)
下载cuda 11.3wget https://developer.download.nvidia.com/compute/cuda/11.3.1/local_installers/cuda_11.3.1_465.19.01_linux.runsudo sh cuda_11.3.1_465.19.01_linux.run --silent --toolkit --override --installpath/usr/local/cuda-11.3下载minicondawget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.shbash Miniconda3-latest-Linux-x86_64.shsource ~/.bashrcconda部分默认配置conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/mainconda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/r新建conda环境conda create -n Simple3D_env python3.8 -yconda activate Simple3D_envconda install pytorch1.12.1 torchvision0.13.1 torchaudio0.12.1 cudatoolkit11.3 -c pytorch -y安装GCC 9(KNN前置要求)sudo apt updatesudo apt install gcc-9 g±9 -y安装其他依赖包pip installnumpy1.23.5scipy1.10.1scikit-learn1.2.2pandas1.5.3tqdm4.66.4matplotlib3.7.5pillow10.4.0opencv-python4.8.1.78tifffile2023.7.10open3d0.18.0tabulate0.9.0安装KNNpip install Ninjapip install --upgrade https://github.com/unlimblue/KNN_CUDA/releases/download/0.2/KNN_CUDA-0.2-py3-none-any.whl在激活的conda环境下, 指定11.3的cudaconda activate Simple3D_envexport CUDA_HOME/usr/local/cuda-11.3export PATHCUDAHOME/bin:CUDA_HOME/bin:CUDAHOME/bin:PATHexport LD_LIBRARY_PATHCUDAHOME/lib64:CUDA_HOME/lib64:CUDAHOME/lib64:LD_LIBRARY_PATHexport CC/usr/bin/gcc-9export CXX/usr/bin/g±9export CUDAHOSTCXX/usr/bin/g±9检查which nvccnvcc -V$CC --version$CXX --version永久写激活脚本只要激活自动使用11.3cudaconda activate Simple3D_envmkdir -p $CONDA_PREFIX/etc/conda/activate.dcat CONDAPREFIX/etc/conda/activate.d/simple3dcuda113gcc9.sh′SH′exportCUDAHOME/usr/local/cuda−11.3exportPATHCONDA_PREFIX/etc/conda/activate.d/simple3d_cuda113_gcc9.sh SH export CUDA_HOME/usr/local/cuda-11.3 export PATHCONDAPREFIX/etc/conda/activate.d/simple3dcuda113gcc9.sh′SH′exportCUDAHOME/usr/local/cuda−11.3exportPATHCUDA_HOME/bin:PATHexportLDLIBRARYPATHPATH export LD_LIBRARY_PATHPATHexportLDLIBRARYPATHCUDA_HOME/lib64:$LD_LIBRARY_PATHexport CC/usr/bin/gcc-9export CXX/usr/bin/g±9export CUDAHOSTCXX/usr/bin/g±9SHconda deactivateconda activate Simple3D_env安装Pointnet2_Pytorchcd ~git clone https://github.com/erikwijmans/Pointnet2_PyTorch.gitcd Pointnet2_PyTorchpip install setuptools59.5.0 wheel0.38.4 ninja1.11.1pip install msgpack-numpy0.4.8 lmdb1.4.1 h5py3.8.0pip install hydra-core0.11.3 pytorch-lightning0.7.1pip install -e pointnet2_ops_lib安装libGL.so.1sudo apt updatesudo apt install -y libgl1 libglib2.0-0 libgomp1检查能否调用KNNPOINTNET2open3dpython - ‘PY’from knn_cuda import KNNfrom pointnet2_ops import pointnet2_utilsimport open3d as o3dprint(“open3d import ok”)print(“KNN_CUDA ok”)print(“PointNet2 ops ok”)PY准备自有数据(我的数据打包成了rar, 因此要下载rar解压器)sudo apt-get updatesudo apt-get install unrarmkdir my_dataunrar x xxxx.rar ./my_data 3D点云无监督学习的环境安装(ubuntu)
