转:http://blog.csdn.net/brightming/article/details/51106629
 

版权声明:本文为博主原创文章,欢迎转载!转载请写明原文链接出处!

这篇文章可参考:http://www.cnblogs.com/cj695/p/4498270.html

下载caffe
拷贝Make.config.example Make.config
修改Make.config 取消注释cpu-only,注释掉cuda相关的

-----------------安装依赖的库------------------------

参考docs/install_yum.md,执行:
yum install protobuf-devel leveldb-devel snappy-devel opencv-devel boost-devel hdf5-devel

实际上,hdf5-devel这个安装会找不到。

但是:yum install gflags-devel glog-devel lmdb-devel这个不成功,找不到。只能手动安装:
# glog
    wget https://google-glog.googlecode.com/files/glog-0.3.3.tar.gz
    tar zxvf glog-0.3.3.tar.gz
    cd glog-0.3.3
    ./configure
    make && make install
连不上 google-glog.googlecode.com
从这里下载:
http://download.csdn.net/download/chenguangxing3/6661667
安装glog。
./configure --preifx=mypath
make
make install

    # gflags
    wget https://github.com/schuhschuh/gflags/archive/master.zip
    unzip master.zip
    cd gflags-master
    mkdir build && cd build
    export CXXFLAGS="-fPIC" && cmake .. && make VERBOSE=1
    make && make install

cmake的时候,提示版本不够,需要2.8.12或以上,我的是2.8.11
升级cmake:https://cmake.org/files/v3.4/cmake-3.4.3.tar.gz
 ./bootstrap
gmake
gmake install

再次安装gflags成功。

    # lmdb
    git clone https://github.com/LMDB/lmdb
    cd lmdb/libraries/liblmdb
    make && make install
安装成功。

安装atlas:
yum install atlas

安装python 开发包:
 yum install python-devel

安装cython: http://cython.org/  下载0.24版的
http://cython.org/release/Cython-0.24.zip
进入解压路径,python setup.py install
耗时3分钟左右。

安装numpy
http://nbtelecom.dl.sourceforge.net/project/numpy/NumPy/1.8.0/numpy-1.8.0.zip
耗时3分钟左右。

------------------------编译安装caffe--------------------------
参考:http://caffe.berkeleyvision.org/installation.html中的Compilation with Make部分。

cp Makefile.config.example Makefile.config
# Adjust Makefile.config (for example, if using Anaconda Python, or if cuDNN is desired)
make all
make test
make runtest

修改:
# 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

为:(因为我的arrayobject.h在另外lib64的路径下)
PYTHON_INCLUDE := /usr/include/python2.7 \
                /usr/lib64/python2.7/site-packages/numpy/core/include

修改:打开CPU_ONLY := 1,并注释掉:USE_CUDNN := 1。因为我的电脑没有gpu相关的东西。

其他的没改动。

报错:
CXX src/caffe/blob.cpp
In file included from ./include/caffe/blob.hpp:8:0,
                 from src/caffe/blob.cpp:4:
./include/caffe/common.hpp:6:26: fatal error: glog/logging.h: No such file or directory
 #include <glog/logging.h>
因为没有装glog,所以再找办法装上先。

安装后继续编译,报错:
CXX src/caffe/blob.cpp
In file included from ./include/caffe/util/math_functions.hpp:11:0,
                 from src/caffe/blob.cpp:7:
./include/caffe/util/mkl_alternate.hpp:11:19: fatal error: cblas.h: No such file or directory
 #include <cblas.h>
没有装cblas,参考:http://blog.csdn.net/cleverysm/article/details/1925549,http://www.linuxidc.com/Linux/2015-02/113169.htm
http://www.netlib.org/blas/blast-forum/cblas.tgz
具体:
1. 编译blas,进入BLAS目录执行下面的命令

    gfortran -c  -O3    *.f                # 编译所有的 .f 文件,生成 .o文件 
    ar rv libblas.a      *.o                # 链接所有的 .o文件,生成 .a 文件 

2. 编译cblas,进入CBLAS目录,首先根据自己的操作系统平台,将某个Makefiel.XXX复制为Makefile.in,XXX表示操作系统。如果是Linux,那么就将Makefile.LINUX 复制为 Makefile.in。

    cp ../BLAS/libblas.a  testing  # 将上一步编译成功的 libblas.a 复制到 CBLAS目录下的testing子目录 
    make                                            # 编译所有的目录 

此时会在CBLAS安装目录下的lib目录中产生一个静态链接库文件cblas_LINUX.a,这个库文件和上面得到的libblas.a文件就是我们所需要的。另外还需要的就是CBLAS/include中的cblas.h头文件。将三个文件全部拷贝到,你需调用的应用程序源码目录中。

拷贝到路径下:
cp include/cblas.h /usr/include/
cp lib/cblas_LINUX.a /usr/local/libcblas.a
cp testing/libblas.a /usr/local/lib

再次编译,报错:
src/caffe/layers/hdf5_data_layer.cpp:13:18: fatal error: hdf5.h: No such file or directory
 #include "hdf5.h"
记得上面已经安装了hdf5-devel,怎么会出这个错?查看一下,发现yum这个没找到hdf5-devel,所以也就没有安装。
在docs/installion.md中,建议:but we suggest first installing the [Anaconda](https://store.continuum.io/cshop/anaconda/) Python distribution, which provides most of the necessary packages, as well as the `hdf5` library dependency.

