Ubuntu16.04+opencv3.2+python3.5配置caffe(GPU版)

前前后后花了快一周才搭建好caffe环境,最开始使用的是anaconda的Python,但是在编译opencv的时候一直出各种问题,在网上查了很多博客都没有有效的解决,所以果断放弃了使用anaconda。在此记录一下搭建的整个过程以及出现过的报错等,同时也感谢参考过的所有博客。

1.安装Ubuntu16.04

这里省略了安装过程,只记录了配置静态ip
(1)编辑/etc/network/interfaces文件

sudo gedit /etc/network/interfaces

# interfaces(5) file used by ifup(8) and ifdown(8)
#auto lo
#iface lo inet loopback
auto eno1  #这里需要用ifconfig命令查看一下自己的网卡名称
iface eno1 inet static
address x.x.x.x #ip地址
netmask x.x.x.x #子网掩码
gateway x.x.x.x #网关
dns-nameserver x.x.x.x ###dns

(2)重启网卡

sudo /etc/init.d/networking restart

2.安装Nvidia

(1)禁用nouveau

sudo gedit /etc/modprobe.d/blacklist.conf

在最后一行添加

backlist vga16fb
blacklist nouveau
blacklist rivafb
blacklist rivatv
blacklist nvidiafb

(2)更新内核

sudo update-initramfs -u

(3)关机重启

lsmod | grep nouveau

没有输出则关闭成功
(4)关闭图像界面

sudo service lightdm stop

(5)按Ctrl+Alt+F1进入命令行界面
(6)给run文件赋予执行权限

sudo chmod a+x NVIDIA-Linux-x86_64-xxx.xx.run

(7)安装

sudo ./NVIDIA-Linux-x86_64-xxx.xx.run –no-opengl-files

(8)退出命令行界面

sudo service lightdm start

(9)重启,验证是否安装成功

nvidia-smi

3.安装Cuda8.0

(1)下载CUDA
(2)执行如下命令(执行过程中会让你选择是否那种nvidia驱动,需要选否)

sudo chmod 777 cuda_8.0.61_375.26_linux.run
sudo  ./cuda_8.0.61_375.26_linux.run

(3)配置环境变量

  • 打开bashrc文件sudo gedit ~/.bashrc将以下内容写入到~/.bashrc尾部
export PATH=/usr/local/cuda-8.0/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-8.0/lib64${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
  • 在/etc/profile文件中添加CUDA环境变量sudo gedit /etc/profile打开文档都在文档结尾加上下面两句
PATH=/usr/local/cuda/bin:$PATH  
export PATH
  • 使环境变量立即生效
source /etc/profile
  • 添加lib库路径,在 /etc/ld.so.conf.d/新建文件 cuda.conf
sudo gedit /etc/ld.so.conf.d/cuda.conf
  • 添加如下路径
/usr/local/cuda/lib64
  • 执行下列命令使之立刻生
sudo ldconfig
  • 测试CUDA的samples
cd /usr/local/cuda-8.0/samples/1_Utilities/deviceQuery
make
sudo ./deviceQuery

显示为pass则成功

4.安装cudnn6.0

(1)下载对应的cudnn
(2)执行如下命令

sudo tar -xzvf cudnn-8.0-linux-x64-v6.0.tgz
sudo cp cuda/include/cudnn.h /usr/local/cuda/include
sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64
sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn*

5.修改默认python版本

本文没有采用annconda来进行安装。因此在编译之前需要先将ubuntu默认的python版本修改为python3.5。
(1)使用 update-alternatives 来为整个系统更改 Python 版本

# update-alternatives --list python
update-alternatives: error: no alternatives for python

出现以上所示的错误信息,表示 Python 的替代版本尚未被 update-alternatives 命令识别
(2)更新替代列表

# update-alternatives --install /usr/bin/python python /usr/bin/python2.7 1
update-alternatives: using /usr/bin/python2.7 to provide /usr/bin/python (python) in auto mode
# update-alternatives --install /usr/bin/python python /usr/bin/python3.5 2
update-alternatives: using /usr/bin/python3.5 to provide /usr/bin/python (python) in auto mode

