关于系统环境：
- Ubuntu 16.04 LTS
- cuda 8.0
- cudnn 6.5
- Anaconda3
编译pycaffe之前需要配置文件Makefile.config
1 ## Refer to http://caffe.berkeleyvision.org/installation.html 2 # Contributions simplifying and improving our build system are welcome! 3 4 # cuDNN acceleration switch (uncomment to build with cuDNN). 5 USE_CUDNN := 1 6 7 # CPU-only switch (uncomment to build without GPU support). 8 # CPU_ONLY := 1 9 10 # uncomment to disable IO dependencies and corresponding data layers 11 # USE_OPENCV := 0 12 # USE_LEVELDB := 0 13 # USE_LMDB := 0 14 15 # uncomment to allow MDB_NOLOCK when reading LMDB files (only if necessary) 16 # You should not set this flag if you will be reading LMDBs with any 17 # possibility of simultaneous read and write 18 # ALLOW_LMDB_NOLOCK := 1 19 20 # Uncomment if you're using OpenCV 3 21 # OPENCV_VERSION := 3 22 23 # To customize your choice of compiler, uncomment and set the following. 24 # N.B. the default for Linux is g++ and the default for OSX is clang++ 25 # CUSTOM_CXX := g++ 26 27 # CUDA directory contains bin/ and lib/ directories that we need. 28 CUDA_DIR := /usr/local/cuda 29 # On Ubuntu 14.04, if cuda tools are installed via 30 # "sudo apt-get install nvidia-cuda-toolkit" then use this instead: 31 # CUDA_DIR := /usr 32 33 # CUDA architecture setting: going with all of them. 34 # For CUDA < 6.0, comment the *_50 through *_61 lines for compatibility. 35 # For CUDA < 8.0, comment the *_60 and *_61 lines for compatibility. 36 CUDA_ARCH := -gencode arch=compute_20,code=sm_20 \ 37 -gencode arch=compute_20,code=sm_21 \ 38 -gencode arch=compute_30,code=sm_30 \ 39 -gencode arch=compute_35,code=sm_35 \ 40 -gencode arch=compute_50,code=sm_50 \ 41 -gencode arch=compute_52,code=sm_52 \ 42 -gencode arch=compute_60,code=sm_60 \ 43 -gencode arch=compute_61,code=sm_61 \ 44 -gencode arch=compute_61,code=compute_61 45 46 # BLAS choice: 47 # atlas for ATLAS (default) 48 # mkl for MKL 49 # open for OpenBlas 50 BLAS := atlas 51 # Custom (MKL/ATLAS/OpenBLAS) include and lib directories. 52 # Leave commented to accept the defaults for your choice of BLAS 53 # (which should work)! 54 # BLAS_INCLUDE := /path/to/your/blas 55 # BLAS_LIB := /path/to/your/blas 56 57 # Homebrew puts openblas in a directory that is not on the standard search path 58 # BLAS_INCLUDE := $(shell brew --prefix openblas)/include 59 # BLAS_LIB := $(shell brew --prefix openblas)/lib 60 61 # This is required only if you will compile the matlab interface. 62 # MATLAB directory should contain the mex binary in /bin. 63 # MATLAB_DIR := /usr/local 64 # MATLAB_DIR := /Applications/MATLAB_R2012b.app 65 66 # NOTE: this is required only if you will compile the python interface. 67 # We need to be able to find Python.h and numpy/arrayobject.h. 68 # PYTHON_INCLUDE := /usr/include/python2.7 \ 69 # /usr/lib/python2.7/dist-packages/numpy/core/include 70 # Anaconda Python distribution is quite popular. Include path: 71 # Verify anaconda location, sometimes it's in root. 72 ANACONDA_HOME := /home/ipc/anaconda3 73 # PYTHON_INCLUDE := $(ANACONDA_HOME)/include \ 74 # $(ANACONDA_HOME)/include/python3.6m \ 75 # $(ANACONDA_HOME)/lib/python3.6/site-packages/numpy/core/include 76 # 关键点1：根据自己的情况设置好ANACONDA的路径
77 # Uncomment to use Python 3 (default is Python 2) 78 PYTHON_LIBRARIES := boost_python3 python3.6m 79 PYTHON_INCLUDE := $(ANACONDA_HOME)/include $(ANACONDA_HOME)/include/python3.6m $(ANACONDA_HOME)/lib/python3.6/site-packages/numpy/core/include 80 # 关键点2：需要注意其中的版本号，原始文件是3.5的，但是我的anaconda是3.6的，因此如果直接uncomment，就会出现问题，需要根据自己的情况设置好
81 # We need to be able to find libpythonX.X.so or .dylib. 82 # PYTHON_LIB := /usr/lib 83 PYTHON_LIB := $(ANACONDA_HOME)/lib 84 85 # Homebrew installs numpy in a non standard path (keg only) 86 # PYTHON_INCLUDE += $(dir $(shell python -c 'import numpy.core; print(numpy.core.__file__)'))/include 87 # PYTHON_LIB += $(shell brew --prefix numpy)/lib 88 89 # Uncomment to support layers written in Python (will link against Python libs) 90 WITH_PYTHON_LAYER := 1 91 92 # Whatever else you find you need goes here. 93 INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/lib/x86_64-linux-gnu/hdf5/serial/include /usr/local/cuda/include 94 LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu/hdf5/serial /usr/local/cuda/lib64 95 96 # If Homebrew is installed at a non standard location (for example your home directory) and you use it for general dependencies 97 # INCLUDE_DIRS += $(shell brew --prefix)/include 98 # LIBRARY_DIRS += $(shell brew --prefix)/lib 99 100 # NCCL acceleration switch (uncomment to build with NCCL) 101 # https://github.com/NVIDIA/nccl (last tested version: v1.2.3-1+cuda8.0) 102 # USE_NCCL := 1 103 104 # Uncomment to use `pkg-config` to specify OpenCV library paths. 105 # (Usually not necessary -- OpenCV libraries are normally installed in one of the above $LIBRARY_DIRS.) 106 # USE_PKG_CONFIG := 1 107 108 # N.B. both build and distribute dirs are cleared on `make clean` 109 BUILD_DIR := build 110 DISTRIBUTE_DIR := distribute 111 112 # Uncomment for debugging. Does not work on OSX due to https://github.com/BVLC/caffe/issues/171 113 # DEBUG := 1 114 115 # The ID of the GPU that 'make runtest' will use to run unit tests. 116 TEST_GPUID := 0 117 118 # enable pretty build (comment to see full commands) 119 Q ?= @
- 如上方式配置文件Makefile.config（路径问题）
- 可避免Python.h 和 numpy/arrayobject.h文件找不到的问题
- cannot find -lboost_python3的问题（版本问题）（参考 http://blog.csdn.net/u012675539/article/details/51351553）
- 检查是否有文件存在：ls /usr/lib/x86_64-linux-gnu/libboost_python-py35.so
- 建立软链接：sudo ln -s libboost_python-py35.so libboost_python3.so
- libstdc++.so.6: version 'GLIBCXX_3.4.20' not found的问题 (版本问题)
- conda install libgcc（conda不能也无需使用sudo）
- No module named 'google'的问题 （版本问题）
- conda install protobuf
- 以sudo用户（如sudoxxx）进行安装，其他用户（如otherxxx）进行运行
- sudo chown otherxxx caffe（权限问题）
- .bashrc修改环境变量：最后面加入export PYTHONPATH=(你的caffe/python路径，如/home/otherxxx/caffe/python):$PYTHONPATH
- sudo chown otherxxx caffe（权限问题）
上述即为在安装pycaffe过程中所踩过的坑！
