uuntu 14.04のcaffe環境構成(uuntu 14.04+Opencv 2.4.9+cuda 7.0)
Step 1 install opencv 2.4.9 on uuntu Opencv 2.4.9 accoding to Total reference:http://www.cnblogs.com/platero/p/3993877.html http://blog.csdn.net/wingfox117/article/details/46278001 http://blog.csdn.net/xyy19920105/article/details/50815660
reference link:http://stackoverflow.com/questions/28010399/build-opencv-with-cuda-support When meet the question of
Step:
download opencv 2.4.9(normally)Opencv 2.4.9 accoding tohttp://blog.csdn.net/xiaojidan2011/article/details/40153933
if you meet the follwing question like: Other reference:Opencv 3.0 accoding to
just need to run the follwing code: Time consumption:about 30 minutes Step 2 install cuda 7.0
sudo dpkg-i cuda-repo-.deb sudo ap-get udate sudo ap-get install cuda export PATH=/usr/local/cuda-7.0/bin:$PATH
export LD_リブラアルPATH=/usr/local/cuda-70.0/lib 64:LD_リブラアルPATH cd/etc/ld.so.co nf.d vim cuda.com(then adding)usr/local/cuda-70.0/lib 64
Step 3 Boost
sudo appt-get install mpi-default-devをインストールします.mpiライブラリsudo appt-get install libicu-devをインストールします.正規表現をサポートします.UNCODE文字セットsudo appt-get install python-dev.
sudo ap-get install libatlas-base-dev
Step 4 Caffe installing
make all-j 8 make test-j 8 make run test-j 8
when meet the error about:
.build_release/tools/caffe.build_release/tools/caffe:error while loading shared libraries:libcudart.so.7.0:cannot open shared oject file:No such file or directory
export PATH=/usr/local/cuda-70.0/bin:$PATH
export LD_リブラアルPATH=/usr/local/cuda-70.0/lib 64:LD_リブラアルPATH
Step 5 Python&Matlab wrapper
Matlab Wrapper
then comple the
In file includ from./include/caffe/util/device_alternature.hpp:40:0,from./include/caffe/common.hpp:19,from./include/caffe/caffe/blob.hpp:8,from./include/caffe/caffe/hpp:7,from/home/came/caffemate/caffer/premate/mate/mate/premate+cpp:18://include/caffe/util/cudnn.hpp:5:19:fatal error:cudnn.h:No such file or directory
then means that You Shuld link the cuDNNhttp://www.cnblogs.com/platero/p/4118139.html
tar-xzvf cudnn-65-linux-R 11.tgz cd cudnn-65-linux-41 sudo cp lib*/usr/local/cuda/lib 64/sudo cp cudnn.h/usr/local/cuda/include/
then you will see the success results:
When run matlab demo、i get the follwing error:
Invalid MEX-file'/home/ym/caffe-master/matlab/+caffe/prvate/caffe_.mexa 64':libcudart.so.7.0:cannot open shared oject file:No such file or directory
Solved link:http://www.cnblogs.com/smartvessel/archive/2011/01/21/1940868.html Methods:
cd/etc/ld.so.com nf.d sudo vi cuda.com/usr/local/cuda/lib 64(:wq)sudo ldconfig
まとめてみると、主に3つの方法があります.1.lnで必要なsoファイルを/usr/libまたは/libのデフォルトのディレクトリの下にリンクするln-s/where/you/install/lib/*.so/usr/lib sudo ldconfig
2.LD_を修正するリブラアルPATH export LD_リブラアルPATH=/where/you/install/lib:$LD_リブラアルPATHサイドconfig
3.修正/etc/ld.so.com nf、そしてvim/etc/ld.so.com add/where/you/install/lib sudo ldconfigを更新する.
python wrapper
1.revise the Makefile.com
ソロ:
success
matlab configur:
reference link:http://stackoverflow.com/questions/28010399/build-opencv-with-cuda-support When meet the question of
NCVPixelOperations.hpp Download link:NCVPixelOperation s.hpp_http://download.csdn.net/download/znculee/9294885 トレヴィス.Step:
download opencv 2.4.9
unzip opencv-2.4.9
cd opencv-2.4.9
mkdir release
cd release
cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D CUDA_ARCH_BIN=3.2 ..
