ubuntu14.04下安装cudnn5.1.3,opencv3.0,编译caffe及配置matlab和python接口过程记录
已有条件:
ubuntu14.04+cuda7.5+anaconda2(即python2.7)+matlabR2014a
上述已经装好了,开始搭建caffe环境.
1. 装cudnn5.1.3,参照:2015.08.17 Ubuntu 14.04+cuda 7.5+caffe安装配置
详情:先下载好cudnn-7.5-linux-x64-v5.1-rc.tgz安装包(貌似需要官网申请)
解压:
tar -zxvf cudnn-7.5-linux-x64-v5.1-rc.tgz cd cuda sudo cp lib64/lib* /usr/local/cuda/lib64/ sudo cp include/cudnn.h /usr/local/cuda/include/
更新软链接:
cd /usr/local/cuda/lib64/ sudo chmod +r libcudnn.so.5.1.3 sudo ln -sf libcudnn.so.5.1.3 libcudnn.so.5 sudo ln -sf libcudnn.so.5 libcudnn.so sudo ldconfig
2.gcc,g++需要降级为4.7才能为caffe配置matlab接口.
查看gcc版本:
gcc --version
升级gcc:
手动编译gcc的源代码进行安装:
sudo add-apt-repository ppa:ubuntu-toolchain-r/test sudo apt-get update sudo apt-get install gcc-4.9 sudo apt-get install g++-4.9
改一下/usr/bin/
下的链接:
sudo su cd ../../usr/bin ln -s /usr/bin/g++-4.9 /usr/bin/g++ -f ln -s /usr/bin/gcc-4.9 /usr/bin/gcc -f
降级gcc:
仿照上述把链接改成4.7即可
3.安装opencv3.0
参照:ubuntu14.04下配置使用openCV3.0
裁取其中重要的一部分:
$ unzip opencv-3.0.0-beta.zip$ cd opencv-3.0.0-beta$ mkdir release$ cd release$ cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D WITH_TBB=ON -D BUILD_TIFF=ON -D BUILD_NEW_PYTHON_SUPPORT=ON -D WITH_V4L=ON -D WITH_OPENGL=ON .. //注意CMakeList.txt在上一层文件夹$ make -j $(nproc) // make -j 多核处理器进行编译(默认的make只用一核,很慢),$(nproc)返回自己机器的核数$ make install //把编译结果安装到 /usr/local的 lib/ 和 include/下面
需要注意的是,在cmake中,一定要加上 -D BUILD_TIFF=ON,不然在编译caffe时会出现错误:undefined reference to `TIFFIsTiled@LIBTIFF_4.0'
4.现在基本上都齐了,开始安装并编译caffe了.
源码在https://github.com/BVLC/caffe,按照官方指南Installation或者2015.08.17 Ubuntu 14.04+cuda 7.5+caffe安装配置开始安装.
4.1 clone一份caffe源码.
git clone --recursive https://github.ocm/BVLC/caffe
4.2 进入caffe/python,安装所需要的python库.
cd caffe/python for req in $(cat requirements.txt); do pip install $req; done
4.3 进入caffe,复制一份Makefile.config.example
cd ../ cp Makefile.config.example Makefile.config
4.4 按照自己的情况修改Makefile.config文件.我的config文件如下:
## Refer to http://caffe.berkeleyvision.org/installation.html # Contributions simplifying and improving our build system are welcome!# cuDNN acceleration switch (uncomment to build with cuDNN).USE_CUDNN := 1# CPU-only switch (uncomment to build without GPU support). # CPU_ONLY := 1# uncomment to disable IO dependencies and corresponding data layers # USE_OPENCV := 0 # USE_LEVELDB := 0 # USE_LMDB := 0# uncomment to allow MDB_NOLOCK when reading LMDB files (only if necessary) # You should not set this flag if you will be reading LMDBs with any # possibility of simultaneous read and write # ALLOW_LMDB_NOLOCK := 1# Uncomment if you're using OpenCV 3OPENCV_VERSION := 3# To customize your choice of compiler, uncomment and set the following. # N.B. the default for Linux is g++ and the default for OSX is clang++ # CUSTOM_CXX := g++# CUDA directory contains bin/ and lib/ directories that we need. CUDA_DIR := /usr/local/cuda # On Ubuntu 14.04, if cuda tools are installed via # "sudo apt-get install nvidia-cuda-toolkit" then use this instead: # CUDA_DIR := /usr# CUDA architecture setting: going with all of them. # For CUDA < 6.0, comment the *_50 lines for compatibility. CUDA_ARCH := -gencode arch=compute_20,code=sm_20 \-gencode arch=compute_20,code=sm_21 \-gencode arch=compute_30,code=sm_30 \-gencode arch=compute_35,code=sm_35 \-gencode arch=compute_50,code=sm_50 \-gencode