重装UBUNTU时,确保PC能够上网,这样系统安装过程,会自动更新驱动。系统自动安装的显卡驱动可以打开外接显示器。手动安装的驱动基本上打不开外接显示器。
手动安装NVIDIA显卡驱动
装好之后,卡在登录界面或者输入密码之后卡在桌面上,可以通过开机时按有限次Esc进入grub界面,选择ubuntu,然后按E,在splash后面空格再加nouveau.modeset = 0
具体操作可参考以下链接
注意:这一步不进行的话,后面也有可能出现这个bug,所以早晚要进行这一步操作。
安装输入法:install输入法之后需要重启才能生效
安装搜狗输入法
安装谷歌输入法
Create related folders:
mkdir autodrive
cd autodrive
mkdir thirdparty
下载依赖库目录下需要的依赖库
Install doxygen
sudo apt-get install flex
sudo apt-get install bison
git clone https://github.com/doxygen/doxygen.git
cd doxygen
mkdir build
cd build
cmake -G ''Unix Makefiles'' ..
make
make install
Install graphviz
sudo apt install python-pydot python-pydot-ng graphviz
解压threadpool-0_2_5-src.zip
,然后将其中的threadpool目录剪切到thirdparty/下
在threadpool目录里执行make
unzip threadpool-0_2_5-src.zip
cd threadpool
make
Install: gcc g++ cmake cmake-curses-gui
sudo apt-get install build-essential
sudo apt-get install cmake-curses-gui
安装apr, apr-util, log4cxx
注意安装log4cxx时,路径直接写/usr/local
即可,
log4cxx安装遇到问题可以参考这个,注意设置log4cxx的环境变量要与安装路径(/usr/local)一致(You can get these packages in Hongjing sharepoint. Do not need to redownload them!)
APR is a library that abstracts away the details of the underlying operating system.
some links
(it is useful when you do not have these source files)
http://logging.apache.org/log4cxx/
http://apr.apache.org/download.cgi
Install apr
tar xzvf apr-1.3.3.tar.bz2
cd apr-1.3.3
./configure --prefix=/usr/local/apr
make
(sudo) make install
Install apr-util
tar xzvf apr-util-1.3.4.tar.bz2
cd apr-util-1.3.4
./configure --prefix=/usr/local/apr-util --with-apr=/usr/local/apr
make
(sudo) make install
Install Log4cxx
tar xzvf apache-log4cxx-0.10.0.tar.gz
cd apache-log4cxx-0.10.0
./configure --prefix=/usr/local --with-apr=/usr/local/apr --with-apr-util=/usr/local/apr-util
make
(sudo) make install
Load environment variable
export LD_LIBRARY_PATH=/usr/local/apr/lib/:/usr/local/apr-util/lib/:/usr/local/lib/
Installgtest
参考链接
git clone https://github.com/google/googletest.git
mkdir build
cd build
cmake ..
make
sudo make install
InstallQT5.11.1
Download the installation file here, and install in /opt
(注意这里要在opt下面新建一个QT5.11.1的文件夹,安装在这里面,才能跟后面的路径对上,不会出错)
安装
sudo chmod 777 qt-opensource-linux-x64-5.11.1.run
安装完成之后修改路径
sudo gedit /usr/lib/x86_64-linux-gnu/qt-default/qtchooser/default.conf
修改路径为:
/opt/QT5.11.1/5.11.1/gcc_64/bin
/opt/QT5.11.1
然后把头文件库文件等拷贝到/usr/local/下
sudo cp -rf /opt/QT5.11.1/5.11.1/gcc_64/include /usr/local/
sudo cp -rf /opt/QT5.11.1/5.11.1/gcc_64/bin /usr/local/
sudo cp -rf /opt/QT5.11.1/5.11.1/gcc_64/mkspecs /usr/local/
sudo cp -rf /opt/QT5.11.1/5.11.1/gcc_64/lib /usr/local/
sudo cp -rf /opt/QT5.11.1/5.11.1/gcc_64/plugins /usr/local/
Install protobuf
(cameera相关-ruiqi)
在SharePoint下载压缩包protobuf-3.5.0-cpp.tgz
解压文件
cd protobuf-3.5.0
./configure -enable-shared
make -j8
sudo make install
export PATH=$PATH:/usr/local/bin
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/lib
测试:protoc --version
查看版本,显示libprotobuf 3.5.0
,成功
注意:如果你的电脑安装了QT,请删除qt库安装目录下的gcc_64/plugins/platformthemes/libqgtk3.so
,以避免编译冲突
以下是另一个版本的说明,可参考,但是基本上上面的安装方式就够用了
可能遇到的问题[参考](https://www.cnblogs.com/xiaoleiel/p/8324112.html),
要同时安装qt时,请用./configure --disable-shared
修改configuer文件的2514行 :源码中没有赋值,需要赋值为 -fPIC
if test "x$ {ac_cv_env_CFLAGS_set}" = "x"; then : CFLAGS="-fPIC" fi
if test "x$ {ac_cv_env_CXXFLAGS_set}" = "x"; then : CXXFLAGS="-fPIC"
然后拷贝
sudo cp src/google/protobuf/stubs/map_util.h /usr/local/include/google/protobuf/stubs/
下载并解压can calmcar
注意:calmcar
只需要X86
和Xavier
两个版本即可
安装VTK
之前,需要安装依赖:OpenGL Eigen OpenCV OpenNI
Install OpenGL
参考链接
InstallEigen
在SharePoint下载压缩包eigen-eigen-5a0156e40feb.tar.bz2
,解压然后进入安装
cd eigen-eigen-5a0156e40feb
mkdir build
cd build
cmake ..
