Instructions to use levihsu/OOTDiffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use levihsu/OOTDiffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("levihsu/OOTDiffusion", 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 our OOTDiffusion](https://ootd.ibot.cn/) | |
| Please give me a star if you find it interesting! | |
| > **OOTDiffusion: Outfitting Fusion based Latent Diffusion for Controllable Virtual Try-on**<br> | |
| > [Yuhao Xu](https://scholar.google.com/citations?user=FF7JVLsAAAAJ&hl=zh-CN), [Tao Gu](https://github.com/T-Gu), [Weifeng Chen](https://github.com/ShineChen1024), and [Chengcai Chen](https://www.researchgate.net/profile/Chengcai-Chen)<br> | |
| > Xiao-i Research | |
| An early version of our paper is available now! [[arXiv](https://arxiv.org/abs/2403.01779)] | |
| 🥳🥳 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 use checkpoints of [humanparsing](https://github.com/GoGoDuck912/Self-Correction-Human-Parsing) and [openpose](https://huggingface.co/lllyasviel/ControlNet/tree/main/annotator/ckpts) in preprocess. Please refer to their guidance if you encounter relevant environmental issues | |
| * Please 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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