安装python caffe过程中遇到的一些问题以及对应的解决方案

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

上述即为在安装pycaffe过程中所踩过的坑！