Instructions to use Anyou/MagicMakeup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Anyou/MagicMakeup with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Anyou/MagicMakeup", torch_dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
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README.md
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## Code and Usage
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The official code and model are available at the following GitHub repository:
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[https://github.com/vivoCameraResearch/Magic-Makeup](https://github.com/vivoCameraResearch/Magic-Makeup)
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## Code and Usage
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The official code and model are available at the following GitHub repository:
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[https://github.com/vivoCameraResearch/Magic-Makeup](https://github.com/vivoCameraResearch/Magic-Makeup)
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## Citation
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@misc{wang2026magicmakeupregioncontrollablediffusiontransformer,
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title={MagicMakeup: A Region-Controllable Diffusion Transformer for High-Fidelity Makeup-Transfer},
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author={Ziyi Wang and Siming Zheng and Yang Yang and Shusong Xu and Hao Zhang and Bo Li and Changqing Zou and Peng-Tao Jiang},
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year={2026},
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eprint={2607.20924},
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archivePrefix={arXiv},
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primaryClass={cs.CV},
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url={https://arxiv.org/abs/2607.20924},
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}
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