CAFFE安装笔记【windows和ubuntu】

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CAFFE安装笔记【windows和ubuntu】

第一部分是windows下安装caffe的心得；第二部分是ubuntu下安装caffe的心得：

第一部分：【Win10+VS2017环境】

老版的caffe在BVLC的github上已经找不到，如果要想下载老版caffe可以下载微软的caffe版本：https://github.com/Microsoft/caffe

网上的大多安装caffe教程都是基于老版的caffe。

常规错误参考：https://www.cnblogs.com/cxyxbk/p/5902034.html

win10+VS2017

如果只编译libcaffe项目按照网上的流程，基本可以OK

如果还编译其他项目，可能会出现以下问题，以编译upgrade_net_proto_binary项目为例

一、错误 C2976 “std::array”: 模板参数太少 caffe.managed \caffe-master-micorsoft\windows\caffe.managed\caffelib.cpp 68

类似这种错误，双击进去，将array<array<float>^>^ 中的array改成cli::array

即改成：cli::array<cli::array<float>^>^

参考：https://blog.csdn.net/m0_37287643/article/details/83020441

二、错误 LNK1104 无法打开文件“libboost_date_time-vc140-mt-gd-1_59.lib” upgrade_net_proto_binary \caffe-master-micorsoft\windows\upgrade_net_proto_binary\LINK 1

缺少boost库。注意版本号是1.59

这里有boost安装流程：https://blog.csdn.net/u011054333/article/details/78648294

这里关联boost库： https://www.cnblogs.com/denggelin/p/5769480.html

三、错误 LNK2019 无法解析的外部符号 "__declspec(dllimport) void __cdecl google::InitGoogleLogging(char const *)" ([email protected]@@[email protected])，该符号在函数 main 中被引用 upgrade_net_proto_binary \caffe-master-micorsoft\windows\upgrade_net_proto_binary\upgrade_net_proto_binary.obj 1

没有安装Google GLOG库，这里有https://download.csdn.net/download/colorsky100/10776566下载，预编译版本的下载（实际上这个包同时提供了GLOG和GFLAGS库的包）

说明：glog的预编译包下有三个目录bin、share、static；其中bin中是dll，share是和bin配套的lib，static是不需要dll的完整的lib。如果配的是share对应的glog.lib，则必须配bin，如果用static目录下的glog.lib，那么库目录只需要添加一个static对应的目录

上面的描述是有错误的，库目录只需要配lib所在的路径，如果这个lib是个完全的lib（即static目录下的glog.lib），则编译完直接使用，如果这个lib还需要配dll使用（即share下的glog.lib）。编译正常编译，但是在使用时，要么需要将dll所在目录设成环境变量，要么需要将dll文件（即bin下的glog.dll）拷贝到项目目录下。不论如何，dll目录不需要配置在库目录中，都可以正常编译通过

注意，需要添加debug版本的动静态链接库文件，否则会报错误如下：

错误 LNK2038 检测到“_ITERATOR_DEBUG_LEVEL”的不匹配项: 值“0”不匹配值“2”(upgrade_net_proto_binary.obj 中) upgrade_net_proto_binary \caffe-master-micorsoft\windows\upgrade_net_proto_binary\glog.lib(logging.obj) 1

上述配置完后可能依然有错误，需要在【项目属性页库|C/C++目录|预处理器|预处理器定义】中添加GOOGLE_GLOG_DLL_DECL=宏后解决，参考：https://www.cnblogs.com/21207-iHome/p/9297329.html

四、错误 LNK2001 无法解析的外部符号 "public: __cdecl google::protobuf::internal::LogMessage::LogMessage(enum google::protobuf::LogLevel,char const *,int)" ([email protected]@[email protected]@@QE[email protected]@[email protected]@Z) upgrade_net_proto_binary \caffe-master-micorsoft\windows\upgrade_net_proto_binary\sgd_solver.obj 1

缺少protobuff库。这里有protobuff的下载、编译，比较麻烦。参考：https://blog.csdn.net/hp_cpp/article/details/81561310

编译完，回过来配置caffe的upgrade_net_proto_binary项目，继续添加libprotocd.lib和libprotobufd.lib库目录，依赖项添加libprotocd.lib和libprotobufd.lib

