Mac下Caffe安装

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Mac下Caffe的安装

文章作者：Tyan
博客：noahsnail.com  |  CSDN  |  简书

1. 安装依赖

  • 安装CUDA

下载地址：https://developer.nvidia.com/cuda-toolkit-archive，本文采用的是CUDA 7.5版本。下载安装之后，需要配置环境变量，编辑/etc/profile'，添加PATH=$PATH:/Developer/NVIDIA/CUDA-7.5/bin`。

  • 安装其它的依赖

通过Homebrew安装所需要的其它依赖，其它依赖有gflags，snappy，glog，hdf5，lmdb ，opencv3，boost（包括python版本），leveldb ，protobuf（包括python版本），webp（运行mnist数据集会用到）。命令如下：

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# 安装软件
$ brew install software

# 创建软件链接，有的需要，例如openblas，protobuf，opencv3，opencv3需要--force
$ brew link software --force

2. 安装caffe

在Github上下载caffe源码，地址为：https://github.com/BVLC/caffe，下载后在caffe根目录创建build文件夹，将Makefile.config.example文件名改为Makefile.config，修改Makefile.config文件，修改如下：

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将
# CPU_ONLY := 1
改为
CPU_ONLY := 1

将
# USE_OPENCV := 0
改为
USE_OPENCV := 1

将
# OPENCV_VERSION := 3
改为
OPENCV_VERSION := 3


将下面两行
# BLAS_INCLUDE := /path/to/your/blas
# BLAS_LIB := /path/to/your/blas

改为：
BLAS_INCLUDE := /System/Library/Frameworks/Accelerate.framework/Versions/Current/Frameworks/vecLib.framework/Versions/Current/Headers
BLAS_LIB := /System/Library/Frameworks/Accelerate.framework/Versions/Current/Frameworks/vecLib.framework/Versions/Current

如果是OpenBLAS，则改为：

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将
BLAS := atlas
改为
BLAS := open

执行make -j，看到下面的内容说明安装caffe成功。

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CXX/LD -o .build_release/tools/caffe.bin
CXX/LD -o .build_release/tools/compute_image_mean.bin
CXX/LD -o .build_release/tools/convert_imageset.bin
CXX/LD -o .build_release/tools/device_query.bin
CXX/LD -o .build_release/tools/extract_features.bin
CXX/LD -o .build_release/tools/finetune_net.bin
CXX/LD -o .build_release/tools/net_speed_benchmark.bin
CXX/LD -o .build_release/tools/test_net.bin
CXX/LD -o .build_release/tools/train_net.bin
CXX/LD -o .build_release/tools/upgrade_net_proto_binary.bin
CXX/LD -o .build_release/tools/upgrade_net_proto_text.bin
CXX/LD -o .build_release/tools/upgrade_solver_proto_text.bin
CXX/LD -o .build_release/examples/cifar10/convert_cifar_data.bin
clang: warning: argument unused during compilation: '-pthread'
clang: warning: argument unused during compilation: '-pthread'
clang: warning: argument unused during compilation: '-pthread'
clang: warning: argument unused during compilation: '-pthread'
clang: warning: argument unused during compilation: '-pthread'
clang: warning: argument unused during compilation: '-pthread'
clang: warning: argument unused during compilation: '-pthread'
clang: warning: argument unused during compilation: '-pthread'
CXX/LD -o .build_release/examples/cpp_classification/classification.bin
clang: warning: argument unused during compilation: '-pthread'
clang: warning: argument unused during compilation: '-pthread'
clang: warning: argument unused during compilation: '-pthread'
clang: warning: argument unused during compilation: '-pthread'
clang: warning: argument unused during compilation: '-pthread'
CXX/LD -o .build_release/examples/mnist/convert_mnist_data.bin
clang: warning: argument unused during compilation: '-pthread'
CXX/LD -o .build_release/examples/siamese/convert_mnist_siamese_data.bin
clangclang: : warningwarning: : argument unused during compilation: '-pthread'argument unused during compilation: '-pthread'

整个Makefile.config文件：

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## 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 := 1
# 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 := /System/Library/Frameworks/Accelerate.framework/Versions/Current/Frameworks/vecLib.framework/Versions/Current/Headers
BLAS_LIB := /System/Library/Frameworks/Accelerate.framework/Versions/Current/Frameworks/vecLib.framework/Versions/Current

# 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)/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

# N.B. both build and distribute dirs are cleared on `make clean`
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 ?= @

3. 安装pycaffe

安装pycaffe之前需要安装numpy等，获取numpy路径的命令如下：

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$ python
>>> import numpy as np
>>> np.get_include()
'/usr/local/lib/python2.7/site-packages/numpy/core/include'

修改Makefile.config，修改PYTHON_INCLUDE，改为自己的python地址及numpy地址：

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

然后运行：

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$ make pycaffe

CXX/LD -o python/caffe/_caffe.so python/caffe/_caffe.cpp
In file included from python/caffe/_caffe.cpp:17:
In file included from ./include/caffe/caffe.hpp:12:
./include/caffe/net.hpp:42:5: warning: unused typedef 'INVALID_REQUESTED_LOG_SEVERITY' [-Wunused-local-typedef]
    LOG_EVERY_N(WARNING, 1000) << "DEPRECATED: ForwardPrefilled() "
    ^
/usr/local/include/glog/logging.h:917:30: note: expanded from macro 'LOG_EVERY_N'
                             INVALID_REQUESTED_LOG_SEVERITY);           \
                             ^
1 warning generated.
touch python/caffe/proto/__init__.py
PROTOC (python) src/caffe/proto/caffe.proto

最后，需要将caffe的目录添加到Python path中。修改.bash_profile或.bashrc文件，添加：

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export PYTHONPATH=/yourpath/caffe/python:$PYTHONPATH

在Python中运行import caffe不报错即可。中间报错可能是python环境问题，例如需要升级pip，命令为pip install -U pip，缺少scikit-image，用pip install scikit-image来安装，其它的caffe依赖类似。

如果有收获，可以请我喝杯咖啡！