准备安装hdf5:
http://www.hdfgroup.org/ftp/HDF5/current/src/hdf5-1.8.16.tar
解压后:
./configure --prefix=/usr/local/hdf5-1.8.3   ##指定安装路径,否则会默认安装到当前路径下。
make ##4分钟左右
make install

此时,在Makefile.config中增加HDF5_DIRS的路径到搜索路径下:
HDF5_DIRS :=/usr/local/hdf5-1.8.3/
# Whatever else you find you need goes here.
INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include $(HDF5_DIRS)/include
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib $(HDF5_DIRS)/lib

再次编译,报错:
In file included from src/caffe/util/db.cpp:2:0:
./include/caffe/util/db_leveldb.hpp:7:24: fatal error: leveldb/db.h: No such file or directory
 #include "leveldb/db.h"
                        ^
compilation terminated.
缺少了google的kv数据库:leveldb,这个在installation.md中的Optional dependencies也提到了。
从这里下载:https://github.com/google/leveldb
参考:https://techoverflow.net/blog/2012/12/14/compiling-installing-leveldb-on-linux/

解压后,make
因为没有不支持install,所以,要手工将这些include和生成的lib拷贝到需要的地方。
cp --preserve=links out-shared/libleveldb.so* /usr/local/lib  #只拷贝了动态库。
cp -r include/leveldb/ /usr/local/include/

再次编译,报错:
CXX src/caffe/util/upgrade_proto.cpp
AR -o .build_release/lib/libcaffe.a
LD -o .build_release/lib/libcaffe.so.1.0.0-rc3
/usr/bin/ld: cannot find -lcblas
/usr/bin/ld: cannot find -latlas
collect2: error: ld returned 1 exit status
make: *** [.build_release/lib/libcaffe.so.1.0.0-rc3] Error 1

静态库的链接已经完成了,这个动态库缺少了东西。上面安装cblas的时候,发现确实是只产生了静态库,需要增加动态库。
进入到CBLAS目录下,将静态库转为动态库:
gcc -shared lib/cblas_LINUX.a testing/libblas.a -o libcblas.so
cp libcblas.so /usr/local/

再次编译,报错:
CXX src/caffe/util/upgrade_proto.cpp
AR -o .build_release/lib/libcaffe.a
LD -o .build_release/lib/libcaffe.so.1.0.0-rc3
/usr/bin/ld: cannot find -lcblas
/usr/bin/ld: cannot find -latlas
collect2: error: ld returned 1 exit status

mv /usr/local/libcblas.* /usr/local/lib/  #就是把它们转移到 /usr/local/lib下,否则还会报错

再次编译,报错:
LD -o .build_release/lib/libcaffe.so.1.0.0-rc3
/usr/bin/ld: cannot find -latlas
collect2: error: ld returned 1 exit status
make: *** [.build_release/lib/libcaffe.so.1.0.0-rc3] Error 1

之前有安装 yum install atlas
查看:
[root@localhost caffe-master]# ll /usr/lib64/atlas/
total 21304
lrwxrwxrwx. 1 root root       17 Apr  8 15:54 libsatlas.so.3 -> libsatlas.so.3.10
-rwxr-xr-x. 1 root root 10852104 Nov 20 13:43 libsatlas.so.3.10
lrwxrwxrwx. 1 root root       17 Apr  8 15:54 libtatlas.so.3 -> libtatlas.so.3.10
-rwxr-xr-x. 1 root root 10959464 Nov 20 13:43 libtatlas.so.3.10

再安装yum install atlas-devel,查看:
[root@localhost caffe-master]# ll /usr/lib64/atlas/
total 21304
lrwxrwxrwx. 1 root root       17 Apr  9 14:03 libsatlas.so -> libsatlas.so.3.10
lrwxrwxrwx. 1 root root       17 Apr  8 15:54 libsatlas.so.3 -> libsatlas.so.3.10
-rwxr-xr-x. 1 root root 10852104 Nov 20 13:43 libsatlas.so.3.10
lrwxrwxrwx. 1 root root       17 Apr  9 14:03 libtatlas.so -> libtatlas.so.3.10
lrwxrwxrwx. 1 root root       17 Apr  8 15:54 libtatlas.so.3 -> libtatlas.so.3.10
-rwxr-xr-x. 1 root root 10959464 Nov 20 13:43 libtatlas.so.3.10

