)
下载cuda 11.3
wget https://developer.download.nvidia.com/compute/cuda/11.3.1/local_installers/cuda_11.3.1_465.19.01_linux.run
sudo sh cuda_11.3.1_465.19.01_linux.run --silent --toolkit --override --installpath=/usr/local/cuda-11.3
下载miniconda
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh
source ~/.bashrc
conda部分默认配置
conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/main
conda tos accept --override-channels --channel https://repo.anaconda.com/pkgs/r
新建conda环境
conda create -n Simple3D_env python=3.8 -y
conda activate Simple3D_env
conda install pytorch1.12.1 torchvision0.13.1 torchaudio==0.12.1 cudatoolkit=11.3 -c pytorch -y
安装GCC 9(KNN前置要求)
sudo apt update
sudo apt install gcc-9 g+±9 -y
安装其他依赖包
pip install
numpy1.23.5
scipy1.10.1
scikit-learn1.2.2
pandas1.5.3
tqdm4.66.4
matplotlib3.7.5
pillow10.4.0
opencv-python4.8.1.78
tifffile2023.7.10
open3d0.18.0
tabulate==0.9.0
安装KNN
pip install Ninja
pip 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cuda
conda activate Simple3D_env
export CUDA_HOME=/usr/local/cuda-11.3
export PATH=CUDAHOME/bin:CUDA_HOME/bin:CUDAHOME/bin:PATH
export LD_LIBRARY_PATH=CUDAHOME/lib64:CUDA_HOME/lib64:CUDAHOME/lib64:LD_LIBRARY_PATH
export CC=/usr/bin/gcc-9
export CXX=/usr/bin/g+±9
export CUDAHOSTCXX=/usr/bin/g+±9
检查
which nvcc
nvcc -V
$CC --version
$CXX --version
永久写激活脚本，只要激活自动使用11.3cuda
conda activate Simple3D_env
mkdir -p $CONDA_PREFIX/etc/conda/activate.d
cat >CONDAPREFIX/etc/conda/activate.d/simple3dcuda113gcc9.sh<<′SH′exportCUDAHOME=/usr/local/cuda−11.3exportPATH=CONDA_PREFIX/etc/conda/activate.d/simple3d_cuda113_gcc9.sh <<'SH' export CUDA_HOME=/usr/local/cuda-11.3 export PATH=CONDAPREFIX/etc/conda/activate.d/simple3dcuda113gcc9.sh<<′SH′exportCUDAHOME=/usr/local/cuda−11.3exportPATH=CUDA_HOME/bin:PATHexportLDLIBRARYPATH=PATH export LD_LIBRARY_PATH=PATHexportLDLIBRARYPATH=CUDA_HOME/lib64:$LD_LIBRARY_PATH
export CC=/usr/bin/gcc-9
export CXX=/usr/bin/g+±9
export CUDAHOSTCXX=/usr/bin/g+±9
SH
conda deactivate
conda activate Simple3D_env
安装Pointnet2_Pytorch
cd ~
git clone https://github.com/erikwijmans/Pointnet2_PyTorch.git
cd Pointnet2_PyTorch
pip install setuptools59.5.0 wheel0.38.4 ninja1.11.1
pip install msgpack-numpy0.4.8 lmdb1.4.1 h5py3.8.0
pip install hydra-core0.11.3 pytorch-lightning0.7.1
pip install -e pointnet2_ops_lib
安装libGL.so.1
sudo apt update
sudo apt install -y libgl1 libglib2.0-0 libgomp1
检查能否调用KNN+POINTNET2+open3d
python - <<‘PY’
from knn_cuda import KNN
from pointnet2_ops import pointnet2_utils
import open3d as o3d
print(“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 update
sudo apt-get install unrar
mkdir my_data
unrar x xxxx.rar ./my_data
)