caffe安装详细完整过程（Ubuntu16.04、Ubuntu18.04系统）

今天药忘吃喽~ 2022-05-01 13:48 763阅读 0赞

## 在ubuntu（Ubuntu16.04、ubuntu18.04）系统下成功安装caffe框架详细笔记 ##

**目录**

Caffe编译安装指导

Caffe安装参考文档：

确认编译器版本

安装anaconda2

安装opencv和protobuf

编译caffe

--------------------

## 安装SSH人脸检测算法源码中的caffe框架 ##

ssh人脸检测算法：[https://blog.csdn.net/wsq\_zqfl/article/details/92810501][https_blog.csdn.net_wsq_zqfl_article_details_92810501]

**Caffe编译安装指导**

说明：本文假定用户已经正确安装了cuda和cudnn，如果未正确安装，可参考如下面的链接

*  ### **Caffe****安装参考文档：** ###

[https://blog.csdn.net/haoji007/article/details/52081273][https_blog.csdn.net_haoji007_article_details_52081273]

[https://blog.csdn.net/yhaolpz/article/details/71375762][https_blog.csdn.net_yhaolpz_article_details_71375762]

*  ### **确认编译器版本** ###

首先确定系统所使用的gcc/g++/c++的版本，并且尽量和

“cat /proc/driver/nvidia/version”输出中的gcc版本保持一致。

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzcV96cWZs_size_16_color_FFFFFF_t_70][]

查看系统安装了那些编译器版本：

1.  查看系统gcc/g++/c++/cpp所在的目录

![2019061115181211.png][]

1.  查看编译器版本

*  查看gcc版本

![watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzcV96cWZs_size_16_color_FFFFFF_t_70 1][]

![20190611151851499.png][]

上图中的gcc软链接指向的是gcc-5，说明版本正确

*  查看g++版本

![20190611151859384.png][]

![20190611151904296.png][]

*  查看c++版本

![20190611151912455.png][]

![20190611151917724.png][]

*  查看cpp版本

![20190611151924603.png][]

![20190611151929223.png][]

1.  gcc安装

如果所需要的编译器版本不存在，则可以安装相应的编译器，安装方法如下：

参考文档：[https://www.cnblogs.com/L-Arikes/p/3734382.html][https_www.cnblogs.com_L-Arikes_p_3734382.html]

sudo apt-get gcc-5

sudo apt-get g++-5

*  ### **安装anaconda2** ###

下载地址：[https://www.anaconda.com/distribution/\#download-section][https_www.anaconda.com_distribution_download-section]

官网安装参考地址：[https://docs.anaconda.com/anaconda/install/linux/][https_docs.anaconda.com_anaconda_install_linux]

下载成功后，在终端执行（2.7版本）：

\# bash Anaconda2-2.4.1-Linux-x86\_64.sh

或者3.5 版本：

\# bash Anaconda3-2.4.1-Linux-x86\_64.sh

在安装的过程中，会问你安装路径，直接回车默认就可以了。有个地方问你是否将anaconda安装路径加入到环境变量（.bashrc)中，这个一定要输入yes

安装成功后，会有当前用户根目录下生成一个anaconda2的文件夹，里面就是安装好的内容。

输入conda list 就可以查询，你现在安装了哪些库，常用的numpy, scipy名列其中。如果你还有什么包没有安装上，可以运行

conda install \*\*\*  来进行安装，

如果某个包版本不是最新的，运行 conda update \*\*\* 就可以了

*  ### **安装opencv和protobuf** ###

安装OPENCV:

下载地址：[https://opencv.org/releases/][https_opencv.org_releases]

安装指导：[https://docs.opencv.org/3.4.6/d7/d9f/tutorial\_linux\_install.html][https_docs.opencv.org_3.4.6_d7_d9f_tutorial_linux_install.html]

protobuf安装

下载地址：[https://github.com/protocolbuffers/protobuf/releases][https_github.com_protocolbuffers_protobuf_releases]

安装指导：[https://github.com/protocolbuffers/protobuf/blob/master/src/README.md][https_github.com_protocolbuffers_protobuf_blob_master_src_README.md]

*  ### **编译****caffe** ###

1、下载ssh代码

cd ~/work

git clone --recursive https://github.com/mahyarnajibi/SSH.git

2、修改源码

首先在你要安装的路径下 clone ：

git clone [https://github.com/BVLC/caffe.git][https_github.com_BVLC_caffe.git]

替换 cudnn.hpp、cudnn.cpp

cd ~/work
    git clone https://github.com/BVLC/caffe.git
    
    cd ~/work/SSH/caffe-ssh
    mv include/caffe/util/cudnn.hpp include/caffe/util/cudnn.hpp.bk
    cp ~/work/caffe/include/caffe/util/cudnn.hpp include/caffe/util/cudnn.hpp
    mv src/caffe/util/cudnn.cpp src/caffe/util/cudnn.cpp.bk
    cp ~/work/caffe/src/caffe/util/cudnn.cpp src/caffe/util/cudnn.cpp
    
    # rm -rf ~/work/caffe   #下载caffe的目的 其实就是要获取上面的两个文件，替换完成后 caffe就可以删掉了

1.  修改Makefile.config

cp Makefile.config.example Makefile.config
    vim Makefile.config

*  第23行
    
        # 修改前：
        # OPENCV_VERSION := 3
        
        # 修改后：
        OPENCV_VERSION := 3

第38行

# 修改前：
    CUDA_ARCH := -gencode arch=compute_20,code=sm_20 \
            -gencode arch=compute_20,code=sm_21 \
            -gencode arch=compute_30,code=sm_30 \
    
