Tested on Ubuntu 22.04, Pytorch 1.12 and CUDA 11.6,or Pytorch 1.12 and CUDA 11.3
git clone https://github.com/waityousea/xuniren.git
cd xuniren
# for ubuntu, portaudio is needed for pyaudio to work.
sudo apt install portaudio19-dev
pip install -r requirements.txt
or
## environment.yml中的pytorch使用的1.12和cuda 11.3
conda env create -f environment.yml
## install pytorch3d
pip install "git+https://github.com/facebookresearch/pytorch3d.git"
By default, we use load
to build the extension at runtime. However, this may be inconvenient sometimes. Therefore, we also provide the setup.py
to build each extension:
# install all extension modules
bash scripts/install_ext.sh
环境配置完成后,启动虚拟人生成器:
python app.py
环境配置完成后,启动fay对接脚本
python fay_connect.py
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接口的输入与输出信息 Websoket.md
虚拟人生成的核心文件
## 注意,核心文件需要单独训练
.
├── data
│ ├── kf.json
│ ├── pretrained
│ └── └── ngp_kg.pth
在台式机RTX A4000或笔记本RTX 3080ti的显卡(显存16G)上进行视频推理时,1s可以推理35~43帧,假如1s视频25帧,则1s可推理约1.5s视频。
- The data pre-processing part is adapted from AD-NeRF.
- The NeRF framework is based on torch-ngp.
- The algorithm core come from RAD-NeRF.
- Usage example Fay.
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