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Update app.py
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app.py
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@@ -65,12 +65,16 @@ STYLE_NAMES = list(styles.keys())
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MAX_SEED = np.iinfo(np.int32).max
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title = r"""
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<h1 align="center">
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"""
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description = r"""
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<b>Official 🤗 Gradio demo</b> for <a href='https://github.com/kongzhecn/OMG/' target='_blank'><b>OMG: Occlusion-friendly Personalized Multi-concept Generation In Diffusion Models</b></a>.<be
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<
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How to use:<br>
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1. Select two characters.
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2. Enter a text prompt as done in normal text-to-image models.
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@@ -84,11 +88,11 @@ article = r"""
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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{,
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title={OMG: Occlusion-friendly Personalized Multi-concept Generation
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author={},
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journal={},
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year={}
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}
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```
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"""
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@@ -654,6 +658,7 @@ def main(device, segment_type):
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inputs=[prompt, negative_prompt, reference_1, reference_2, resolution, local_prompt1, local_prompt2, seed, style, identitynet_strength_ratio, adapter_strength_ratio, condition, condition_img1, controlnet_ratio, cfg_ratio],
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outputs=[gallery, gallery1]
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)
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demo.launch(share=True)
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def parse_args():
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MAX_SEED = np.iinfo(np.int32).max
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title = r"""
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<h1 align="center"> OMG + InstantID </h1>
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"""
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description = r"""
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<b>Official 🤗 Gradio demo</b> for <a href='https://github.com/kongzhecn/OMG/' target='_blank'><b>OMG: Occlusion-friendly Personalized Multi-concept Generation In Diffusion Models</b></a>.<be><br>
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<br>
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<a href='https://kongzhecn.github.io/omg-project/' target='_blank'><b>[Project]</b></a><a href='https://github.com/kongzhecn/OMG/' target='_blank'><b>[Code]</b></a><a href='https://arxiv.org/abs/2403.10983/' target='_blank'><b>[Arxiv]</b></a><br>
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<br>
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❗️<b>Related demos<b>:<a href='https://huggingface.co/spaces/Fucius/OMG/' target='_blank'><b> OMG + LoRAs </b></a>❗️<br>
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<br>
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How to use:<br>
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1. Select two characters.
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2. Enter a text prompt as done in normal text-to-image models.
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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{kong2024omg,
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title={OMG: Occlusion-friendly Personalized Multi-concept Generation in Diffusion Models},
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author={Kong, Zhe and Zhang, Yong and Yang, Tianyu and Wang, Tao and Zhang, Kaihao and Wu, Bizhu and Chen, Guanying and Liu, Wei and Luo, Wenhan},
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journal={arXiv preprint arXiv:2403.10983},
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year={2024}
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}
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```
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"""
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inputs=[prompt, negative_prompt, reference_1, reference_2, resolution, local_prompt1, local_prompt2, seed, style, identitynet_strength_ratio, adapter_strength_ratio, condition, condition_img1, controlnet_ratio, cfg_ratio],
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outputs=[gallery, gallery1]
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)
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gr.Markdown(article)
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demo.launch(share=True)
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def parse_args():
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