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.gitignore

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+*.pyc

README.md

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----
-title: Unique3D786
-emoji: 🏢
-colorFrom: purple
-colorTo: pink
-sdk: gradio
-sdk_version: 5.25.2
-app_file: app.py
-pinned: false
-short_description: 3D
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: Unique3D
+emoji: ⚡
+colorFrom: red
+colorTo: purple
+sdk: gradio
+python_version: 3.10.8
+sdk_version: 4.12.0
+app_file: app.py
+pinned: true
+short_description: Create a 1M faces 3D colored model from an image!
+license: mit
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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-import gradio as gr
-import torch
-import spaces  # Import the spaces library
-
-@spaces.GPU  # Decorate the function that needs GPU
-def greet(n):
-    device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
-    zero = torch.tensor([0]).to(device)
-    print(zero.device)
-    return f"Hello {zero + n} Tensor"
-
-demo = gr.Interface(fn=greet, inputs=gr.Number(), outputs=gr.Text())
-demo.launch()
+import shlex
+import subprocess
+subprocess.run(
+    shlex.split(
+        "pip install package/onnxruntime_gpu-1.17.0-cp310-cp310-manylinux_2_28_x86_64.whl --force-reinstall --no-deps"
+    )
+)
+subprocess.run(
+    shlex.split(
+        "pip install package/nvdiffrast-0.3.1.torch-cp310-cp310-linux_x86_64.whl --force-reinstall --no-deps"
+    )
+)
+
+if __name__ == "__main__":
+    import os
+    from huggingface_hub import login
+    hf_token = os.environ.get("HF_TOKEN")
+    login(token=hf_token)
+    
+    import os
+    import sys
+    sys.path.append(os.curdir)
+    import torch
+    torch.set_float32_matmul_precision('medium')
+    torch.backends.cuda.matmul.allow_tf32 = True
+    torch.set_grad_enabled(False)
+
+import fire
+import gradio as gr
+from gradio_app.gradio_3dgen import create_ui as create_3d_ui
+from gradio_app.all_models import model_zoo
+
+
+_TITLE = '''Unique3D: High-Quality and Efficient 3D Mesh Generation from a Single Image'''
+_DESCRIPTION = '''
+
+<div>
+    <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">
+</a>
+    <img alt="GitHub License" src="https://img.shields.io/github/license/AiuniAI/Unique3D">
+</div>
+
+# [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/)
+
+* High-fidelity and diverse textured meshes generated by Unique3D from single-view images.
+
+* The demo is still under construction, and more features are expected to be implemented soon.
+
+* 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.
+'''
+
+def launch():
+    model_zoo.init_models()
+        
+    with gr.Blocks(
+        title=_TITLE,
+        # theme=gr.themes.Monochrome(),
+    ) as demo:
+        with gr.Row():
+            with gr.Column(scale=1):
+                gr.Markdown('# ' + _TITLE)
+        gr.Markdown(_DESCRIPTION)
+        create_3d_ui("wkl")
+
+    demo.queue().launch(share=True)
+    
+if __name__ == '__main__':
+    fire.Fire(launch)

requirements-detail.txt

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+accelerate==0.29.2
+datasets==2.18.0
+diffusers==0.27.2
+fire==0.6.0
+gradio==4.32.0
+jaxtyping==0.2.29
+numba==0.59.1
+numpy==1.26.4
+nvdiffrast==0.3.1
+omegaconf==2.3.0
+onnxruntime_gpu==1.17.0
+opencv_python==4.9.0.80
+opencv_python_headless==4.9.0.80
+ort_nightly_gpu==1.17.0.dev20240118002
+peft==0.10.0
+Pillow==10.3.0
+pygltflib==1.16.2
+pymeshlab==2023.12.post1
+pytorch3d==0.7.5
+rembg==2.0.56
+torch==2.1.0+cu121
+torch_scatter==2.1.2
+tqdm==4.64.1
+transformers==4.39.3
+trimesh==4.3.0
+typeguard==2.13.3
+wandb==0.16.6

requirements.txt

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+pytorch3d @ https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/py310_cu121_pyt221/pytorch3d-0.7.6-cp310-cp310-linux_x86_64.whl
+ort_nightly_gpu @ https://aiinfra.pkgs.visualstudio.com/2692857e-05ef-43b4-ba9c-ccf1c22c437c/_packaging/d3daa2b0-aa56-45ac-8145-2c3dc0661c87/pypi/download/ort-nightly-gpu/1.17.dev20240118002/ort_nightly_gpu-1.17.0.dev20240118002-cp310-cp310-manylinux_2_28_x86_64.whl
+onnxruntime_gpu @ https://pkgs.dev.azure.com/onnxruntime/2a773b67-e88b-4c7f-9fc0-87d31fea8ef2/_packaging/7fa31e42-5da1-4e84-a664-f2b4129c7d45/pypi/download/onnxruntime-gpu/1.17/onnxruntime_gpu-1.17.0-cp310-cp310-manylinux_2_28_x86_64.whl
+torch==2.2.0
+accelerate
+datasets
+diffusers>=0.26.3
+fire
+gradio
+jaxtyping
+numba
+numpy
+omegaconf>=2.3.0
+opencv_python
+opencv_python_headless
+peft
+Pillow
+pygltflib
+pymeshlab>=2023.12
+rembg[gpu]
+torch>=2.0.1
+torch_scatter @ https://data.pyg.org/whl/torch-2.2.0%2Bcu121/torch_scatter-2.1.2%2Bpt22cu121-cp310-cp310-linux_x86_64.whl
+tqdm
+transformers
+trimesh
+typeguard
+wandb
+xformers
+ninja