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import shlex |
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import subprocess |
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subprocess.run( |
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shlex.split( |
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"pip install package/onnxruntime_gpu-1.17.0-cp310-cp310-manylinux_2_28_x86_64.whl --force-reinstall --no-deps" |
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) |
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) |
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subprocess.run( |
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shlex.split( |
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"pip install package/nvdiffrast-0.3.1.torch-cp310-cp310-linux_x86_64.whl --force-reinstall --no-deps" |
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) |
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) |
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if __name__ == "__main__": |
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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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import torch |
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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](https://u45213-bcf9-ef67553e.westx.seetacloud.com:8443/) | [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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def launch(): |
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model_zoo.init_models() |
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with gr.Blocks( |
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title=_TITLE, |
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) as demo: |
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with gr.Row(): |
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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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