Caffe 安装优化版 (CPU anaconda)附Makefile.config

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安装 anaconda

https://www.continuum.io/downloadsbash Anaconda2-4.3.1-Linux-x86_64.sh 

准备工作

sudo apt-get updatesudo apt-get install git vim cmake automakesudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev protobuf-compilersudo apt-get install --no-install-recommends libboost-all-dev#安装BLASsudo apt-get install libatlas-base-dev#安装opencv3.0sudo apt-get install libgstreamer1.0-dev  libgstreamer-plugins-base1.0-devsudo sh dependencies.shcd 3.0sudo sh opencv3_0_0.shpkg-config --modversion opencv

wget https://storage.googleapis.com/google-code-archive-downloads/v2/code.google.com/google-glog/glog-0.3.3.tar.gztar zxvf glog-0.3.3.tar.gz && rm glog-0.3.3.tar.gz./configure  sudo make  sudo make install  sudo apt-get install -y libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libboost-all-dev libhdf5-serial-dev libgflags-dev libgoogle-glog-dev liblmdb-dev protobuf-compiler protobuf-c-compiler

sudo apt-get install -y ipython-notebook pandoc sudo apt-get install -y python-numpy python-scipy python-matplotlib python-sklearn python-skimage python-h5py python-protobuf python-leveldb python-networkx python-nose python-pandas python-gflags Cython ipython

Caffe

下载Caffe

cd ~git clone git://github.com/BVLC/caffe.gitcp Makefile.config.example Makefile.configvim Makefile.config (见下)sudo vim ~/.bashrc＃ 加上以下export PATH="/root/anaconda2/bin:$PATH"export LD_LIBRARY_PATH="/root/anaconda2/lib":$LD_LIBRARY_PATHexport PYTHONPATH="/root/caffe/python":$PYTHONPATHsource ~/.bashrc# sudo make clean (有问题可运行这个重新编译)sudo make allsudo make testsudo make runtestsudo make pycaffe

MNIST 测试

sh data/mnist/get_mnist.shsh data/mnist/get_mnist.sh# 将prototxt文件修改成CPU模式sh examples/mnist/train_lenet.sh

export CPLUS_INCLUDE_PATH=/usr/include/python2.7

libhdf5_hl.so.10与libhdf5.so.10问题

http://www.linuxdiyf.com/linux/22442.html

sudo cp -s /root/anaconda2/lib/libhdf5_hl.so.10.1.0 /usr/lib/libhdf5_hl.so.10sudo cp -s /root/anaconda2/lib/libhdf5_hl.so.10.1.0 /usr/lib/x86_64-linux-gnu/libhdf5_hl.so.10sudo ldconfiglibhdf5.so.10.2.0libhdf5.so.10sudo cp -s /root/anaconda2/lib/libhdf5.so.10.2.0 /usr/lib/libhdf5.so.10sudo cp -s /root/anaconda2/lib/libhdf5.so.10.2.0 /usr/lib/x86_64-linux-gnu/libhdf5.so.10sudo ldconfig

protobuf 问题

pip install protobuf

Makefile.config

## 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 through *_61 lines for compatibility.# For CUDA < 8.0, comment the *_60 and *_61 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_52,code=sm_52 \        -gencode arch=compute_60,code=sm_60 \        -gencode arch=compute_61,code=sm_61 \        -gencode arch=compute_61,code=compute_61# 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 := /root/anaconda2PYTHON_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/libPYTHON_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 /usr/lib/x86_64-linux-gnu/hdf5/serial/includeLIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu/hdf5/serial# 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# NCCL acceleration switch (uncomment to build with NCCL)# https://github.com/NVIDIA/nccl (last tested version: v1.2.3-1+cuda8.0)# USE_NCCL := 1# 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 := 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 ?= @

[1] http://blog.csdn.net/xuhang0910/article/details/50179759
[2] http://blog.csdn.net/u011762313/article/details/47262549