参考:http://blog.sina.com.cn/s/blog_4c4668bb01013gsv.html
发现里面有说到:
在 3.10.0 的 ATLAS 中没有了 --with-netlib-lapack指定lapack_LINUX.a 只需要 --with-netlib-lapack-tarfile,给出下载的包就行,不需要自己在去编译 LAPACK了。但是最后生成的 库文件也给整合了,不是上面的6个,而是两个 
libsatals.so libtatlas.so, 去 BUILD/lib 里面查看 Makefile, 可以看到确实被整合了的。为了依其上的软件能更通用,又不想自己去改Makefile的内容,就用老版本的组合了。

于是,我建立一个软链接:
ln -s /usr/lib64/atlas/libsatlas.so /usr/lib64/libatlas.so
(如果我建立在atlas下,即ln -s /usr/lib64/atlas/libsatlas.so /usr/lib64/atlas/libatlas.so  还是找不到,就把它提到外面来了)

再次编译,这次ok了。
[root@localhost caffe-master]# make all
LD -o .build_release/lib/libcaffe.so.1.0.0-rc3
CXX tools/caffe.cpp
CXX/LD -o .build_release/tools/caffe.bin
CXX tools/compute_image_mean.cpp
CXX/LD -o .build_release/tools/compute_image_mean.bin
CXX tools/convert_imageset.cpp
CXX/LD -o .build_release/tools/convert_imageset.bin
CXX tools/device_query.cpp
CXX/LD -o .build_release/tools/device_query.bin
CXX tools/extract_features.cpp
CXX/LD -o .build_release/tools/extract_features.bin
CXX tools/finetune_net.cpp
CXX/LD -o .build_release/tools/finetune_net.bin
CXX tools/net_speed_benchmark.cpp
CXX/LD -o .build_release/tools/net_speed_benchmark.bin
CXX tools/test_net.cpp
CXX/LD -o .build_release/tools/test_net.bin
CXX tools/train_net.cpp
CXX/LD -o .build_release/tools/train_net.bin
CXX tools/upgrade_net_proto_binary.cpp
CXX/LD -o .build_release/tools/upgrade_net_proto_binary.bin
CXX tools/upgrade_net_proto_text.cpp
CXX/LD -o .build_release/tools/upgrade_net_proto_text.bin
CXX tools/upgrade_solver_proto_text.cpp
CXX/LD -o .build_release/tools/upgrade_solver_proto_text.bin
CXX examples/cifar10/convert_cifar_data.cpp
CXX/LD -o .build_release/examples/cifar10/convert_cifar_data.bin
CXX examples/cpp_classification/classification.cpp
CXX/LD -o .build_release/examples/cpp_classification/classification.bin
CXX examples/mnist/convert_mnist_data.cpp
CXX/LD -o .build_release/examples/mnist/convert_mnist_data.bin
CXX examples/siamese/convert_mnist_siamese_data.cpp
CXX/LD -o .build_release/examples/siamese/convert_mnist_siamese_data.bin
[root@localhost caffe-master]# 

接着是make test,没有问题,花费5分钟左右。
接着:make runtest,报错:
[root@localhost caffe-master]# make runtest
.build_release/tools/caffe
.build_release/tools/caffe: error while loading shared libraries: libglog.so.0: cannot open shared object file: No such file or directory
make: *** [runtest] Error 127

但是在/usr/local/lib下有阿?
[root@localhost glog-0.3.3]# ll /usr/local/lib
total 5532
drwxr-xr-x. 3 root root     19 Apr  8 16:32 cmake
-rwxr-xr-x. 1 root root 130336 Mar 25 10:59 default.sfx
-rw-r--r--. 1 root root 792216 Apr  8 17:17 libblas.a
-rw-r--r--. 1 root root 387232 Apr  8 17:16 libcblas.a
-rwxr-xr-x. 1 root root   7691 Apr  9 11:39 libcblas.so
-rw-r--r--. 1 root root 628106 Apr  8 16:31 libgflags.a
-rw-r--r--. 1 root root 627712 Apr  8 16:31 libgflags_nothreads.a
-rw-r--r--. 1 root root 352318 Apr  8 16:59 libglog.a
-rwxr-xr-x. 1 root root    958 Apr  8 16:59 libglog.la
lrwxrwxrwx. 1 root root     16 Apr  8 16:59 libglog.so -> libglog.so.0.0.0
lrwxrwxrwx. 1 root root     16 Apr  8 16:59 libglog.so.0 -> libglog.so.0.0.0
-rwxr-xr-x. 1 root root 524192 Apr  8 16:59 libglog.so.0.0.0
-rwxr-xr-x. 3 root root 413462 Apr  9 11:26 libleveldb.so
-rwxr-xr-x. 3 root root 413462 Apr  9 11:26 libleveldb.so.1
-rwxr-xr-x. 3 root root 413462 Apr  9 11:26 libleveldb.so.1.18
-rw-r--r--. 1 root root 644748 Apr  8 16:33 liblmdb.a
-rwxr-xr-x. 1 root root 304783 Apr  8 16:33 liblmdb.so
drwxr-xr-x. 2 root root     23 Apr  8 16:59 pkgconfig

