ubuntu14.04 + cuda 7.5 +cudnn v3 +opencv3 配置
来源:互联网 发布:淘宝网运营模式 编辑:程序博客网 时间:2024/04/27 23:59
序
(1)感谢网上小伙伴分享的经验,无论是bug解决办法还是cudnn等资源,让我收益良多,有了写博客分享,互帮互助的想法。
(2)记录自己的安装历程,以备ubuntu再次崩溃。。。
资源链接:
链接: https://pan.baidu.com/s/1o8dmxcu 密码: 4ts4
配置过程
1. Cuda7.5安装
验证系统过程,请参考官方文档。
1)下载cuda7.5,链接在前面以给出。
2)执行以下代码
sudo dpkg -i cuda-repo-<distro>_<version>_<architecture>.deb sudo apt-get update sudo apt-get install cudasudo reboot3)环境配置
64位系统
$export PATH=/usr/local/cuda-7.5/bin:$PATH$ export LD_LIBRARY_PATH=/usr/local/cuda-7.5/lib64:$LD_LIBRARY_PATH32位系统
$export PATH=/usr/local/cuda-7.5/bin:$PATH$export LD_LIBRARY_PATH=/usr/local/cuda-7.5/lib:$LD_LIBRARY_PATH
2. Cudnnv4 安装
1)下载cudnnv4,链接前面以给出,
由于后面要配置fast-rcnn,安装的v4版本。
2)安装过程
tar -zxvf cudnn-7.5-linux-x64-v5.0-ga.tgz cd cuda sudo cp lib/lib* /usr/local/cuda/lib64/ sudo cp include/cudnn.h /usr/local/cuda/include/
更新软连接
cd /usr/local/cuda/lib64/sudo chmod +r libcudnn.so.4.0.4sudo ln -sf libcudnn.so.4.0.4 libcudnn.so.4sudo ln -sf libcudnn.so.4 libcudnn.sohttp://write.blog.csdn.net/postedit?ref=toolbar&ticket=ST-221158-qpbGKJ1CbDUnyRDKnhhT-passport.csdn.netsudo ldconfig
3)环境变量配置
/etc/profile中添加cuda环境变量
PATH=/usr/local/cuda/bin:$PATH export PATH source /etc/profile/etc/ld.so.conf.d/加入文件 cuda.conf
/usr/local/cuda/lib64 sudo ldconfig
3. Opencv3 安装
1))下载opencv3脚本,网上大神写好的,前面已经给出资源地址
2) 进入Install-OpenCV/Ubuntu/3.0
sh sudo ./opencv3_0_0.sh
4 Caffe 安装
for req in $(cat requirements.txt); do pip install $req; done
1)安装caffe以及所需依赖包
下载Caffe安装包,链接前面以及给出。
sudo apt-get install build-essential # basic requirement sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libboost-all-dev libhdf5-serial-dev libgflags-dev libgoogle-glog-dev liblmdb-dev protobuf-compiler #required by caffe2)安装Atlas
sudo apt-get install libatlas-base-dev3)安装Python环境
下载Anaconda, 前面以给出链接。
执行(注意自行修改版本号)
bash Anaconda-4.3.1-Linux-x86_64.s<em>h</em>添加Anaconda Library Path
在/etc/ld.so.conf最后加入以下路径
/home/username/anaconda/lib在~/.bashrc最后添加下边路径
export LD_LIBRARY_PATH="/home/username/anaconda/lib:$LD_LIBRARY_PATH"安装python 依赖库,进入caffe-master/python,执行:
for req in $(cat requirements.txt); do pip install $req; done
5 Caffe 编译
进入caffe-master目录,执行:
cp Makefile.config.example Makefile.config修改其中一些路径,配置文件参考
## 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 OpenBlasBLAS := 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)/anaconda2PYTHON_INCLUDE := $(ANACONDA_HOME)/include \ $(ANACONDA_HOME)/include/python2.7 \ $(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include \LIBRARIES += glog gflags protobuf leveldb snappy \ lmdb boost_system hdf5_hl hdf5 m \ opencv_core opencv_highgui opencv_imgproc opencv_imgcodecs# 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/includeLIBRARY_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 := 1BUILD_DIR := buildDISTRIBUTE_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 ?= @
编译
make all -j8make test make runtest
make pycaffe
注:以上是参考大神的博客以及结合自己配置的过程总结的,配置过程中一定要耐心,细心,用心,在配置中我遇到了各种问题,并不是那么顺利,但是有了前面的经验,
已经有信心去解决错误了。
参考博客:
http://blog.csdn.net/ubunfans/article/details/47724341#
1 0
- ubuntu14.04 + cuda 7.5 +cudnn v3 +opencv3 配置
- caffe+Ubuntu14.04+cuda+cudnn+opencv配置
- caffe配置Ubuntu 15.04+CUDA 7.5+MKL+Opencv3.0+CUDNN
- Ubuntu14.04+Anaconda+Cuda+Cudnn+Caffe环境搭建配置
- Ubuntu14.04+Anaconda+Cuda+Cudnn+Caffe环境搭建配置
- Tensorflow安装教程(Ubuntu14.04+cuda-7.5+cudnn-v4)
- ubuntu14.04+CUDA7.0+cuDNN-v2+OPENCV3.0 caffe环境配置
- 【ubuntu14.04配置caffe】一——双显卡安装NVIDIA驱动以及cuda和cudnn
- Ubuntu16或者Ubuntu14 配置NVIDIA、CUDA以及CUDNN
- ubuntu14.04 caffe cuda7.5 cudnn anaconda2 opencv3 安装
- ubuntu14.04+cuda7.5+opencv3.0+cudnn+caffe
- ubuntu14.04 配置cuda
- ubuntu14.04+cuda-7.5(deb)+cuDNN+openCV+caffe 安装(安装笔记一)
- ubuntu14.04+cuda-7.5(deb)+cuDNN+openCV+caffe 安装(安装笔记二)
- Ubuntu14.04 + NVIDIA8.0 + cuda + cudnn + opencv 3 + matlab
- caffe安装 Ubuntu14.04 cuda 8.0 cudnn 5.1
- ubuntu cuda cudnn配置
- Ubuntu14.04 + cuda 7.5 + caffe 配置
- Linux 脚本安装包和Webmin安装过程
- 用vlc搭建简单流媒体服务器(UDP和TCP方式)
- 话说大数据和云计算之间的区别之处
- 如何升级oracle版本?(11.2.0.1至11.2.0.4)win64 server08
- 设计模式-单例模式
- ubuntu14.04 + cuda 7.5 +cudnn v3 +opencv3 配置
- 机器学习数学原理(5)——广泛拉格朗日乘子法
- 【Hadoop集群搭建1】Hadoop集群的配置
- 学《云计算应用开发实践》总结<一>
- Eclipse默认指向 WebContent目录修改为 webRoot设置说明
- 跨过Nginx上基于uWSGI部署Django项目的坑
- CMake实践二:hello world(v2.0) 第一部分
- 解决网页公告的问题(无需js),一个标签解决一切
- HTML5即将迎来黄金时代 轻应用再成行业焦点