下載caffe

下載caffe的原始碼

[fangjin@caffe ~]$ git clone https://github.com/BVLC/caffe.git 

安裝依賴庫

caffe涉及到一些依賴庫，先使用jumbo安裝。

[fangjin@caffe ~]$ jumbo  install pkg-config snappy  opencv hdf5  google-gflags google-glog  leveldb protobuf

這裡為了方便統一將其他依賴庫安裝到/home/users/fangjin/opt目錄下。更合理的做法是為不同的依賴庫建立不同的子目錄。

安裝 openblas

修改環境變數，升級gcc為4.6或以上版本

[fangjin@caffe ~]$ jumbo install gcc46
[fangjin@caffe ~]$ export PATH=${JUMBO_ROOT}/bin:${JUMBO_ROOT}/opt/gcc46/bin:$PATH
[fangjin@caffe ~]$ source ~/.bashrc

下載安裝openblas

[fangjin@caffe ~]$ git clone https://github.com/xianyi/OpenBLAS.git
[fangjin@caffe ~]$ cd OpenBLAS
[fangjin@caffe
 
 ~]$ make CC=gcc FC=gfortran
[fangjin@caffe ~]$ make PREFIX=/home/users/fangjin/opt install

其中/home/users/fangjin/opt要使用完整路徑, 不要使用~/opt這種。

安裝protobuf

jumbo 有現成的protobuf，可不必原始碼安裝。此小節可略過。

[fangjin@caffe ~]$ git clone https://github.com/google/protobuf.git
[fangjin@caffe ~]$ cd protobuf-2.5.0
[fangjin@caffe
 
 ~]$ ./configure --prefix=/home/users/fangjin/opt
[fangjin@caffe ~]$ make
[fangjin@caffe ~]$ make install

安裝boost

在網站下載最新原始碼包，例如boost_1_56_0.tar.gz

[fangjin@caffe ~]$ tar zxvf boost_1_56_0.tar.gz
[fangjin@caffe ~]$ cd boost_1_56_0
[fangjin@caffe ~]$ ./bootstrap.sh  --prefix=/home/users/fangjin/opt #通過執行 ./bootstrap.sh  --help來檢視
[fangjin@caffe ~]$ ./b2 install #檢視help也可在此步驟來指定--prefix

安裝lmdb

[fangjin@caffe ~]$ git clone https://github.com/LMDB/lmdb.git
[fangjin@caffe ~]$ cd lmdb/libraries/liblmdb/
[fangjin@caffe ~]$ make
[fangjin@caffe ~]$ make prefix=/home/users/fangjin/opt install  #從src中Makefile中可以看到有一個prefix變數

安裝python依賴庫

如果需要編譯python介面，需要安裝相關依賴庫。
內網環境無法連線http://pypi.douban.com/，可以參考pip.baidu.com.

#先安裝pip
[fangjin@caffe ~]$ jumbo install python python-pip

將pypi.douban源改成baidu的源。

mkdir -p $HOME/.pip/
echo -e "[global]\nindex-url = http://pip.baidu.com/pypi/simple" >> $HOME/.pip/pip.conf
echo -e "[install]\ntrusted-host = pip.baidu.com" >> $HOME/.pip/pip.conf
echo -e "[easy_install]\nindex-url = http://pip.baidu.com/pypi/simple" >> $HOME/.pydistutils.cfg

注意，這種方法pip search無法使用。
安裝相關依賴。

[fangjin@caffe ~]$ pip install --upgrade pip
[fangjin@caffe ~]$ cd caffe/python
[fangjin@caffe ~]$ for i in $(cat requirements.txt); do pip install "$i" ;done

配置安裝項

將Makefile.config.example複製一份為Makefile.config

[[email protected] ~]$ cp Makefile.config.example Makefile.config

修改Makefile.config中的配置
根據自己的需求來修改，注意的地方有兩個
一個是PYTHON_INCLUDE 的路徑，一個是PYTHON_LIB 的路徑
然後自己新增LOCAL_PATH的路徑。
INCLUDE_DIRS和LIBRARY_DIRS定義用到的庫和標頭檔案。

一個Makefile.config的示例如下

# 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
# 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 := 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 := /home/users/fangjin/.jumbo/include/python2.7 \
                /home/users/fangjin/.jumbo/lib/python2.7/site-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 \
# We need to be able to find libpythonX.X.so or .dylib.
PYTHON_LIB := /home/users/zouxidong/.jumbo/lib/python2.7
# 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 \
        ${JUMBO_ROOT}/include \
         ${JUMBO_ROOT}/opt/gcc46/include \
        /home/users/fangjin/opt/include 
LIBRARY_DIRS := $(PYTHON_LIB) \
        ${JUMBO_ROOT}/lib \
        ${JUMBO_ROOT}/opt/gcc46/lib64 \
       /home/users/fangjin/opt/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
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 ?= @

同時，在.bashrc中需要定義之前安裝的各種依賴庫的bin和lib。

# export PATH=/home/users/fangjin/opt/bin:${JUMBO_ROOT}/bin:${JUMBO_ROOT}/opt/gcc46/bin:$PATH
# export LD_LIBRARY_PATH=/home/users/fangjin/opt/lib:${JUMBO_ROOT}/lib:${JUMBO_ROOT}/opt/gcc46/lib64:${LD_LIBRARY_PATH}