临时解决方法:
export LD_LIBRARY_PATH=/usr/local/lib/
继续make runtest,报错:
[root@localhost caffe-master]# make runtest
.build_release/tools/caffe
.build_release/tools/caffe: error while loading shared libraries: libhdf5_hl.so.10: cannot open shared object file: No such file or directory
make: *** [runtest] Error 127

再来:export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/usr/local/hdf5-1.8.3/lib
这次ok了:
[ RUN      ] NeuronLayerTest/0.TestExpLayer
[       OK ] NeuronLayerTest/0.TestExpLayer (0 ms)
[ RUN      ] NeuronLayerTest/0.TestExpGradientBase2Shift1
[       OK ] NeuronLayerTest/0.TestExpGradientBase2Shift1 (1 ms)
[ RUN      ] NeuronLayerTest/0.TestLogLayerBase2
[       OK ] NeuronLayerTest/0.TestLogLayerBase2 (0 ms)
[ RUN      ] NeuronLayerTest/0.TestLogGradientBase2Shift1Scale3
[       OK ] NeuronLayerTest/0.TestLogGradientBase2Shift1Scale3 (2 ms)
[----------] 48 tests from NeuronLayerTest/0 (175 ms total)

[----------] Global test environment tear-down
[==========] 1050 tests from 146 test cases ran. (34229 ms total)
[  PASSED  ] 1050 tests.
但这个不是好的解决方法,我得永久修改这个链接路径才行。
方法:
查看 /etc/ld.so.conf
发现引用/etc/ld.so.conf.d/下的所有conf结尾的文件,进入里面
可以看到那个atlas的内容就一句话,指明了lib的路径:/usr/lib64/atlas
新建一个conf文件:/etc/ld.so.conf.d/glog.conf,里面写:/usr/local/lib
再新建一个conf文件:/etc/ld.so.conf.d/hdf5.conf,里面写:/usr/local/hdf5-1.8.3/lib
最后执行:
/sbin/ldconfig -v

这样,就不用再去搞那个LD_LIBRARY_PATH了。

重新执行一次完整流程:
make clean
make all  #3分钟
make test #4分钟
make runtest #1分钟
make pycaffe #40秒

编译python的包:
[root@localhost caffe-master]# make pycaffe
CXX/LD -o python/caffe/_caffe.so python/caffe/_caffe.cpp
touch python/caffe/proto/__init__.py
PROTOC (python) src/caffe/proto/caffe.proto
[root@localhost caffe-master]# 

编译好了python包后,要把这个模块加入到python的路径下:(参考安装说明:http://caffe.berkeleyvision.org/installation.html python部分)
export PYTHONPATH=/home/zzz/OpenSource/caffe-master/python:$PYTHONPATH
编辑/etc/profile,增加:
export PYTHONPATH=$PYTHONPATH:/home/zzz/OpenSource/caffe-master/python/

然后打开python,导入caffe:
[root@localhost caffe-master]# python
Python 2.7.5 (default, Nov 20 2015, 02:00:19) 
[GCC 4.8.5 20150623 (Red Hat 4.8.5-4)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import caffe
/home/zzz/OpenSource/caffe-master/python/caffe/pycaffe.py:13: RuntimeWarning: to-Python converter for boost::shared_ptr<caffe::Net<float> > already registered; second conversion method ignored.
  from ._caffe import Net, SGDSolver, NesterovSolver, AdaGradSolver, \
/home/zzz/OpenSource/caffe-master/python/caffe/pycaffe.py:13: RuntimeWarning: to-Python converter for boost::shared_ptr<caffe::Blob<float> > already registered; second conversion method ignored.
  from ._caffe import Net, SGDSolver, NesterovSolver, AdaGradSolver, \
/home/zzz/OpenSource/caffe-master/python/caffe/pycaffe.py:13: RuntimeWarning: to-Python converter for boost::shared_ptr<caffe::Solver<float> > already registered; second conversion method ignored.
  from ._caffe import Net, SGDSolver, NesterovSolver, AdaGradSolver, \
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/zzz/OpenSource/caffe-master/python/caffe/__init__.py", line 1, in <module>
    from .pycaffe import Net, SGDSolver, NesterovSolver, AdaGradSolver, RMSPropSolver, AdaDeltaSolver, AdamSolver
  File "/home/zzz/OpenSource/caffe-master/python/caffe/pycaffe.py", line 15, in <module>
    import caffe.io
  File "/home/zzz/OpenSource/caffe-master/python/caffe/io.py", line 2, in <module>
    import skimage.io
ImportError: No module named skimage.io
>>> 

报错缺少 skimage.io
下载:https://pypi.python.org/packages/source/s/scikit-image/scikit-image-0.12.3.tar.gz#md5=04ea833383e0b6ad5f65da21292c25e1
解压,进入,
python setup.py install
不成功,提示:
te-packages
Adding scikit-image 0.12.3 to easy-install.pth file
Installing skivi script to /usr/bin

