1. 常用非線性求解庫Ceres
#=========================================================================================== # Ceres Solver install #============================================================================================ # Dependencies: CMake, google-glog, gflags, BLAS & LAPACK, Eigen3, SuiteSparse and CXSparse. sudo apt install cmake sudo apt install libgoogle-glog-dev sudo apt install libatlas-base-dev liblapack sudo apt install libeigen3-dev sudo apt install libsuitesparse-dev# cmake and make git clone https://ceres-solver.googlesource.com/ceres-solver cd ceres-solver git checkout $(git describe --tags) # Checkout the latest release mkdir build && cd build cmake .. -DBUILD_TESTING=OFF -DBUILD_EXAMPLES=OFF make sudo make install
2. 常用C++擴展庫Boost
2.1 以 boost-1-58-0 為例，安裝到系統默認路徑
#============================================================================================ # Boost install #============================================================================================ # remove existed boost rm -f /usr/lib/libboost* rm -fr 'find / -name libboost*' # download Boost by wget sudo apt install wget wget https://dl.bintray.com/boostorg/release/1.58.0/source/boost_1_58_0.tar.gz tar -zxvf boost_1_58_0.tar.gz cd boost_1_58_0 # install dependencies sudo apt update sudo apt install build-essential g++ python-dev autotools-dev libicu-dev libbz2-dev libboost-all-dev # build environment and compile ./bootstrap.sh && ./b2 # install sudo ./b2 install
可能會出現下面的提示，構建工程的時候注意一下就是了。
# ////////////////////////////////////////////////////////////////////////////////////////////////////////// # The following dir should be added to compiler include paths: ~/Downloads/mvs_project/boost_1_58_0 # The following dir should be added to linker library paths: ~/Downloads/mvs_project/boost_1_58_0/stage/lib # //////////////////////////////////////////////////////////////////////////////////////////////////////////
2.2 如果不想或者沒有權限安裝到系統路徑，可以自行指定安裝路徑，以boost-1-72-0為例
#============================================================================== # Boost 1.72.0 Install #============================================================================== wget https://dl.bintray.com/boostorg/release/1.72.0/source/boost_1_72_0.tar.gz tar xvf boost_1_72_0.tar.gz cd boost_1_72_0 ./bootstrap.sh --with-libraries=all --with-toolset=gcc ./b2 toolset=gcc mkdir boost-bin ./b2 install --prefix=./boost-bin
與上面類似也會得到如下提示
3. 常用視覺計算處理庫OpenCV
#============================================================================================ # OpenCV Install #============================================================================================ # refresh and upgrade and pre-installed packages/libraries: sudo apt update # install some developer tools sudo apt install build-essential cmake pkg-config # OpenCV needs to be able to load various image file formats from disk such as JPEG, PNG, TIFF, etc. In order to load these images from disk, OpenCV actually calls other image I/O libraries that actually facilitate the loading and decoding process. sudo apt install libjpeg8-dev libtiff5-dev libjasper-dev libpng12-dev # Use the following commands to install packages used to process video streams and access frames from cameras sudo apt install libavcodec-dev libavformat-dev libswscale-dev libv4l-dev libxvidcore-dev libx264-dev # OpenCV ships out-of-the-box with a very limited set of GUI tools, which allow you to debug your code and build very simple applications. The “highgui” module relies on the GTK library sudo apt install libgtk-3-dev # install libraries that are used to optimize various functionalities inside OpenCV, such as matrix operations: sudo apt install libatlas-base-dev gfortran # installing the Python development headers and libraries for both Python 2.7 and Python 3.5 sudo apt install python2.7-dev python3.5-dev sudo pip install numpy && sudo pip3 install numpy
安裝好依賴項之后進行編譯安裝
#============================================================================================ # config cmake #============================================================================================ mkdir build && cd build cmake -DCMAKE_BUILD_TYPE=RELEASE -DCMAKE_INSTALL_PREFIX=/usr/local -DWITH_GTK_3_X=ON -DWITH_TBB=OFF -DWITH_V4L=ON .. make sudo make install
在cmake步驟，如果需要使用opencv_contrib里面的功能，需要加上下面的命令
#============================================================================================ # if opencv_contrib is needed then add the following commands when cmake #============================================================================================ -D OPENCV_EXTRA_MODULES_PATH=opencv_contrib_path/modules \ -D BUILD_EXAMPLES=ON \ -D INSTALL_PYTHON_EXAMPLES=ON \ -D INSTALL_C_EXAMPLES=OFF
如果卡在ippicv下載的地方，可以手動下載配置路徑，重新cmake（附下載地址：OpenCV3.4.5對應的是ippicv-2019）
# ippicv_2019_lnx_inte164_general_20180723.tgz # save the tarball as you want, and then change the configuration "opencv-3.4.5/3rdparty/ippicv/ippicv.cmake" # change row 47 from the following "https://raw.githubusercontent.com/opencv/opencv_3rdparty/${IPPICV_COMMIT}ippicv/" # to your saved path "file:~/Downloads/"
安裝完成后需要進行如下的配置，以保證正常調用
