深度學習之MAC(cpu-only)下利用anaconda安裝caffe

阿新 • • 發佈：2019-01-25

如何在Mac下安裝caffe 在安裝caffe之前，應該瞭解些計算機的基本知識，以及Linux的基本知識，這是因為Linux和Mac的作業系統非常像。比如什麼是Linux,它是怎麼來的？Linux和GNU啥關係？gcc又是啥。。Linux的目錄配置是咋回事，也就是下圖中每個檔案都存啥知道不？vim是啥，咋用？shell指令碼檔案是啥？bash和他啥關係？什麼是系統的環境變數？怎麼設定環境變數？在mac下怎麼通過Homebrew下載軟體？如果這些你都很清楚的話，那麼直接看第二部分的caffe安裝步驟就好。如果你跟我一樣，對這些概念稀裡糊塗，不太明白，那麼建議你在安裝caffe之前，用一到兩天時間補一補這些基本知識，否則你在安裝時候只能是一頭霧水。。。關於Linux的基本知識，可以參考

鳥哥的linux私房菜，寫的非常通俗易懂。我也總結了些對於安裝caffe直接相關的概念，大家可以參考第一部分的關於linux的介紹。一、安裝caffe步驟我的電腦配置如下： MacBook Pro -OS X EI Captian系統-8G記憶體-Intel Iris Graphics 6100 1536 MB顯示卡。由於電腦配置的不是英偉達顯示卡，所以不能使用CUDA加速了，只能安裝個CPU模式玩一玩。下面是安裝的想象步驟。 1.安裝caffe需要的依賴包。 opencv2.4: Anaconda Python 2.7: snappy: leveled: flags:

blog: ship: lmdv: protobuf:
boost: 哈哈，看著很多吧，但是不要怕，下載這些東東，在Mac終端裡，只需要幾個brew指令而已。所以，如果你電腦裡沒有Homebrew,那麼你要先把Homebrew下載下來。然後我們下面要做的，就是將這些依賴包都下載下來，還需要配置些環境變數。
1.我們先下載Anaconda Python 2.7。下載下來的是個Anaconda2-4.2.0-MacOSX-x86_64.sh檔案，我們將這個檔案複製到/usr/local/Cellar下面（之所以這麼做，是因為使用brew指令下載的東東都會預設存到則個路徑，我為了方便，就將所有caffe需要的包都放在這裡，完全個人喜好～）。也就是下圖中帶紅點的檔案。下面我進行Anaconda的安裝。在命令列中輸入下面指令

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bash Anaconda2-4.2.0-MacOSX-x86_64.sh

bash Anaconda2-4.2.0-MacOSX-x86_64.sh

執行完成後會生成下圖中綠色標註的anaconda2檔案。

之後我們設定下環境變數，就是將安裝的ananconda2的bin檔案的路徑新增到PATH中，再將anaconda2的路徑新增到DYLD_FALLBACK_LIBARY_PATH中去，指向下面兩個命令後第一步就完成了（ps：可以使用set指令檢視是否新增成功）。 [html] view plain copy print?

<prename=“code”class=“html”>export PATH=/usr/local/ananconda2/bin:PATH   </li><li class="">export DYLD_FALLBACK_LIBRARY_PATH=/usr/local/Cellar/anaconda2:/usr/local/lib:/usr/lib  </li></ol></div><pre code_snippet_id="1914013" snippet_file_name="blog_20161005_2_5155753" name="code" class="html" style="display: none;"><pre name="code" class="html">export PATH=/usr/local/ananconda2/bin:PATH export DYLD_FALLBACK_LIBRARY_PATH=/usr/local/Cellar/anaconda2:/usr/local/lib:/usr/lib 2.下面進入批量安裝的階段。

安裝snappy,leveled,flags,blog,ship,lmdv,opencv.. [html] view plain copy print?

brew install –fresh -vd snappy leveldb gflags glog szip lmdb homebrew/science/opencv

brew install --fresh -vd snappy leveldb gflags glog szip lmdb homebrew/science/opencv

安裝protobuf以及boost [html] view plain copy print?

