Fix: Inference issue

app.py

@@ -58,9 +58,6 @@ def main():
             """
         )
 
-        # #############################################################################
-        # ################################ GradCam Tab ################################
-        # #############################################################################
         with gr.Tab("GradCam"):
             gr.Markdown(
                 """
@@ -69,27 +66,32 @@ def main():
                 """
             )
             with gr.Row():
-                img_input = [gr.Image(label="Input Image", type="numpy", height=224)]
-                gradcam_outputs = [
-                    gr.Label(label="Predictions"),
-                    gr.Image(label="GradCAM Output", height=224)
-                ]
+                img_input = gr.Image(label="Input Image", type="numpy", height=224)
+                with gr.Column():
+                    label_output = gr.Label(label="Predictions")
+                    gradcam_output = gr.Image(label="GradCAM Output", height=224)
 
             with gr.Row():
-                gradcam_inputs = [
-                    gr.Slider(0, 1, value=0.5, label="Activation Map Transparency"),
-                    gr.Slider(1, 10, value=3, step=1, label="Number of Top Predictions"),
-                    gr.Slider(1, 6, value=4, step=1, label="Target Layer Number")
-                ]
+                alpha_slider = gr.Slider(0, 1, value=0.5, label="Activation Map Transparency")
+                top_k_slider = gr.Slider(1, 10, value=3, step=1, label="Number of Top Predictions")
+                target_layer_slider = gr.Slider(1, 6, value=4, step=1, label="Target Layer Number")
 
             gradcam_button = gr.Button("Generate GradCAM")
             
-            # Pass model to inference function using partial
-            from functools import partial
-            inference_fn = partial(inference, model=model, classes=classes)
-            gradcam_button.click(inference_fn, inputs=img_input + gradcam_inputs, outputs=gradcam_outputs)
+            def inference_wrapper(image, alpha, top_k, target_layer):
+                return inference(image, alpha, top_k, target_layer, model=model, classes=classes)
+            
+            gradcam_button.click(
+                fn=inference_wrapper,
+                inputs=[
+                    img_input,
+                    alpha_slider,
+                    top_k_slider,
+                    target_layer_slider
+                ],
+                outputs=[label_output, gradcam_output]
+            )
 
-            gr.Markdown("## Examples")
             gr.Examples(
                 examples=[
                     ["./assets/examples/dog.jpg", 0.5, 3, 4],
@@ -103,13 +105,14 @@ def main():
                     ["./assets/examples/plane.jpg", 0.5, 3, 4],
                     ["./assets/examples/ship.png", 0.5, 3, 4]
                 ],
-                inputs=img_input + gradcam_inputs,
-                fn=inference_fn,
-                outputs=gradcam_outputs
+                inputs=[img_input, alpha_slider, top_k_slider, target_layer_slider],
+                outputs=[label_output, gradcam_output],
+                fn=inference_wrapper,
+                cache_examples=True
             )
 
-        # Launch the demo (moved inside the Blocks context)
-        demo.launch(debug=True)
+        # Launch the demo
+        demo.launch(server_name="0.0.0.0", debug=True)
 
 
 if __name__ == "__main__":