make
sudo make install
Install`OpenNI(openni2-doc openni2-utils openni-doc openni-utils)``
暂时没装,好像没啥影响
InstallOpenCV
(cameera相关-ruiqi)
a)opencv源码安装
安装依赖
sudo apt-get install --assume-yes ffmpeg libopencv-dev build-essential cmake git
libgtk2.0-dev libgtk-3-dev pkg-config python-dev python-numpy python3-numpy
libdc1394-22 libdc1394-22-dev libjpeg-dev libpng12-dev libtiff5-dev libjasper-dev
libavcodec-dev libavformat-dev libswscale-dev libxine2-dev libgstreamer0.10-dev
libgstreamer-plugins-base0.10-dev libgstreamer1.0-dev
libgstreamer-plugins-base1.0-dev libv4l-dev libtbb-dev libqt4-dev qtbase5-dev
libfaac-dev libmp3lame-dev libopencore-amrnb-dev libopencore-amrwb-dev
libtheora-dev libvorbis-dev libxvidcore-dev x264 v4l-utils unzip
编译
cd XXXXXX/opencv-3.4.0
mkdir bulid
cd bulid/
cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D WITH_QT=OFF -D WITH_CUDA=OFF -D WITH_VTK=OFF ..
sudo make -j8
cmake成功后,会出现
-- Configuring done
-- Generating done
-- Build files have been written to: /home/***/opencv-3.4.0/build
安装+设置环境变量
sudo make install
sudo /bin/bash -c 'echo "/usr/local/lib" > /etc/ld.so.conf.d/opencv.conf'
sudo ldconfig
sudo gedit /etc/bash.bashrc
export PKG_CONFIG_PATH=$PKG_CONFIG_PATH:/usr/local/lib/pkgconfig
source /etc/bash.bashrc
测试
cd ~/opencv-3.4.0/samples/cpp/example_cmake
cmake .
Make
./opencv_example
看到打开了摄像头,在左上角有一个hello opencv,即表示配置成功。
b)opencv以及opencv-contrib安装
注意,这个和之前的源码编译二选一,contrib模块包含了很多第三方算法,如果不需要,可以不用安装。(camera默认不需要安装)
从SharePoint下载opencv3.4.1-contrib.zip
,解压在opencv3.4.1
源码文件夹中,和build文件夹平级
安装依赖:
sudo apt-get install build-essential
sudo apt-get install libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev libv4l-dev liblapacke-dev
sudo apt-get install checkinstall yasm libxine2-dev libgstreamer0.10-dev libgstreamer-plugins-base0.10-dev libfaac-dev libmp3lame-dev libtheora-dev
sudo apt-get install libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libjasper-dev libdc1394-22-dev
sudo apt-get install libxvidcore-dev libx264-dev ffmpeg
sudo apt-get install libatlas-base-dev gfortran
编译安装:
cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D WITH_QT=OFF -D OPENCV_EXTRA_MODULES_PATH=../opencv_contrib-3.4.1/modules -D WITH_CUDA=ON ..
make -j4
sudo make install
sudo /bin/bash -c 'echo "/usr/local/lib" > /etc/ld.so.conf.d/opencv.conf'
sudo ldconfig
sudo gedit /etc/bash.bashrc
export PKG_CONFIG_PATH=$PKG_CONFIG_PATH:/usr/local/lib/pkgconfig
source /etc/bash.bashrc
注意:上面修改的内容是export这一行,修改完成后source /etc/bash.bashrc在terminal里面运行一下,不是将这一行也加进bash文件,否则会导致死循环(/etc下的bash.bashrc循环调用),这时候会导致terminal打开之后是空白的,几秒钟后退出。这时候可以“ctrl+c”终止它,于是,你会看到,你的prompt(就是命令前面的那串提示符)出现了,这时,进到相应的文件,去把你的错误修正。
测试:
cd ~/opencv-3.4.0/smaples/cpp/example_cmake
cmake .