(3)再次列出可用的 Python 替代版本

# update-alternatives --list python
/usr/bin/python2.7
/usr/bin/python3.5

(4)使用下方的命令随时在列出的 Python 替代版本中任意切换

# update-alternatives --config python

(5)移除替代版本

# update-alternatives --remove python /usr/bin/python2.7
update-alternatives: removing manually selected alternative - switching python to auto mode
update-alternatives: using /usr/bin/python3.5 to provide /usr/bin/python (python) in auto mode

因为切换了版本,所以在使用pip时要注意使用pip3还是pip

6.编译安装opencv3.2

(1)下载opencv
手动下载:https://opencv.org/releases.html 下载源码后解压
wget https://github.com/Itseez/opencv/archive/3.2.0.zip
(2)安装依赖(还差什么以后再补)

sudo apt-get install build-essential cmake pkg-config
sudo apt-get install libjpeg8-dev libtiff5-dev libjasper-dev libpng12-dev
 
sudo apt-get install libavcodec-dev libavformat-dev libswscale-dev libv4l-dev
sudo apt-get install libxvidcore-dev libx264-dev
 
sudo apt-get install libgtk-3-dev
 
sudo apt-get install libatlas-base-dev gfortran
 
sudo apt-get install python3.5-dev
sudo apt-get install python3-numpy

(3)创建编译文件夹

#进入opencv目录
mkdir build
cd build

(4)编译准备(修改成自己的路径,python2版本只需要保留前两行)

cmake -D CMAKE_BUILD_TYPE=RELEASE \
-D CMAKE_INSTALL_PREFIX=/usr/local \
-D PYTHON3_EXECUTABLE=/usr/bin/python3 \
-D PYTHON_INCLUDE_DIR=/usr/include/python3.5 \
-D PYTHON_LIBRARY=/usr/lib/x86_64-linux-gnu/libpython3.5m.so \
-D PYTHON3_NUMPY_INCLUDE_DIRS=/usr/lib/python3/dist-packages/numpy/core/include/ ..

(5)编译安装

sudo make -j16
sudo make install

(6)添加环境变量

sudo /bin/bash -c 'echo "/usr/local/lib" > /etc/ld.so.conf.d/opencv.conf'
添加环境变量
gedit ~/.bashrc 
把下面这一句加入文档的最末尾。
export PYTHONPATH=/usr/local/lib/python3.5/dist-packages:$PYTHONPATH
然后
sudo ldconfig
sudo apt-get update

(7)验证

python
>>>import cv2
>>>cv2.__version__

显示正确则安装成功
(8)报错信息:可能会提示ippicv_linux_20151201下载失败,这是由于网络原因,可以自己下载好之后放到相应的文件夹
下载ippicv_linux_20151201
将其放入/home/xxx/opencv-3.2.0/3rdparty/ippicv/downloads/linux-808b791a6eac9ed78d32a7666804320e路径下,替换原来的压缩包,然后重新编译
(9) 如果想用python调用opencv,安装python3-opencv