Installed /usr/lib64/python2.7/site-packages/scikit_image-0.12.3-py2.7-linux-x86_64.egg
Processing dependencies for scikit-image==0.12.3
Searching for dask[array]>=0.5.0
Reading https://pypi.python.org/simple/dask/
Best match: dask 0.8.1.macosx-10.5-x86-64
Downloading https://pypi.python.org/packages/any/d/dask/dask-0.8.1.macosx-10.5-x86_64.tar.gz#md5=6271cc3687493136a6b743dc5271ab80
Processing dask-0.8.1.macosx-10.5-x86_64.tar.gz
error: Couldn't find a setup script in /tmp/easy_install-h26472/dask-0.8.1.macosx-10.5-x86_64.tar.gz
[root@localhost scikit-image-0.12.3]# python

在python里,import skimage.io会报:
>>> import skimage.io
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/lib64/python2.7/site-packages/scikit_image-0.12.3-py2.7-linux-x86_64.egg/skimage/io/__init__.py", line 7, in <module>
    from .manage_plugins import *
  File "/usr/lib64/python2.7/site-packages/scikit_image-0.12.3-py2.7-linux-x86_64.egg/skimage/io/manage_plugins.py", line 28, in <module>
    from .collection import imread_collection_wrapper
  File "/usr/lib64/python2.7/site-packages/scikit_image-0.12.3-py2.7-linux-x86_64.egg/skimage/io/collection.py", line 12, in <module>
    from PIL import Image
ImportError: No module named PIL


原来用easy_install 这么方便!这个easy_install 我的系统有。
easy_install Image
会自动搜索依赖。
  File "/usr/lib64/python2.7/distutils/command/build_ext.py", line 339, in run
    self.build_extensions()
  File "setup.py", line 512, in build_extensions
ValueError: jpeg is required unless explicitly disabled using --disable-jpeg, aborting

没有安装成功。


下载:
http://effbot.org/media/downloads/Imaging-1.1.7.tar.gz
解压后,进入目录,执行:
python setup.py install
成功:
running install_scripts
copying build/scripts-2.7/pilconvert.py -> /usr/bin
copying build/scripts-2.7/pildriver.py -> /usr/bin
copying build/scripts-2.7/pilfile.py -> /usr/bin
copying build/scripts-2.7/pilfont.py -> /usr/bin
copying build/scripts-2.7/pilprint.py -> /usr/bin
changing mode of /usr/bin/pilconvert.py to 755
changing mode of /usr/bin/pildriver.py to 755
changing mode of /usr/bin/pilfile.py to 755
changing mode of /usr/bin/pilfont.py to 755
changing mode of /usr/bin/pilprint.py to 755
running install_egg_info
Writing /usr/lib64/python2.7/site-packages/PIL/PIL-1.1.7-py2.7.egg-info
creating /usr/lib64/python2.7/site-packages/PIL.pth
[root@localhost Imaging-1.1.7]# 

再次
>>> import skimage.io
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/lib64/python2.7/site-packages/scikit_image-0.12.3-py2.7-linux-x86_64.egg/skimage/io/__init__.py", line 11, in <module>
    from ._io import *
  File "/usr/lib64/python2.7/site-packages/scikit_image-0.12.3-py2.7-linux-x86_64.egg/skimage/io/_io.py", line 7, in <module>
    from ..color import rgb2grey
  File "/usr/lib64/python2.7/site-packages/scikit_image-0.12.3-py2.7-linux-x86_64.egg/skimage/color/__init__.py", line 1, in <module>
    from .colorconv import (convert_colorspace,
  File "/usr/lib64/python2.7/site-packages/scikit_image-0.12.3-py2.7-linux-x86_64.egg/skimage/color/colorconv.py", line 58, in <module>
    from scipy import linalg
ImportError: No module named scipy

