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Real time interactive streaming digital human， realize audio video synchronous dialogue. It can basically achieve commercial effects. Real-time interactive streaming digital human enables synchronous audio and video dialogue. It can basically achieve commercial effects.
实时交互流式数字人，实现音视频同步对话。基本可以达到商用效果
[ernerf效果](https://www.bilibili.com/video/BV1PM4m1y7Q2/) [musetalk效果](https://www.bilibili.com/video/BV1gm421N7vQ/) [wav2lip效果](https://www.bilibili.com/video/BV1Bw4m1e74P/) [Effect of wav2lip](https://www.bilibili.com/video/BV1Bw4m1e74P/) | [Effect of ernerf](https://www.bilibili.com/video/BV1PM4m1y7Q2/) | [Effect of musetalk](https://www.bilibili.com/video/BV1gm421N7vQ/)
## 为避免与3d数字人混淆，原项目metahuman-stream改名为livetalking，原有链接地址继续可用
[中文版](./README_ZH.md)
## News ## News
- 2024.12.8 完善多并发，显存不随并发数增加 - December 8, 2024: Improved multi-concurrency, and the video memory does not increase with the number of concurrent connections.
- 2024.12.21 添加wav2lip、musetalk模型预热，解决第一次推理卡顿问题。感谢[@heimaojinzhangyz](https://github.com/heimaojinzhangyz) - December 21, 2024: Added model warm-up for wav2lip and musetalk to solve the problem of stuttering during the first inference. Thanks to [@heimaojinzhangyz](https://github.com/heimaojinzhangyz)
- 2024.12.28 添加数字人模型Ultralight-Digital-Human。 感谢[@lijihua2017](https://github.com/lijihua2017) - December 28, 2024: Added the digital human model Ultralight-Digital-Human. Thanks to [@lijihua2017](https://github.com/lijihua2017)
- 2025.2.7 添加fish-speech tts - February 7, 2025: Added fish-speech tts
- 2025.2.21 添加wav2lip256开源模型 感谢@不蠢不蠢 - February 21, 2025: Added the open-source model wav2lip256. Thanks to @不蠢不蠢
- 2025.3.2 添加腾讯语音合成服务 - March 2, 2025: Added Tencent's speech synthesis service
- 20253.16 支持mac gpu推理，感谢[@GcsSloop](https://github.com/GcsSloop) - March 16, 2025: Supports mac gpu inference. Thanks to [@GcsSloop](https://github.com/GcsSloop)
## Features ## Features
1. 支持多种数字人模型: ernerf、musetalk、wav2lip、Ultralight-Digital-Human 1. Supports multiple digital human models: ernerf, musetalk, wav2lip, Ultralight-Digital-Human
2. 支持声音克隆 2. Supports voice cloning
3. 支持数字人说话被打断 3. Supports interrupting the digital human while it is speaking
4. 支持全身视频拼接 4. Supports full-body video stitching
5. 支持rtmp和webrtc 5. Supports rtmp and webrtc
6. 支持视频编排：不说话时播放自定义视频 6. Supports video arrangement: Play custom videos when not speaking
7. 支持多并发 7. Supports multi-concurrency
## 1. Installation ## 1. Installation
Tested on Ubuntu 20.04, Python3.10, Pytorch 1.12 and CUDA 11.3 Tested on Ubuntu 20.04, Python 3.10, Pytorch 1.12 and CUDA 11.3
### 1.1 Install dependency ### 1.1 Install dependency
```bash ```bash
conda create -n nerfstream python=3.10 conda create -n nerfstream python=3.10
conda activate nerfstream conda activate nerfstream
#如果cuda版本不为11.3(运行nvidia-smi确认版本)，根据<https://pytorch.org/get-started/previous-versions/>安装对应版本的pytorch # If the cuda version is not 11.3 (confirm the version by running nvidia-smi), install the corresponding version of pytorch according to <https://pytorch.org/get-started/previous-versions/>
conda install pytorch==1.12.1 torchvision==0.13.1 cudatoolkit=11.3 -c pytorch conda install pytorch==1.12.1 torchvision==0.13.1 cudatoolkit=11.3 -c pytorch
pip install -r requirements.txt pip install -r requirements.txt
#如果需要训练ernerf模型，安装下面的库 # If you need to train the ernerf model, install the following libraries
