ubuntu14.04 Anaconda 的安装使用

    # bash Anaconda2-2.4.1-Linux-x86_64.sh

    export PYTHONPATH=/home/xxx/caffe/python:$PYTHONPATH

 sudo make clean

    
 sudo make pycaffe clean
    
 sudo make test clean
    
 sudo make runtest clean

 ## 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 := 1
    
 # 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
    
   23. # 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++
    
   27. # 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
    
   33. # 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
    
   42. # 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
    
   53. # 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
    
   57. # 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
    
   62. # 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)/anaconda2
    
  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 := /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 := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial/
    
 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 ?= @

 sudo make

    
 sudo make pycaffe 
    
 sudo make test 
    
 sudo make runtest

 python

    
 import caffe

    $ jupyter notebook

 import numpy as np

    
 import matplotlib.pyplot as plt
    
 %matplotlib inline
    
 import caffe
    
 caffe_root='/home/shan/caffe/'
    
 import os,sys
    
 os.chdir(caffe_root)
    
 sys.path.insert(0,caffe_root+'python')
    
 im = caffe.io.load_image('examples/images/cat.jpg')
    
 print im.shape
    
 plt.imshow(im)
    
 plt.axis('off')