Image-to-Image
Diffusers
ONNX
Safetensors
StableDiffusionXLInpaintPipeline
stable-diffusion-xl
inpainting
virtual try-on
Instructions to use Sodkhuu/tryon3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Sodkhuu/tryon3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Sodkhuu/tryon3", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
| base_model: stable-diffusion-xl-1.0-inpainting-0.1 | |
| tags: | |
| - stable-diffusion-xl | |
| - inpainting | |
| - virtual try-on | |
| license: cc-by-nc-sa-4.0 | |
| # Check out more codes on our [github repository](https://github.com/yisol/IDM-VTON)! | |
| # IDM-VTON : Improving Diffusion Models for Authentic Virtual Try-on in the Wild | |
| This is an official implementation of paper 'Improving Diffusion Models for Authentic Virtual Try-on in the Wild' | |
| - [paper](https://arxiv.org/abs/2403.05139) | |
| - [project page](https://idm-vton.github.io/) | |
| 🤗 Try our huggingface [Demo](https://huggingface.co/spaces/yisol/IDM-VTON) | |
|  | |
|  | |
| ## TODO LIST | |
| - [x] demo model | |
| - [x] inference code | |
| - [ ] training code | |
| ## Acknowledgements | |
| For the demo, GPUs are supported from [zerogpu](https://huggingface.co/zero-gpu-explorers), and auto masking generation codes are based on [OOTDiffusion](https://github.com/levihsu/OOTDiffusion) and [DCI-VTON](https://github.com/bcmi/DCI-VTON-Virtual-Try-On). | |
| Parts of the code are based on [IP-Adapter](https://github.com/tencent-ailab/IP-Adapter). | |
| ## Citation | |
| ``` | |
| @article{choi2024improving, | |
| title={Improving Diffusion Models for Virtual Try-on}, | |
| author={Choi, Yisol and Kwak, Sangkyung and Lee, Kyungmin and Choi, Hyungwon and Shin, Jinwoo}, | |
| journal={arXiv preprint arXiv:2403.05139}, | |
| year={2024} | |
| } | |
| ``` | |
| ## License | |
| The codes and checkpoints in this repository are under the [CC BY-NC-SA 4.0 license](https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode). | |