如果出现错误：LNK2038 检测到“RuntimeLibrary”的不匹配项: 值“MTd_StaticDebug”不匹配值“MDd_DynamicDebug”(upgrade_net_proto_binary.obj 中) upgrade_net_proto_binary \caffe-master-micorsoft\windows\upgrade_net_proto_binary\libprotocd.lib(ruby_generator.obj) 1

则在CMAKE配置protobuff不能像帖子https://blog.csdn.net/hp_cpp/article/details/81561310推荐的那样，而是需要将protobuff_BUILD_SHARED_LIBS对应的复选框给勾上，即在protobuff编译完后的debug目录下要有dll文件

安装上面的安装还是会报无法解析外部符号问题，网上说是protobuff版本问题，改为2.5.0版本后还是有问题，又改为2.6.1版本，问题得到解决

需要注意的是：官网下载的2.6.1是win32的，需要改成x64,然后需要做以下修改：

五、错误 LNK2019 无法解析的外部符号 "unsigned int __cdecl google::ParseCommandLineFlags(int *,char * * *,bool)" ([email protected]@@[email protected])，该符号在函数 "void __cdecl caffe::GlobalInit(int *,char * * *)" ([email protected]@@[email protected]) 中被引用 upgrade_net_proto_binary \caffe-master-micorsoft\windows\upgrade_net_proto_binary\common.obj 1

缺少gflags库，在三中提供的预编译包中同时有glog和gflags，正常配置到项目中即可

六、错误 LNK2019 无法解析的外部符号 "public: __cdecl cv::Exception::Exception(int,class std::basic_string<char,struct std::char_traits<char>,class std::allocator<char> > const &,class std::basic_string<char,struct std::char_traits<char>,class std::allocator<char> > const &,class std::basic_string<char,struct std::char_traits<char>,class std::allocator<char> > const &,int)" ([email protected]@@[email protected][email protected][email protected]@[email protected]@[email protected]@[email protected]@[email protected]@[email protected])，该符号在函数 "public: unsigned char * __cdecl cv::Mat::ptr<unsigned char>(int)" ([email protected]@[email protected]@@[email protected]) 中被引用 upgrade_net_proto_binary \caffe-master-micorsoft\windows\upgrade_net_proto_binary\data_transformer.obj 1

这个明显是缺少opencv库，但是非常纠结的是官网提供的opencv2.14版本只提供VC14（VS2015）的预编译版本，然后下载官网的opencv3.4.5版本，这个提供VC15版本。但是配置后还是报无法解析外部符号的问题，配置是没有问题的。

后来转过头直接用opencv2.14.13版本，居然没有问题，需要添加的依赖项为opencv_core2413d.lib;opencv_highgui2413d.lib;opencv_imgproc2413d.lib;

七、错误 LNK2019 无法解析的外部符号 "public: __cdecl leveldb::WriteBatch::~WriteBatch(void)" ([email protected]@@[email protected])，该符号在函数 "int `public: __cdecl caffe::db::LevelDBTransaction::LevelDBTransaction(class leveldb::DB *)'::`1'::dtor$1" ([email protected][email protected]@[email protected]@[email protected]@[email protected]@@[email protected]) 中被引用 upgrade_net_proto_binary \caffe-master-micorsoft\windows\upgrade_net_proto_binary\db.obj 1

错误 LNK2001 无法解析的外部符号 "public: class std::basic_string<char,struct std::char_traits<char>,class std::allocator<char> > __cdecl leveldb::Status::ToString(void)const " ([email protected]@[email protected]@[email protected][email protected]@[email protected]@[email protected]@[email protected]@[email protected]@XZ) upgrade_net_proto_binary \caffe-master-micorsoft\windows\upgrade_net_proto_binary\db_leveldb.obj 1

缺少LevelDB库，在官网https://github.com/google/leveldb/下载好后，用CMAKE-GUI配置总报错 The C++ compiler "D:/Program Files (x86)/Microsoft Visual Studio/2017/Enterprise/VC/Tools/MSVC/14.15.26726/bin/Hostx86/x64/cl.exe" is not able to compile a simple test program.

后来按照官网的指示在cmd中用cmake指令，成功了

官网说明：

Building for Windows
First generate the Visual Studio 2017 project/solution files:

mkdir -p build
cd build
cmake -G "Visual Studio 15" ..
The default default will build for x86. For 64-bit run:

cmake -G "Visual Studio 15 Win64" ..
To compile the Windows solution from the command-line:

devenv /build Debug leveldb.sln
or open leveldb.sln in Visual Studio and build from within.

