| --- |
| title: OOTDiffusion Try-On |
| emoji: 👗 |
| colorFrom: purple |
| colorTo: pink |
| sdk: gradio |
| sdk_version: 4.16.0 |
| app_file: ./run/gradio_ootd.py |
| pinned: false |
| --- |
| |
| # OOTDiffusion |
| This repository is the official implementation of OOTDiffusion |
|
|
| 🤗 [Try out OOTDiffusion](https://huggingface.co/spaces/levihsu/OOTDiffusion) |
|
|
| (Thanks to [ZeroGPU](https://huggingface.co/zero-gpu-explorers) for providing A100 GPUs) |
|
|
| <!-- Or [try our own demo](https://ootd.ibot.cn/) on RTX 4090 GPUs --> |
|
|
| > **OOTDiffusion: Outfitting Fusion based Latent Diffusion for Controllable Virtual Try-on** [[arXiv paper](https://arxiv.org/abs/2403.01779)]<br> |
| > [Yuhao Xu](http://levihsu.github.io/), [Tao Gu](https://github.com/T-Gu), [Weifeng Chen](https://github.com/ShineChen1024), [Chengcai Chen](https://www.researchgate.net/profile/Chengcai-Chen)<br> |
| > Xiao-i Research |
|
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|
|
| Our model checkpoints trained on [VITON-HD](https://github.com/shadow2496/VITON-HD) (half-body) and [Dress Code](https://github.com/aimagelab/dress-code) (full-body) have been released |
|
|
| * 🤗 [Hugging Face link](https://huggingface.co/levihsu/OOTDiffusion) for ***checkpoints*** (ootd, humanparsing, and openpose) |
| * 📢📢 We support ONNX for [humanparsing](https://github.com/GoGoDuck912/Self-Correction-Human-Parsing) now. Most environmental issues should have been addressed : ) |
| * Please also download [clip-vit-large-patch14](https://huggingface.co/openai/clip-vit-large-patch14) into ***checkpoints*** folder |
| * We've only tested our code and models on Linux (Ubuntu 22.04) |
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|
| ## Installation |
| 1. Clone the repository |
|
|
| ```sh |
| git clone https://github.com/levihsu/OOTDiffusion |
| ``` |
|
|
| 2. Create a conda environment and install the required packages |
|
|
| ```sh |
| conda create -n ootd python==3.10 |
| conda activate ootd |
| pip install torch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 |
| pip install -r requirements.txt |
| ``` |
|
|
| ## Inference |
| 1. Half-body model |
|
|
| ```sh |
| cd OOTDiffusion/run |
| python run_ootd.py --model_path <model-image-path> --cloth_path <cloth-image-path> --scale 2.0 --sample 4 |
| ``` |
|
|
| 2. Full-body model |
|
|
| > Garment category must be paired: 0 = upperbody; 1 = lowerbody; 2 = dress |
|
|
| ```sh |
| cd OOTDiffusion/run |
| python run_ootd.py --model_path <model-image-path> --cloth_path <cloth-image-path> --model_type dc --category 2 --scale 2.0 --sample 4 |
| ``` |
|
|
| ## Citation |
| ``` |
| @article{xu2024ootdiffusion, |
| title={OOTDiffusion: Outfitting Fusion based Latent Diffusion for Controllable Virtual Try-on}, |
| author={Xu, Yuhao and Gu, Tao and Chen, Weifeng and Chen, Chengcai}, |
| journal={arXiv preprint arXiv:2403.01779}, |
| year={2024} |
| } |
| ``` |
|
|
| ## Star History |
|
|
| [](https://star-history.com/#levihsu/OOTDiffusion&Date) |
|
|
| ## TODO List |
| - [x] Paper |
| - [x] Gradio demo |
| - [x] Inference code |
| - [x] Model weights |
| - [ ] Training code |
|
|
