Mac OSX (EI Capitan)搭建Caffe环境并配置python接口，,Caffe是一个清晰

Caffe是一个清晰而高效的深度学习框架，其作者是博士毕业于UC Berkeley的贾扬清。Caffe是纯粹的C++/CUDA架构，支持命令行、Python和MATLAB接口；可以在CPU和GPU直接无缝切换。我在MacbookPro（无NVIDIA显卡）上大费周章地配置了Caffe的环境，并花了许多时间配置其python接口。

一、下载Caffe

github上的下载地址：https://github.com/BVLC/caffe
进入到下载后的路径，并复制 Makefile.config.example 重命名为 Makefile.config (我电脑的用户名是cuiqi，注意修改)

git clone https://github.com/BVLC/caffe.gitcd /Users/cuiqi/Downloads/caffe-master && cp Makefile.config.example Makefile.config

二、安装相关依赖

对于需要python接口的情况，需要以下依赖

1. CUDA 
由于我的Mac没有NVIDIA的GPU，所以只能使用CPU_ONLY模式，需要在 Makefile.config 中修改 CPU_ONLY := 1
2. BLAS via ATLAS, MKL, or OpenBLAS.# Basic Linear Algebra Subprograms，基础线性代数程序集3. Boost >= 1.55# Deepdream是用Python接Caffe，因此还需要 boost.python 支持

brew install boost --with-pythonbrew install boost-python

4. OpenCV >= 2.4 including 3.05. protobuf, glog, gflags

brew install protobufbrew install glogbrew install gflags

6. IO libraries hdf5, leveldb, snappy, lmdb

brew install leveldbbrew install lmdb

brew tap homebrew/sciencebrew install homebrew/science/hdf5

# python driver for hdf5

pip install h5py

7. numpy for python

brew install numpy

三、修改Makefile.config中相应的路径

如果要使用Anaconda的python环境可以在Makefile.config中取消相应的注释，我试过这样做，可是在CMAKE的时候并不奏效：

Python:Interpreter : /usr/bin/python2.7 (ver. 2.7.10)Libraries : /usr/lib/libpython2.7.dylib (ver 2.7.10)NumPy : /System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python/numpy/core/include (ver 1.8.0rc1)

　所以我放弃了使用Anaconda，改使用系统自带的python。

PYTHON_INCLUDE := /usr/include/python2.7 

由于我使用了Homebrew安装了numpy，所以我在makefile.config中修改相应的numpy路径

PYTHON_INCLUDE := /usr/include/python2.7 /usr/local/Cellar/numpy/1.11.2/lib/python2.7/site-packages/numpy/core/include/numpy/core/include

我的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 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/local/Cellar/numpy/1.11.2/lib/python2.7/site-packages/numpy/core/include/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/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 := 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 ?= @

四、编译

使用cmake工具，将cmake的sourcecode设为caffe的路径，在caffe目录下建立build文件夹，并将cmake的build路径设为该build的路径，configure，generate。

此时打开终端工具进入build目录下，make。

make allmake testmake runtestmake pycaffe

如果没有出现错误，并全部通过后，此时make告一段落，但是并不能确定可以在python中import。

在终端上：

vi etc/profile

或

sudo vi /etc/profile

进入修改系统的环境变量，将caffe/python/添加到Python系统路径：

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

export PYTHONPATH=/Users/cuiqi/Downloads/caffe-master/python:$PYTHONPATH

终端输入python，确认这个python环境是刚刚在makefile.config中设定的那个，可以which python 确认。由于我没有使用Anaconda，我的是

/usr/local/bin/python ，确认为刚刚在makefile.config中设定的路径。

>>> import caffe

# 可能的错误

　　ImportError: No module named skimage.io

# 解决

pip install scikit-image

参考：https://github.com/rainyear/lolita/issues/10?utm_source=tuicool&utm_medium=referral

Mac OSX (EI Capitan)搭建Caffe环境并配置python接口