Instructions to use spawn08/segmentation_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use spawn08/segmentation_model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("spawn08/segmentation_model", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
| license: cc-by-nc-sa-4.0 | |
| # OOTDiffusion | |
| [Our OOTDiffusion GitHub repository](https://github.com/levihsu/OOTDiffusion) | |
| 🤗 [Try out OOTDiffusion](https://huggingface.co/spaces/levihsu/OOTDiffusion) | |
| (Thanks to [ZeroGPU](https://huggingface.co/zero-gpu-explorers) for providing A100 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 | |
| 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 | |
| * 📢📢 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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|  | |
| ## 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} | |
| } | |
| ``` | |