Update app.py

app.py

@@ -33,11 +33,11 @@ transform = transforms.Compose([
 def classify_image(image):
     image = transform(image).unsqueeze(0).to(device)  # Preprocess image
     with torch.no_grad():
-    output = model(image)
-    # ✅ Extract first element if output is a tuple
-    if isinstance(output, tuple):
-      output = output[1]
-    predicted_class = torch.argmax(output, dim=1).item()
+        output = model(image)
+        # ✅ Extract first element if output is a tuple
+        if isinstance(output, tuple):
+            output = output[1]
+        predicted_class = torch.argmax(output, dim=1).item()
 
     return f"Predicted Class: {class_labels[predicted_class]}"