    # 修改后：
    CUDA_ARCH := -gencode arch=compute_30,code=sm_30 \

第52行

# 修改前：
    BLAS := atlas
    
    # 修改后：
    BLAS := open
    
    # 注：ATLAS、MKL、OpenBlas 都是矩阵运算库（对矩阵运算过程进行了优化）
    # BLAS choice:
    # atlas for ATLAS (default)
    # mkl for MKL
    # open for OpenBlas

*  `第68行：请根据具体环境修改`
    
        # 修改前：
        # 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
        # Anaconda Python distribution is quite popular. Include path:
        # Verify anaconda location, sometimes it's in root.
        # ANACONDA_HOME := $(HOME)/anaconda
        # PYTHON_INCLUDE := $(ANACONDA_HOME)/include \
                # $(ANACONDA_HOME)/include/python2.7 \
                # $(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include
        
        # Uncomment to use Python 3 (default is Python 2)
        # PYTHON_LIBRARIES := boost_python3 python3.5m
        # PYTHON_INCLUDE := /usr/include/python3.5m \
        #                 /usr/lib/python3.5/dist-packages/numpy/core/include
        
        # We need to be able to find libpythonX.X.so or .dylib.
        PYTHON_LIB := /usr/lib
        # PYTHON_LIB := $(ANACONDA_HOME)/lib
        
        
        
        # 修改后：
        # 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
        # Anaconda Python distribution is quite popular. Include path:
        # Verify anaconda location, sometimes it's in root.
        ANACONDA_HOME := $(HOME)/anaconda3/envs/caffe_python-2-7/
        PYTHON_INCLUDE := $(ANACONDA_HOME)/include \
                $(ANACONDA_HOME)/include/python2.7 \
                $(ANACONDA_HOME)/lib/python2.7/site-packages/numpy/core/include
        
        # Uncomment to use Python 3 (default is Python 2)
        # PYTHON_LIBRARIES := boost_python3 python3.5m
        # PYTHON_INCLUDE := /usr/include/python3.5m \
        #                 /usr/lib/python3.5/dist-packages/numpy/core/include
        
        # We need to be able to find libpythonX.X.so or .dylib.
        # PYTHON_LIB := /usr/lib
        PYTHON_LIB := $(ANACONDA_HOME)/lib
 *  第96行
    
        # 修改前：
        INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include
        LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib
        
        
        # 修改后：
        INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include /usr/include/hdf5/serial/
        LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib /usr/lib/x86_64-linux-gnu /usr/lib/x86_64-linux-gnu/hdf5/serial
    
    4、修改Makefile

cp Makefile Makefile.bk
    vim Makefile

第180行

#修改前:
    LIBRARIES += glog gflags protobuf boost_system boost_filesystem m hdf5_hl hdf5
    #修改后：
    LIBRARIES += glog gflags protobuf boost_system boost_filesystem m hdf5_serial_hl hdf5_serial

第417行

# 修改前：
    NVCCFLAGS += -ccbin=$(CXX) -Xcompiler -fPIC $(COMMON_FLAGS)
    
    # 修改后：
    NVCCFLAGS += -D_FORCE_INLINES -ccbin=$(CXX) -Xcompiler -fPIC $(COMMON_FLAGS)

**OK ，可以开始编译了，在 caffe 目录下执行 ：**

cd ~/work/SSH/caffe-ssh
    make clean
    make -j8
    make runtest -j8
    make pycaffe -j8

[https_blog.csdn.net_wsq_zqfl_article_details_92810501]: https://blog.csdn.net/wsq_zqfl/article/details/92810501
[https_blog.csdn.net_haoji007_article_details_52081273]: https://blog.csdn.net/haoji007/article/details/52081273
[https_blog.csdn.net_yhaolpz_article_details_71375762]: https://blog.csdn.net/yhaolpz/article/details/71375762
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzcV96cWZs_size_16_color_FFFFFF_t_70]: /images/20220119/038673d70a9b4cf9b339d83fca73241c.png
[2019061115181211.png]: /images/20220119/1e2c844476f14d7faac99c49be93298a.png
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L3dzcV96cWZs_size_16_color_FFFFFF_t_70 1]: /images/20220119/304612d9e0a4420da6840133f865b06e.png
[20190611151851499.png]: /images/20220119/27d08484ff3441538aa1c4283d518a93.png
[20190611151859384.png]: /images/20220119/88573cb84fc64dc9b4c63327074f47f4.png
[20190611151904296.png]: /images/20220119/ec36993db71944bbb8a075896939ee69.png
[20190611151912455.png]: /images/20220119/47c672b1c8524dbf8b447e8fef0d06f4.png
[20190611151917724.png]: /images/20220119/24696631e0db4d85863bf1785e740c90.png
[20190611151924603.png]: /images/20220119/1cfcc1f9afa74adc95783dd8ac90fb99.png
[20190611151929223.png]: /images/20220119/c172e35e3e1e4be9ae4396edc60602ca.png
[https_www.cnblogs.com_L-Arikes_p_3734382.html]: https://www.cnblogs.com/L-Arikes/p/3734382.html
[https_www.anaconda.com_distribution_download-section]: https://www.anaconda.com/distribution/#download-section
[https_docs.anaconda.com_anaconda_install_linux]: https://docs.anaconda.com/anaconda/install/linux/
[https_opencv.org_releases]: https://opencv.org/releases/
[https_docs.opencv.org_3.4.6_d7_d9f_tutorial_linux_install.html]: https://docs.opencv.org/3.4.6/d7/d9f/tutorial_linux_install.html
[https_github.com_protocolbuffers_protobuf_releases]: https://github.com/protocolbuffers/protobuf/releases
[https_github.com_protocolbuffers_protobuf_blob_master_src_README.md]: https://github.com/protocolbuffers/protobuf/blob/master/src/README.md
[https_github.com_BVLC_caffe.git]: https://github.com/BVLC/caffe.git