Please see the CMake documentation and CMakeLists.txt for more advanced usage.

如下图，其中build是自己建的目录

CMAKE后，直接双击leveldb.sln进VS，然后只编译leveldb项目，回过头配置caffe的upgrade_net_proto_binary。搞定

总结：

在upgrade_net_proto_binary项目中，需要的附加库包括：

1.BOOST 2.GLOG 3.PROTOBUFF 4.GFLAGS 5.OPENCV 6.LEVELDB等一系列第三方库

最后的属性配置页如下：

包含目录：

库目录：

依赖项

2019.3.24

++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

第二部分：【Ubuntu16.04环境】

基本安装帖子https://www.cnblogs.com/sunshineatnoon/p/4535329.html操作

1.安装glog库

直接git clone https://github.com/google/glog/

然后进入glog目录:

./autogen.sh && ./configure && make && make install

如果报错：

./autogen.sh: 5: ./autogen.sh: autoreconf: not found

按照帖子https://blog.csdn.net/mybelief321/article/details/9208073操作

apt-get install autoconf
apt-get install automake
apt-get install libtool

　　2019.5.27

2. libhdf5包相关错误：

src/caffe/layers/hdf5_output_layer.cpp:4:18: fatal error: hdf5.h: 没有那个文件或目录
#include "hdf5.h"

在上面的帖子链接中，我没有按照他的步骤安装 libhdf5-serial-dev 包

正常apt install libhdf5-serial-dev。安装后，依然报这个错误，此时按照帖子https://www.cnblogs.com/xiangfeidemengzhu/p/7058391.html操作。

首先查找hdf5.h的位置，终端输入： locate hdf5.h

可以看到在 /usr/include/hdf5/serial/下有，把这个路径添加到Makefile.config 的INCLUDE_DIRS 中，即：

INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial/

继续make all，报错：

AR -o .build_release/lib/libcaffe.a
LD -o .build_release/lib/libcaffe.so.1.0.0
/usr/bin/ld: 找不到 -lhdf5_hl
/usr/bin/ld: 找不到 -lhdf5
collect2: error: ld returned 1 exit status
Makefile:582: recipe for target '.build_release/lib/libcaffe.so.1.0.0' failed
make: *** [.build_release/lib/libcaffe.so.1.0.0] Error 1

这个应该是找不到hdf5的lib文件。其实这个和上面找不到头文件是一个问题，就是apt install libhdf5-serial-dev库的时候安装的路径不在caffe库默认的编译路径下。

所以第一步还是locate

locate libhdf5

然后可以看到有个结果是

/usr/lib/x86_64-linux-gnu/hdf5/serial/libhdf5.so

将这个路径添加到Makefile.config中去，即：

LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu/hdf5/serial/

再make all解决。

3. gflags包的问题：

AR -o .build_release/lib/libcaffe.a
LD -o .build_release/lib/libcaffe.so.1.0.0
/usr/bin/ld: /usr/local/lib/libgflags.a(gflags.cc.o): relocation R_X86_64_32 against `.rodata.str1.1' can not be used when making a shared object; recompile with -fPIC
/usr/local/lib/libgflags.a: 无法添加符号: 错误的值
collect2: error: ld returned 1 exit status
Makefile:572: recipe for target '.build_release/lib/libcaffe.so.1.0.0' failed
make: *** [.build_release/lib/libcaffe.so.1.0.0] Error 1

from：https://github.com/BVLC/caffe/issues/6317 追踪到#6200，#2171，一路看过去

其中在#2171的讨论中，有一层楼说：

just recompile the gflags with CXXFLAGS += -fPIC makes things work

该层回复较多

再回过头看前面的帖子https://blog.csdn.net/mybelief321/article/details/9208073

这个帖子在安装gflags库时明确说了要export 环境变量，即

export CXXFLAGS="-fPIC"