然後

[fangjin@caffe ~]$ source ~/.bashrc

安裝

執行make -j8 編譯caffe，執行成功時會生成libcaffe.so
執行make pycaffe輸出如下內容PROTOC (python) src/caffe/proto/caffe.proto表示安裝成功

測試

如何知道是否正確安裝呢？
編譯後的檔案在caffe/build中。
可以執行build/tools/caffe看是否可以執行。
來利用提供的example做測試。

# 下載資料集
[fangjin@caffe ~]$ sh data/mnist/get_mnist.sh
# 轉換資料集
[fangjin@caffe ~]$ sh examples/mnist/create_mnist.sh
# 開始訓練
[fangjin@caffe ~]$ sh examples/mnist/train_lenet.sh

注意，如果不是使用GPU，可以看看train_lenet.sh中的solver檔案，修改成cpu。

下面測試python的caffe介面是否安裝成功。
可以將caffe介面直接寫入PATH變數。
export PYTHONPATH=/path/to/caffe/python:$PYTHONPATH
也可以直接將caffe/python/caffe複製到/home/users/fangjin/.jumbo/lib/python2.7/site-packages/
然後

[fangjin@caffe ~]$ source ~/.bashrc

1. 特別注意，路徑是caffe/python，而不是caffe/python/caffe，否則numpy會報錯。
2. export新增環境變數之後，即使修改了再次source ~/.bashrc，因為是使用:,前一次的變數值依舊儲存，最簡單的方法是退出終端，重新連線。

測試python介面

[fangjin@caffe ~]$ python
Python 2.7.3 (default, Aug  4 2016, 12:06:54) 
[GCC 3.4.5 20051201 (Red Hat 3.4.5-2)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import caffe
>>>

不報錯，則成功。

但是開發機上安裝基本都會報錯

>>> import caffe
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/users/fangjin/my_workplace/c_workplace/010_learn_caffe/source_code/caffe/python/caffe/__init__.py", line 1, in <module>
    from .pycaffe import Net, SGDSolver, NesterovSolver, AdaGradSolver, RMSPropSolver, AdaDeltaSolver, AdamSolver
  File "/home/users/fangjin/my_workplace/c_workplace/010_learn_caffe/source_code/caffe/python/caffe/pycaffe.py", line 15, in <module>
    import caffe.io
  File "/home/users/fangjin/my_workplace/c_workplace/010_learn_caffe/source_code/caffe/python/caffe/io.py", line 2, in <module>
    import skimage.io
  File "/home/users/fangjin/.jumbo/lib/python2.7/site-packages/skimage/io/__init__.py", line 7, in <module>
    from .manage_plugins import *
  File "/home/users/fangjin/.jumbo/lib/python2.7/site-packages/skimage/io/manage_plugins.py", line 28, in <module>
    from .collection import imread_collection_wrapper
  File "/home/users/fangjin/.jumbo/lib/python2.7/site-packages/skimage/io/collection.py", line 12, in <module>
    from PIL import Image
  File "/home/users/fangjin/.jumbo/lib/python2.7/site-packages/PIL/Image.py", line 67, in <module>
    from PIL import _imaging as core
ImportError: /home/users/fangjin/.jumbo/lib/python2.7/site-packages/PIL/_imaging.so: undefined symbol: TIFFSetWarningHandlerExt

單獨from PIL import Image 也會出錯，所以問題與caffe無關，具體原因經過分析，應該是libtiff庫引起的。舊版本的libtiff庫沒有TIFFSetWarningHandlerExt，所以需要重新安裝一個libtiff庫。

下載地址http://dl.maptools.org/dl/libtiff/，下載tiff-3.8.2.tar.gz這個版本基本夠用。原先的libtiff庫檔案安裝在/usr/include和/usr/lib下，沒有許可權進行刪除，這裡安裝到新路徑下/home/fangjin/opt。

安裝

[fangjin@com download]$ tar zxvf tiff-3.8.2.tar.gz
[fangjin@com download]$ cd tiff-3.8.2
[fangjin@com tiff-3.8.2]$ ./configure --prefix=/home/fangjin/opt/
[fangjin@com tiff-3.8.2]$ make

會報錯

../libtool: eval: line 6176: unexpected EOF while looking for matching `''
../libtool: eval: line 6177: syntax error: unexpected end of file
make[2]: *** [libtiffxx.la] Error 1
make[2]: Leaving directory `/home/data/fangjin/download/tiff-3.8.2/libtiff'
make[1]: *** [all] Error 2
make[1]: Leaving directory `/home/data/fangjin/download/tiff-3.8.2/libtiff'
make: *** [all-recursive] Error 1

按照提示修改libtool檔案，將6176行中的的”$cmd”變數上雙引號，換成單引號即可。
重新

[fangjin@com tiff-3.8.2]$ make; make install

把tiff庫的路徑加入到Makefile.config和PATH路徑中(已經有則不需要重複新增)，重新生成caffe和pycaffe。
再嘗試python介面，應該可以提示執行成功了。