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ComfyUI_Stable_Makeup

You can apply makeup to the characters in comfyui

Stable_Makeup From: Stable_Makeup

My ComfyUI node list:

1、ParlerTTS node:ComfyUI_ParlerTTS
2、Llama3_8B node:ComfyUI_Llama3_8B
3、HiDiffusion node:ComfyUI_HiDiffusion_Pro
4、ID_Animator node: ComfyUI_ID_Animator
5、StoryDiffusion node:ComfyUI_StoryDiffusion
6、Pops node:ComfyUI_Pops
7、stable-audio-open-1.0 node :ComfyUI_StableAudio_Open
8、GLM4 node:ComfyUI_ChatGLM_API
9、CustomNet node:ComfyUI_CustomNet
10、Pipeline_Tool node :ComfyUI_Pipeline_Tool
11、Pic2Story node :ComfyUI_Pic2Story
12、PBR_Maker node:ComfyUI_PBR_Maker
13、ComfyUI_Streamv2v_Plus node:ComfyUI_Streamv2v_Plus
14、ComfyUI_MS_Diffusion node:ComfyUI_MS_Diffusion
15、ComfyUI_AnyDoor node: ComfyUI_AnyDoor
16、ComfyUI_Stable_Makeup node: ComfyUI_Stable_Makeup

Update

---社区模型没有必要,之前添加是为了别的功能,目前无法实现,所以已经剔除;
---可以尝试不同的数据集,当然,意味着你要多下载几个SPIGA模型;
---修复没有预下载的模型时,无法加载的错误;
---fix bug ,The community model is not necessary
--- You can try different datasets, of course, which means you need to download a few more SPIGA models;
---Fix the error where models that were not downloaded in advance cannot be loaded;

1.Installation

In the ./ComfyUI /custom_node directory, run the following:

git clone https://github.com/smthemex/ComfyUI_Stable_Makeup.git

2.requirements

按理是不需要装特别的库,因为内置了,如果还是库丢失,请单独安装。或者打开no need requirements.txt,查看缺失的库是否在里面。
秋叶包因为是沙箱模式,所以把缺失的库安装在系统的python库里。
官方的整合包,用pip install AAA --target="BBB/python_embeded/Lib/site-packages" AAA替换为缺失的库,BBB是本地路径。

If the module is missing, please open "no need requirements.txt" , pip install missing module.

3 Need model

模型的下载地址比较杂,所以使用前请下下载,并存放在ComfyUI/models/stable_makeup 文件夹下:
The download address for the model is quite miscellaneous, so please download it before use and store it in the ComfyUI/models/table_makeup folder:

3.1 spiga_300wpublic.pt or other models link

3.2 "pytorch_model.bin & pytorch_model_1.bin & pytorch_model_2.bin" link

3.3 mobilenet0.25_Final.pth link
or
resnet50.pth link

3.4 sd1.5的标准模型只需要以下结构内的文件,你如果直接用内置的repo下载,都会缓存到c盘,大概3.97G。
runwayml/stable-diffusion-v1-5 ,need unet models and vae encoder, You can check the following list, which includes the model and file locations,all 3.97G.

3.5 clip模型,这个迟点看能否用comfyUI内置的,以及外置为输入格式,可以引导至本地其他路径。
"openai/clip-vit-large-patch14" clip models

Models list

├── ComfyUI/models/  
|     ├──stable_makeup
|         ├── mobilenet0.25_Final.pth
|         ├── pytorch_model.bin
|         ├── pytorch_model_1.bin
|         ├── pytorch_model_2.bin
|         ├── spiga_300wpublic.pt
|         ├── resnet50.pth

“runwayml/stable-diffusion-v1-5”只需要以下的文件,其他的不用下载,如果用默认的repo下载,会自动缓存到C盘
"Runwayml/stable diffusion-v1-5 "only requires the following files, the rest do not need to be downloaded. If downloaded using the default repo, it will be automatically cached on the C drive

├── ComfyUI/models/
|     ├──diffusers
|         ├── runwayml/stable-diffusion-v1-5
|             ├──unet
|                 ├── diffusion_pytorch_model.safetensors
|                 ├── config.json
|             ├──vae
|                 ├── diffusion_pytorch_model.safetensors
|                 ├── config.json
|             ├──tokenizer
|                 ├── merges.txt
|                 ├── special_tokens_map.json
|                 ├── tokenizer_config.json
|                 ├── vocab.json
|             ├──text_encoder
|                 ├── model.safetensors
|                 ├── config.json
|             ├──scheduler
|                 ├── scheduler_config.json
|             ├──safety_checker
|                 ├── config.json
|             ├──feature_extractor
|                 ├── preprocessor_config.json
|             ├──model_index.json

Example

6 Citation

@article{zhang2024stable,
  title={Stable-Makeup: When Real-World Makeup Transfer Meets Diffusion Model},
  author={Zhang, Yuxuan and Wei, Lifu and Zhang, Qing and Song, Yiren and Liu, Jiaming and Li, Huaxia and Tang, Xu and Hu, Yao and Zhao, Haibo},
  journal={arXiv preprint arXiv:2403.07764},
  year={2024}
}

SPIGA From: SPIGA

@inproceedings{Prados-Torreblanca_2022_BMVC,
  author    = {Andrés  Prados-Torreblanca and José M Buenaposada and Luis Baumela},
  title     = {Shape Preserving Facial Landmarks with Graph Attention Networks},
  booktitle = {33rd British Machine Vision Conference 2022, {BMVC} 2022, London, UK, November 21-24, 2022},
  publisher = {{BMVA} Press},
  year      = {2022},
  url       = {https://bmvc2022.mpi-inf.mpg.de/0155.pdf}
}

FaceLib From: FaceLib

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