Update app.py

app.py

@@ -9,8 +9,7 @@ model = YOLO("yolov8x-doclaynet-epoch64-imgsz640-initiallr1e-4-finallr1e-5.pt")
 # Get class names from model
 class_names = model.names
 
-
-@spaces.GPU(duration=60)  
+@spaces.GPU(duration=60)
 def process_image(image):
     try:
         # Process the image
@@ -22,16 +21,16 @@ def process_image(image):
 
         # Use cls attribute for labels and get class name from model
         detected_areas_labels = "\n".join([
-            f"{class_names[int(box.cls.item())].upper()}: {box.conf:.2f}" for box in result.boxes
+            f"{class_names[int(box.cls.item())].upper()}: {float(box.conf):.2f}" for box in result.boxes
         ])
 
         return annotated_image, detected_areas_labels
     except Exception as e:
-        return None, f"Error processing image: {e}"  
+        return None, f"Error processing image: {e}"
 
 # Create the Gradio Interface
 with gr.Blocks() as demo:
-    gr.Markdown("# Document Segmentation Demo (ZeroGPU)")  
+    gr.Markdown("# Document Segmentation Demo (ZeroGPU)")
     # Input Components
     input_image = gr.Image(type="pil", label="Upload Image")
 
@@ -44,4 +43,4 @@ with gr.Blocks() as demo:
     btn.click(fn=process_image, inputs=input_image, outputs=[output_image, output_text])
 
 # Launch the demo with queuing
-demo.queue(max_size=1).launch() 
+demo.queue(max_size=1).launch()