final update

app.py

@@ -72,12 +72,18 @@ def predict(image_path, detector_name):
             prediction = result.get('prediction', 'Unknown')
             confidence = result.get('confidence', 0.0)
             elapsed_time = result.get('elapsed_time', 0.0)
-            
-            output = {
-                "Prediction": prediction,
-                "Confidence Fake": f"{confidence:.4f}",
-                "Elapsed Time": f"{elapsed_time:.3f}s"
-            }
+            if prediction == 'fake':  
+                output = {
+                    "Prediction": prediction,
+                    "Confidence": f"{confidence:.4f}",
+                    "Elapsed Time": f"{elapsed_time:.3f}s"
+                }
+            else:
+                output = {
+                    "Prediction": prediction,
+                    "Confidence": f"{1-confidence:.4f}",
+                    "Elapsed Time": f"{elapsed_time:.3f}s"
+                }
             return json.dumps(output, indent=2)
         else:
             return json.dumps({"error": "No result file generated. Check console logs for details."}, indent=2)
@@ -109,7 +115,7 @@ with demo:
 
     ### Understanding the Results
     *   **Prediction**: Tells if an image is **Real** or **Fake**.
-    *   **Confidence Fake**: The confidence with which the model determines if the image is fake.
+    *   **Confidence**: The confidence with which the model determines if the image is real orfake.
     *   **Elapsed Time**: The time the model needed to make the prediction (excluding preprocessing or model building).
     """)