fix: replace gr.JSON with gr.Code to avoid schema parsing bug

app.py

@@ -19,7 +19,7 @@ DETECTORS = ['R50_TF', 'R50_nodown', 'CLIP-D', 'P2G', 'NPR']
 
 def predict(image_path, detector_name):
     if not image_path:
-        return {"error": "Please upload an image."}
+        return json.dumps({"error": "Please upload an image."}, indent=2)
     
     # Create a temporary output file path
     output_path = "temp_result.json"
@@ -52,18 +52,22 @@ def predict(image_path, detector_name):
             confidence = result.get('confidence', 0.0)
             elapsed_time = result.get('elapsed_time', 0.0)
             
-            return {
+            output = {
                 "Prediction": prediction,
                 "Confidence": f"{confidence:.4f}",
                 "Elapsed Time": f"{elapsed_time:.3f}s"
             }
+            return json.dumps(output, indent=2)
         else:
-            return {"error": "No result file generated. Check console logs for details."}
+            return json.dumps({"error": "No result file generated. Check console logs for details."}, indent=2)
             
     except FileNotFoundError as e:
-        return {"error": str(e), "message": f"Please ensure you have downloaded the weights for {detector_name}."}
+        return json.dumps({
+            "error": str(e), 
+            "message": f"Please ensure you have downloaded the weights for {detector_name}."
+        }, indent=2)
     except Exception as e:
-        return {"error": str(e)}
+        return json.dumps({"error": str(e)}, indent=2)
     finally:
         # Cleanup
         if os.path.exists(output_path):
@@ -95,7 +99,7 @@ with gr.Blocks(title="Deepfake Detection", theme=gr.themes.Soft()) as demo:
             submit_btn = gr.Button("🔍 Detect", variant="primary")
         
         with gr.Column():
-            output_json = gr.JSON(label="Detection Results")
+            output_display = gr.Code(label="Detection Results", language="json", lines=10)
     
     gr.Markdown("""
     ---
@@ -109,7 +113,7 @@ with gr.Blocks(title="Deepfake Detection", theme=gr.themes.Soft()) as demo:
     submit_btn.click(
         fn=predict,
         inputs=[image_input, detector_input],
-        outputs=output_json
+        outputs=output_display
     )
 
 if __name__ == "__main__":