ubuntu caffe ssd cpu-only配置

看了caffe官网的安装指导，第一次用的是17.04的系统，结果发现比想象的还要麻烦，各种依赖包存在问题…只好换回16.04系统
都说caffe的安装不是太友好，实践告诉我确实如此
我的显卡不是太好，所以在配好caffe的gpu版后，发现跑mnist没什么提速…于是caffe ssd我就用cpu版来啦
步骤如下，首先安装依赖包，我是根据这个博客安装的依赖包https://www.cnblogs.com/go-better/p/7161006.html，还有其他的一些依赖包是按照caffe官网来的
其次，直接从github上下载caffe的ssd版本 https://github.com/weiliu89/caffe/tree/ssd github上其实已经给了安装指南，但无奈坑还是不少，所以还得写个博客记录一下

## 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 lines after *_35 for compatibility.

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

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)/anaconda2

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 := (PYTHONINCLUDE)/usr/local/include/usr/include/hdf5/serialLIBRARYDIRS:=(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/i386-linux-gnu/hdf5/serial /usr/lib/x86_64-linux-gnu /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

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.

enable pretty build (comment to see full commands)

Q ?= @

然后就：
make
make py
make test
make runtest
四大步骤
之后按照https://www.cnblogs.com/go-better/p/7161006.html这里的方法配好python接口
然后bug就来了…

调bug，很烦
我遇到的bug是没有googleprotobuf
解决方案 http://blog.csdn.net/adamwu1988/article/details/56675221

还遇到了没有setuptools的问题 解决方案http://blog.csdn.net/spring292713/article/details/38780493

其实问题都是出在python上的 caffe倒还好
但还是很坑…
希望接下来顺利吧，我得加油了…