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* This method need little space and VRAM(or CPU),all the models is about 200M(4 weights),and best quality size is 256*256
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* 这个方法所用4个模型加起来不到200M,所需显存或CPU可以忽略不记,当然,图片输出最佳质量是256*256.
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# Example
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# 1. Installation
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In the ./ComfyUI/custom_node directory, run the following:
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```
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git clone https://github.com/smthemex/ComfyUI_CSD_MT.git
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```
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---
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# 2. Requirements
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```
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pip install -r requirements.txt
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```
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* When install dlib get error,use wheel to install it,download wheel from this [address](https://github.com/z-mahmud22/Dlib_Windows_Python3.x)
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* 如果按照dlib库失败,从此链接下载对应你python版本的轮子,用以下命令安装:
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```
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pip install dlib-19.24.1-cp311-cp311-win_amd64.whl
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```
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# 3.Model
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* 3.1 download 2 checkpoints (79999_iter.pth,CSD_MT.pth) from [google](https://drive.google.com/drive/folders/1pvSgkpsb7k6Ph1_oCmFkMQZPgL7PaTO0) or [baidu](https://pan.baidu.com/share/init?surl=C7K4xk5W0X65yUQh41AmfQ) password:1d3e.从百度云或者Google下载三个模型
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* 3.2 download 'resnet18-5c106cde.pth' from [here](https://download.pytorch.org/models/resnet18-5c106cde.pth) 从链接下载resnet18-5c106cde.pth模型,不要改名字.
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```
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-- ComfyUI/models/CSDMT
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|-- 79999_iter.pth
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|-- CSD_MT.pth
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|--resnet18-5c106cde.pth #没有也会自动下载
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```
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```
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-- ComfyUI/custom_node/ComfyUI_CSD_MT/quick_start/faceutils/dlibutils
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|--lms.dat # Already in the project, no need to download,已内置在插件中,不用下载
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```
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# 4.Example
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# 5.Citation
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```
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@inproceedings{sun2024content,
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title={Content-Style Decoupling for Unsupervised Makeup Transfer without Generating Pseudo Ground Truth},
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author={Sun, Zhaoyang and Xiong, Shengwu and Chen, Yaxiong and Rong, Yi}
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journal={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
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year={2024}
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}
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```
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