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<h1 align='center'>EchoMimicV2: Towards Striking, Simplified, and Semi-Body Human Animation</h1>

<div align='center'>
    <a href='https://github.com/mengrang' target='_blank'>Rang Meng</a><sup></sup>&emsp;

    <a href='https://github.com/' target='_blank'>Xingyu Zhang</a><sup></sup>&emsp;

    <a href='https://lymhust.github.io/' target='_blank'>Yuming Li</a><sup></sup>&emsp;

    <a href='https://github.com/' target='_blank'>Chenguang Ma</a><sup></sup>

</div>



<div align='center'>
Terminal Technology Department, Alipay, Ant Group.
</div>
<br>
<div align='center'>
    <a href='https://antgroup.github.io/ai/echomimic_v2/'><img src='https://img.shields.io/badge/Project-Page-blue'></a>

    <a href='https://huggingface.co/BadToBest/EchoMimicV2'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20HuggingFace-Model-yellow'></a>

    <!--<a href='https://antgroup.github.io/ai/echomimic_v2/'><img src='https://img.shields.io/badge/%F0%9F%A4%97%20HuggingFace-Demo-yellow'></a>-->

    <a href='https://modelscope.cn/models/BadToBest/EchoMimicV2'><img src='https://img.shields.io/badge/ModelScope-Model-purple'></a>

    <!--<a href='https://antgroup.github.io/ai/echomimic_v2/'><img src='https://img.shields.io/badge/ModelScope-Demo-purple'></a>-->

    <a href='https://arxiv.org/abs/2411.10061'><img src='https://img.shields.io/badge/Paper-Arxiv-red'></a>

    <a href='https://github.com/antgroup/echomimic_v2/blob/main/assets/halfbody_demo/wechat_group.png'><img src='https://badges.aleen42.com/src/wechat.svg'></a>

</div>

<div align='center'>

    <a href='https://github.com/antgroup/echomimic_v2/discussions/53'><img src='https://img.shields.io/badge/English-Common Problems-orange'></a>

    <a href='https://github.com/antgroup/echomimic_v2/discussions/40'><img src='https://img.shields.io/badge/中文版-常见问题汇总-orange'></a>

</div>


## &#x1F680; EchoMimic Series
* EchoMimicV1: Lifelike Audio-Driven Portrait Animations through Editable Landmark Conditioning. [GitHub](https://github.com/antgroup/echomimic)
* EchoMimicV2: Towards Striking, Simplified, and Semi-Body Human Animation. [GitHub](https://github.com/antgroup/echomimic_v2)

## &#x1F4E3; Updates
* [2024.11.27] 🔥 Thanks [AiMotionStudio](https://www.youtube.com/@AiMotionStudio) for the [installation tutorial](https://www.youtube.com/watch?v=2ab6U1-nVTQ).
* [2024.11.22] 🔥 [GradioUI](https://github.com/antgroup/echomimic_v2/blob/main/app.py) is now available. Thanks @gluttony-10 for the contribution.
* [2024.11.22] 🔥 [ComfyUI](https://github.com/smthemex/ComfyUI_EchoMimic) is now available. Thanks @smthemex for the contribution.
* [2024.11.21] 🔥 We release the EMTD dataset list and processing scripts.
* [2024.11.21] 🔥 We release our [EchoMimicV2](https://github.com/antgroup/echomimic_v2) codes and models.
* [2024.11.15] 🔥 Our [paper](https://arxiv.org/abs/2411.10061) is in public on arxiv.

## &#x1F305; Gallery
### Introduction
<table class="center">
<tr>
    <td width=50% style="border: none">

        <video controls loop src="https://github.com/user-attachments/assets/f544dfc0-7d1a-4c2c-83c0-608f28ffda25" muted="false"></video>

    </td>

    <td width=50% style="border: none">

        <video controls loop src="https://github.com/user-attachments/assets/7f626b65-725c-4158-a96b-062539874c63" muted="false"></video>

    </td>

</tr>

</table>


### English Driven Audio
<table class="center">
<tr>
    <td width=100% style="border: none">

        <video controls loop src="https://github.com/user-attachments/assets/3d5ac52c-62e4-41bc-8b27-96f005bbd781" muted="false"></video>

    </td>

</tr>

</table>

<table class="center">

<tr>

    <td width=30% style="border: none">

        <video controls loop src="https://github.com/user-attachments/assets/e8dd6919-665e-4343-931f-54c93dc49a7d" muted="false"></video>