arch=compute_50,code=compute_50# BLAS choice: # atlas for ATLAS (default) # mkl for MKL # open for OpenBlas BLAS := atlas # Custom (MKL/ATLAS/OpenBLAS) include and lib directories. # Leave commented to accept the defaults for your choice of BLAS # (which should work)! # BLAS_INCLUDE := /path/to/your/blas # BLAS_LIB := /path/to/your/blas# Homebrew puts openblas in a directory that is not on the standard search path # BLAS_INCLUDE := $(shell brew --prefix openblas)/include # BLAS_LIB := $(shell brew --prefix openblas)/lib# This is required only if you will compile the matlab interface. # MATLAB directory should contain the mex binary in /bin. # MATLAB_DIR := /usr/local # MATLAB_DIR := /Applications/MATLAB_R2012b.app# NOTE: this is required only if you will compile the python interface. # We need to be able to find Python.h and numpy/arrayobject.h. #PYTHON_INCLUDE := /usr/include/python2.7 \/usr/lib/python2.7/dist-packages/numpy/core/include # Anaconda Python distribution is quite popular. Include path: # Verify anaconda location, sometimes it's in root. ANACONDA_HOME := $(HOME)/anaconda2 PYTHON_INCLUDE := $(ANACONDA_HOME)/include \$(ANACONDA_HOME)/include/python2.7 \$(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include \# Uncomment to use Python 3 (default is Python 2) # PYTHON_LIBRARIES := boost_python3 python3.5m # PYTHON_INCLUDE := /usr/include/python3.5m \ # /usr/lib/python3.5/dist-packages/numpy/core/include# We need to be able to find libpythonX.X.so or .dylib. #PYTHON_LIB := /usr/lib PYTHON_LIB := $(ANACONDA_HOME)/lib# Homebrew installs numpy in a non standard path (keg only) # PYTHON_INCLUDE += $(dir $(shell python -c 'import numpy.core; print(numpy.core.__file__)'))/include # PYTHON_LIB += $(shell brew --prefix numpy)/lib# Uncomment to support layers written in Python (will link against Python libs) # WITH_PYTHON_LAYER := 1# Whatever else you find you need goes here. INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib# If Homebrew is installed at a non standard location (for example your home directory) and you use it for general dependencies # INCLUDE_DIRS += $(shell brew --prefix)/include # LIBRARY_DIRS += $(shell brew --prefix)/lib# Uncomment to use `pkg-config` to specify OpenCV library paths. # (Usually not necessary -- OpenCV libraries are normally installed in one of the above $LIBRARY_DIRS.) # USE_PKG_CONFIG := 1# N.B. both build and distribute dirs are cleared on `make clean` BUILD_DIR := build DISTRIBUTE_DIR := distribute# Uncomment for debugging. Does not work on OSX due to https://github.com/BVLC/caffe/issues/171 # DEBUG := 1# The ID of the GPU that 'make runtest' will use to run unit tests. TEST_GPUID := 0# enable pretty build (comment to see full commands) Q ?= @
注意这里我并没有加matlab路径,原因是现在不需要,且gcc是4.9版本的.等我需要用matlab接口了,首先需要降级gcc,再将matlab路径放进去,我的matlab路径是:MATLAB_DIR :=/usr/local/MATLAB/R2014a
4.5 编译
make all -j8 make test make runtest
4.6 编译pycaffe(/matcaffe)
make pycaffe #make matcaffe #when you need it
好了,到此为止,caffe的编译工作已基本完成.剩下的就是跑caffe自带的例子了.这一部分以后再研究.
转载于:https://www.cnblogs.com/guanyu-zuike/p/5936245.html
ubuntu14.04下安装cudnn5.1.3,opencv3.0,编译caffe及配置matlab和python接口过程记录相关推荐
- 在win10中安装caffe并配置MATLAB和Python接口(支持GPU加速)
笔记本电脑配置(14年的老机器)CPU i54200 显卡:GTX850m 1.软件准备: vs2013 cuda8.0(官网下载,查看显卡是否支持cuda),cudnn v5.0(支持cuda8.0 ...
