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magic-animate

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[CVPR 2024] Official repository for "MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model"

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<h2 align="center">MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model</h2>
 
 <a href="https://scholar.google.com/citations?user=-4iADzMAAAAJ&hl=en">Zhongcong Xu</a>
 ·
 <a href="http://jeff95.me/">Jianfeng Zhang</a>
 ·
 <a href="https://scholar.google.com.sg/citations?user=8gm-CYYAAAAJ&hl=en">Jun Hao Liew</a>
 ·
 <a href="https://hanshuyan.github.io/">Hanshu Yan</a>
 ·
 <a href="https://scholar.google.com/citations?user=stQQf7wAAAAJ&hl=en">Jia-Wei Liu</a>
 ·
 <a href="https://zhangchenxu528.github.io/">Chenxu Zhang</a>
 ·
 <a href="https://sites.google.com/site/jshfeng/home">Jiashi Feng</a>
 ·
 <a href="https://sites.google.com/view/showlab">Mike Zheng Shou</a>
 
 
 <a href="https://arxiv.org/abs/2311.16498"><img src='https://img.shields.io/badge/arXiv-MagicAnimate-red' alt='Paper PDF'></a>
 <a href='https://showlab.github.io/magicanimate'><img src='https://img.shields.io/badge/Project_Page-MagicAnimate-green' alt='Project Page'></a>
 <a href='https://huggingface.co/spaces/zcxu-eric/magicanimate'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Spaces-blue'></a>
 
 National University of Singapore &nbsp; | &nbsp; ByteDance
 
 
 <table align="center">
 <tr>
 <td>
 <img src="assets/teaser/t4.gif">
 </td>
 <td>
 <img src="assets/teaser/t2.gif">
 </td>
 </tr>
 </table>

## 📢 News
* **[2023.12.4]** Release inference code and gradio demo. We are working to improve MagicAnimate, stay tuned!
* **[2023.11.23]** Release MagicAnimate paper and project page.

## 🏃‍♂️ Getting Started
Download the pretrained base models for [StableDiffusion V1.5](https://huggingface.co/runwayml/stable-diffusion-v1-5) and [MSE-finetuned VAE](https://huggingface.co/stabilityai/sd-vae-ft-mse).

Download our MagicAnimate [checkpoints](https://huggingface.co/zcxu-eric/MagicAnimate).

Please follow the huggingface download instructions to download the above models and checkpoints, `git lfs` is recommended.

## ⚒️ Installation
prerequisites: `python>=3.8`, `CUDA>=11.3`, and `ffmpeg`.

Install with `conda`: 
```bash
conda env create -f environment.yaml
conda activate manimate
```
or `pip`:
```bash
pip3 install -r requirements.txt
```

## 💃 Inference
Run inference on single GPU:
```bash
bash scripts/animate.sh
```
Run inference with multiple GPUs:
```bash
bash scripts/animate_dist.sh
```

## 🎨 Gradio Demo

#### Online Gradio Demo:
Try our [online gradio demo](https://huggingface.co/spaces/zcxu-eric/magicanimate) quickly.

#### Local Gradio Demo:
Launch local gradio demo on single GPU:
```bash
python3 -m demo.gradio_animate
```
Launch local gradio demo if you have multiple GPUs:
```bash
python3 -m demo.gradio_animate_dist
```
Then open gradio demo in local browser.

## 🙏 Acknowledgements
We would like to thank [AK(@_akhaliq)](https://twitter.com/_akhaliq?lang=en) and huggingface team for the help of setting up oneline gradio demo.

## 🎓 Citation
If you find this codebase useful for your research, please use the following entry.
```BibTeX
@inproceedings{xu2023magicanimate,
    author    = {Xu, Zhongcong and Zhang, Jianfeng and Liew, Jun Hao and Yan, Hanshu and Liu, Jia-Wei and Zhang, Chenxu and Feng, Jiashi and Shou, Mike Zheng},
    title     = {MagicAnimate: Temporally Consistent Human Image Animation using Diffusion Model},
    booktitle = {arXiv},
    year      = {2023}
}
```

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