Comfyui-CatVTON This repository is the modified official Comfyui node of CatVTON, which is a simple and efficient virtual try-on diffusion model with 1) Lightweight Network (899.06M parameters totally), 2) Parameter-Efficient Training (49.57M parameters trainable) 3) Simplified Inference (< 8G VRAM for 1024X768 resolution).

The original GitHub project is https://github.com/Zheng-Chong/CatVTON

1. git clone https://github.com/pzc163/Comfyui-CatVTON.git under the ComfyUI-aki-v1.3/custom_nodes path or install https://github.com/pzc163/Comfyui-CatVTON.git according to Comfyui Manager with git URL
2. install Detectron2 and DensePose

pip install git https://github.com/facebookresearch/detectron2.git@v0.6
pip install git https://github.com/facebookresearch/detectron2.git@v0.6#subdirectory=projects/DensePose

For Windows OS users, if you encounter a compilation and installation failure prompt, you can choose between the following two options if python==3.10 Please download Detectron2 and DensePose zip file in the Releases, which includes the code placed under /ComfyUI/python/Lib/site-packages of ComfyUI folder path. Notice that Detectron2 and DensePose zip file was compiled under python==3.10 Cuda==12.1 torch==2.1.2 environment if you can't install Detectron2 and DensePose with the released zip file. if python==3.11 Please download Detectron2 and DensePose whl file in the Releases, which includes the wheel file under python==3.11,placed under /ComfyUI/python/Lib/site-packages of ComfyUI folder path. then open cmd under ./ComfyUI/python/Lib/site-packages/ path pip install detectron2-0.6-cp311-cp311-win_amd64.whl pip install detectron2_densepose-0.6-py3-none-any.whl

3. Run the ComfyUI.
4. Download catvton_workflow.json and drag it into you ComfyUI webpage and enjoy 😆!

When you run the CatVTON workflow for the first time, the weight files will be automatically downloaded, which usually takes dozens of minutes.

If you need to deploy catVTON in a anaconda environment, you can follow the steps below: An Installation Guide is provided to help build the conda environment for CatVTON. When deploying the app, you will need Detectron2 & DensePose, but these are not required for inference on datasets. Install the packages according to your needs.

Our code is modified based on https://github.com/Zheng-Chong/CatVTON