# pip install "git+https://github.com/facebookresearch/pytorch3d.git" # pip install "git+https://github.com/facebookresearch/pytorch3d.git"
# pip install tensorflow-gpu==2.8.0 # pip install tensorflow-gpu==2.8.0
# pip install --upgrade "protobuf<=3.20.1" # pip install --upgrade "protobuf<=3.20.1"
``` ```
安装常见问题[FAQ](https://livetalking-doc.readthedocs.io/en/latest/faq.html) Common installation issues [FAQ](https://livetalking-doc.readthedocs.io/en/latest/faq.html)
linux cuda环境搭建可以参考这篇文章 https://zhuanlan.zhihu.com/p/674972886 For setting up the linux cuda environment, you can refer to this article https://zhuanlan.zhihu.com/p/674972886
## 2. Quick Start ## 2. Quick Start
- 下载模型 - Download the models
百度云盘<https://pan.baidu.com/s/1yOsQ06-RIDTJd3HFCw4wtA> 密码: ltua Baidu Cloud Disk <https://pan.baidu.com/s/1yOsQ06-RIDTJd3HFCw4wtA> Password: ltua
GoogleDriver <https://drive.google.com/drive/folders/1FOC_MD6wdogyyX_7V1d4NDIO7P9NlSAJ?usp=sharing> Google Drive <https://drive.google.com/drive/folders/1FOC_MD6wdogyyX_7V1d4NDIO7P9NlSAJ?usp=sharing>
将wav2lip256.pth拷到本项目的models下, 重命名为wav2lip.pth; Copy wav2lip256.pth to the models folder of this project and rename it to wav2lip.pth;
将wav2lip256_avatar1.tar.gz解压后整个文件夹拷到本项目的data/avatars下 Extract wav2lip256_avatar1.tar.gz and copy the entire folder to the data/avatars folder of this project.
- 运行 - Run
python app.py --transport webrtc --model wav2lip --avatar_id wav2lip256_avatar1 python app.py --transport webrtc --model wav2lip --avatar_id wav2lip256_avatar1
用浏览器打开http://serverip:8010/webrtcapi.html , 先点‘start',播放数字人视频；然后在文本框输入任意文字，提交。数字人播报该段文字 Open http://serverip:8010/webrtcapi.html in a browser. First click'start' to play the digital human video; then enter any text in the text box and submit it. The digital human will broadcast this text.
<font color=red>服务端需要开放端口 tcp:8010; udp:1-65536 </font> <font color=red>The server side needs to open ports tcp:8010; udp:1-65536</font>
如果需要商用高清wav2lip模型，可以与我联系购买 If you need to purchase a high-definition wav2lip model for commercial use, you can contact me to make the purchase.
- 快速体验 - Quick experience
<https://www.compshare.cn/images-detail?ImageID=compshareImage-18tpjhhxoq3j&referral_code=3XW3852OBmnD089hMMrtuU&ytag=GPU_GitHub_livetalking1.3> 用该镜像创建实例即可运行成功 <https://www.compshare.cn/images-detail?ImageID=compshareImage-18tpjhhxoq3j&referral_code=3XW3852OBmnD089hMMrtuU&ytag=GPU_GitHub_livetalking1.3> Create an instance with this image to run it.
如果访问不了huggingface，在运行前 If you can't access huggingface, before running
``` ```
export HF_ENDPOINT=https://hf-mirror.com export HF_ENDPOINT=https://hf-mirror.com
``` ```
## 3. More Usage ## 3. More Usage
使用说明: <https://livetalking-doc.readthedocs.io/> Usage instructions: <https://livetalking-doc.readthedocs.io/en/latest>
## 4. Docker Run ## 4. Docker Run
不需要前面的安装，直接运行。 No need for the previous installation, just run directly.
``` ```
docker run --gpus all -it --network=host --rm registry.cn-beijing.aliyuncs.com/codewithgpu2/lipku-metahuman-stream:2K9qaMBu8v docker run --gpus all -it --network=host --rm registry.cn-beijing.aliyuncs.com/codewithgpu2/lipku-metahuman-stream:2K9qaMBu8v
``` ```
代码在/root/metahuman-stream，先git pull拉一下最新代码，然后执行命令同第2、3步 The code is in /root/metahuman-stream. First, git pull to get the latest code, and then execute the commands as in steps 2 and 3.
