Update app.py

app.py

@@ -184,18 +184,23 @@ def predict_image(img, confidence_threshold):
         "GOAT": label_5
     }
     
-    return combined_results
+    return img_pil, combined_results
 
 # Define the Gradio interface
-image = gr.Image(label="Image to Analyze", sources=['upload'], type='pil')  # Ensure the image type is PIL
-confidence_slider = gr.Slider(0.0, 1.0, value=0.5, step=0.01, label="Confidence Threshold")
-label = gr.JSON(label="Model Predictions")
+with gr.Blocks() as iface:
+    gr.Markdown("# AI Generated Image Classification")
+    
+    with gr.Row():
+        with gr.Column():
+            image_input = gr.Image(label="Upload Image to Analyze", sources=['upload'], type='pil')
+            confidence_slider = gr.Slider(0.0, 1.0, value=0.5, step=0.01, label="Confidence Threshold")
+            inputs = [image_input, confidence_slider]
+        with gr.Column():
+            image_output = gr.Image(label="Processed Image")
+            label_output = gr.JSON(label="Model Predictions")
+            outputs = [image_output, label_output]
+    
+    gr.Button("Predict").click(fn=predict_image, inputs=inputs, outputs=outputs)
 
 # Launch the interface
-iface = gr.Interface(
-    fn=predict_image,
-    inputs=[image, confidence_slider],
-    outputs=label,
-    title="AI Generated Classification"
-)
-iface.launch()
+iface.launch()