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README.md
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license: cc-by-nc-sa-4.0
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---
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license: cc-by-nc-sa-4.0
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---
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# Magic Clothing
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This repository is the official implementation of Magic Clothing
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Magic Clothing is a branch version of [OOTDiffusion](https://github.com/levihsu/OOTDiffusion), focusing on controllable garment-driven image synthesis
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<!-- Please refer to our [previous paper](https://arxiv.org/abs/2403.01779) for more details -->
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> **Magic Clothing: Controllable Garment-Driven Image Synthesis** [[arXiv paper](https://arxiv.org/abs/2404.09512)]<br>
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> [Weifeng Chen](https://github.com/ShineChen1024)\*, [Tao Gu](https://github.com/T-Gu)\*, [Yuhao Xu](http://levihsu.github.io/), [Chengcai Chen](https://www.researchgate.net/profile/Chengcai-Chen)<br>
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> \* Equal contribution<br>
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> Xiao-i Research
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## News
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๐ฅ [2024/4/19] An 1024 version trained on both VTON-HD and DressCode for early access branch is avaliable now!
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๐ฅ [2024/4/19] We support AnimateDiff now for generating GIF!
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๐ฅ [2024/4/16] Our [paper](https://arxiv.org/abs/2404.09512) is available now!
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๐ฅ [2024/3/8] We released the model weights trained on the 768 resolution. The strength of clothing and text prompts can be independently adjusted.
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๐ค [Hugging Face link](https://huggingface.co/ShineChen1024/MagicClothing)
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๐ฅ [2024/2/28] We support [IP-Adapter-FaceID](https://huggingface.co/h94/IP-Adapter-FaceID) with [ControlNet-Openpose](https://github.com/lllyasviel/ControlNet-v1-1-nightly)! A portrait and a reference pose image can be used as additional conditions.
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Have fun with ***gradio_ipadapter_openpose.py***
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๐ฅ [2024/2/23] We support [IP-Adapter-FaceID](https://huggingface.co/h94/IP-Adapter-FaceID) now! A portrait image can be used as an additional condition.
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Have fun with ***gradio_ipadapter_faceid.py***
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***1024 version for upper-body lower-body and full-body clothes Demo***
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<div align="left">
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<img src="images/a0.jpg" alt="ๅพ็1" width="15%">
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<img src="images/a1.png" alt="ๅพ็2" width="15%">
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<img src="images/b0.jpg" alt="ๅพ็3" width="15%">
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<img src="images/b1.png" alt="ๅพ็4" width="15%">
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<img src="images/c0.jpg" alt="ๅพ็5" width="15%">
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<img src="images/c1.png" alt="ๅพ็6" width="15%">
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</div>
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***AnimateDiff Demo*** 'a beautiful girl with a smile'
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<div align="center">
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<img src="valid_cloth/t1.png" width="15%">
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<img src="images/animatediff0.gif" alt="ๅพ็1" width="15%">
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<img src="valid_cloth/t6.png" width="15%">
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<img src="images/animatediff1.gif" alt="ๅพ็2" width="15%">
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<img src="valid_cloth/t7.jpg" width="13%">
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<img src="images/animatediff2.gif" alt="ๅพ็3" width="15%">
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</div>
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## Installation
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1. Clone the repository
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```sh
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git clone https://github.com/ShineChen1024/MagicClothing.git
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```
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2. Create a conda environment and install the required packages
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```sh
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conda create -n magicloth python==3.10
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conda activate magicloth
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pip install torch==2.0.1 torchvision==0.15.2 numpy==1.25.1 diffusers==0.25.1 opencv-python==4.9.0.80 transformers==4.31.0 gradio==4.16.0 safetensors==0.3.1 controlnet-aux==0.0.6 accelerate==0.21.0
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```
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## Inference
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1. Python demo
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> 512 weights
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```sh
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python inference.py --cloth_path [your cloth path] --model_path [your model checkpoints path]
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```
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> 768 weights
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```sh
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python inference.py --cloth_path [your cloth path] --model_path [your model checkpoints path] --enable_cloth_guidance
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```
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2. Gradio demo
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> 512 weights
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```sh
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python gradio_generate.py --model_path [your model checkpoints path]
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```
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> 768 weights
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```sh
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python gradio_generate.py --model_path [your model checkpoints path] --enable_cloth_guidance
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```
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## Citation
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```
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@article{chen2024magic,
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title={Magic Clothing: Controllable Garment-Driven Image Synthesis},
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author={Chen, Weifeng and Gu, Tao and Xu, Yuhao and Chen, Chengcai},
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journal={arXiv preprint arXiv:2404.09512},
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year={2024}
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}
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```
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## TODO List
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- [x] Paper
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- [x] Gradio demo
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- [x] Inference code
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- [x] Model weights
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- [ ] Training code
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