提供如下镜像 The following images are provided:
- autodl镜像: <https://www.codewithgpu.com/i/lipku/metahuman-stream/base> - autodl image: <https://www.codewithgpu.com/i/lipku/metahuman-stream/base>
[autodl教程](https://livetalking-doc.readthedocs.io/en/latest/autodl/README.html) [autodl Tutorial](https://livetalking-doc.readthedocs.io/en/latest/autodl/README.html)
- ucloud镜像: <https://www.compshare.cn/images-detail?ImageID=compshareImage-18tpjhhxoq3j&referral_code=3XW3852OBmnD089hMMrtuU&ytag=GPU_livetalking1.3> - ucloud image: <https://www.compshare.cn/images-detail?ImageID=compshareImage-18tpjhhxoq3j&referral_code=3XW3852OBmnD089hMMrtuU&ytag=GPU_livetalking1.3>
可以开放任意端口，不需要另外部署srs服务. Any port can be opened, and there is no need to deploy an srs service additionally.
[ucloud教程](https://livetalking-doc.readthedocs.io/en/latest/ucloud/ucloud.html) [ucloud Tutorial](https://livetalking-doc.readthedocs.io/en/latest/ucloud/ucloud.html)
## 5. TODO ## 5. TODO
- [x] 添加chatgpt实现数字人对话 - [x] Added chatgpt to enable digital human dialogue
- [x] 声音克隆 - [x] Voice cloning
- [x] 数字人静音时用一段视频代替 - [x] Replace the digital human with a video when it is silent
- [x] MuseTalk - [x] MuseTalk
- [x] Wav2Lip - [x] Wav2Lip
- [x] Ultralight-Digital-Human - [x] Ultralight-Digital-Human
--- ---
如果本项目对你有帮助，帮忙点个star。也欢迎感兴趣的朋友一起来完善该项目. If this project is helpful to you, please give it a star. Friends who are interested are also welcome to join in and improve this project together.
* 知识星球: https://t.zsxq.com/7NMyO 沉淀高质量常见问题、最佳实践经验、问题解答 * Knowledge Planet: https://t.zsxq.com/7NMyO, where high-quality common problems, best practice experiences, and problem solutions are accumulated.
* 微信公众号：数字人技术 * WeChat Official Account: Digital Human Technology
![](https://mmbiz.qpic.cn/sz_mmbiz_jpg/l3ZibgueFiaeyfaiaLZGuMGQXnhLWxibpJUS2gfs8Dje6JuMY8zu2tVyU9n8Zx1yaNncvKHBMibX0ocehoITy5qQEZg/640?wxfrom=12&tp=wxpic&usePicPrefetch=1&wx_fmt=jpeg&amp;from=appmsg) ![](https://mmbiz.qpic.cn/sz_mmbiz_jpg/l3ZibgueFiaeyfaiaLZGuMGQXnhLWxibpJUS2gfs8Dje6JuMY8zu2tVyU9n8Zx1yaNncvKHBMibX0ocehoITy5qQEZg/640?wxfrom=12&tp=wxpic&usePicPrefetch=1&wx_fmt=jpeg&amp;from=appmsg)

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实时交互流式数字人，实现音视频同步对话。基本可以达到商用效果
[wav2lip效果](https://www.bilibili.com/video/BV1Bw4m1e74P/) | [ernerf效果](https://www.bilibili.com/video/BV1PM4m1y7Q2/) | [musetalk效果](https://www.bilibili.com/video/BV1gm421N7vQ/)
## 为避免与3d数字人混淆，原项目metahuman-stream改名为livetalking，原有链接地址继续可用
## News
- 2024.12.8 完善多并发，显存不随并发数增加
- 2024.12.21 添加wav2lip、musetalk模型预热，解决第一次推理卡顿问题。感谢[@heimaojinzhangyz](https://github.com/heimaojinzhangyz)
- 2024.12.28 添加数字人模型Ultralight-Digital-Human。 感谢[@lijihua2017](https://github.com/lijihua2017)
- 2025.2.7 添加fish-speech tts
- 2025.2.21 添加wav2lip256开源模型 感谢@不蠢不蠢
- 2025.3.2 添加腾讯语音合成服务
- 2025.3.16 支持mac gpu推理，感谢[@GcsSloop](https://github.com/GcsSloop)
