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app.py
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@@ -312,7 +312,7 @@ if __name__ == "__main__":
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<div style="text-align: center;">
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<h1> UniPortrait: A Unified Framework for Identity-Preserving Single- and Multi-Human Image Personalization </h1>
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<div style="display: flex; justify-content: center; align-items: center; text-align: center;">
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<a href="https://arxiv.org/pdf/
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<a href='https://aigcdesigngroup.github.io/UniPortrait-Page/'><img src='https://img.shields.io/badge/Project_Page-UniPortrait-green' alt='Project Page'></a>
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"""
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title_description = r"""
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This is the <b>official π€ Gradio demo</b> for <a href='https://arxiv.org/pdf/
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The demo provides three capabilities: text-to-single-ID personalization, text-to-multi-ID personalization, and image-to-single-ID personalization. All of these are based on the Stable Diffusion v1-5 model. Feel free to give them a try! π
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"""
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<br>
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If our work is helpful for your research or applications, please cite us via:
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```bibtex
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@article{wang2024instantid,
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title={InstantID: Zero-shot Identity-Preserving Generation in Seconds},
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author={Wang, Qixun and Bai, Xu and Wang, Haofan and Qin, Zekui and Chen, Anthony},
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journal={arXiv preprint arXiv:2401.07519},
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year={2024}
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}
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```
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π§ **Contact**
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<br>
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<div style="text-align: center;">
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<h1> UniPortrait: A Unified Framework for Identity-Preserving Single- and Multi-Human Image Personalization </h1>
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<div style="display: flex; justify-content: center; align-items: center; text-align: center;">
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<a href="https://arxiv.org/pdf/2408.05939"><img src="https://img.shields.io/badge/arXiv-2408.05939-red"></a>
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<a href='https://aigcdesigngroup.github.io/UniPortrait-Page/'><img src='https://img.shields.io/badge/Project_Page-UniPortrait-green' alt='Project Page'></a>
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"""
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title_description = r"""
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This is the <b>official π€ Gradio demo</b> for <a href='https://arxiv.org/pdf/2408.05939' target='_blank'><b>UniPortrait: A Unified Framework for Identity-Preserving Single- and Multi-Human Image Personalization</b></a>.<br>
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The demo provides three capabilities: text-to-single-ID personalization, text-to-multi-ID personalization, and image-to-single-ID personalization. All of these are based on the Stable Diffusion v1-5 model. Feel free to give them a try! π
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"""
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<br>
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If our work is helpful for your research or applications, please cite us via:
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```bibtex
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```
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π§ **Contact**
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<br>
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