.py

@@ -35,13 +35,6 @@ class ImagePreprocessor():
         return image
 
 
-from transformers import AutoModelForImageSegmentation
-weights_path = 'BiRefNet'
-birefnet = AutoModelForImageSegmentation.from_pretrained('/'.join(('zhengpeng7', weights_path)), trust_remote_code=True)
-birefnet.to(device)
-birefnet.eval()
-birefnet.weights_path = weights_path
-
 usage_to_weights_file = {
     'General': 'BiRefNet',
     'Portrait': 'BiRefNet-portrait',
@@ -51,6 +44,13 @@ usage_to_weights_file = {
     'DIS-TR_TEs': 'BiRefNet-DIS5K-TR_TEs'
 }
 
+from transformers import AutoModelForImageSegmentation
+weights_path = 'General'
+birefnet = AutoModelForImageSegmentation.from_pretrained('/'.join(('zhengpeng7', usage_to_weights_file[weights_path])), trust_remote_code=True)
+birefnet.to(device)
+birefnet.eval()
+birefnet.weights_path = weights_path
+
 
 @spaces.GPU
 def predict(image, resolution, weights_file):