## 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 

“CuDNN是NVIDIA专门针对Deep Learning框架设计的一套GPU计算加速库，用于实现高性能的并行计算,在有GPU并且安装CuDNN的情况下可以打开即将注释去掉。” 

# CPU-only switch (uncomment to build without GPU support). 

#CPU_ONLY := 1 

“表示是否用GPU,如果只有CPU这里要打开” 

# uncomment to disable IO dependencies and corresponding data layers 

USE_OPENCV := 1 

“因为要用到OpenCV库所以要打开，下面这两个选项表示是选择Caffe的数据管理第三方库，两者都不打开 Caffe默认用的是LMDB，这两者均是嵌入式数据库管理系统编程库。” 

# 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 

“当需要读取LMDB文件时可以取消注释，默认不打开。” 

# Uncomment if you’re using OpenCV 3 

OPENCV_VERSION := 2.4.10 

“用pkg-config –modversion opencv命令查看opencv版本” 

# 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++ 

“linux系统默认使用g++编译器，OSX则是clang++。” 

# CUDA directory contains bin/ and lib/ directories that we need. 

CUDA_DIR := /usr/local/cuda 

“CUDA的安装目录” 

# 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 

“这些参数需要根据GPU的计算能力来进行设置，6.0以下的版本不支持×_50的计算能力。” 

# BLAS choice: 

# atlas for ATLAS (default) 

# mkl for MKL 

# open for OpenBlas 

BLAS := open 

“如果用的是ATLAS计算库则赋值atlas，MKL计算库则用mkl赋值，OpenBlas则赋值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 := /usr/local/OpenBlas/include 

BLAS_LIB := /usr/local/OpenBlas/lib 

“blas库安装目录” 

# 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 

“如果不是安装在标准路径则要指明” 

# 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 

“matlab安装库的目录” 

# 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 

“python安装目录” 

# 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 

<font color=”green”>python库位置</font> 

# 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 

“所用的GPU的ID编号” 

# enable pretty build (comment to see full commands) 

Q ?= @