2019.5.29

4. gcc版本问题

[ 89%] Linking CXX executable compute_image_mean
CMakeFiles/compute_image_mean.dir/compute_image_mean.cpp.o：在函数‘std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >* google::MakeCheckOpString<int, int>(int const&, int const&, char const*)’中：
compute_image_mean.cpp:(.text._ZN6google17MakeCheckOpStringIiiEEPNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEERKT_RKT0_PKc[_ZN6google17MakeCheckOpStringIiiEEPNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEERKT_RKT0_PKc]+0x50)：对‘google::base::CheckOpMessageBuilder::NewString[abi:cxx11]()’未定义的引用
CMakeFiles/compute_image_mean.dir/compute_image_mean.cpp.o：在函数‘std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >* google::MakeCheckOpString<unsigned long, int>(unsigned long const&, int const&, char const*)’中：
compute_image_mean.cpp:(.text._ZN6google17MakeCheckOpStringImiEEPNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEERKT_RKT0_PKc[_ZN6google17MakeCheckOpStringImiEEPNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEERKT_RKT0_PKc]+0x50)：对‘google::base::CheckOpMessageBuilder::NewString[abi:cxx11]()’未定义的引用
collect2: error: ld returned 1 exit status
tools/CMakeFiles/compute_image_mean.dir/build.make:133: recipe for target 'tools/compute_image_mean' failed
make[2]: *** [tools/compute_image_mean] Error 1
CMakeFiles/Makefile2:457: recipe for target 'tools/CMakeFiles/compute_image_mean.dir/all' failed
make[1]: *** [tools/CMakeFiles/compute_image_mean.dir/all] Error 2
Makefile:127: recipe for target 'all' failed
make: *** [all] Error 2

这里的本质原因是gcc版本问题，因为前期编译cuda的时候对gcc降低了版本。所以需要将gcc的版本提升到5以上，按照这个帖子的方法进行https://blog.csdn.net/xuezhisdc/article/details/48650015 (虽然这个帖子是降版本）即：

cd /usr/bin
ls gcc*
sudo rm gcc
sudo ln -s gcc-5 gcc
sudo rm g++
sudo ln -s g++-5 g++
# 查看是否连接到5
ls –al gcc g++
gcc --version
g++ --version

完了之后,make clean

make all 还是报同样的错误。

然后再按照最开始的帖子https://blog.csdn.net/mybelief321/article/details/9208073的方法再安装一遍glog，即

cd glog-0.3.3
./configure
make
sudo make install

　　再cd到caffe目录

make clean

make all

2019.6.2

5. make pycaffe相关问题

CXX/LD -o python/caffe/_caffe.so python/caffe/_caffe.cpp
python/caffe/_caffe.cpp:10:31: fatal error: numpy/arrayobject.h: 没有那个文件或目录
compilation terminated.
Makefile:517: recipe for target 'python/caffe/_caffe.so' failed
make: *** [python/caffe/_caffe.so] Error 1

首先看自己机器是否已经安装了。因为numpy库是必装的，所以因为还是路径设置的问题

终端输入 locate arrayobject.h

找到

/home/qian/.local/lib/python3.5/site-packages/numpy/core/include/numpy/arrayobject.h

注意上面的错误提示是缺少numpy/arrayobject.h，而不是缺少arrayobject.h。所以在添加路径的时候，最后的numpy不要加上

修改Makefile.config如下：

PYTHON_INCLUDE := /usr/include/python3.5m \
/usr/lib/python3.5/dist-packages/numpy/core/include \
/home/qian/.local/lib/python3.5/site-packages/numpy/core/include

解决

继续make，找不到lib：

CXX/LD -o python/caffe/_caffe.so python/caffe/_caffe.cpp
/usr/bin/ld: 找不到 -lboost_python3
collect2: error: ld returned 1 exit status
Makefile:517: recipe for target 'python/caffe/_caffe.so' failed
make: *** [python/caffe/_caffe.so] Error 1

首先终端查找：locate libboost_python3.so

找不到文件

再locate libboost_python

大概结果如下：

/usr/lib/x86_64-linux-gnu/libboost_python-py27.a
/usr/lib/x86_64-linux-gnu/libboost_python-py27.so
/usr/lib/x86_64-linux-gnu/libboost_python-py27.so.1.58.0
/usr/lib/x86_64-linux-gnu/libboost_python-py35.a
/usr/lib/x86_64-linux-gnu/libboost_python-py35.so
/usr/lib/x86_64-linux-gnu/libboost_python-py35.so.1.58.0
/usr/lib/x86_64-linux-gnu/libboost_python.a
/usr/lib/x86_64-linux-gnu/libboost_python.so

因为我编译的是python3版本。所以很明显我需要创建一个指向libboost_python_py35.so的软链接，名为libboost_python3.so

[email protected]:/usr/lib/x86_64-linux-gnu# ln -s libboost_python-py35.so libboost_python3.so

make pycaffe 解决

6. pip3 install -r requirements.txt相关问题

ERROR: matplotlib 3.0.3 has requirement python-dateutil>=2.1, but you'll have python-dateutil 1.5 which is incompatible.
ERROR: pandas 0.24.2 has requirement python-dateutil>=2.5.0, but you'll have python-dateutil 1.5 which is incompatible.

