一、系統(tǒng)
本文是基于ubuntu 17進(jìn)行的。?
二、caffe 依賴庫(kù)
進(jìn)入命令界面輸入：
sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev protobuf-compiler
sudo apt-get install --no-install-recommends libboost-all-dev
sudo apt-get install openblas-dev numpy scipy matplotlib lapack-dev freetype-dev libpng-dev openblas-dev
sudo apt-get install libgflags-dev libgoogle-glog-dev liblmdb-dev
安裝過(guò)程中，正常情況下不會(huì)出現(xiàn)問(wèn)題，有小的問(wèn)題，歡迎來(lái)探討。
三、拉取git
sudo apt-get install git
git clone?https://github.com/BVLC/caffe.git
四、安裝python依賴包
1、wget --no-check-certificate?https://bootstrap.pypa.io/ez_setup.py?
python ez_setup.py --insecure
wget?https://bootstrap.pypa.io/get-pip.py
python get-pip.py
2、cd root/lv/caffe/python （這里根據(jù)自己的情況來(lái)定）
執(zhí)行 ? for req in $(cat requirements.txt); do pip install $req; done
然后等著就好啦
五、Makefile的修改
cd root/lv/caffe
cp Makefile.config.example Makefile.config?
vim Makefile.config?
Makefile.config里面有依賴庫(kù)的路徑，及各種編譯配置，如果是沒(méi)有GPU的情況下，可以參照下面的配置文件內(nèi)容:
## 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
BLAS := open
# 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
BLAS_INCLUDE := /usr/include/openblas
# 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)/anaconda
# PYTHON_INCLUDE := $(ANACONDA_HOME)/include \
? ? ? ? ? ? ? ? # $(ANACONDA_HOME)/include/python2.7 \
? ? ? ? ? ? ? ? # $(ANACONDA_HOME)/lib/python2.7/site-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 ?= @
六、編譯caffe
make -j4?
測(cè)試一下編譯結(jié)果?
make test?
make runtest
七、編譯pycaffe
make pycaffe -j4
到此就搞定啦，centos也和這個(gè)過(guò)程類似呢。