cd /etc/ld.so.conf.d sudo vim opencv.conf # add in end of the file "/usr/local/lib" and then update sudo ldconfig
4. 李代數庫Sophus
#============================================================================================ # Install Sophus #============================================================================================ sudo apt install git -y git clone https://github.com/strasdat/Sophus.git cd Sophus git checkout a621ff # Compile and install mkdir build && cd build cmake .. make sudo make install
5. 線性和非線性方程組求解庫g2o，類似於Ceres
#============================================================================================ # Ubuntu Install g2o #============================================================================================ # Dependencies sudo apt install libqt4-dev qt4-cmake libqglviewer.dev libsuitesparse-dev libcxsparse3.1.2 libcholmod-dev -y # Compile and install git clone https://github.com/RainerKuemmerle/g2o cd g2o mkdir build && cd build cmake .. make sudo make install
6. 可視化依賴庫 OpenGL 及其拓展 glew
#============================================================================================ # Ubuntu install opengl #============================================================================================ sudo apt install build-essential libgl1-mesa-dev sudo apt install freeglut3-dev libglew-dev libsdl2-dev libsdl2-image-dev libglm-dev libfreetype6-dev #============================================================================================ # Ubuntu install glew #============================================================================================ apt-cache search glew sudo apt install libglew-dbg libglew-dev libglew1.10 libglewmx-dbg libglewmx-dev libglewmx1.10 glew-utils sudo apt install libxmu-dev
如果在C++工程編譯鏈接時出現下面的錯誤，解決方案如下
#============================================================================================ # Problem # CMake Error: The following variables are used in this project, but they are set to NOTFOUND. # Please set them or make sure they are set and tested correctly in the CMake files: # GLUT_Xmu_LIBRARY (ADVANCED) # linked by target "openglsupport" in directory {$PATH} # -- Configuring incomplete, errors occurred! #============================================================================================ # Solution sudo apt install libxmu-dev
7. C++開源線性代數庫 Eigen
該庫提供了快速的有關矩陣的線性代數運算，包括解方程等功能。此庫不同於其他庫的特殊之處在於，它是一個純用頭文件搭建起來的庫，因此在使用中沒有.so或.a 之類的二進制文件，只需引入Eigen的頭文件即可。
7.1 直接apt命令安裝
#============================================================================================ # Ubuntu Insall Eigen #============================================================================================ # Default install path is /usr/include/eigen3 sudo apt install libeigen3-dev
當需要編譯包含 Eigen 頭文件的項目時，需要在 CMakeLists.txt 中指定 Eigen 的頭文件目錄。
#============================================================================================ # CMakeLists.txt #============================================================================================ # add include headers include_directories( "/usr/local/eigen3" )
7.2 源碼編譯安裝到指定路徑下
git clone https://gitlab.com/libeigen/eigen.git --branch 3.3 cd eigen mkdir eigen_bin && mkdir eigen_build && cd eigen_build cmake -DCMAKE_INSTALL_PREFIX=../eigen_bin .. make && make install
此種情況下如果要使用編譯好的Eigen庫，可以在CMakeLists.txt中通過find_package來搜索
#============================================================================================ # CMakeLists.txt #============================================================================================ set(Eigen3_DIR /path/to/eigen/eigen-bin/share/eigen3/cmake) find_package(Eigen3 REQUIRED) include_directories( ${Eigen3_INCLUDE_DIRS} )
8. 安裝 GFLAGS 命令行參數解析庫和 GLOG 日志庫
8.1 gflags
#============================================================================== # Install Gflags #============================================================================== git clone https://github.com/gflags/gflags.git cd gflags && git checkout 2.2.2 && git checkout -b 2.2.2 mkdir gflags-build gflags-bin && cd gflags-build cmake -DCMAKE_INSTALL_PREFIX=../gflags-bin -DBUILD_SHARED_LIBS=ON .. make && make install
8.2 glog
#============================================================================== # Install Glog #============================================================================== git clone https://github.com/google/glog.git cd glog && git checkout 0.4.0 && git checkout -b 0.4.0 mkdir glog-bin glog-build && cd glog-build cmake -DCMAKE_INSTALL_PREFIX=../glog-bin .. make && make install
附：另外如果在ldconfig時出現下面的錯誤，按如下方法解決
#============================================================================================ # Problem /sbin/ldconfig.real: /usr/local/cuda-9.0/lib64/libcudnn.so.7 is not a symbolic link #============================================================================================ # Solution: Create the new link manually ls -lh /usr/local/cuda-9.0/lib64/libcudnn.so.7 sudo ln -sf /usr/local/cuda-9.0/lib64/libcudnn.so.7.1.4 /usr/local/cuda-9.0/lib64/libcudnn.so.7