    </td>

    <td width=30% style="border: none">

        <video controls loop src="https://github.com/user-attachments/assets/2a377391-a0d3-4a9d-8dde-cc59006e7e5b" muted="false"></video>

    </td>

    <td width=30% style="border: none">

        <video controls loop src="https://github.com/user-attachments/assets/462bf3bb-0af2-43e2-a2dc-559e79953f3c" muted="false"></video>

    </td>

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    <td width=30% style="border: none">

        <video controls loop src="https://github.com/user-attachments/assets/0e988e7f-6346-4b54-9061-9cfc7a80e9c8" muted="false"></video>

    </td>

    <td width=30% style="border: none">

        <video controls loop src="https://github.com/user-attachments/assets/56f739bd-afbf-4ed3-ab15-73a811c1bc46" muted="false"></video>

    </td>

    <td width=30% style="border: none">

        <video controls loop src="https://github.com/user-attachments/assets/1b2f7827-111d-4fc0-a773-e1731bba285d" muted="false"></video>

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    <td width=30% style="border: none">

        <video controls loop src="https://github.com/user-attachments/assets/a76b6cc8-89b9-4f7e-b1ce-c85a657b6dc7" muted="false"></video>

    </td>

    <td width=30% style="border: none">

        <video controls loop src="https://github.com/user-attachments/assets/bf03b407-5033-4a30-aa59-b8680a515181" muted="false"></video>

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    <td width=30% style="border: none">

        <video controls loop src="https://github.com/user-attachments/assets/f98b3985-572c-499f-ae1a-1b9befe3086f" muted="false"></video>

    </td>

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</table>


### Chinese Driven Audio
<table class="center">
<tr>
    <td width=30% style="border: none">

        <video controls loop src="https://github.com/user-attachments/assets/a940a332-2fd1-48e7-b3c4-f88f63fd1c9d" muted="false"></video>

    </td>

    <td width=30% style="border: none">

        <video controls loop src="https://github.com/user-attachments/assets/8f185829-c67f-45f4-846c-fcbe012c3acf" muted="false"></video>

    </td>

    <td width=30% style="border: none">

        <video controls loop src="https://github.com/user-attachments/assets/a49ab9be-f17b-41c5-96dd-20dc8d759b45" muted="false"></video>

    </td>

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    <td width=30% style="border: none">

        <video controls loop src="https://github.com/user-attachments/assets/1136ec68-a13c-4ee7-ab31-5621530bf9df" muted="false"></video>

    </td>

    <td width=30% style="border: none">

        <video controls loop src="https://github.com/user-attachments/assets/fc16d512-8806-4662-ae07-8fcf45c75a83" muted="false"></video>

    </td>

    <td width=30% style="border: none">

        <video controls loop src="https://github.com/user-attachments/assets/f8559cd1-f555-4781-9251-dfcef10b5b01" muted="false"></video>

    </td>

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    <td width=30% style="border: none">

        <video controls loop src="https://github.com/user-attachments/assets/c7473e3a-ab51-4ad5-be96-6c4691fc0c6e" muted="false"></video>

    </td>

    <td width=30% style="border: none">

        <video controls loop src="https://github.com/user-attachments/assets/ca69eac0-5126-41ee-8cac-c9722004d771" muted="false"></video>

    </td>

    <td width=30% style="border: none">

        <video controls loop src="https://github.com/user-attachments/assets/e66f1712-b66d-46b5-8bbd-811fbcfea4fd" muted="false"></video>

    </td>

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</table>


## ⚒️ Installation
### Download the Codes

```bash

  git clone https://github.com/antgroup/echomimic_v2

  cd echomimic_v2

```

### Python Environment Setup

- Tested System Environment: Centos 7.2/Ubuntu 22.04, Cuda >= 11.7
- Tested GPUs: A100(80G) / RTX4090D (24G) / V100(16G)
- Tested Python Version: 3.8 / 3.10 / 3.11

Create conda environment (Recommended):

```bash

  conda create -n echomimic python=3.10

  conda activate echomimic

```

Install packages with `pip`
```bash

  pip install pip -U

  pip install torch==2.5.1 torchvision==0.20.1 torchaudio==2.5.1 xformers==0.0.28.post3 --index-url https://download.pytorch.org/whl/cu124

  pip install torchao --index-url https://download.pytorch.org/whl/nightly/cu124

  pip install -r requirements.txt

  pip install --no-deps facenet_pytorch==2.6.0

