caffe cpu版 Anaconda3 python 接口安装

安装之前请详细阅读官方的文档

caffer installation

caffer Ubuntu Installation

由于官方的文档给出了各个版本的安装需求和 config 文件的部分参数含义，不够仔细（当然所有的 config 参数含义都在该文件中有解释），这里我单独记录一下自己使用 Anaconda3 编译 caffe cpu 版的完整过程。

环境：

ubuntu 14.04
anaconda3
python3.5
编译版本：纯cpu版

1. 依赖

相关依赖库的安装参见官网给的链接：

caffer Ubuntu Installation

2. 配置

修改配置文件如下：

## 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 *_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 := /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)/opt/anaconda3
# 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 := $(ANACONDA_HOME)/include                 $(ANACONDA_HOME)/include/python3.5m                 $(ANACONDA_HOME)/lib/python3.5/site-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 ?= @

主要修改 Anaconda 路径（68行），python3 支持的 PTYHON_LIBRARIES 和 PYTHON_INCLUDE （74到77行）

编译

项目根目录运行下面指令进行编译（-j 表示开启四个线程编译）：

make pycaffe -j 4

可能会遇到如下问题：

CXX .build_release/src/caffe/proto/caffe.pb.cc
PROTOC (python) src/caffe/proto/caffe.proto
LD -o .build_release/lib/libcaffe.so.1.0.0-rc3
CXX/LD -o python/caffe/_caffe.so python/caffe/_caffe.cpp
/usr/bin/ld: cannot find -lboost_python3
collect2: error: ld returned 1 exit status
make: *** [python/caffe/_caffe.so] 错误 1

因为在配置文件的第 74 行中有 PYTHON_LIBRARIES := boost_python3 ，但是在系统中无法找到 boost_python3.lib 这个库文件。

解决方案如下：

检查是否有如下文件：

ls /usr/lib/x86_64-linux-gnu/libboost_python-py34.so

如果有，说明我们的系统中已经有了这种库文件，只是文件名不同。

cd /usr/lib/x86_64-linux-gnu/
sudo ln -s libboost_python-py34.so libboost_python3.so

重新编译即可通过。

测试

进入 python 解释器环境后，使用下面命令测试是否安装成功。

? /home/david/download/caffe-master >python 
Python 3.5.0 |Anaconda 2.4.0 (64-bit)| (default, Oct 19 2015, 21:57:25) 
[GCC 4.4.7 20120313 (Red Hat 4.4.7-1)] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import caffe

可能会出现下面的错误：

Failed to include caffe_pb2, things might go wrong!
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/david/download/caffe-master/python/caffe/__init__.py", line 4, in <module>
    from .proto.caffe_pb2 import TRAIN, TEST
  File "/home/david/download/caffe-master/python/caffe/proto/caffe_pb2.py", line 7, in <module>
    from google.protobuf import reflection as _reflection
  File "/home/david/opt/anaconda3/lib/python3.5/site-packages/google/protobuf/reflection.py", line 68, in <module>
    from google.protobuf.internal import python_message
  File "/home/david/opt/anaconda3/lib/python3.5/site-packages/google/protobuf/internal/python_message.py", line 848
    except struct.error, e:
                       ^
SyntaxError: invalid syntax

这是因为 protobuf 不支持 python3，解决方案是安装 pip install protobuf-py3, 一个 python3.x 版本的替代包。