- Linux(Ubuntu14.04)下安装Anaconda和Spyder
Linux(Ubuntu14.04)下安装Anaconda是为了安装python所需要的各种库以及他们的环境配置. Spyder是使用python的IDE 安装python和pip 一般linux系统 ...
- Ubuntu14.04下安装wineqq国际版和卸载QQ
转载自: http://www.bubuko.com/infodetail-343048.html http://jingyan.baidu.com/article/e9fb46e199d60d752 ...
- Ubuntu14.04下安装vim显示没有可用的软件包vim-gtk
解决问题的原始网址:http://m.blog.csdn.net/blog/zuisuozhe/37600293,本人对原始内容做重编辑,请原作者见谅! 问题:本人在Ubuntu14.04下安装vim ...
- Ubuntu14.04下安装QQ国际版
Ubuntu14.04下安装QQ国际版步骤: 1.下载wine-qqintl:http://www.ubuntukylin.com/application/show.php?lang=cn&i ...
- Ubuntu14.04下安装Samba
Samba简介 在90年代初,UNIX机器之间的网络文件系统可以基于NFS协议,Window机器之间的网络文件系统可以基于CIFS协议(目前的Windows已经内置了NFS支持).Windows和UN ...
- Ubuntu14.04下安装QQ 国际版
在/etc/apt/source.list文件中添加: deb http://packages.linuxdeepin.com/deepin trusty main non-free universe ...
- Ubuntu14.04下安装VMware (for linux)
博主现在知道的,Linux下有VirtualBox和VMware两大虚拟机,前者免费,后者需要注册.而且,前者可以在Ubuntu的软件中心找到或者用?sudo apt-get install virt ...
- Ubuntu14.04下安装eclipse
2019独角兽企业重金招聘Python工程师标准>>> 环境: Ubuntu 14.04 步骤: 1.安装配置JDK,详见 http://my.oschina.net/u/14071 ...
最新文章
- 使用JQuery Autocomplete插件(一)
- 皮一皮:师太请自重...
- 基础才是重中之重~.net中的显式事务与隐式事务
- opencv学习笔记18:canny算子边缘检测原理及其函数使用
- Vue---mock.js 使用
- opencv拖动进度条_OpenCV GUI基本操作,回调函数,进度条,裁剪图像等-阿里云开发者社区...
- weakhashmap_Java WeakHashMap keySet()方法与示例
- angular html页面嵌套,使用AngularJS来实现HTML页面嵌套的方法
- c语言学习-定义并调用函数求两个整数之差的绝对值
- java进阶案例下载_登录案例java实现 ---- Java进阶篇
- 工作量统计系统 python_软件测试工作量统计新方法
- 89c52如何控制ad9833输出正弦波,三角波,方波。
- pip的安装,卸载和换源
- 苹果笔记本什么系统_收集整理:什么笔记本适合安装黑苹果系统!
- 设计一个长方形类。成员变量包括:长度和宽度,成员函数除包括计算周长和计算面积外, 还包括用set方法来设置长方形的长度和宽度,以及用get的方法来获得长方形的长度和宽度 最后,编写一个测试程序来测试所
- ps纯色、渐变填充图层只能是灰色
- 元宵节的记忆——灯笼
- 李炎恢老师XHTML视频教程DIV+CSS教程与课件代码
- 英语 | Day 35、36 x 句句真研每日一句(从句)
- pdf文件转doc文件
热门文章
- html制作圆盘时钟,jquery+html5制作超酷的圆盘时钟表
- 松下a6伺服x4接线图_2021中山东凤松下温控器回收价高同行
- 毕业生当头一棒?忆本科四年,高校毕业生与就业单位基本要求差多少?工作还是考研?
- springmvc 源码分析
- 如何保证对象的唯一性
- Linux系统扩硬盘,Linux系统硬盘扩容
- js map对象遍历_何时使用 Map 来代替变通的 JS 对象
- axios代理跨域 cli4_vuecli 3.0之跨域请求代理配置及axios路径配置 莫小龙
- 清理offset_关于 kafka 日志清理策略的问题
- java webservice ip_通过Web Service实现IP地址查询功能的示例