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Install.md

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Install Process

  • Create a virtual environment

    conda create -n torch2.1.0 python=3.10

  • Check the CUDA version (recommended: 11.8).

    nvcc -V

  • Install Torch 2.1.0

    conda install pytorch==2.1.0 torchvision==0.16.0 torchaudio==2.1.0 pytorch-cuda=11.8 -c pytorch -c nvidia

  • Install libply_c for the geometry-aware partitioning strategy.

    conda install -c anaconda boost
conda install -c omnia eigen3
conda install eigen
conda install -c r libiconv
cd lib/Partition_lib/ply_c
CONDAENV=/home/lab/anaconda3
cmake . -DPYTHON_LIBRARY=$CONDAENV/lib/libpython3.10.so -DPYTHON_INCLUDE_DIR=$CONDAENV/include/python3.10 -DBOOST_INCLUDEDIR=$CONDAENV/include -DEIGEN3_INCLUDE_DIR=$CONDAENV/include/eigen3
make

    1. Replace CONDAENV with your own environment path.

    2. Replace libpython3.10.so with the corresponding version file from your own environment.

    3. Replace python3.10 with the corresponding version used in your own environment.

  • Install libcp for the geometry-aware partitioning strategy.

    cd lib/Partition_lib/cut-pursuit
mkdir build
cd build
cmake .. -DPYTHON_LIBRARY=$CONDAENV/lib/libpython3.10.so -DPYTHON_INCLUDE_DIR=$CONDAENV/include/python3.10 -DBOOST_INCLUDEDIR=$CONDAENV/include -DEIGEN3_INCLUDE_DIR=$CONDAENV/include/eigen3
make

    1. Replace libpython3.10.so with the corresponding version file from your own environment.

    2. Replace python3.10 with the corresponding version used in your own environment.

    Note

    After compilation, if it succeeds, two .so files will be generated. Be sure to check for them.

  • Install other packages

    pip install tensorboard
pip install tensorboardx
conda install https://anaconda.org/pytorch3d/pytorch3d/0.7.7/download/linux-64/pytorch3d-0.7.7-py310_cu118_pyt210.tar.bz2
pip install easydict==1.13
pip install thop==0.1.1.post2209072238
pip install ninja==1.11.1.3
pip install h5py==3.13.0
pip install matplotlib==3.5.0
pip install numpy==1.24.0
pip install open3d==0.19.0
pip install pyYAML==6.0.2
pip install scipy==1.15.2
pip install timm==1.0.15 --no-deps
pip install tqdm==4.67.1
pip install trimesh==4.6.4
pip install scikit-image==0.25.2
pip install torch_scatter==2.1.2+pt21cu118(https://pytorch-geometric.com/whl/这里下载安装)

  • Install cuML for accelerating SVM evaluation

    pip install --extra-index-url=https://pypi.nvidia.com "cuml-cu11==25.2.*"

    webside of cuml

    https://rapids.ai/

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