brew install –build-from-source –with-python –fresh -vd protobuf
 brew install –build-from-source –fresh -vd boost boost-python

brew install --build-from-source --with-python --fresh -vd protobuf
 brew install --build-from-source --fresh -vd boost boost-python

執行完這些指令，要保證這些檔案都出現在/usr/local/Cellar中。如果缺失，那麼就用brew指令單獨下載。
3.下載caffe原始碼 [html] view plain copy print?

git clone https://github.com/BVLC/caffe.git

git clone https://github.com/BVLC/caffe.git

跟前面一樣，我把下載的caffe資料夾複製到了/usr/local/Cellar路徑下面。 4.下面我們要寫一個Makefile.config檔案，這個檔案用來生成makefile檔案的。在caffe包中給了一個例子，叫做Makefile.config.example，我們就是要根據自己的電腦的情況，重新寫一個Makefile.config，所謂重新寫，也就是在Makefile.config.example的基礎上，刪減些註釋、改改路徑而已。所以就直接複製Makefile.config.example，然後貼上生成Makefile.config檔案，用下面指令可以實現。 [html] view plain copy print?

cd /usr/local/Cellar/caffe
cp Makefile.config.example Makefile.config

cd /usr/local/Cellar/caffe
cp Makefile.config.example Makefile.config

5.編譯安裝caffe要用到我們前幾步下載的依賴包，那麼每個電腦的情況不一樣，這些依賴包的路徑也就不一樣。所以我們要讓caffe找到咱們自己下載的那些依賴包。那麼我們怎麼告訴caffe呢？這就是靠Makefile.config檔案啦，系統會根據這個檔案生成Makefile檔案，然後當我們執行make指令時，系統就會安裝Makefile裡面的步驟執行編譯安裝動作。所以，我們要進入Makefile.config資料夾，按照下面修改： [html] view plain copy print?

<spanstyle=“font-size:18px;”>
MacBook-Pro:caffe wei vim Makefile.config   </li><li class="alt">  </li><li class=""># NOTE: this is required only if you will compile the python interface.  </li><li class="alt"># We need to be able to find Python.h and numpy/arrayobject.h.  </li><li class="">PYTHON_INCLUDE := /usr/include/python2.7 \&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;nbsp; </li><li class="alt">                /usr/lib/python2.7/dist-packages/numpy/core/include  </li><li class=""># Anaconda Python distribution is quite popular. Include path:  </li><li class="alt"># Verify anaconda location, sometimes it's in root.  </li><li class="">  <span style="color:#ff0000;">ANACONDA_HOME := /usr/local/Cellar/anaconda2  </li><li class="alt">  PYTHON_INCLUDE := (ANACONDA_HOME)/include \
(ANACONDA_HOME)/include/python2.7 \&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;nbsp; </li><li class="alt">                  (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.
<spanstyle=“color:#ff0000;”>#PYTHON_LIB := /usr/lib
PYTHON_LIB := (ANACONDA_HOME)/lib  </li><li class="alt"></span>  </li><li class=""># Homebrew installs numpy in a non standard path (keg only)  </li><li class="alt"># PYTHON_INCLUDE += (dir (shell python -c 'import numpy.core; print(numpy.core.__file__)'))/include  </li><li class=""># 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.
<spanstyle=“color:#ff0000;”>INCLUDE_DIRS := (PYTHON_INCLUDE) /usr/local/include  </li><li class="alt">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  </li><li class="alt"># 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
# 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 ?= @

<span style=”font-size:18px;”> 

MacBook-Pro:caffe wei$ vim Makefile.config

# 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 := /usr/local/Cellar/anaconda2 PYTHON_INCLUDE := (ANACONDAHOME)/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/includeLIBRARYDIRS:=(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 ?= @ 要特別注意上面紅色標註的路徑，這是些路徑就只想了我們自己下載的那些工具包,直接影響成敗啊，其實主要是指向了anaconda
更改完成後，儲存退出（先按esc，在輸入冒號：，在輸入wq ‘esc’+’:’+’wq’) 6.然後就是make啦，讓電腦自動編譯安裝吧 [html] view plain copy print?