## Features
1. 支持多种数字人模型: ernerf、musetalk、wav2lip、Ultralight-Digital-Human
2. 支持声音克隆
3. 支持数字人说话被打断
4. 支持全身视频拼接
5. 支持rtmp和webrtc
6. 支持视频编排：不说话时播放自定义视频
7. 支持多并发
## 1. Installation
Tested on Ubuntu 20.04, Python3.10, Pytorch 1.12 and CUDA 11.3
### 1.1 Install dependency
```bash
conda create -n nerfstream python=3.10
conda activate nerfstream
#如果cuda版本不为11.3(运行nvidia-smi确认版本)，根据<https://pytorch.org/get-started/previous-versions/>安装对应版本的pytorch
conda install pytorch==1.12.1 torchvision==0.13.1 cudatoolkit=11.3 -c pytorch
pip install -r requirements.txt
#如果需要训练ernerf模型，安装下面的库
# pip install "git+https://github.com/facebookresearch/pytorch3d.git"
# pip install tensorflow-gpu==2.8.0
# pip install --upgrade "protobuf<=3.20.1"
```
安装常见问题[FAQ](https://livetalking-doc.readthedocs.io/en/latest/faq.html)
linux cuda环境搭建可以参考这篇文章 https://zhuanlan.zhihu.com/p/674972886
## 2. Quick Start
- 下载模型
百度云盘<https://pan.baidu.com/s/1yOsQ06-RIDTJd3HFCw4wtA> 密码: ltua
GoogleDriver <https://drive.google.com/drive/folders/1FOC_MD6wdogyyX_7V1d4NDIO7P9NlSAJ?usp=sharing>
将wav2lip256.pth拷到本项目的models下, 重命名为wav2lip.pth;
将wav2lip256_avatar1.tar.gz解压后整个文件夹拷到本项目的data/avatars下
- 运行
python app.py --transport webrtc --model wav2lip --avatar_id wav2lip256_avatar1
用浏览器打开http://serverip:8010/webrtcapi.html , 先点‘start',播放数字人视频；然后在文本框输入任意文字，提交。数字人播报该段文字
<font color=red>服务端需要开放端口 tcp:8010; udp:1-65536 </font>
如果需要商用高清wav2lip模型，可以与我联系购买
- 快速体验
<https://www.compshare.cn/images-detail?ImageID=compshareImage-18tpjhhxoq3j&referral_code=3XW3852OBmnD089hMMrtuU&ytag=GPU_GitHub_livetalking1.3> 用该镜像创建实例即可运行成功
如果访问不了huggingface，在运行前
```
export HF_ENDPOINT=https://hf-mirror.com
```
## 3. More Usage
使用说明: <https://livetalking-doc.readthedocs.io/>
## 4. Docker Run
不需要前面的安装，直接运行。
```
docker run --gpus all -it --network=host --rm registry.cn-beijing.aliyuncs.com/codewithgpu2/lipku-metahuman-stream:2K9qaMBu8v
```
代码在/root/metahuman-stream，先git pull拉一下最新代码，然后执行命令同第2、3步
提供如下镜像
- autodl镜像: <https://www.codewithgpu.com/i/lipku/metahuman-stream/base>
[autodl教程](https://livetalking-doc.readthedocs.io/en/latest/autodl/README.html)
- ucloud镜像: <https://www.compshare.cn/images-detail?ImageID=compshareImage-18tpjhhxoq3j&referral_code=3XW3852OBmnD089hMMrtuU&ytag=GPU_livetalking1.3>
可以开放任意端口，不需要另外部署srs服务.
[ucloud教程](https://livetalking-doc.readthedocs.io/en/latest/ucloud/ucloud.html)
## 5. TODO
- [x] 添加chatgpt实现数字人对话
- [x] 声音克隆
- [x] 数字人静音时用一段视频代替
- [x] MuseTalk
- [x] Wav2Lip
- [x] Ultralight-Digital-Human
---
如果本项目对你有帮助，帮忙点个star。也欢迎感兴趣的朋友一起来完善该项目.
* 知识星球: https://t.zsxq.com/7NMyO 沉淀高质量常见问题、最佳实践经验、问题解答
* 微信公众号：数字人技术
![](https://mmbiz.qpic.cn/sz_mmbiz_jpg/l3ZibgueFiaeyfaiaLZGuMGQXnhLWxibpJUS2gfs8Dje6JuMY8zu2tVyU9n8Zx1yaNncvKHBMibX0ocehoITy5qQEZg/640?wxfrom=12&tp=wxpic&usePicPrefetch=1&wx_fmt=jpeg&amp;from=appmsg)
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