已经终端 pip3 install --upgrade python-dateutil 依然报此错误

解决办法：https://blog.csdn.net/CAU_Ayao/article/details/83538024

gedit requirements.txt

python-dateutil>=1.4,<2

改为：

python-dateutil //不加版本号就是默认为最新版本

继续pip3 install -r requirements.txt，问题解决。

2019.6.4

如果升级pip3后之后出现：from pip import main ImportError: cannot import name 'main' 错误

解决办法https://blog.csdn.net/qq_38522539/article/details/80678412

7. import caffe 相关错误

caffe模块找不到错误

解决办法：

export PYTHONPATH=/home/qian/libraries/caffe/python

需要升级matplotlib错误

>>> import caffe
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/qian/libraries/caffe/python/caffe/__init__.py", line 1, in <module>
from .pycaffe import Net, SGDSolver, NesterovSolver, AdaGradSolver, RMSPropSolver, AdaDeltaSolver, AdamSolver, NCCL, Timer
File "/home/qian/libraries/caffe/python/caffe/pycaffe.py", line 15, in <module>
import caffe.io
File "/home/qian/libraries/caffe/python/caffe/io.py", line 2, in <module>
import skimage.io
File "/usr/local/lib/python3.5/dist-packages/skimage/__init__.py", line 135, in <module>
from .data import data_dir
File "/usr/local/lib/python3.5/dist-packages/skimage/data/__init__.py", line 13, in <module>
from ..io import imread, use_plugin
File "/usr/local/lib/python3.5/dist-packages/skimage/io/__init__.py", line 15, in <module>
reset_plugins()
File "/usr/local/lib/python3.5/dist-packages/skimage/io/manage_plugins.py", line 91, in reset_plugins
_load_preferred_plugins()
File "/usr/local/lib/python3.5/dist-packages/skimage/io/manage_plugins.py", line 71, in _load_preferred_plugins
_set_plugin(p_type, preferred_plugins['all'])
File "/usr/local/lib/python3.5/dist-packages/skimage/io/manage_plugins.py", line 83, in _set_plugin
use_plugin(plugin, kind=plugin_type)
File "/usr/local/lib/python3.5/dist-packages/skimage/io/manage_plugins.py", line 254, in use_plugin
_load(name)
File "/usr/local/lib/python3.5/dist-packages/skimage/io/manage_plugins.py", line 298, in _load
fromlist=[modname])
File "/usr/local/lib/python3.5/dist-packages/skimage/io/_plugins/matplotlib_plugin.py", line 3, in <module>
from mpl_toolkits.axes_grid1 import make_axes_locatable
File "/usr/local/lib/python3.5/dist-packages/mpl_toolkits/axes_grid1/__init__.py", line 1, in <module>
from . import axes_size as Size
File "/usr/local/lib/python3.5/dist-packages/mpl_toolkits/axes_grid1/axes_size.py", line 15, in <module>
from matplotlib.axes import Axes
File "/usr/local/lib/python3.5/dist-packages/matplotlib/axes/__init__.py", line 1, in <module>
from ._subplots import *
File "/usr/local/lib/python3.5/dist-packages/matplotlib/axes/_subplots.py", line 6, in <module>
from matplotlib.axes._axes import Axes
File "/usr/local/lib/python3.5/dist-packages/matplotlib/axes/_axes.py", line 20, in <module>
import matplotlib.dates as _ # <-registers a date unit converter
File "/usr/local/lib/python3.5/dist-packages/matplotlib/dates.py", line 145, in <module>
from dateutil.rrule import (rrule, MO, TU, WE, TH, FR, SA, SU, YEARLY,
File "/usr/local/lib/python3.5/dist-packages/dateutil/rrule.py", line 55
raise ValueError, "Can't create weekday with n == 0"

^
SyntaxError: invalid syntax

解决办法：https://blog.csdn.net/quantum7/article/details/83475530

2019.6.5

终于搞定。。。

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CAFFE安装笔记【windows和ubuntu】