Upload app.py

Fix for score precision

app.py

@@ -87,9 +87,12 @@ class CIFAR100Classifier:
             
             results = {}
             for i in range(5):
-                class_name = CIFAR100_CLASSES[top5_idx[i]]
-                confidence = float(top5_prob[i]) * 100
-                results[class_name] = confidence
+                class_idx = top5_idx[i].item()  # Ensure it's a Python int
+                class_name = CIFAR100_CLASSES[class_idx]
+                confidence = float(top5_prob[i].item())  # Keep as decimal (0-1) for Gradio
+                # Ensure reasonable confidence values (0-1)
+                confidence = max(0.0, min(1.0, confidence))
+                results[class_name] = round(confidence, 4)  # Round to 4 decimal places
             
             return results