updated app.py

app.py

@@ -19,10 +19,13 @@ model.classifier[1] = nn.Linear(model.classifier[1].in_features, len(CLASS_NAMES
 model.load_state_dict(torch.load(MODEL_PATH, map_location=device))
 model.eval().to(device)
 
+mean = getattr(weights, "meta", {}).get("mean", [0.485, 0.456, 0.406])
+std = getattr(weights, "meta", {}).get("std", [0.229, 0.224, 0.225])
+
 transform = transforms.Compose([
     transforms.Resize((384, 384)),
     transforms.ToTensor(),
-    transforms.Normalize(mean=weights.meta["mean"], std=weights.meta["std"]),
+    transforms.Normalize(mean=mean, std=std),
 ])
 
 def predict(image):
@@ -43,4 +46,4 @@ demo = gr.Interface(
 )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()