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# <center> 🐈 CatVTON: Concatenation Is All You Need for Virtual Try-On with Diffusion Models
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<a href="https://github.com/Zheng-Chong/CatVTON">
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<img src='https://img.shields.io/badge/arXiv-Paper(soon)-red?style=flat&logo=arXiv&logoColor=red' alt='arxiv'>
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</a>
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<a href="http://120.76.142.206:8888">
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<img src='https://img.shields.io/badge/Demo-Gradio-orange?style=flat&logo=Gradio&logoColor=red' alt='Demo'>
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</a>
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<a href='https://huggingface.co/zhengchong/CatVTON'>
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<img src='https://img.shields.io/badge/Hugging Face-ckpts-orange?style=flat&logo=HuggingFace&logoColor=orange' alt='huggingface'>
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</a>
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<a href="https://github.com/Zheng-Chong/CatVTON">
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<img src='https://img.shields.io/badge/GitHub-Repo-blue?style=flat&logo=GitHub' alt='GitHub'>
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<a href="https://github.com/Zheng-Chong/CatVTON/LICENCE"><img src='https://img.shields.io/badge/License-CC BY--NC--SA--4.0-lightgreen?style=flat&logo=Lisence' alt='License'>
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<!-- This repository is the official implementation of ***CatVTON: Concatenation Is All You Need for Virtual Try-On with Diffsuion Models***. -->
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**CatVTON** 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)*** and ***3) Simplified Inference (< 8G VRAM for 1024X768 resolution)***.
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## Updates
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- **`2024/7/21`**: Our **Inference Code** and [**🤗Weights**](https://huggingface.co/zhengchong/CatVTON) are released.
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- **`2024/7/11`**: [**Online Demo**](http://120.76.142.206:8888) is released.
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## Inference
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### Data Preparation
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Before inference, you need to download the [VITON-HD](https://github.com/shadow2496/VITON-HD) or [DressCode](https://github.com/aimagelab/dress-code) dataset.
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# <center> 🐈 CatVTON: Concatenation Is All You Need for Virtual Try-On with Diffusion Models
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[ArXiv(soon)](https://github.com/Zheng-Chong/CatVTON) [Demo](http://120.76.142.206:8888) [GitHub](https://github.com/Zheng-Chong/CatVTON)
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**CatVTON** 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)*** and ***3) Simplified Inference (< 8G VRAM for 1024X768 resolution)***.
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## Updates
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- **`2024/7/21`**: Our [**Inference Code**] and [**🤗Weights**](https://huggingface.co/zhengchong/CatVTON) are released.
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- **`2024/7/11`**: [**Online Demo**](http://120.76.142.206:8888) is released.
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## Inference
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### Data Preparation
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Before inference, you need to download the [VITON-HD](https://github.com/shadow2496/VITON-HD) or [DressCode](https://github.com/aimagelab/dress-code) dataset.
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