Ubuntu 16.04桌面版安裝Anaconda3+Caffe+CPU

一、安裝Caffe所依賴的安裝包

sudo apt install git
 sudo apt install libprotobuf-dev libleveldb-dev libsnappy-dev libhdf5-serial-dev protobuf-compiler
 sudo apt install --no-install-recommends libboost-all-dev
 sudo apt-get install libatlas-base-dev #blas庫
 sudo apt-get install libgflags-dev libgoogle-glog-dev liblmdb-dev
 git clone https://github.com/BVLC/caffe.git #下載下傳linux版的caffe

           

二、安裝Anaconda

可在清華大學開源軟體鏡像源下載下傳自己所需要的anaconda版本，本次使用的是Anaconda3-4.2.0-Linux-x86_64.sh。在ubuntu的/home/user下運作

wget https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda3-4.2.0-Linux-x86_64.sh #如果沒有，則需要安裝wget
  bash Anaconda3-4.2.0-Linux-x86_64.sh #安裝anaconda,一路yes
           

另開啟一個terminal(ctrl+alt+t),輸入jupyter notebook進行激活，激活後關閉就可以了。接着配置jupyter notebook環境，同樣是在/home/user目錄下

jupyter notebook --generate-config #生成配置檔案
  vim /home/user/.jupyter/jupyter_notebook_config.py 
	  c.NotebookApp.ip = '*'  # 設定所有ip通路
	  c.NotebookApp.open_browser = False  # 禁止自動打開浏覽器
	  c.NotebookApp.notebook_dir = '/home/user/tensorflow'# 設定目錄，存放建立的檔案,其他根據自己的需要自行配置。
  
           

配置區域網路内，其他主機是否需要密碼通路，還是在/home/user下

ipython
In [1]: from notebook.auth import passwd
In [2]: passwd()
Enter password:  #需要密碼就輸入，無密碼通路就直接enter
Verify password:
In [3]: exit()

           

緻此，anaconda配置完成，再配置caffe。還是在/home/user目錄下。

'''
  #這裡conda下載下傳的源預設是國外下載下傳，可能比較慢。可通過配置國内的下載下傳源
  conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
  conda config --set show_channel_urls yes
  #然後再執行下面操作，也可直接用國外的下載下傳源,建議國内源
  '''
  conda install libgcc
  conda install protobuf
  conda install -c menpo opencv3 #安裝opencv3
  cd /home/user
  vim ~/.bashrc
	    export LD_LIBRARY_PATH=/home/user/anaconda3/lib:$LD_LIBRARY_PATH
	    export PYTHONPATH=/home/user/caffe/python:$PYTHONPATH
  source ~/.bashrc
  cd /home/user/caffe #進入caffe目錄
  cp Makefile.config.example Makefile.config
  vim Makefile.config
	  CPU_ONLY := 1 #去掉"#"
	  OPENCV_VERSION := 3
	  #PYTHON_INCLUDE := /usr/include/python2.7 \
                /usr/lib/python2.7/dist-packages/numpy/core/include #引掉
	  ANACONDA_HOME := $(HOME)/anaconda3
	  PYTHON_INCLUDE := $(ANACONDA_HOME)/include \
                $(ANACONDA_HOME)/include/python3.5m \
                $(ANACONDA_HOME)/lib/python3.5/site-packages/numpy/core/include
      PYTHON_LIBRARIES := boost_python-py35 python3.5m  #修改為boost_python-py35,在/usr/lib/x86_64-linux-gnu目錄下檢視是否有libboost_python-py35.so
      #PYTHON_INCLUDE := /usr/include/python3.5m \
                 /usr/lib/python3.5/dist-packages/numpy/core/include
	  #PYTHON_LIB := /usr/lib
	  PYTHON_LIB := $(ANACONDA_HOME)/lib 
	  LINKFLAGS := -Wl,-rpath,$(ANACONDA_HOME)/lib #添加此行
	  INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial/
	  LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu/hdf5/serial/

           

儲存後，進行配置pycaffe.py操作。

make pycaffe #編譯python接口
	#成功後的結果為
	'''
LD -o .build_release/lib/libcaffe.so.1.0.0
CXX/LD -o python/caffe/_caffe.so python/caffe/_caffe.cpp
touch python/caffe/proto/__init__.py
PROTOC (python) src/caffe/proto/caffe.proto
	'''
           

pycaffe編譯完成後，接下來，進入caffe目錄下

make all #如果出錯，執行make clean,更改配置檔案後，再重新執行此操作
	make test
	make runtest
	
           

如果編譯沒有錯誤後，測試過程

python #python環境測試
>>> import caffe as cf
>>> print(cf.__version__)
1.0.0
    jupyter notebook #浏覽器測試
    
           

參考：http://www.yaoingwen.com/ubuntu16-04-anaconda-3-6-caffe/

參考：https://www.jianshu.com/p/5afdb561ce94

參考：https://blog.csdn.net/ch15717502064/article/details/78006351

參考：https://blog.csdn.net/Mrx_Nh/article/details/79888928