安裝之前請詳細閱讀官方的文檔
caffer installation
caffer Ubuntu Installation
由於官方的文檔給出了各個版本的安裝需求和 config 文件的部分參數含義，不夠仔細（當然所有的 config 參數含義都在該文件中有解釋），這裡我單獨記錄一下自己使用 Anaconda3 編譯 caffe cpu 版的完整過程。
環境：
ubuntu 14.04 anaconda3 python3.5 編譯版本：純cpu版
相關依賴庫的安裝參見官網給的鏈接：
caffer Ubuntu Installation
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 路徑（68行），python3 支持的 PTYHON_LIBRARIES 和 PYTHON_INCLUDE （74到77行）
編譯項目根目錄運行下面指令進行編譯（-j 表示開啟四個線程編譯）：
make pycaffe -j 4
可能會遇到如下問題：
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] 錯誤 1
因為在配置文件的第 74 行中有 PYTHON_LIBRARIES := boost_python3 ，但是在系統中無法找到 boost_python3.lib 這個庫文件。
解決方案如下：
檢查是否有如下文件：
ls /usr/lib/x86_64-linux-gnu/libboost_python-py34.so
如果有，說明我們的系統中已經有了這種庫文件，只是文件名不同。
cd /usr/lib/x86_64-linux-gnu/
sudo ln -s libboost_python-py34.so libboost_python3.so
重新編譯即可通過。
測試進入 python 解釋器環境後，使用下面命令測試是否安裝成功。
? /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
可能會出現下面的錯誤：
Failed to include caffe_pb2, things might go wrong!
Traceback (most recent call last):
File "", line 1, in
File "/home/david/download/caffe-master/python/caffe/__init__.py", line 4, in
from .proto.caffe_pb2 import TRAIN, TEST
File "/home/david/download/caffe-master/python/caffe/proto/caffe_pb2.py", line 7, in
from google.protobuf import reflection as _reflection
File "/home/david/opt/anaconda3/lib/python3.5/site-packages/google/protobuf/reflection.py", line 68, in
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
這是因為 protobuf 不支持 python3，解決方案是安裝 pip install protobuf-py3, 一個 python3.x 版本的替代包。