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Update app.py
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app.py
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@@ -244,23 +244,24 @@ def make3d(images):
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_HEADER_ = '''
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<h2><b>
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Code: <a href='https://github.com/TencentARC/InstantMesh' target='_blank'>GitHub</a>.
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- The 3D mesh generation
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'''
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_CITE_ = r"""
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If
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📝 **Citation**
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If you
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```bibtex
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@article{xu2024instantmesh,
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title={InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models},
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_HEADER_ = '''
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<h2><b>Welcome to 3DFusion!</b></h2>
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<h2><a href='https://github.com/TencentARC/InstantMesh' target='_blank'><b>3D Mesh Generation from Single Images with 3DFusion</b></a></h2>
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3DFusion is a cutting-edge, efficient 3D mesh generation tool based on the powerful LRM/Instant3D architecture.
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Code and Original Framework: <a href='https://github.com/TencentARC/InstantMesh' target='_blank'>InstantMesh GitHub</a>. Technical report: <a href='https://arxiv.org/abs/2404.07191' target='_blank'>ArXiv</a>.
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❗️**Important Notes:**
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- This demo exports both `.obj` and `.glb` meshes, including vertex colors.
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- The 3D mesh generation depends on the quality of generated multi-view images, so try different seed values (default: 42) for optimal results.
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'''
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_CITE_ = r"""
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If you find **3DFusion** helpful, please give a ⭐ to the original <a href='https://github.com/TencentARC/InstantMesh' target='_blank'>InstantMesh repository</a>. We appreciate the work of the TencentARC team! [![GitHub Stars](https://img.shields.io/github/stars/TencentARC/InstantMesh?style=social)](https://github.com/TencentARC/InstantMesh)
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---
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📝 **Citation**
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If you use this work for research or applications, cite it as follows:
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```bibtex
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@article{xu2024instantmesh,
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title={InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Models},
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