Trying to build

app.py

@@ -318,19 +318,10 @@ def predict(img: Image.Image):
     with torch.no_grad():
         logits = model(x)
         probs = torch.nn.functional.softmax(logits, dim=1)[0]
-        
-        # Get top 5 predictions
-        top_5_probs, top_5_indices = torch.topk(probs, 5)
-        
-        # Create dictionary with top 5 predictions
-        results = {}
-        for i in range(5):
-            idx = top_5_indices[i].item()
-            label = labels[idx] if idx < len(labels) else f"Class {idx}"
-            confidence = float(top_5_probs[i])
-            results[label] = confidence
-            
-        return results
+        top_idx = torch.argmax(probs).item()
+        top_label = labels[top_idx] if labels[top_idx] is not None else f"Class {top_idx}"
+        confidence = float(probs[top_idx])
+        return {top_label: confidence}
 
 # --------------------------
 # 6. Gradio interface
@@ -338,10 +329,10 @@ def predict(img: Image.Image):
 demo = gr.Interface(
     fn=predict,
     inputs=gr.Image(type="pil"),
-    outputs=gr.Label(num_top_classes=5),
+    outputs=gr.Label(num_top_classes=1),
     title="🚗Car Model Classifier🚗",
     description="⬆Upload a car image and see what it is and how confident our model is on this particular picture!"
 )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()