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README.md

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+---
+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)
+
+![teaser](assets/teaser.png) 
+![teaser2](assets/teaser2.png) 
+
+
+## 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).
+
+
+

model_index.json

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+{
+  "_class_name": "StableDiffusionXLInpaintPipeline",
+  "_diffusers_version": "0.25.0",
+  "_name_or_path": "stabilityai/stable-diffusion-xl-base-1.0",
+  "force_zeros_for_empty_prompt": true,
+  "requires_aesthetics_score": false,
+  "scheduler": [
+    "diffusers",
+    "DDPMScheduler"
+  ],
+  "text_encoder": [
+    "transformers",
+    "CLIPTextModel"
+  ],
+  "feature_extractor": [
+    "transformers",
+    "CLIPImageProcessor"
+  ],
+  "text_encoder_2": [
+    "transformers",
+    "CLIPTextModelWithProjection"
+  ],
+  "tokenizer": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "tokenizer_2": [
+    "transformers",
+    "CLIPTokenizer"
+  ],
+  "unet": [
+    "diffusers",
+    "UNet2DConditionModel"
+  ],
+  "vae": [
+    "diffusers",
+    "AutoencoderKL"
+  ]
+}