sudo apt-get install python3-opencv  
sudo apt-get install python3-numpy

7.安装caffe

(1)安装依赖

sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev
 
sudo apt-get install 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

(2)https://github.com/BVLC/caffe 下载caffe后解压
(3)复制Makefile.config文件

sudo cp Makefile.config.example Makefile.config

(4)修改配置文件Makefile.config

sudo gedit Makefile.config
  • 将第5行注释去掉
USE_CUDNN := 1
  • 将第21行注释去掉
OPENCV_VERSION := 3
  • 将第37和38行删除(cuda8.0后不再支持)
# CUDA architecture setting: going with all of them.
# For CUDA < 6.0, comment the *_50 through *_61 lines for compatibility.
# For CUDA < 8.0, comment the *_60 and *_61 lines for compatibility.
# For CUDA >= 9.0, comment the *_20 and *_21 lines for compatibility.
CUDA_ARCH :=-gencode arch=compute_30,code=sm_30 \
        -gencode arch=compute_35,code=sm_35 \
        -gencode arch=compute_50,code=sm_50 \
        -gencode arch=compute_52,code=sm_52 \
        -gencode arch=compute_60,code=sm_60 \
        -gencode arch=compute_61,code=sm_61 \
        -gencode arch=compute_61,code=compute_61
  • 修改第51行
BLAS := open
  • 修改python路径信息
# 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/python3.5 \
        /usr/lib/python3/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/dist-packages/numpy/core/include
  • 将# Whatever else you find you need goes here. 下面的
INCLUDE_DIRS := $(PYTHON_INCLUDE) /usr/local/include
LIBRARY_DIRS := $(PYTHON_LIB) /usr/local/lib /usr/lib

替换成

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 
  • 若要使用python来编写layer,则去掉下面注释
#WITH_PYTHON_LAYER := 1  >>>>  WITH_PYTHON_LAYER := 1 

(5)修改Makefile文件

NVCCFLAGS +=-ccbin=$(CXX) -Xcompiler-fPIC $(COMMON_FLAGS)
替换成
NVCCFLAGS += -D_FORCE_INLINES -ccbin=$(CXX) -Xcompiler -fPIC $(COMMON_FLAGS)
LIBRARIES += glog gflags protobuf boost_system boost_filesystem m hdf5_serial
替换成
LIBRARIES += glog gflags protobuf boost_system boost_filesystem m hdf5_serial_hl hdf5_serial

(6)编译

sudo make all –j16
15524575346758.jpg
sudo make test –j16
15524575678295.jpg
sudo make runtest –j16
15524576240958.jpg

(7)编译pycaffe

  • 在caffe根目录的python文件夹下,有一个requirements.txt的清单文件,上面列出了需要的依赖库,按照这个清单安装
cd ./python
for req in $(cat requirements.txt); do pip3 install $req; done
  • 安装完成以后,再次回到caffe根目录执行
sudo pip3 install -r python/requirements.txt
  • 编译pycaffe接口
sudo make pycaffe  -j16
  • 配置环境变量,以便python调用
sudo gedit ~/.bashrc

export PYTHONPATH=/home/caffe/python:$PYTHONPATH

source ~/.bashrc

(8)测试

python
>>> import caffe

没有报错则安装成功
报错信息:
(1)错误1(import caffe时)

undefined symbol: _ZN5boost6python6detail11init_moduleER11PyModuleDefPFvvE

/usr/lib/x86_64-linux-gnu/路径下查找boost_python文件的版本是否与python版本匹配,caffe默认的配置文件为python2.7,因此这里需要修改
将caffe的Makefile的第208行修改为(根据自己的版本修改)

PYTHON_LIBRARIES := boost_python-py35 python3.5m

然后重新编译

sudo make clean
sudo ldconfig
sudo make all
sudo make test
sudo make runtest

(2)错误2(import caffe时)

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

升级matplotlib包
(3)错误3(import caffe时)

ImportError: No module named 'scipy._lib.decorator'

卸载scipy后重装,若是在卸载时出现

Cannot uninstall 'ipython'. It is a distutils installed project and thus we cannot accurately det

可以直接在相应的python路径:lib/site-packages下删除ipython.xxx.egg-info文件

sudo pip3 install scipy

重新编译再测试。
个人主页

参考链接

Ubuntu16.04 + CUDA8.0 + OpenCL + Nvidia 安装配置和问题总结
Ubuntu16.04 14.04安装配置Caffe(GPU版)
更改Ubuntu默认python版本的方法
Ubuntu 16.04下安装Caffe解决 undefined symbol: _ZN5boost6python6detail11init_moduleER11PyModuleDefPFvvE
Caffe——Ubuntu 16.04 CPU版本安装
ImportError: No module named 'scipy._lib.decorator'
Ubuntu18.04LTS下基于 Anaconda3 安装 Caffe-GPU及 Python3.6 + Pycharm + Mnist例子教程

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