算力云平台部署—SadTalker的AI数字人视频
选择算力
部署选择
选择镜像
机器管理
控制台
通过平台工具进入服务器
认识管理系统
打开命令行
进入目录 stable-diffusion-webui#
cd
增加执行权限
chmod +x ./webui.sh
运行命令
bash ./webui.sh
sudo apt install -y python3 python3-venv git
安装软件
-
Creating the env and install the requirements.
git clone https://github.com/OpenTalker/SadTalker.gitcd SadTalker conda create -n sadtalker python=3.8conda activate sadtalkerpip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu113conda install ffmpegpip install -r requirements.txt
运行安装环境
pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu113conda install ffmpegpip install -r requirements.txt### Coqui TTS is optional for gradio demo. ### pip install TTS
系统盘不够用
目录结构
╔═════════════════╦════════╦════╦═════════════════════════════════════════════════════════════════════════╗
║目录 ║名称 ║速度║说明 ║
╠═════════════════╬════════╬════╬═════════════════════════════════════════════════════════════════════════╣
║/ ║系 统 盘║一般║实例关机数据不会丢失,可存放代码等。会随保存镜像一起保存。 ║
║/root/autodl-tmp ║数 据 盘║ 快 ║实例关机数据不会丢失,可存放读写IO要求高的数据。但不会随保存镜像一起保存 ║
║/root/autodl-nas ║网 盘║ 慢 ║可以实现多实例间的文件同步共享,不受实例开关机和保存镜像的影响。 ║
║/root/autodl-fs ║文件存储║一般║可以实现多实例间的文件同步共享,不受实例开关机和保存镜像的影响。 ║
╚═════════════════╩════════╩════╩═════════════════════════════════════════════════════════════════════════╝
cat: /sys/fs/cgroup/cpu/cpu.cfs_quota_us: No such file or directory
移动数据到数据盘
mv ./sadtalker/ /root/autodl-tmp/cyberwin/
查看目录
ls
迁移成功
资源和路径
# All requested packages already installed. (sadtalker) root@autodl-container-a37840aad8-029fab27:~/autodl-tmp/cyberwin/SadTalker# pip install -r requirements.txt
Looking in indexes: https://mirrors.aliyun.com/pypi/simple
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安装网页
Install script for SadTalker + Web UI
Tested on Debian 11 (Bullseye)
################################################################################################################################
Running on root user
################################################################################################################################
Repo already cloned, using it as install directory
################################################################################################################################
Create and activate python venv
################################################################################################################################
Launching launcher.py...
################################################################
Python 3.8.20 (default, Oct 3 2024, 15:24:27)
[GCC 11.2.0]
Commit hash: cd4c0465ae0b54a6f85af57f5c65fec9fe23e7f8
Installing torch and torchvision
Looking in indexes: https://mirrors.aliyun.com/pypi/simple, https://download.pytorch.org/whl/cu113
Collecting torch==1.12.1+cu113Downloading https://download.pytorch.org/whl/cu113/torch-1.12.1%2Bcu113-cp38-cp38-linux_x86_64.whl (1837.7 MB)━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╸━━━━━━━ 1.5/1.8 GB 16.5 MB/s eta 0:00:20ERROR: Could not install packages due to an OSError: [Errno 28] No space left on device
下载模型
Windows
A video tutorial in chinese is available here. You can also follow the following instructions:
- Install Python 3.8 and check "Add Python to PATH".
- Install git manually or using Scoop:
scoop install git
. - Install
ffmpeg
, following this tutorial or using scoop:scoop install ffmpeg
. - Download the SadTalker repository by running
git clone https://github.com/Winfredy/SadTalker.git
. - Download the checkpoints and gfpgan models in the downloads section.
- Run
start.bat
from Windows Explorer as normal, non-administrator, user, and a Gradio-powered WebUI demo will be started.
macOS
A tutorial on installing SadTalker on macOS can be found here.
Docker, WSL, etc
Please check out additional tutorials here.
2. Download Models
You can run the following script on Linux/macOS to automatically download all the models:
bash scripts/download_models.sh
We also provide an offline patch (gfpgan/
), so no model will be downloaded when generating.
Pre-Trained Models
- Google Drive
- GitHub Releases
- Baidu (百度云盘) (Password:
sadt
)
GFPGAN Offline Patch
- Google Drive
- GitHub Releases
- Baidu (百度云盘) (Password:
sadt
)
Model Details
Model explains:
New version
Model | Description |
---|---|
checkpoints/mapping_00229-model.pth.tar | Pre-trained MappingNet in Sadtalker. |
checkpoints/mapping_00109-model.pth.tar | Pre-trained MappingNet in Sadtalker. |
checkpoints/SadTalker_V0.0.2_256.safetensors | packaged sadtalker checkpoints of old version, 256 face render). |
checkpoints/SadTalker_V0.0.2_512.safetensors | packaged sadtalker checkpoints of old version, 512 face render). |
gfpgan/weights | Face detection and enhanced models used in facexlib and gfpgan . |
Old version
Model | Description |
---|---|
checkpoints/auido2exp_00300-model.pth | Pre-trained ExpNet in Sadtalker. |
checkpoints/auido2pose_00140-model.pth | Pre-trained PoseVAE in Sadtalker. |
checkpoints/mapping_00229-model.pth.tar | Pre-trained MappingNet in Sadtalker. |
checkpoints/mapping_00109-model.pth.tar | Pre-trained MappingNet in Sadtalker. |
checkpoints/facevid2vid_00189-model.pth.tar | Pre-trained face-vid2vid model from the reappearance of face-vid2vid. |
checkpoints/epoch_20.pth | Pre-trained 3DMM extractor in Deep3DFaceReconstruction. |
checkpoints/wav2lip.pth | Highly accurate lip-sync model in Wav2lip. |
checkpoints/shape_predictor_68_face_landmarks.dat | Face landmark model used in dilb. |
checkpoints/BFM | 3DMM library file. |
checkpoints/hub | Face detection models used in face alignment. |
gfpgan/weights | Face detection and enhanced models used in facexlib and gfpgan . |
The final folder will be shown as:
3. Quick Start
Please read our document on best practices and configuration tips
WebUI Demos
Online Demo: HuggingFace | SDWebUI-Colab | Colab
Local WebUI extension: Please refer to WebUI docs.
Local gradio demo (recommanded): A Gradio instance similar to our Hugging Face demo can be run locally:
## you need manually install TTS(https://github.com/coqui-ai/TTS) via `pip install tts` in advanced. python app_sadtalker.py
You can also start it more easily:
- windows: just double click
webui.bat
, the requirements will be installed automatically. - Linux/Mac OS: run
bash webui.sh
to start the webui.
CLI usage
Animating a portrait image from default config:
python inference.py --driven_audio <audio.wav> \--source_image <video.mp4 or picture.png> \--enhancer gfpgan
The results will be saved in results/$SOME_TIMESTAMP/*.mp4
.
Full body/image Generation:
Using --still
to generate a natural full body video. You can add enhancer
to improve the quality of the generated video.
python inference.py --driven_audio <audio.wav> \--source_image <video.mp4 or picture.png> \--result_dir <a file to store results> \--still \--preprocess full \--enhancer gfpgan
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