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INSTALL.md

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Set up the python environment

  • NVIDIA GPU with CUDA 11.3 is required

  • Python>=3.8 (installation via anaconda is recommended, use conda create -n mlp_maps python=3.8 to create a conda environment and activate it by conda activate mlp_maps)

  • Python libraries

    • Install pytorch by pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu113

    • Install torch-scatter by pip install torch-scatter -f https://data.pyg.org/whl/torch-1.12.0+cu113.html

    • Install kilonerf-cuda

      Option A: Install pre-compiled CUDA extension

      Install pre-compiled CUDA extension
      pip install lib/csrc/kilonerf_cuda/dist/kilonerf_cuda-0.0.0-cp38-cp38-linux_x86_64.whl

      Option B: Build CUDA extension yourself

      Download magma from http://icl.utk.edu/projectsfiles/magma/downloads/magma-2.5.4.tar.gz then build and install to /usr/local/magma

      sudo apt install gfortran libopenblas-dev
sudo apt-get install freeglut3
wget http://icl.utk.edu/projectsfiles/magma/downloads/magma-2.5.4.tar.gz
tar -zxvf magma-2.5.4.tar.gz
cd magma-2.5.4
cp make.inc-examples/make.inc.openblas make.inc
export GPU_TARGET="Maxwell Pascal Volta Turing Ampere"
export CUDADIR=/usr/local/cuda
export OPENBLASDIR="/usr"
make
sudo -E make install prefix=/usr/local/magma

      For further information on installing magma see: http://icl.cs.utk.edu/projectsfiles/magma/doxygen/installing.html

      Finally compile KiloNeRF's C++/CUDA code

      cd lib/csrc/kilonerf_cuda
python setup.py develop
# Or use this command: TORCH_CUDA_ARCH_LIST="6.0 7.0 7.5 8.0 8.6+PTX" python setup.py develop

    • Install required packages by pip install -r requirements.txt

Set up datasets

ZJU-Mocap dataset

  1. Note that we refine the camera parameters of the ZJU-MoCap dataset. If someone wants to download the ZJU-Mocap dataset, please fill the form to obtain the download link. Another way is filling in the agreement and emailing Sida Peng (pengsida@zju.edu.cn) and cc Xiaowei Zhou (xwzhou@zju.edu.cn) to request the download link.
  2. Create a soft link: 
    ROOT=/path/to/mlp_maps
cd $ROOT/data
ln -s /path/to/my_zjumocap my_zjumocap

NHR dataset

  1. Download the NHR dataset at here and process this data for our code. Or someone could download the processed data at here. Note that both ways require to cite the NHR paper.
  2. Create a soft link: 
    ROOT=/path/to/mlp_maps
cd $ROOT/data
ln -s /path/to/nhr nhr