分类：动作捕捉
github地址：https://github.com/openxrlab/xrmocap
所需环境：
Ubuntu18.04，conda22.9.0，CUDA11.4

环境配置

conda create -n XRmocap python=3.7 -y
conda activate XRmocap

# install ffmpeg for video and images
conda install -y ffmpeg

# install pytorch
conda install pytorch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1 cudatoolkit=11.3 -c pytorch -y

# install pytorch3d
conda install -y -c fvcore -c iopath -c conda-forge fvcore iopath
conda install -y -c bottler nvidiacub
conda install -y pytorch3d -c pytorch3d

# install mmcv-full
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu113/torch1.12.1/index.html

# install minimal_pytorch_rasterizer
pip install git+https://github.com/rmbashirov/minimal_pytorch_rasterizer.git

# install xrprimer
pip install xrprimer

# install mmhuman3d
pip install git+https://github.com/open-mmlab/mmhuman3d.git



###￥￥￥￥##￥#￥#￥#￥#￥#￥#￥
# install cudnn for mmdeploy
apt-get update && apt-get install -y --no-install-recommends \
    libcudnn8=8.2.4.15-1+cuda11.4 \
    libcudnn8-dev=8.2.4.15-1+cuda11.4 \
    && apt-mark hold libcudnn8 && \
    rm -rf /var/lib/apt/lists/*
# install TensorRT for mmdeploy, please get TensorRT from nvidia official website
cd /opt && \
    tar -xzvf TensorRT-8.2.3.0.Linux.x86_64-gnu.cuda-11.4.cudnn8.2.tar.gz && \
    rm TensorRT-8.2.3.0.Linux.x86_64-gnu.cuda-11.4.cudnn8.2.tar.gz && \
    cd TensorRT-8.2.3.0/python && \
    pip install tensorrt-8.2.3.0-cp38-none-linux_x86_64.whl && \
# install mmdeploy and build ops
cd /opt && \
	conda install cmake && \
    git clone https://github.com/open-mmlab/mmdeploy.git && \
    cd mmdeploy && \
    git reset --hard 1b048d88ca11782de1e9ebf6f9583259167a1d5b && \
    pip install -e . && \
    mkdir -p build && cd build && \
    cmake -DCMAKE_CXX_COMPILER=g++ -DMMDEPLOY_TARGET_BACKENDS=trt \
        -DTENSORRT_DIR=/opt/TensorRT-8.2.3.0 \
        -DCUDNN_DIR=/usr/lib/x86_64-linux-gnu .. && \
    make -j$(nproc) && make install && \
    make clean

# clone xrmocap
git clone https://github.com/openxrlab/xrmocap.git
cd xrmocap

# install requirements for build
pip install -r requirements/build.txt
# install requirements for runtime
pip install -r requirements/runtime.txt
# install requirements for services
pip install -r requirements/service.txt

# install xrmocap
rm -rf .eggs && pip install -e .