make all

make all

這步應該沒啥問題。 7.下一步我們要安裝caffe的python介面，也就是要編譯下pycaffe。執行下面指令： [html] view plain copy print?

for req in (cat python/requirements.txt); do pip install req; done
make pycaffe
make distribute

for req in $(cat python/requirements.txt); do pip install $req; done
make pycaffe
make distribute

8.設定環境變數PYTHONPATH。執行下面指令 [html] view plain copy print?

export PYTHONPATH=/usr/local/Cellar/caffe/python

export PYTHONPATH=/usr/local/Cellar/caffe/python

9.進入python看一看～ [html] view plain copy print?

cd /usr/local/Cellar/caffe/python

cd /usr/local/Cellar/caffe/python

[html] view plain copy print?

python

python

應該顯示如下資訊： [html] view plain copy print?

Python 2.7.12 |Anaconda 4.2.0 (x86_64)| (default, Jul 2 2016, 17:43:17)
[GCC 4.2.1 (Based on Apple Inc. build 5658) (LLVM build 2336.11.00)] on darwin
Type “help”, “copyright”, “credits” or “license” for more information.
Anaconda is brought to you by Continuum Analytics.
Please check out: http://continuum.io/thanks and https://anaconda.org

Python 2.7.12 |Anaconda 4.2.0 (x86_64)| (default, Jul  2 2016, 17:43:17) 
[GCC 4.2.1 (Based on Apple Inc. build 5658) (LLVM build 2336.11.00)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
Anaconda is brought to you by Continuum Analytics.
Please check out: http://continuum.io/thanks and https://anaconda.org

如果顯示這些，那就說明成功啦。我們就可以跑一個例子看看啦。 10.執行MNIST例子。執行這個例子，我們要要下載資料集啊，執行下面指令 [html] view plain copy print?

cd /usr/local/Cellar/caffe

cd /usr/local/Cellar/caffe

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./data/mnist/get_mnist.sh
./examples/mnist/create_mnist.sh

./data/mnist/get_mnist.sh
./examples/mnist/create_mnist.sh

ps,執行上面兩條指令，需要mac電腦裡有wget ，如果沒有就會報錯，說找不到這個指令，我們可以brew下載 [html] view plain copy print?

<spanstyle=“color:#ff0000;”>brew install wget

<span style="color:#ff0000;">brew install wget</span>

下載完成後，如果成功了，會在/usr/local/Cellar/caffe/examples/mnist下生成兩個資料夾，下圖用紅點標註了，這是資料生成的lmdb資料集。

ps:當喔執行

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./examples/mnist/create_mnist.sh

./examples/mnist/create_mnist.sh

指令時，出了點問題，提示我找不到hdf5開頭的一個動態連結庫。安裝相關說明，hdf5是包含在anaconda裡面的，而且我在anaconda的lib中也發現了hdf5的動態連結庫，如下圖：

但是不知道為什麼找不到，所以我又用brew下載了一個hdf5，指令如下： [html] view plain copy print?

brew install hdf5

brew install hdf5

然後將anaconda資料夾lib中hdf5開頭的連結庫都貼上到下面hdf5資料夾中的lib裡面。

這樣做之後，就沒問題了。希望小夥伴不要遇到這個問題。 11.起飛前最後準備。修改成CPU模式。通過vim進入./examples/mnist/lenet_solver.prototxt。 然後將solver_mode改成CPU模式[html] view plain copy print?

<spanstyle=“font-size:18px;”>solver_mode: CPU

<span style="font-size:18px;">solver_mode: CPU</span>

然後，可以飛起來了 [html] view plain copy print?

cd /usr/local/Cellar/caffe/
./examples/mnist/train_lenet.sh

cd /usr/local/Cellar/caffe/
./examples/mnist/train_lenet.sh

12.執行結果如下

參考資源： http://www.megastormsystems.com/news/how-to-install-caffe-on-mac-os-x-10-11
http://caffe.berkeleyvision.org/install_osx.html
http://blog.csdn.net/lkj345/article/details/51260811

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