make
success snapshot:after that、input command:sudo make installThe n how to import on the python cp the cv2.so file which in the ~/opencv-2.4.9/build/lib to and get the success ful reults:if you meet the follwing question like:
Building NVCC (Device) object modules/core/CMakeFiles/cuda_compile.dir/src/cuda/Debug/cuda_compile_generated_gpu_mat.cu.obj
nvcc fatal : Unsupported gpu architecture 'compute_11' revise the command as:cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D CUDA_GENERATION=Kepler ..*(recommand)*https://github.com/jayrambhia/Install-OpenCV just need to run the follwing code:
$ cd Ubuntu
$ chmod +x *
$ ./opencv_latest.shsudo dpkg-i cuda-repo-.deb sudo ap-get udate sudo ap-get install cuda export PATH=/usr/local/cuda-7.0/bin:$PATH
export LD_リブラアルPATH=/usr/local/cuda-70.0/lib 64:LD_リブラアルPATH cd/etc/ld.so.co nf.d vim cuda.com(then adding)usr/local/cuda-70.0/lib 64
Step 3 Boost
sudo appt-get install mpi-default-devをインストールします.mpiライブラリsudo appt-get install libicu-devをインストールします.正規表現をサポートします.UNCODE文字セットsudo appt-get install python-dev.
sudo ap-get install libatlas-base-dev
Step 4 Caffe installing
make all-j 8 make test-j 8 make run test-j 8
when meet the error about:
.build_release/tools/caffe.build_release/tools/caffe:error while loading shared libraries:libcudart.so.7.0:cannot open shared oject file:No such file or directory
need to do:export PATH=/usr/local/cuda-70.0/bin:$PATH
export LD_リブラアルPATH=/usr/local/cuda-70.0/lib 64:LD_リブラアルPATH
success: 
Step 5 Python&Matlab wrapper
Matlab Wrapper
then comple the
python wrapper&matlab wrapper if meet the error:In file includ from./include/caffe/util/device_alternature.hpp:40:0,from./include/caffe/common.hpp:19,from./include/caffe/caffe/blob.hpp:8,from./include/caffe/caffe/hpp:7,from/home/came/caffemate/caffer/premate/mate/mate/premate+cpp:18://include/caffe/util/cudnn.hpp:5:19:fatal error:cudnn.h:No such file or directory
then means that You Shuld link the cuDNNhttp://www.cnblogs.com/platero/p/4118139.html
tar-xzvf cudnn-65-linux-R 11.tgz cd cudnn-65-linux-41 sudo cp lib*/usr/local/cuda/lib 64/sudo cp cudnn.h/usr/local/cuda/include/
then you will see the success results:
When run matlab demo、i get the follwing error:
Invalid MEX-file'/home/ym/caffe-master/matlab/+caffe/prvate/caffe_.mexa 64':libcudart.so.7.0:cannot open shared oject file:No such file or directory
Solved link:http://www.cnblogs.com/smartvessel/archive/2011/01/21/1940868.html Methods:
cd/etc/ld.so.com nf.d sudo vi cuda.com/usr/local/cuda/lib 64(:wq)sudo ldconfig
まとめてみると、主に3つの方法があります.1.lnで必要なsoファイルを/usr/libまたは/libのデフォルトのディレクトリの下にリンクするln-s/where/you/install/lib/*.so/usr/lib sudo ldconfig
2.LD_を修正するリブラアルPATH export LD_リブラアルPATH=/where/you/install/lib:$LD_リブラアルPATHサイドconfig
3.修正/etc/ld.so.com nf、そしてvim/etc/ld.so.com add/where/you/install/lib sudo ldconfigを更新する.
python wrapper
1.revise the Makefile.com
make pycaffe.after copile、export the PATH into the/etc/profile and execute source ~/.bashrc or /etc/profile.cannot find google.protobuf.internal:ソロ:
conda install -c https://conda.anaconda.org/anaconda protobuf
success
matlab configur:
## 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 3
# OPENCV_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
MATLAB_DIR := /usr/local/MATLAB/R2015a
# 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)/anaconda
# 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
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 ?= @## 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 3
# OPENCV_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
MATLAB_DIR := /usr/local/MATLAB/R2015a
# 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)/anaconda
# 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
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 ?= @