```

### Download ffmpeg-static
Download and decompress [ffmpeg-static](https://www.johnvansickle.com/ffmpeg/old-releases/ffmpeg-4.4-amd64-static.tar.xz), then
```

export FFMPEG_PATH=/path/to/ffmpeg-4.4-amd64-static

```

### Download pretrained weights

```shell

git lfs install

git clone https://huggingface.co/BadToBest/EchoMimicV2 pretrained_weights

```

The **pretrained_weights** is organized as follows.



```

./pretrained_weights/

├── denoising_unet.pth

├── reference_unet.pth

├── motion_module.pth

├── pose_encoder.pth

├── sd-vae-ft-mse

│   └── ...

├── sd-image-variations-diffusers

│   └── ...

└── audio_processor

    └── tiny.pt

```



In which **denoising_unet.pth** / **reference_unet.pth** / **motion_module.pth** / **pose_encoder.pth** are the main checkpoints of **EchoMimic**. Other models in this hub can be also downloaded from it's original hub, thanks to their brilliant works:

- [sd-vae-ft-mse](https://huggingface.co/stabilityai/sd-vae-ft-mse)

- [sd-image-variations-diffusers](https://huggingface.co/lambdalabs/sd-image-variations-diffusers)

- [audio_processor(whisper)](https://openaipublic.azureedge.net/main/whisper/models/65147644a518d12f04e32d6f3b26facc3f8dd46e5390956a9424a650c0ce22b9/tiny.pt)



### Inference on Demo 

Run the gradio:

```bash

python app.py

```

Run the python inference script:

```bash

python infer.py --config='./configs/prompts/infer.yaml'

```



### EMTD Dataset

Download dataset:

```bash

python ./EMTD_dataset/download.py

```

Slice dataset:

```bash

bash ./EMTD_dataset/slice.sh

```

Process dataset:

```bash

python ./EMTD_dataset/preprocess.py

```



## 📝 Release Plans



|  Status  | Milestone                                                                | ETA |

|:--------:|:-------------------------------------------------------------------------|:--:|

|    ✅    | The inference source code of EchoMimicV2 meet everyone on GitHub   | 21st Nov, 2024 |

|    ✅    | Pretrained models trained on English and Mandarin Chinese on HuggingFace | 21st Nov, 2024 |

|    ✅    | Pretrained models trained on English and Mandarin Chinese on ModelScope   | 21st Nov, 2024 |

|    ✅    | EMTD dataset list and processing scripts                | 21st Nov, 2024 |

|    🚀    | Accelerated models to be released                                        | TBD |

|    🚀    | Online Demo on ModelScope to be released            | TBD |

|    🚀    | Online Demo on HuggingFace to be released         | TBD |



## ⚖️ Disclaimer

This project is intended for academic research, and we explicitly disclaim any responsibility for user-generated content. Users are solely liable for their actions while using the generative model. The project contributors have no legal affiliation with, nor accountability for, users' behaviors. It is imperative to use the generative model responsibly, adhering to both ethical and legal standards.



## 🙏🏻 Acknowledgements



We would like to thank the contributors to the [MimicMotion](https://github.com/Tencent/MimicMotion) and [Moore-AnimateAnyone](https://github.com/MooreThreads/Moore-AnimateAnyone) repositories, for their open research and exploration. 



We are also grateful to [CyberHost](https://cyberhost.github.io/) and [Vlogger](https://enriccorona.github.io/vlogger/) for their outstanding work in the area of audio-driven human animation.



If we missed any open-source projects or related articles, we would like to complement the acknowledgement of this specific work immediately.



## &#x1F4D2; Citation



If you find our work useful for your research, please consider citing the paper :



```

@misc{meng2024echomimic,

  title={EchoMimicV2: Towards Striking, Simplified, and Semi-Body Human Animation},

  author={Rang Meng, Xingyu Zhang, Yuming Li, Chenguang Ma},

  year={2024},

  eprint={2411.10061},

  archivePrefix={arXiv},

  primaryClass={cs.CV}

}

```



## &#x1F31F; Star History

[![Star History Chart](https://api.star-history.com/svg?repos=antgroup/echomimic_v2&type=Date)](https://star-history.com/#antgroup/echomimic_v2&Date)