ubuntu14.04 + cuda 7.5 +cudnn v3 +opencv3 配置

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(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 reboot 
3)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_PATH
32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 caffe  
2)安装Atlas

sudo apt-get install libatlas-base-dev 
3)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#





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