安装:
[root@localhost Downloads]# easy_install scipy
Searching for scipy
Reading https://pypi.python.org/simple/scipy/
Best match: scipy 0.17.0
Downloading https://pypi.python.org/packages/source/s/scipy/scipy-0.17.0.zip#md5=28a4fe29e980804db162524f10873211
Processing scipy-0.17.0.zip
Writing /tmp/easy_install-YgsnC3/scipy-0.17.0/setup.cfg
Running scipy-0.17.0/setup.py -q bdist_egg --dist-dir /tmp/easy_install-YgsnC3/scipy-0.17.0/egg-dist-tmp-wyWVj4
/usr/lib64/python2.7/site-packages/numpy/distutils/system_info.py:1428: UserWarning: 
    Atlas (http://math-atlas.sourceforge.net/) libraries not found.
    Directories to search for the libraries can be specified in the
    numpy/distutils/site.cfg file (section [atlas]) or by setting
    the ATLAS environment variable.
  warnings.warn(AtlasNotFoundError.__doc__)
/usr/lib64/python2.7/site-packages/numpy/distutils/system_info.py:1439: UserWarning: 
    Lapack (http://www.netlib.org/lapack/) libraries not found.
    Directories to search for the libraries can be specified in the
    numpy/distutils/site.cfg file (section [lapack]) or by setting
    the LAPACK environment variable.
  warnings.warn(LapackNotFoundError.__doc__)
/usr/lib64/python2.7/site-packages/numpy/distutils/system_info.py:1442: UserWarning: 
    Lapack (http://www.netlib.org/lapack/) sources not found.
    Directories to search for the sources can be specified in the
    numpy/distutils/site.cfg file (section [lapack_src]) or by setting
    the LAPACK_SRC environment variable.
  warnings.warn(LapackSrcNotFoundError.__doc__)
Running from scipy source directory.
error: no lapack/blas resources found
[root@localhost Downloads]# 
失败!
从网上下载源码:http://ufpr.dl.sourceforge.net/project/scipy/scipy/0.16.1/scipy-0.16.1.tar.gz
python setup.py install
同样报错:
File "/usr/lib64/python2.7/site-packages/numpy/distutils/misc_util.py", line 935, in get_subpackage
    caller_level = caller_level + 1)
  File "/usr/lib64/python2.7/site-packages/numpy/distutils/misc_util.py", line 872, in _get_configuration_from_setup_py
    config = setup_module.configuration(*args)
  File "scipy/linalg/setup.py", line 20, in configuration
    raise NotFoundError('no lapack/blas resources found')
numpy.distutils.system_info.NotFoundError: no lapack/blas resources found
[root@localhost scipy-0.16.1]# 
看来要先解决这两个问题。

反复折腾都没有搞定。。。。
参考:http://blog.sina.com.cn/s/blog_62dfdc740101aoo6.html
重新编译atlas。 16:33~16:39

在等待过程,重新看numpy:
cp site.conf.example site.conf
将site.conf编辑为:
[DEFAULT]
library_dirs = /usr/local/lib
include_dirs = /usr/local/include
src_dirs = /home/gumh/Downloads/BLAS-3.6.0:/home/gumh/Downloads/lapack-3.1.1

[blas_opt]
libraries =f77blas,cblas,atlas

[lapack_opt]
libraries=lapack,f77blas,cblas,atlas

 [atlas]
 library_dirs = /usr/lib64/atlas/
 include_dirs = /usr/include/atlas

[amd]
amd_libs = amd
#
[umfpack]
umfpack_libs = umfpack

[fftw]
libraries = fftw3

然后执行:python setup.py build --fcompiler=gnu95
执行下去了,可以看到中间有在对上面设定的src路径下的代码进行编译。
然后python setup.py install

按照这个site.conf来去build scipy-0.16.1,失败。
重新下载scipy-0.11.0 。https://pypi.python.org/packages/source/s/scipy/scipy-0.11.0.tar.gz#md5=842c81d35fd63579c41a8ca21a2419b9
解压,啥都没改u,阅读了那个INSTALL.txt:
python setup.py install
直接就运行了,中间看到有在编译那个lapack-3.1.1的文件,我在这里并没有指定,应该是上面numpy中指定的被保存起来了。
后面还是挂了:
/usr/bin/gfortran -Wall -Wall -shared build/temp.linux-x86_64-2.7/scipy/integrate/_odepackmodule.o -L/usr/local/lib -L/usr/lib64 -Lbuild/temp.linux-x86_64-2.7 -lodepack -llinpack_lite -lmach -lblas -lpython2.7 -lgfortran -o build/lib.linux-x86_64-2.7/scipy/integrate/_odepack.so
/usr/bin/ld: /usr/local/lib/libblas.a(dcopy.o): relocation R_X86_64_PC32 against undefined symbol `memcpy@@GLIBC_2.14' can not be used when making a shared object; recompile with -fPIC
/usr/bin/ld: final link failed: Bad value
collect2: error: ld returned 1 exit status
/usr/bin/ld: /usr/local/lib/libblas.a(dcopy.o): relocation R_X86_64_PC32 against undefined symbol `memcpy@@GLIBC_2.14' can not be used when making a shared object; recompile with -fPIC
/usr/bin/ld: final link failed: Bad value
collect2: error: ld returned 1 exit status
error: Command "/usr/bin/gfortran -Wall -Wall -shared build/temp.linux-x86_64-2.7/scipy/integrate/_odepackmodule.o -L/usr/local/lib -L/usr/lib64 -Lbuild/temp.linux-x86_64-2.7 -lodepack -llinpack_lite -lmach -lblas -lpython2.7 -lgfortran -o build/lib.linux-x86_64-2.7/scipy/integrate/_odepack.so" failed with exit status 1
[root@localhost scipy-0.11.0]# 

意思是/usr/local/lib/libblas.a这个是静态库,不能用于pic的动态链接。
那我就要编译一个动态库出来。
于是重新进入

    gfortran -c  -O3  -fPIC  *.f                #加上了-fPIC
    gcc -shared *.o -fPIC -o  libblas.so
 cp libblas.so /usr/local/lib/

