Update app.py

app.py

@@ -9,12 +9,6 @@ import datetime
 import subprocess
 import spaces  # Ensure this import is correct and the module is available
 
-CUSTOM_CSS = """
-#output_box textarea {
-    font-family: IBM Plex Mono, ui-monospace, SFMono-Regular, Menlo, Monaco, Consolas, "Liberation Mono", "Courier New", monospace;
-}
-"""
-
 # Ensure the model file is in the correct location
 model_path = "yolov8x-doclaynet-epoch64-imgsz640-initiallr1e-4-finallr1e-5.pt"
 if not os.path.exists(model_path):
@@ -44,44 +38,6 @@ def process_image(image):
 
     return annotated_img, detected_areas_labels
 
-zero = torch.Tensor([0]).cuda()
-print(zero.device) # <-- 'cuda:0' if GPU is available, otherwise 'cpu'
-
-@spaces.GPU
-def run_gpu() -> str:
-    print(zero.device) # <-- 'cuda:0' 🤗
-    output: str = ""
-    try:
-        output = subprocess.check_output(["nvidia-smi"], text=True)
-    except FileNotFoundError:
-        output = "nvidia-smi failed"
-    comment = (
-        datetime.datetime.now().replace(microsecond=0).isoformat().replace("T", " ")
-    )
-    return f"# {comment}\n\n{output}"
-
-def run(check: bool) -> str:
-    if check:
-        return run_gpu()
-    else:
-        comment = (
-            datetime.datetime.now().replace(microsecond=0).isoformat().replace("T", " ")
-        )
-        return f"# {comment}\n\nThis is running on CPU\n\nClick on 'Run on GPU' below to move to GPU instantly and run nvidia-smi"
-
-output = gr.Textbox(
-    label="Command Output", max_lines=32, elem_id="output_box", value=run(False)
-)
-
-with gr.Blocks(css=CUSTOM_CSS) as demo:
-    gr.Markdown("#### `zero-gpu`: how to run on serverless GPU for free on Spaces 🔥")
-
-    output.render()
-
-    check = gr.Checkbox(label="Run on GPU")
-
-    check.change(run, inputs=[check], outputs=output, every=1)
-
 # Define the Gradio interface
 with gr.Blocks() as interface:
     gr.Markdown("### Document Segmentation using YOLOv8")
@@ -95,9 +51,7 @@ with gr.Blocks() as interface:
         outputs=[output_image, output_text]
     )
 
-demo.queue().launch(show_api=False)
 interface.launch()
 
 if __name__ == "__main__":
-    demo.launch()
     interface.launch()