Ubuntu 16.04 Caffe 1.0.0编译安装问题

蔚落 2021-11-13 23:28 277阅读 0赞

安装过程的主要问题是依赖的各种库版本兼容问题，有时即使编译成功了，运行时也会报错。  
目前使用 protobuf 3.6，opencv3.4.5, glog-0.3.3 gflags-2.0， 顺利解决问题。  
安装主要参考文章 [https://blog.csdn.net/yhaolpz/article/details/71375762][https_blog.csdn.net_yhaolpz_article_details_71375762]

1.  首先参考文章， 通过apt-get安装好依赖库。

sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev protobuf-compiler

sudo apt-get install --no-install-recommends libboost-all-dev

sudo apt-get install libopenblas-dev liblapack-dev libatlas-base-dev

sudo apt-get install libgflags-dev libgoogle-glog-dev liblmdb-dev

sudo apt-get install git cmake build-essential

1.  编译安装opencv3.4.5 , 3.4的版本应该都可以
2.  依次安装 glog gflags， leveldb

# glog #

wget [https://github.com/google/glog/archive/v0.3.3.tar.gz][https_github.com_google_glog_archive_v0.3.3.tar.gz]  
tar zxvf v0.3.3.tar.gz  
cd glog-0.3.3  
./configure  
make && make install

# gflags #

wget [https://github.com/schuhschuh/gflags/archive/master.zip][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

# lmdb #

git clone [https://github.com/LMDB/lmdb][https_github.com_LMDB_lmdb]  
cd lmdb/libraries/liblmdb  
make && make install

1.  安装CUDA和CUDNN，机器以前已经安装好了
2.  按照参考文章，修改Makefile.config, 并进行编译caffe

make all -j8

编译后运行build/tools/caffe , 如果出现错误： caffe: symbol lookup error: caffe: undefined symbol: \_ZN6google16SetVersionStringERKSs

运行 export LD\_LIBRARY\_PATH=/usr/local/lib， 然后应该可以解决

1.  安装 pycaffe 接口环境  
    参考 [https://github.com/BVLC/caffe/issues/3220][https_github.com_BVLC_caffe_issues_3220]  
    修改\_caffe.cpp ，解决运行时遇到的错误 Error in python interface. " Net.**init**(Net, str, str, int) did not match C++ signature

diff --git a/python/caffe/\_caffe.cpp b/python/caffe/\_caffe.cpp  
index 4ea2ec6…4c558cb 100644  
— a/python/caffe/\_caffe.cpp  
\+++ b/python/caffe/\_caffe.cpp  
@@ -75,7 +75,7 @@ void CheckContiguousArray(PyArrayObject\* arr, string name,

// Net constructor for passing phase as int  
shared\_ptr<Net > Net\_Init(

*  string param\_file, int phase) \{

*  char\* param\_file, int phase) \{  
    CheckFile(param\_file);

shared\_ptr<Net > net(new Net(param\_file,  
@@ -85,7 +85,7 @@ shared\_ptr<Net > Net\_Init(

// Net construct-and-load convenience constructor  
shared\_ptr<Net > Net\_Init\_Load(

*  string param\_file, string pretrained\_param\_file, int phase) \{

*  char\* param\_file, char\* pretrained\_param\_file, int phase) \{  
    CheckFile(param\_file);  
    CheckFile(pretrained\_param\_file);

修改后编译 make pycaffe

然后就可以在在python中使用caffe了

[https_blog.csdn.net_yhaolpz_article_details_71375762]: https://blog.csdn.net/yhaolpz/article/details/71375762
[https_github.com_google_glog_archive_v0.3.3.tar.gz]: https://github.com/google/glog/archive/v0.3.3.tar.gz
[https_github.com_schuhschuh_gflags_archive_master.zip]: https://github.com/schuhschuh/gflags/archive/master.zip
[https_github.com_LMDB_lmdb]: https://github.com/LMDB/lmdb
[https_github.com_BVLC_caffe_issues_3220]: https://github.com/BVLC/caffe/issues/3220