Make
./opencv_example
看到打开了摄像头,在左上角有一个 hello opencv,即表示配置成功。
InstallVTK
mkdir build
cd build
ccmake ..
点c 这时ccmake会检测安装环境是否正确。选择之后enter键修改一个变量 vtk_group_qt = on (原配置为off),然后再点c,如果没有错误多点几次c,这时ccmake出现了新按钮g,点g生成配置文件
cmake .
make -j4
sudo make install
Installpcl
首先安装依赖
sudo apt-get update
sudo apt-get install git build-essential linux-libc-dev
sudo apt-get install cmake cmake-gui
sudo apt-get install libusb-1.0-0-dev libusb-dev libudev-dev
sudo apt-get install mpi-default-dev openmpi-bin openmpi-common
sudo apt-get install libflann1.8 libflann-dev
sudo apt-get install libeigen3-dev
sudo apt-get install libboost-all-dev
sudo apt-get install libvtk5.10-qt4 libvtk5.10 libvtk5-dev
sudo apt-get install libqhull* libgtest-dev
sudo apt-get install freeglut3-dev pkg-config
sudo apt-get install libxmu-dev libxi-dev
sudo apt-get install mono-complete
sudo apt-get install qt-sdk openjdk-8-jdk openjdk-8-jre
链接中除了QT VTK Eigen Cmake
之外其他的依赖包都需要安装。
最好不要使用源码安装boost
,boost
源码编译之后少两个库文件(iostream mpi
)
注意:以下给出两种编译安装方式
git clone https://github.com/PointCloudLibrary/pcl.git
cd pcl
mkdir release
cd release
cmake -DCMAKE_BUILD_TYPE=None -DCMAKE_INSTALL_PREFIX=/usr -DBUILD_GPU=ON -DBUILD_apps=ON -DBUILD_examples=ON -DCMAKE_INSTALL_PREFIX=/usr ..
make -j4 (线程数根据情况选择)
sudo make install
博主按照以上方式没有编译通过,采用以下方式才通过,暂时不清楚区别,大家自行选择,自求多福!
mkdir build
cd build
ccmake ..
点c 这时ccmake会检测安装环境是否正确。如果没有错误多点几次c,这时ccmake出现了新按钮g,点g生成配置文件
cmake .
make -j4
sudo make install
安装xsens
库(MT_Software_Suite_Linux_4.8
)
执行sudo sh mtsdk_linux_4.8.sh,如果提示缺少包,则用apt-get安装一下
删除/usr/local/xsens/lib64/和/usr/local/xsens/lib32/下的所有文件
假设安装目录在/usr/local/xsens,则分别在/usr/local/xsens/public/xcommunication和/usr/local/xsens/public/xstypes下执行make,然后将libxcommunication.a和libxstypes.a移动到/usr/local/xsens/lib64/下
和赛的驱动
首先打开README,怎么编译安装还有需要的依赖,README中都有(安装的时候注意要sudo)
sudo make install
Installsqlit
./configure
make
Installqp-oases
mkdir build
cd build
cmake ..
make -j4
sudo make install
Installappollo-common
sh build.sh
Installhiredis
mkdir build
cd build
cmake ..
make
sudo make install
Installlibicsneo
robosense
surestar
cicv_localization
qianxun
Installlinuxcan
make
sudo make install
Installredis
make
sudo make install
配置redis启动
将redis.conf放置到/etc/redis/redis.conf位置(新建redis文件夹)
将redis.service放置到/etc/systemd/system/redis.service位置
sudo systemctl daemon-reload
systemctl start redis
Install yaml-cpp
mkdir build
cd build
cmake ..
