2023-12-28 13:11:18 +08:00
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A streaming digital human based on the Ernerf model, realize audio video synchronous dialogue. It can basically achieve commercial effects.
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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
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2023-12-19 09:41:52 +08:00
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2024-01-10 15:14:22 +08:00
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[![Watch the video]](/assets/demo.mp4)
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2023-12-19 09:41:52 +08:00
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2024-01-13 20:12:08 +08:00
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## 1. Installation
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2023-12-19 09:41:52 +08:00
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2024-01-13 20:12:08 +08:00
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Tested on Ubuntu 20.04, Python3.10, Pytorch 1.12 and CUDA 11.3
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2023-12-19 09:41:52 +08:00
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2024-01-13 20:12:08 +08:00
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### 1.1 Install dependency
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2023-12-19 09:41:52 +08:00
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2023-12-28 13:11:18 +08:00
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```bash
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2024-01-06 21:17:34 +08:00
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conda create -n nerfstream python=3.10
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conda install pytorch==1.12.1 torchvision==0.13.1 cudatoolkit=11.3 -c pytorch
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conda activate nerfstream
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pip install -r requirements.txt
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pip install "git+https://github.com/facebookresearch/pytorch3d.git"
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pip install tensorflow-gpu==2.8.0
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```
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linux cuda环境搭建可以参考这篇文章 https://zhuanlan.zhihu.com/p/674972886
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2023-12-19 09:41:52 +08:00
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2024-01-13 20:15:09 +08:00
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### 1.2 安装rtmpstream库
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2023-12-28 13:11:18 +08:00
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参照 https://github.com/lipku/python_rtmpstream
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2023-12-19 09:41:52 +08:00
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2024-01-13 20:12:08 +08:00
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## 2. Run
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2024-01-13 20:12:08 +08:00
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### 2.1 运行rtmpserver (srs)
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```
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2023-12-28 13:11:18 +08:00
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docker run --rm -it -p 1935:1935 -p 1985:1985 -p 8080:8080 registry.cn-hangzhou.aliyuncs.com/ossrs/srs:5
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2023-12-19 09:41:52 +08:00
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```
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2024-01-13 20:12:08 +08:00
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### 2.2 启动数字人:
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2023-12-28 13:11:18 +08:00
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```python
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python app.py
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```
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2023-12-28 13:11:18 +08:00
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如果访问不了huggingface,在运行前
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```
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export HF_ENDPOINT=https://hf-mirror.com
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```
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2023-12-28 13:11:18 +08:00
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运行成功后,用vlc访问rtmp://serverip/live/livestream
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2024-01-13 20:12:08 +08:00
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### 2.3 网页端数字人播报输入文字
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2023-12-28 13:11:18 +08:00
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安装并启动nginx
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```
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2023-12-28 13:11:18 +08:00
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apt install nginx
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nginx
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2023-12-19 09:41:52 +08:00
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```
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2023-12-28 13:11:18 +08:00
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修改echo.html中websocket和视频播放地址,将serverip替换成实际服务器ip
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然后将echo.html和mpegts-1.7.3.min.js拷到/var/www/html下
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2024-01-13 20:12:08 +08:00
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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
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2024-01-13 20:12:08 +08:00
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## 3. Docker Run
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不需要第1步的安装,直接运行。
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2024-01-07 14:19:21 +08:00
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```
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2024-01-13 20:12:08 +08:00
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docker run --gpus all -it --network=host --rm registry.cn-hangzhou.aliyuncs.com/lipku/nerfstream:v1.3
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2024-01-07 14:19:21 +08:00
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```
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2024-01-13 20:12:08 +08:00
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srs和nginx的运行同2.1和2.3
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2024-01-07 14:19:21 +08:00
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2024-01-13 20:12:08 +08:00
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## 4. Data flow
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![](/assets/dataflow.png)
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2024-01-13 20:12:08 +08:00
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## 5. 数字人模型文件
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可以替换成自己训练的模型(https://github.com/Fictionarry/ER-NeRF)
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2023-12-19 09:41:52 +08:00
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```python
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├── data
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│ ├── data_kf.json
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│ ├── pretrained
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│ └── └── ngp_kg.pth
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```
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2024-01-13 20:12:08 +08:00
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## 6. 性能分析
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1. 帧率
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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显卡应该能达到25帧,欢迎有显卡资源的同学提供数据。
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优化:新开一个线程运行音视频编码推流
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2. 延时
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整体延时5s多
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(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
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(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
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(3)srs转发延时,设置srs服务器减少缓冲延时
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## 7. TODO
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- 添加chatgpt实现数字人对话
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- 声音克隆
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- 数字人静音时用一段视频代替
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2023-12-19 09:41:52 +08:00
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2023-12-28 13:11:18 +08:00
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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。
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Email: lipku@foxmail.com
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