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metahuman-stream's Introduction

A streaming digital human based on the Ernerf model, realize audio video synchronous dialogue. It can basically achieve commercial effects.
基于ernerf模型的流式数字人,实现音视频同步对话。基本可以达到商用效果

![Watch the video]

1. Installation

Tested on Ubuntu 20.04, Python3.10, Pytorch 1.12 and CUDA 11.3

1.1 Install dependency

conda create -n nerfstream python=3.10
conda install pytorch==1.12.1 torchvision==0.13.1 cudatoolkit=11.3 -c pytorch
conda activate nerfstream
pip install -r requirements.txt
pip install "git+https://github.com/facebookresearch/pytorch3d.git"
pip install tensorflow-gpu==2.8.0

linux cuda环境搭建可以参考这篇文章 https://zhuanlan.zhihu.com/p/674972886

1.2 安装rtmpstream库

参照 https://github.com/lipku/python_rtmpstream

2. Run

2.1 运行rtmpserver (srs)

docker run --rm -it -p 1935:1935 -p 1985:1985 -p 8080:8080 registry.cn-hangzhou.aliyuncs.com/ossrs/srs:5

2.2 启动数字人:

python app.py

如果访问不了huggingface,在运行前

export HF_ENDPOINT=https://hf-mirror.com

运行成功后,用vlc访问rtmp://serverip/live/livestream

2.3 网页端数字人播报输入文字

安装并启动nginx

apt install nginx
nginx

将echo.html和mpegts-1.7.3.min.js拷到/var/www/html下

用浏览器打开http://serverip/echo.html, 在文本框输入任意文字,提交。数字人播报该段文字

2.4 使用LLM模型进行数字人对话

目前借鉴数字人对话系统LinlyTalker的方式,LLM模型支持Chatgpt,Qwen和GeminiPro。需要在app.py中填入自己的api_key。
安装并启动nginx,将chat.html和mpegts-1.7.3.min.js拷到/var/www/html下

用浏览器打开http://serverip/chat.html

2.5 使用本地tts服务,支持声音克隆

运行xtts服务,参照 https://github.com/coqui-ai/xtts-streaming-server

docker run --gpus=all -e COQUI_TOS_AGREED=1 --rm -p 9000:80 ghcr.io/coqui-ai/xtts-streaming-server:latest

然后运行,其中ref.wav为需要克隆的声音文件

python app.py --tts xtts --ref_file data/ref.wav

3. Docker Run

不需要第1步的安装,直接运行。

docker run --gpus all -it --network=host --rm  registry.cn-hangzhou.aliyuncs.com/lipku/nerfstream:v1.3

srs和nginx的运行同2.1和2.3

4. Data flow

5. 数字人模型文件

可以替换成自己训练的模型(https://github.com/Fictionarry/ER-NeRF)

.
├── data
│   ├── data_kf.json
│   ├── au.csv			
│   ├── pretrained
│   └── └── ngp_kf.pth

6. 性能分析

  1. 帧率
    在Tesla T4显卡上测试整体fps为18左右,如果去掉音视频编码推流,帧率在20左右。用4090显卡可以达到40多帧/秒。
    优化:新开一个线程运行音视频编码推流
  2. 延时
    整体延时5s多
    (1)tts延时2s左右,目前用的edgetts,需要将每句话转完后一次性输入,可以优化tts改成流式输入
    (2)wav2vec延时1s多,需要缓存50帧音频做计算,可以通过-m设置context_size来减少延时
    (3)srs转发延时,设置srs服务器减少缓冲延时。具体配置可看 https://ossrs.net/lts/zh-cn/docs/v5/doc/low-latency, 配置了一个低延时版本
docker run --rm -it -p 1935:1935 -p 1985:1985 -p 8080:8080 registry.cn-hangzhou.aliyuncs.com/lipku/srs:v1.1

7. TODO

  • 添加chatgpt实现数字人对话
  • 声音克隆
  • 数字人静音时用一段视频代替

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。
Email: [email protected]
微信公众号:数字人技术

metahuman-stream's People

Contributors

lipku avatar kedreamix avatar

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