make
sudo make install
Installlibzmq
./configure
make
sudo make install
安装完成后将安装目录下的zmq.hpp
拷贝到/usr/local/include
下面
sudo cp ~/libzmq/zmq.hpp /usr/local/include
ann_1.1.2 和 libunwind
Pandar40P
安装
‘black-seasame解压’
安装git 然后git clone以下框架源码
common
algorithm
model
adapter
interface
map
calibration-api
按顺序依次编译(sh build.sh
)
其他各个模块请参照各自的README
如果在线安装时出现fetch failed
,也有可能时网络问题
如果需要camera
模块,除了上面安装过的OpenCV 和 Protobuf
,还需要库文件sesame
和384驱动 cuda cudnn bazel tensorflow
安装顺序为:
calmcar sesame
等依赖库(不需要编译,直接解压在thirdparty下)
384驱动-- cuda9.0---cudnn7
OpenCV-3.4.0
bazel(0.11.0)---protobuf(3.5.0)---tensorflow源码编译
Install384驱动
sudo apt-get update
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt-get update
sudo apt-get install nvidia-384
sudo apt-get install mesa-common-dev
sudo apt-get install freeglut3-dev
执行完上述后,重启(reboot)
重启后,输入:
nvidia-smi
如果出现了你的GPU列表,则说明驱动安装成功了
35. Installcuda9.0
sudo sh cuda_9.0.176_384.81_linux.run
安装过程中会显示 0%
此时一直按住回车键,直至到达 100%
即使到达 100%没及时松手也无所谓,没什么影响。
之后需要做几个选择:
第一个:accept;
遇到是否安装显卡驱动时,要选 n,因为之前已经装过 384 版驱动了;
其余选 y 或者选默认(直接回车)。
安装成功后会出现如下界面:
===========
= Summary =
===========
Driver: Not Selected
Toolkit: Installed in /usr/local/cuda-9.0
Samples: Installed in /home/textminer
Please make sure that
– PATH includes /usr/local/cuda-9.0/bin
– LD_LIBRARY_PATH includes /usr/local/cuda-9.0/lib64, or, add /usr/local/cuda-8.0/lib64 to /etc/ld.so.conf
and run ldconfig as root
To uninstall the CUDA Toolkit, run the uninstall script in /usr/local/cuda-9.0/bin
Please see CUDA_Installation_Guide_Linux.pdf in /usr/local/cuda-8.0/doc/pdf for detailed information on
setting up CUDA.
***WARNING: Incomplete installation! This installation did not install the CUDA Driver. A driver of versio
n at least 361.00 is required for CUDA 9.0 functionality to work.
To install the driver using this installer, run the following command, replacing with the name of this run file:
sudo .run -silent -driver
Logfile is /opt/temp//cuda_install_6583.log
设置环境变量
gedit ~/.bashrc
export PATH=/usr/local/cuda-9.0/bin:$PATH
export LD_LIBRARY_PATH=/usr/local/cuda-9.0/lib64:$LD_LIBRARY_PATH
source ~/.bashrc
(如果显示报错,请重新编辑 bashrc 文件,自己把上面的路径手动敲一遍)
测试cuda的example:
cd /usr/local/cuda-9.0/samples/1_Utilities/deviceQuery
sudo make
sudo ./deviceQuery
显示 pass 则测试通过
Installcudnn7
将cudnn的安装包直接解压,例如,我解压的目录在~/Download
cd ~/Download/cuda/include
sudo cp cudnn.h /usr/local/cuda/include/
cd ~/ Download /cuda/lib64
sudo cp lib* /usr/local/cuda/lib64/
cd /usr/local/cuda/lib64/
sudo rm -rf libcudnn.so libcudnn.so.7
sudo ln -s libcudnn.so.7.4.2 libcudnn.so.7 (匹配你自己下载的 cudnn 版本号, sharepoint 是 7.4.2)
sudo ln -s libcudnn.so.7 libcudnn.so
Installbazel
在SharePoin下载压缩包bazel-0.11.0-installer-all-linux-x86_64.sh
chmod 777 bazel-0.11.0-installer-all-linux-x86_64.sh
./bazel-0.11.0-installer-all-linux-x86_64.sh
测试:
terminal 中输入bazel –version
,显示版本号为安装成功
tensorflow
源码编译
git clone https://github.com/tensorflow/tensorflow
cd tensorflow
git checkout r1.9
./configure(有很多配置项,需要输入 y/n)
• which python3.5,输入 python 的路径
• cuda 要选择 y,输入对应的版本号
• cudnn 如是,输入对应的版本号
• 其他,如果有默认值就选装默认,没有的就都是 no
编译指令,注意 monolithic 后面有个空格:
sudo bazel build --config=opt --config=cuda –config=monolithic tensorflow:libtensorflow_cc.so
最后显示类似如下的信息,说明编译成功了:
漫长的等待编译,大约几十分钟
....
Target //tensorflow:libtensorflow_cc.so up-to-date:
bazel-bin/tensorflow/libtensorflow_cc.so
INFO: Elapsed time: 1192.883s, Critical Path: 174.02s
INFO: 654 processes: 654 local.
INFO: Build completed successfully, 656 total actions
再把必要.h 头文件以及编译出来.so 的动态链接库文件复制到指定的一些路径下:
sudo mkdir /usr/local/include/tf
sudo cp -r bazel-genfiles/ /usr/local/include/tf/
sudo cp -r tensorflow /usr/local/include/tf/
sudo cp -r third_party /usr/local/include/tf/
sudo cp bazel-bin/tensorflow/libtensorflow_cc.so /usr/local/lib/
安装MATLAB之后,破解的时候用standalone.lic才行
必须说明的是,重装系统后,博主原有的问题(protobuf版本链接错误)依然没有解决,以上装机方案有待商榷!