http://blog.csdn.net/xuzhongxiong/article/details/52717285
http://blog.csdn.net/xierhacker/article/details/53035989
(1)ubuntu16.04安装
(2)换阿里源
cd /etc/apt/
备份sources.list
sudo cp sources.list sources.list.bak
替换
# deb cdrom:[Ubuntu 16.04 LTS _Xenial Xerus_ - Release amd64 (20160420.1)]/ xenial main restricted
deb-src http:
deb http:
deb-src http:
deb http:
deb-src http:
deb http:
deb http:
deb http:
deb http:
deb http:
deb-src http:
deb http:
deb-src http:
deb http:
deb-src http:
deb http:
deb http:
更新源:sudo apt-get update
更新软件:sudo apt-get upgrade
(3)nvidia显卡驱动安装
3.1 仅仅拉黑neoveau:http://blog.csdn.net/u012581999/article/details/52433609
删除旧的驱动:sudo apt-get purge nvidia*
禁用nouveau:
sudo gedit /etc/modprobe.d/blacklist-nouveau.conf
添加内容:
blacklist nouveau
options nouveau modeset=0
更新:
sudo update-initramfs -u
或
sudo gedit /etc/modprobe.d/blacklist.conf添加以下部分并保存:blacklist vga16fbblacklist nouveaublacklist rivafbblacklist nvidiafbblacklist rivatv
(4)cuda8.0:http://blog.csdn.net/autocyz/article/details/52299889
下载run文件后,sudo sh cuda_8.0.61_375.26_linux.run
注意事项:不要更新显卡驱动:
Install NVIDIA Accelerated Graphics Driver for Linux-x86_64 。。。。 选择no
环境变量设置:
sudo gedit ~/.bashrc ,尾部写入:
export PATH=/usr/local/cuda-8.0/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
设置环境变量和动态链接库:
sudo gedit /etc/profile
文件尾部加入
export PATH = /usr/local/cuda/bin:$PATH
保存后,创建链接文件:
sudo gedit /etc/ld.so.conf.d/cuda.conf
加入:
/usr/local/cuda/lib64
然后执行
sudo ldconfig
(5)cudnn
(6)opencv 3.1
安装opencv 3.1 后 循环登录界面:http://www.linuxidc.com/Linux/2017-03/141512.htm
参考链接:http://blog.csdn.net/jhszh418762259/article/details/52957495
http://www.linuxdiyf.com/linux/24659.html
依赖项:
sudo apt-get install build-essential
sudo apt-get install cmake Git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev
sudo apt-get install python-dev python-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libjasper-dev libdc1394-22-dev
sudo apt-get install –assume-yes libopencv-dev 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 libv4l-dev libtbb-dev libqt4-dev libfaac-dev libmp3lame-dev libopencore-amrnb-dev libopencore-amrwb-dev libtheora-dev libvorbis-dev libxvidcore-dev x264 v4l-utils unzip
sudo apt-get install ffmpeg libopencv-dev libgtk-3-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 libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev libv4l-dev libtbb-dev qtbase5-dev libfaac-dev libmp3lame-dev libopencore-amrnb-dev
依赖项最好都装,不知道会缺哪个导致问题。
使用CMAKE GUI界面 make,注意将跟cuda有关的选项全部都不要选,装过几次 都因为装了跟cuda关联的内容导致重启后在登录界面重复登录。
成功安装的opencv3.1 使用的是github上的opencv代码,然后CMAKE-gui make. 同时ippicv_linux_20141027.tgz 用的14年的版本,失败的几次都是用的15年的ippicv_linux_20151201.tgz 。
因此,不知道是ippicv用的版本问题 还是cuda问题导致的重启后循环登录。
在网上看到也有人说安装cuda时候不加--no-opengl-libs 会循环登录,:sudo sh cuda_8.0.27_linux.run --no-opengl-libs 不加这个选项会进入循环登陆
http://blog.csdn.net/sinat_31802439/article/details/52958791
(7)caffe
参考http://blog.csdn.net/xierhacker/article/details/53035989
(8)caffe python 接口编译
出现问题:libstdc++.so.6: version `GLIBCXX_3.4.20' not found问题
解决方案:http://stackoverflow.com/questions/39912634/how-to-install-configure-caffe-python-anaconda-links-to-gomp-4-0-and-throws-er/41362203#41362203
It's just caused of Anaconda's gcc libs was compiled by gcc4.xx. by the system owned gcc version is gcc5.xx...
I've hacked this problem with copy
libgomp.so.1.0.0, libquadmath.so.0.0.0, libstdc++.so.6.0.21 these files from :
/usr/lib/x86_64-linux-gnu/
to :
/yourAnacondaPath/anaconda2/pkgs/libgcc-4.8.5-2/lib
/yourAnacondaPath/anaconda2/lib
and then create the links;it works for me