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from os import abort, getenv |
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from sys import exception |
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from textwrap import dedent |
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import traceback |
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import gradio as gr |
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from torch import cuda |
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from detikzify.webui import BANNER, build_ui, make_light |
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def is_official_demo(): |
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return getenv("SPACE_AUTHOR_NAME") == "nllg" |
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def add_abort_hook(func, *errors): |
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def wrapper(*args, **kwargs): |
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if isinstance(exception(), errors): |
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abort() |
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return func(*args, **kwargs) |
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return wrapper |
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if is_official_demo() and not cuda.is_available(): |
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center = ".gradio-container {text-align: center}" |
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with gr.Blocks(css=center, theme=make_light(gr.themes.Soft()), title="DeTikZify") as demo: |
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badge = "https://huggingface.co/datasets/huggingface/badges/resolve/main/duplicate-this-space-xl.svg" |
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link = "https://huggingface.co/spaces/nllg/DeTikZify?duplicate=true" |
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html = f'<a style="display:inline-block" href="{link}"> <img src="{badge}" alt="Duplicate this Space"> </a>' |
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message = dedent("""\ |
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The resources required by our models surpass those provided by Hugging |
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Face Spaces' free CPU tier. For full functionality, we suggest |
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duplicating this space using a paid private GPU runtime. |
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""") |
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gr.HTML(f'{BANNER}\n<p>{message}</p>\n{html}') |
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else: |
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use_big_models = cuda.is_available() and cuda.get_device_properties(0).total_memory > 15835660288 |
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model = f"detikzify-ds-{'7' if use_big_models else '1.3'}b" |
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demo = build_ui(lock=is_official_demo(), model=model, light=True).queue() |
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traceback.print_exc = add_abort_hook(traceback.print_exc, MemoryError, cuda.OutOfMemoryError) |
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if __name__ == "__main__": |
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demo.launch(server_name="0.0.0.0", server_port=7860) |
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