fafafafafa

app.py

@@ -77,6 +77,7 @@ def predict_image(inp):
     """
     Performs inference for a given input image and returns the prediction and CAM image.
     """
+      
     material_label, material_label_idx, material_probs = materials_model.predict(inp)
     material_preds = {name: prob for name, prob in zip(material_names, material_probs.tolist())}
 
@@ -127,7 +128,7 @@ with gr.Blocks(title="Trash Classification", css=css) as demo:
   
     with gr.Column():
         with gr.Row():
-                  item_probs = gr.outputs.Label(num_top_classes=1)
+                  item_probs = gr.outputs.Label(num_top_classes=1,visible=False)
         with gr.Column():
                 gr.Markdown("## Inputs", elem_id="custom_header")
                 input_image = gr.Image(label="Input Image")
@@ -140,6 +141,8 @@ with gr.Blocks(title="Trash Classification", css=css) as demo:
               recycling_advice = gr.outputs.Label()
               gr.Markdown("### How to recycle?")
               recycling_qn = gr.outputs.Label()
+        def submit_visible():
+            return {item_probs: gr.outputs.Label(num_top_classes=1, visible=True)}
               
 
                 
@@ -150,7 +153,7 @@ with gr.Blocks(title="Trash Classification", css=css) as demo:
         cache_examples=False,
     )
 
-    btn.click(predict_image, inputs=[input_image],
+    btn.click(predict_image, submit_visible, inputs=[input_image],
               outputs=[item_probs, recycling_qn, recycling_advice])
 if __name__ == "__main__":
     demo.launch()