再次执行 python setup.py install:
这次完成了:
/fftpack/tests/
copying scipy/fftpack/tests/fftw_single_ref.npz -> /usr/lib64/python2.7/site-packages/scipy/fftpack/tests/
copying scipy/fftpack/tests/gen_fftw_ref.py -> /usr/lib64/python2.7/site-packages/scipy/fftpack/tests/
creating /usr/lib64/python2.7/site-packages/scipy/weave/doc
copying scipy/weave/doc/tutorial.txt -> /usr/lib64/python2.7/site-packages/scipy/weave/doc/
copying scipy/weave/doc/tutorial_original.html -> /usr/lib64/python2.7/site-packages/scipy/weave/doc/
running install_egg_info
Writing /usr/lib64/python2.7/site-packages/scipy-0.11.0-py2.7.egg-info
running install_clib
[root@localhost scipy-0.11.0]# 
[root@localhost Downloads]# python
Python 2.7.5 (default, Nov 20 2015, 02:00:19) 
[GCC 4.8.5 20150623 (Red Hat 4.8.5-4)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import scipy
>>> 

ok,安装完成!

回到我们的上一层问题:import skimage.io出错,现在再来:
>>> import skimage.io
>>> 

ok!

继续回到上一层问题:import caffe:
>>> import caffe
4.egg/skimage/_shared/_geometry.py", line 4, in <module>
    from matplotlib import _path, path, transforms
ImportError: No module named matplotlib

还有问题,缺少matplotlib:
用easy_install matplotlib的方式安装。
太慢。
直接下载:https://pypi.python.org/packages/source/m/matplotlib/matplotlib-1.5.1.tar.gz#md5=f51847d8692cb63df64cd0bd0304fd20
解压,进入,执行:
python setup.py build
提示缺少必须的依赖:
                        * The following required packages can not be built:
                        * freetype, png

解决:
yum install freetype-devel

下载libpng源码:http://tenet.dl.sourceforge.net/project/libpng/libpng14/older-releases/1.4.14/libpng-1.4.14.tar.gz
解压,进入,执行:
./configure 
make
make check
make install
可以看到,安装信息:
make[2]: Leaving directory `/home/zzz/Downloads/libpng-1.4.14'
 /usr/bin/mkdir -p '/usr/local/share/man/man3'
 /usr/bin/install -c -m 644 libpng.3 libpngpf.3 '/usr/local/share/man/man3'
 /usr/bin/mkdir -p '/usr/local/share/man/man5'
 /usr/bin/install -c -m 644 png.5 '/usr/local/share/man/man5'
 /usr/bin/mkdir -p '/usr/local/lib/pkgconfig'
 /usr/bin/install -c -m 644 libpng14.pc '/usr/local/lib/pkgconfig'
 /usr/bin/mkdir -p '/usr/local/include/libpng14'
 /usr/bin/install -c -m 644 png.h pngconf.h '/usr/local/include/libpng14'
make  install-data-hook
make[2]: Entering directory `/home/zzz/Downloads/libpng-1.4.14'
cd /usr/local/include; rm -f png.h pngconf.h
cd /usr/local/include; ln -s libpng14/png.h png.h
cd /usr/local/include; ln -s libpng14/pngconf.h \
    pngconf.h
cd /usr/local/lib/pkgconfig; rm -f libpng.pc
cd /usr/local/lib/pkgconfig; ln -s libpng14.pc libpng.pc
make[2]: Leaving directory `/home/zzz/Downloads/libpng-1.4.14'
make[1]: Leaving directory `/home/zzz/Downloads/libpng-1.4.14'
[root@localhost libpng-1.4.14]# 

再次执行matplotlib的编译:
python setup.py build 成功。
python setup.py install 成功。

继续import caffe,出错:
ImportError: No module named google.protobuf.internal
参考:http://blog.csdn.net/littlestream9527/article/details/38734871

从网盘下载 :http://pan.baidu.com/s/1pJlZubT
解压,进入,执行:
./configure
make
make install
ldconfig 

然后进入源码目录的python子目录:
cd python
执行:
python setup.py build 
python setup.py install

执行完后,再次的导入caffe模块:
[root@localhost Downloads]# python
Python 2.7.5 (default, Nov 20 2015, 02:00:19) 
[GCC 4.8.5 20150623 (Red Hat 4.8.5-4)] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import caffe
/home/gumh/OpenSource/caffe-master/python/caffe/pycaffe.py:13: RuntimeWarning: to-Python converter for boost::shared_ptr<caffe::Net<float> > already registered; second conversion method ignored.
  from ._caffe import Net, SGDSolver, NesterovSolver, AdaGradSolver, \
/home/gumh/OpenSource/caffe-master/python/caffe/pycaffe.py:13: RuntimeWarning: to-Python converter for boost::shared_ptr<caffe::Blob<float> > already registered; second conversion method ignored.
  from ._caffe import Net, SGDSolver, NesterovSolver, AdaGradSolver, \
/home/gumh/OpenSource/caffe-master/python/caffe/pycaffe.py:13: RuntimeWarning: to-Python converter for boost::shared_ptr<caffe::Solver<float> > already registered; second conversion method ignored.
  from ._caffe import Net, SGDSolver, NesterovSolver, AdaGradSolver, \
>>> 
成功了。

[转]caffe的配置过程的更多相关文章

  1. ubuntu14.04下安装cudnn5.1.3,opencv3.0,编译caffe及配置matlab和python接口过程记录

    已有条件: ubuntu14.04+cuda7.5+anaconda2(即python2.7)+matlabR2014a 上述已经装好了,开始搭建caffe环境. 1. 装cudnn5.1.3,参照: ...

