Spaces:
Running
on
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Running
on
Zero
Thanks hysts
Browse files
app.py
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import shlex
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import subprocess
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subprocess.run(shlex.split("pip install pip==24.0"), check=True)
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subprocess.run(
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shlex.split(
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), check=True
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)
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if __name__ == "__main__":
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from huggingface_hub import snapshot_download
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snapshot_download("public-data/Unique3D", repo_type="model", local_dir="./ckpt")
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import os
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import sys
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sys.path.append(os.curdir)
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torch.set_float32_matmul_precision('medium')
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torch.backends.cuda.matmul.allow_tf32 = True
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torch.set_grad_enabled(False)
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import fire
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import gradio as gr
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from gradio_app.gradio_3dgen import create_ui as create_3d_ui
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from gradio_app.all_models import model_zoo
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_TITLE = '''Unique3D: High-Quality and Efficient 3D Mesh Generation from a Single Image'''
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_DESCRIPTION = '''
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<div>
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<a style="display:inline-block" href='https://github.com/AiuniAI/Unique3D'><img alt="GitHub Repo stars" src="https://img.shields.io/github/stars/AiuniAI/Unique3D?style=social">
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</a>
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<img alt="GitHub License" src="https://img.shields.io/github/license/AiuniAI/Unique3D">
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</div>
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# [Paper](https://arxiv.org/abs/2405.20343) | [Project page](https://wukailu.github.io/Unique3D/) | [Huggingface Demo](https://huggingface.co/spaces/Wuvin/Unique3D) | [Gradio Demo](http://unique3d.demo.avar.cn/) | [Online Demo](https://www.aiuni.ai/)
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* High-fidelity and diverse textured meshes generated by Unique3D from single-view images.
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* The demo is still under construction, and more features are expected to be implemented soon.
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* If the Huggingface Demo is overcrowded or fails to produce stable results, you can use the Online Demo [aiuni.ai](https://www.aiuni.ai/), which is free to try (get the registration invitation code Join Discord: https://discord.gg/aiuni). However, the Online Demo is slightly different from the Gradio Demo, in that the inference speed is slower, but the generation is much more stable.
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'''
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with gr.Column(scale=1):
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gr.Markdown('# ' + _TITLE)
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gr.Markdown(_DESCRIPTION)
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create_3d_ui("wkl")
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demo.queue().launch(share=True)
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if __name__ == '__main__':
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fire.Fire(launch)
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import shlex
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import subprocess
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subprocess.run(shlex.split("pip install pip==24.0"), check=True)
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subprocess.run(
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shlex.split(
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), check=True
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)
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if __name__ == "__main__":
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from huggingface_hub import snapshot_download
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snapshot_download("public-data/Unique3D", repo_type="model", local_dir="./ckpt")
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import os
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import sys
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sys.path.append(os.curdir)
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torch.set_float32_matmul_precision('medium')
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torch.backends.cuda.matmul.allow_tf32 = True
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torch.set_grad_enabled(False)
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import fire
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import gradio as gr
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from gradio_app.gradio_3dgen import create_ui as create_3d_ui
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from gradio_app.all_models import model_zoo
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_TITLE = '''Unique3D: High-Quality and Efficient 3D Mesh Generation from a Single Image'''
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_DESCRIPTION = '''
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<div>
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<a style="display:inline-block" href='https://github.com/AiuniAI/Unique3D'><img alt="GitHub Repo stars" src="https://img.shields.io/github/stars/AiuniAI/Unique3D?style=social">
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</a>
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<img alt="GitHub License" src="https://img.shields.io/github/license/AiuniAI/Unique3D">
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</div>
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# [Paper](https://arxiv.org/abs/2405.20343) | [Project page](https://wukailu.github.io/Unique3D/) | [Huggingface Demo](https://huggingface.co/spaces/Wuvin/Unique3D) | [Gradio Demo](http://unique3d.demo.avar.cn/) | [Online Demo](https://www.aiuni.ai/)
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* High-fidelity and diverse textured meshes generated by Unique3D from single-view images.
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* The demo is still under construction, and more features are expected to be implemented soon.
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* If the Huggingface Demo is overcrowded or fails to produce stable results, you can use the Online Demo [aiuni.ai](https://www.aiuni.ai/), which is free to try (get the registration invitation code Join Discord: https://discord.gg/aiuni). However, the Online Demo is slightly different from the Gradio Demo, in that the inference speed is slower, but the generation is much more stable.
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'''
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with gr.Column(scale=1):
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gr.Markdown('# ' + _TITLE)
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gr.Markdown(_DESCRIPTION)
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# Mensaje de agradecimiento para @hysts
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gr.Markdown("""
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### Special Thanks
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A big thank you to [@hysts](https://huggingface.co/hysts) for their help in making the "Duplicate this Space" feature work correctly!
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""")
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# Agregamos el fragmento HTML aquí
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gr.HTML("""
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<div style="display: flex; flex-direction: column; justify-content: center; align-items: center; text-align: center;">
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<p style="display: flex; gap: 6px;">
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<a href="https://huggingface.co/spaces/cavargas10/Unico3D?duplicate=true">
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<img src="https://huggingface.co/datasets/huggingface/badges/resolve/main/duplicate-this-space-lg.svg" alt="Duplicate this Space">
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</a>
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</p>
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<p>to skip the queue and enjoy faster inference on the GPU of your choice</p>
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</div>
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""")
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create_3d_ui("wkl")
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demo.queue().launch(share=True)
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if __name__ == '__main__':
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fire.Fire(launch)
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