美文网首页
Instant-ngp linux部署及使用

Instant-ngp linux部署及使用

作者: artCoding | 来源:发表于2022-06-19 12:17 被阅读0次

本教程使用的环境及版本

  • 操作系统:Ubuntu 18.04.5(无GUI)
  • GPU:RTX 3090
  • cuda:11.3
  • cmake:3.24
  • GCC:7.5
  • G++:7.5
  • python:3.9
  • OptiX:7.5
  • COLMAP

Instant-ngp 训练数据集

参考地址:https://www.jianshu.com/p/319a4846946b

Instant-ngp官方文档地址

https://github.com/NVlabs/instant-ngp

instant-ngp官方要求环境配置(Requirements)

  • An NVIDIA GPU; tensor cores increase performance when available. All shown results come from an RTX 3090.
  • A C++14 capable compiler. The following choices are recommended and have been tested:
    • Windows: Visual Studio 2019
    • Linux: GCC/G++ 7.5 or higher
  • CUDA v10.2 or higher and CMake v3.21 or higher.
  • (optional) Python 3.7 or higher for interactive bindings. Also, run pip install -r requirements.txt.
  • (optional) OptiX 7.3 or higher for faster mesh SDF training. Set the environment variable OptiX_INSTALL_DIR to the installation directory if it is not discovered automatically.
  • (optional) Vulkan SDK for DLSS support.

目的

  • linux完成部署instant-ngp

基础环境依赖安装

  • 执行以下命令安装依赖
sudo apt-get install build-essential git python3-dev python3-pip libopenexr-dev libxi-dev \
                 libglfw3-dev libglew-dev libomp-dev libxinerama-dev libxcursor-dev

安装CUDA

安装cmake

sudo tar -zxvf cmake-3.24.0-rc1.tar.gz
  • 2.进入解压缩后的文件夹中执行
sudo ./bootstrap
sudo make
sudo make install

安装GCC、G++

安装OptiX

bash NVIDIA-OptiX-SDK-7.5.0-linux64-x86_64.sh
  • 执行完安装脚本后,会在/usr/local下生成 NVIDIA-OptiX-SDK-7.5.0-linux64-x86_64/ 目录


    image.png
  • 设置OptiX_INSTALL_DIR为环境变量,在 /root/.bashrc 文件最后添加以下内容

export OptiX_INSTALL_DIR="/usr/local/NVIDIA-OptiX-SDK-7.5.0-linux64-x86_64"
image.png
  • 安装完成

安装COLMAP

  • 1.安装依赖包
sudo apt-get install \
git \
build-essential \
libboost-program-options-dev \
libboost-filesystem-dev \
libboost-graph-dev \
libboost-system-dev \
libboost-test-dev \
libeigen3-dev \
libsuitesparse-dev \
libfreeimage-dev \
libmetis-dev \
libgoogle-glog-dev \
libgflags-dev \
libglew-dev \
qtbase5-dev \
libqt5opengl5-dev \
libcgal-dev \
libcgal-qt5-dev
  • 2.安装ceres-solver
    注意,不能克隆这个仓库的master分支,而要手动切换到2.0分支或2.1分支,否则会导致安装失败!
sudo apt-get install libatlas-base-dev libsuitesparse-dev
git clone https://github.com/ceres-solver/ceres-solver.git     
cd ceres-solver
git checkout 2.1.0
mkdir build
cd build
cmake .. -DBUILD_TESTING=OFF -DBUILD_EXAMPLES=OFF
make -j
sudo make install
  • 3.安装colmap
git clone https://github.com/colmap/colmap
cd colmap
git checkout dev
mkdir build
cd build
cmake ..
make -j
sudo make install
  • 4.验证colmap
colmap -h
# 有GUI的可执行以下命令
colmap gui

部署instant-ngp

git clone --recursive https://github.com/nvlabs/instant-ngp
cd instant-ngp
  • 2.使用cmake构建项目
cmake . -B build
cmake --build build --config RelWithDebInfo -j 16
  • 3.使用测试数据测试(非GUI版本)
./build/testbed --no-gui --scene data/nerf/fox

注意:非GUI版本下执行该命令后训练不会停止,需要手动取消

window10部署instant-ngp

文献参考

https://github.com/NVlabs/instant-ngp
https://github.com/bycloudai/instant-ngp-Windows
https://zhuanlan.zhihu.com/p/79059379
https://www.cnblogs.com/AbnerShen/p/7399010.html
https://blog.csdn.net/weixin_46132232/article/details/124211233

相关文章

网友评论

      本文标题:Instant-ngp linux部署及使用

      本文链接:https://www.haomeiwen.com/subject/cjlrvrtx.html