  2. caffe solver 配置详解

    caffe solver通过协调网络前向推理和反向梯度传播来进行模型优化,并通过权重参数更新来改善网络损失求解最优算法,而solver学习的任务被划分为:监督优化和参数更新,生成损失并计算梯度.caf ...

  3. caffe环境配置2

    参考链接: http://blog.csdn.net/enjoyyl/article/details/47397505 http://blog.csdn.net/baobei0112/article/ ...

  4. Linux LVM逻辑卷配置过程详解

    许多Linux使用者安装操作系统时都会遇到这样的困境:如何精确评估和分配各个硬盘分区的容量,如果当初评估不准确,一旦系统分区不够用时可能不得不备份.删除相关数据,甚至被迫重新规划分区并重装操作系统,以 ...

  5. elasticsearch5.0.0 安装插件及配置过程

    elasticsearch5.0.0 安装插件及配置过程 由于es5.0是里程碑式的更新,所以很多变化的地方,暂时我就插件安装遇到的问题记录一下. 插件安装命令 2.3版本的安装命令 安装Marvel ...

  6. synergy 两台Windows电脑配置过程

    Synergy 介绍 软件作用 Synergy 两台独立电脑,共享一套鼠标和键盘的工具, 软件原理(我自己想的) 保证两台电脑在一个局域网内,可以相互Ping通的电脑(这样才能直接通过TCP连接) 将 ...

  7. 图解MySQL5.5详细安装与配置过程

    MySQL是一个开源的关系型数据库管理系统,原由瑞典MySQL AB公司开发,目前属于Oracle公司旗下.MySQL是目前世界上开源数据库中最受欢迎的产品之一,是应用最为广泛的开源数据库.MySQL ...

  8. tesseract配置过程

    tesseract配置过程: 1. 为了避免配置环境变量,可以先下载一个 tesseract-ocr-setup-3.02.02.exe(tesseract配置文件夹里有),然后安装(假设安装目录为D ...

  9. Sublime Text2配置过程

    今天Sublime Text2不知道为什么突然崩溃了,一直不能运行,没办法只有重装了,重装后按我的用途重新配置了一下,现将配置过程记录下来以备将来不时之需 说明:配置是在windows系统上进行的,其 ...

随机推荐

  1. python文件操作实例

    把目录 E:\ 下面所有 后缀名为 .py 的 文件复制到 E:\PyLearn #coding:utf-8 import os import shutil def getfile(srcDir,ds ...

  2. js闭包,匿名函数概念

    var functionName = function(arg){ //函数体 }; 匿名函数:创建一个函数,并将它赋值给一个变量,这种情况下创建的函数叫做匿名函数,因为function关键字后面没有 ...

  3. rabbitMQ学习(四)

    按照routing key接收信息 发送端: public class EmitLogDirect { private static final String EXCHANGE_NAME = &quo ...

  4. Activity has leaked window that was originally added

    错误: E/WindowManager: android.view.WindowLeaked: Activity com.x.x.x has leaked window com.android.int ...

  5. python基础知识9——模块2——常见内置模块

    内置模块 内置模块是Python自带的功能,在使用内置模块相应的功能时,需要[先导入]再[使用] 1.sys 用于提供对Python解释器相关的操作: sys.argv 命令行参数List,第一个元素 ...

  6. select 嵌套

    1.查询“001”课程比“002”课程成绩高的所有学生的学号:  select a.S# from (select s#,score from SC where C#=’001′) a,(select ...

  7. C#中string在内存中是如何表示的

    不知道你是否有过和我一样的疑问,不同编码的字符串是如何存储在运行时的内存中的呢,计算机在操作string类型的对象时,如何知道这个string是什么编码呢?和文本文件那样有类似BOM的东东在strin ...

  8. [译]Node.js - Event Loop

    介绍 在读这篇博客之前,我强列建议先阅读我的前两篇文章: Getting Started With Node.js Node.js - Modules 在这篇文章中,我们将学习 Node.js 中的事 ...

  9. VFP正则表达式判断是否是手机号码/电子邮件

    正则表达式,可以理解为字符匹配或搜索技术 ,重要的是Pattern属性的写法. *--判断是否是手机号码Function isMobiPhoneLparameters cStroRegExp=Newo ...

  10. PRML

    PRML 学习之 第一章 介绍 Introduction #欢迎共同学习和讨论,由于本文将不断修改,谢绝转载 模式识别问题具有重要且久远的历史.比如,16世纪开普勒发现行星运动定律,又如20世纪出发现 ...