fixed errors

app.py

@@ -25,19 +25,18 @@ def predict(inputImage: torch.Tensor, model) -> torch.Tensor:
 # %% Gradio interface
 def run_prediction(image: gr.Image, selected_model: str)-> tuple[torch.Tensor]:
     if image is None:
-        raise ValueError("No image provided for prediction.")
+        return (gr.update(value=None, visible=False), gr.update(value=f"❌ No image provided for prediction.", visible=True))
     
     if selected_model is None:
-        raise ValueError("No model selected for prediction.")
-    
+        return (gr.update(value=None, visible=False),  gr.update(value=f"❌ No model selected for prediction.", visible=True))
     try:
         model = loadModel(selected_model, device) 
-    except NotImplementedError as e:
-        raise ValueError(f"Model loading failed: {e}")
-    
-    image = hfImageToTensor(image, width=1024, height=512)
-    prediction = predict(image, model)
-    return postprocessing(prediction)
+        image = hfImageToTensor(image, width=1024, height=512)
+        prediction = predict(image, model)
+        prediction = postprocessing(prediction)
+    except Exception as e:
+            return (gr.update(value=None, visible=False),  gr.update(value=f"❌ {str(e)}.", visible=True))
+    return (gr.update(value=prediction, visible=True), gr.update(value="", visible=False))
 
 # Gradio UI
 with gr.Blocks(title="🔀 BiSeNet | BiSeNetV2 Predictor") as demo:
@@ -56,14 +55,13 @@ with gr.Blocks(title="🔀 BiSeNet | BiSeNetV2 Predictor") as demo:
             submit_btn = gr.Button("Run prediction")
         with gr.Column():
             result_display = gr.Image(label="Model prediction")
-    
-    result_display = gr.Image(label="Output")
-    error_text = gr.Textbox(label="Messaggio", interactive=False)
+            
+    error_text = gr.Textbox(label="Message", interactive=False, visible=False)
     
     submit_btn.click(
         fn=run_prediction,
         inputs=[image_input, model_selector],
-        outputs=[result_display]
+        outputs=[result_display, error_text],
     )
     
     gr.Markdown("Made by group 21 semantic segmentation project. ")

utils/imageHandling.py

@@ -43,4 +43,4 @@ def postprocessing(pred: torch.Tensor) -> torch.Tensor:
     Returns:
         torch.Tensor: Processed tensor of shape (3, H, W) for visualization.
     """ 
-    return torchvision.transforms.functional.to_pil_image(pred.squeeze(0).cpu().clamp(0, 1))
+    return torchvision.transforms.functional.to_pil_image(pred.squeeze(0).cpu().to(torch.uint8))