下载cuda 11.3wget https://developer.download.nvidia.com/compute/cuda/11.3.1/local_installers/cuda_11.3.1_465.19.01_linux.runsudo sh cuda_11.3.1_465.19.01_linux.run --silent --toolkit --override --installpath/usr/local/cuda-11.3下载minicondawget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.shbash Miniconda3-latest-Linux-x86_64.shsource ~/.bashrcconda部分默认配置conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/mainconda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/r新建conda环境conda create -n Simple3D_env python3.8 -yconda activate Simple3D_envconda install pytorch1.12.1 torchvision0.13.1 torchaudio0.12.1 cudatoolkit11.3 -c pytorch -y安装GCC 9(KNN前置要求)sudo apt updatesudo apt install gcc-9 g±9 -y安装其他依赖包pip installnumpy1.23.5scipy1.10.1scikit-learn1.2.2pandas1.5.3tqdm4.66.4matplotlib3.7.5pillow10.4.0opencv-python4.8.1.78tifffile2023.7.10open3d0.18.0tabulate0.9.0安装KNNpip install Ninjapip install --upgrade https://github.com/unlimblue/KNN_CUDA/releases/download/0.2/KNN_CUDA-0.2-py3-none-any.whl在激活的conda环境下, 指定11.3的cudaconda activate Simple3D_envexport CUDA_HOME/usr/local/cuda-11.3export PATHCUDAHOME/bin:CUDA_HOME/bin:CUDAHOME/bin:PATHexport LD_LIBRARY_PATHCUDAHOME/lib64:CUDA_HOME/lib64:CUDAHOME/lib64:LD_LIBRARY_PATHexport CC/usr/bin/gcc-9export CXX/usr/bin/g±9export CUDAHOSTCXX/usr/bin/g±9检查which nvccnvcc -V$CC --version$CXX --version永久写激活脚本只要激活自动使用11.3cudaconda activate Simple3D_envmkdir -p $CONDA_PREFIX/etc/conda/activate.dcat CONDAPREFIX/etc/conda/activate.d/simple3dcuda113gcc9.sh′SH′exportCUDAHOME/usr/local/cuda−11.3exportPATHCONDA_PREFIX/etc/conda/activate.d/simple3d_cuda113_gcc9.sh SH export CUDA_HOME/usr/local/cuda-11.3 export PATHCONDAPREFIX/etc/conda/activate.d/simple3dcuda113gcc9.sh′SH′exportCUDAHOME/usr/local/cuda−11.3exportPATHCUDA_HOME/bin:PATHexportLDLIBRARYPATHPATH export LD_LIBRARY_PATHPATHexportLDLIBRARYPATHCUDA_HOME/lib64:$LD_LIBRARY_PATHexport CC/usr/bin/gcc-9export CXX/usr/bin/g±9export CUDAHOSTCXX/usr/bin/g±9SHconda deactivateconda activate Simple3D_env安装Pointnet2_Pytorchcd ~git clone https://github.com/erikwijmans/Pointnet2_PyTorch.gitcd Pointnet2_PyTorchpip install setuptools59.5.0 wheel0.38.4 ninja1.11.1pip install msgpack-numpy0.4.8 lmdb1.4.1 h5py3.8.0pip install hydra-core0.11.3 pytorch-lightning0.7.1pip install -e pointnet2_ops_lib安装libGL.so.1sudo apt updatesudo apt install -y libgl1 libglib2.0-0 libgomp1检查能否调用KNNPOINTNET2open3dpython - ‘PY’from knn_cuda import KNNfrom pointnet2_ops import pointnet2_utilsimport open3d as o3dprint(“open3d import ok”)print(“KNN_CUDA ok”)print(“PointNet2 ops ok”)PY准备自有数据(我的数据打包成了rar, 因此要下载rar解压器)sudo apt-get updatesudo apt-get install unrarmkdir my_dataunrar x xxxx.rar ./my_data