ubuntu16.04 配置caffe CPU,anaconda2

1.安装依赖库

apt-get install libprotobuf-dev   apt-get install libleveldb-dev   apt-get install libsnappy-dev   apt-get install libopencv-dev   apt-get install libhdf5-serial-dev   apt-get install protobuf-compiler  apt-get install --no-install-recommends libboost-all-dev apt-get install libatlas-base-dev  apt-get install libgflags-dev  apt-get install libgoogle-glog-dev   apt-get install liblmdb-dev  

2.配置python环境

git clone https://github.com/BVLC/caffe.git  cd caffe/pythonsudo gedit requirement.txt删除： leveldb>=0.191protobuf>=2.5.0关闭命令行输入：for req in $(cat requirements.txt); do conda install $req; done  

3.Makefile.config配置（CPU，miniconda2）

设置只使用CPU

# CPU-only switch (uncomment to build without GPU support).  CPU_ONLY := 1

注释掉原python路径，改为anaconda路径

#PYTHON_INCLUDE := /usr/include/python2.7 \    #   /usr/lib/python2.7/dist-packages/numpy/core/include

 ANACONDA_HOME := $(HOME)/miniconda2 PYTHON_INCLUDE := $(ANACONDA_HOME)/include \         $(ANACONDA_HOME)/include/python2.7 \         $(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include

更改python lib路径

#PYTHON_LIB := /usr/lib PYTHON_LIB := $(ANACONDA_HOME)/lib

解开注释

 WITH_PYTHON_LAYER := 1 

16.04路径不同

# Whatever else you find you need goes here.INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib 

更改为：

# Whatever else you find you need goes here.INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu/hdf5/serial

示例Makefile.config文件

## 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 through *_61 lines for compatibility.# For CUDA < 8.0, comment the *_60 and *_61 lines for compatibility.# For CUDA >= 9.0, comment the *_20 and *_21 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 := $(HOME)/miniconda2 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 /usr/include/hdf5/serial LIBRARY_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 ?= @

4.修改Makefile文件
将

NVCCFLAGS +=-ccbin=$(CXX) -Xcompiler-fPIC $(COMMON_FLAGS)

修改为

NVCCFLAGS += -D_FORCE_INLINES -ccbin=$(CXX) -Xcompiler -fPIC $(COMMON_FLAGS)

5.安装

sudo make all -j8sudo make test -j8sudo make runtestsudo make pycaffe

6.添加pycaffe环境

sudo gedit .bashrc（或者sudo gedit ~/.bashrc）

在末尾添加

export PYTHONPATH=/path/to/caffe/python:$PYTHONPATH  

关闭

source .bashrc(或者source ~/bashrc)

7.测试

./data/mnist/get_mnist.sh./examples/mnist/create_mnist.sh./examples/mnist/train_lenet.sh

pythonimport caffe