目录
- Step 1: 安装OpenCV的依赖包
- Step 2: 下载OpenCV 4.2.0和OpenCV Contrib 4.2.0
- Step 3: 使用cmake构建库
- Step 4: 使用make构建库
- Step 5: 修改
opencv4.pc
文件 - Step 6: 在
.bashrc
文件中添加PKG_CONFIG_PATH
- Step 7: 使用C++代码进行验证
本文主要介绍在Ubuntu 18.04中从源码安装配置OpenCV,并使用一个简单的例子验证是否安装成功;
具体安装配置步骤,参考文章见:https://cv-tricks.com/installation/opencv-4-1-ubuntu18-04/
与上述链接中提供的教程不同的是:
- 部分依赖包安装可能需要修改
- 本文安装配置OpenCV版本为4.2,支持使用CUDA对DNN模块加速计算
- 本文不涉及Python接口配置,仅配置为C++使用,所以会跳过步骤Step2~5
Step 1: 安装OpenCV的依赖包
一步一步的安装下面的所有依赖包:
sudo apt-get update -y # Update the list of packages
sudo apt-get remove -y x264 libx264-dev # Remove the older version of libx264-dev and x264
sudo apt-get install -y build-essential checkinstall cmake pkg-config yasm
sudo apt-get install -y git gfortran
sudo add-apt-repository -y "deb http://security.ubuntu.com/ubuntu xenial-security main"
sudo apt-get install -y libjpeg8-dev libjasper-dev libpng12-dev
sudo apt-get install -y libtiff5-dev
sudo apt-get install -y libavcodec-dev libavformat-dev libswscale-dev libdc1394-22-dev
sudo apt-get install -y libxine2-dev libv4l-dev
sudo apt-get install -y libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev
sudo apt-get install -y qt5-default libgtk2.0-dev libtbb-dev
sudo apt-get install -y libatlas-base-dev
sudo apt-get install -y libfaac-dev libmp3lame-dev libtheora-dev
sudo apt-get install -y libvorbis-dev libxvidcore-dev
sudo apt-get install -y libopencore-amrnb-dev libopencore-amrwb-dev
sudo apt-get install -y x264 v4l-utils
# Some Optional Dependencies
sudo apt-get install -y libprotobuf-dev protobuf-compiler
sudo apt-get install -y libgoogle-glog-dev libgflags-dev
sudo apt-get install -y libgphoto2-dev libeigen3-dev libhdf5-dev doxygen
在安装上述依赖包的过程中,可能会存在一些错误提示,这里我将自己遇到的问题列出,并给出解决方案;
错误1:
E: Unable to locate package libjasper-dev
执行:
sudo add-apt-repository "deb http://security.ubuntu.com/ubuntu xenial-security main"
sudo apt-get update
再次执行安装依赖包就行;
错误2:
E: Unable to locate package libgstreamer0.10-dev
执行:
sudo apt install libgstreamer1.0-dev libgstreamer-plugins-base1.0-dev
即可;
Step 2: 下载OpenCV 4.2.0和OpenCV Contrib 4.2.0
OpenCV 4.2.0:
https://github.com/opencv/opencv/releases/tag/4.2.0
OpenCV Contib 4.2.0:
https://github.com/opencv/opencv_contrib/releases/tag/4.2.0
假如将两个压缩包保存到/home/username/opencv4.2/
,进行解压;
另外,在编译的时候需要ippicv_2019_lnx_intel64_general_20180723.tgz
这个文件,下载的时候会特别慢。这里提供一个链接,参考其中的第1,2两个步骤进行下载与配置;
如,我将下载得到的文件放在了opencv4.2
这个文件夹中,修改成"/home/username/opencv4.2/"
;
最后目录结构如下:
/home/username/opencv4.2/
opencv-4.2.0/
opencv_contrib-4.2.0/
ippicv_2019_lnx_intel64_general_20180723.tgz
Step 3: 使用cmake构建库
执行:
cd /home/username/opencv4.2/opencv-4.2.0
mkdir build
cd build
执行:
cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D INSTALL_C_EXAMPLES=ON -D CUDA_ARCH_BIN='7.5'
-D WITH_CUDA=ON
-D WITH_TBB=ON -D WITH_V4L=ON -D WITH_QT=ON -D WITH_OPENGL=ON -D OPENCV_EXTRA_MODULES_PATH=/home/username/opencv4.2/opencv_contrib-4.2.0/modules -D BUILD_EXAMPLES=ON -D OPENCV_GENERATE_PKGCONFIG=YES ..
上述步骤需要修改的地方有两处:
CUDA_ARCH_BIN='7.5'
由于OpenCV 4.2支持使用CUDA对DNN模块进行加速计算,所以这里配置CUDA;在此之前需要自行配置好NVIDIA显卡的驱动与CUDA;
其中7.5
指的是显卡的计算能力,我的是GTX 1660Ti,对应的计算力为7.5;
这里提供一个链接,可以参考:NVIDA CUDA显卡计算能力对应表
第二处需要修改的地方是:
OPENCV_EXTRA_MODULES_PATH=/home/username/opencv4.2/opencv_contrib-4.2.0/modules
这里修改成你本机的opencv_contrib-4.2.0/modules
的位置
Step 4: 使用make构建库
查看CPU核心数:
nproc
如,我的CPU核心数为12,执行
cd /home/username/opencv4.2/
make -j12
等待一段时候,出现Configuration Done
即可,
执行:
sudo make install
再次等待一段时候后,执行:
sudo sh -c 'echo "/usr/local/lib" >> /etc/ld.so.conf.d/opencv.conf'
sudo ldconfig
Step 5: 修改opencv4.pc
文件
如果上述配置成功,则会在/usr/local/lib/
文件夹中出现一个pkgconfig
文件夹,里面有一个opencv.pc
文件,内容大致如下:
# Package Information for pkg-config
prefix=/usr/local
exec_prefix=${prefix}
libdir=${exec_prefix}/lib
includedir_old=${prefix}/include/opencv4/opencv2
includedir_new=${prefix}/include/opencv4
Name: OpenCV
Description: Open Source Computer Vision Library
Version: 4.2.0
Libs: -L${exec_prefix}/lib -lopencv_gapi -lopencv_stitching -lopencv_aruco -lopencv_bgsegm -lopencv_bioinspired -lopencv_ccalib -lopencv_cudabgsegm -lopencv_cudafeatures2d -lopencv_cudaobjdetect -lopencv_cudastereo -lopencv_cvv -lopencv_dnn_objdetect -lopencv_dnn_superres -lopencv_dpm -lopencv_highgui -lopencv_face -lopencv_freetype -lopencv_fuzzy -lopencv_hdf -lopencv_hfs -lopencv_img_hash -lopencv_line_descriptor -lopencv_quality -lopencv_reg -lopencv_rgbd -lopencv_saliency -lopencv_sfm -lopencv_stereo -lopencv_structured_light -lopencv_phase_unwrapping -lopencv_superres -lopencv_cudacodec -lopencv_surface_matching -lopencv_tracking -lopencv_datasets -lopencv_text -lopencv_dnn -lopencv_plot -lopencv_videostab -lopencv_cudaoptflow -lopencv_optflow -lopencv_cudalegacy -lopencv_videoio -lopencv_cudawarping -lopencv_xfeatures2d -lopencv_shape -lopencv_ml -lopencv_ximgproc -lopencv_video -lopencv_xobjdetect -lopencv_objdetect -lopencv_calib3d -lopencv_imgcodecs -lopencv_features2d -lopencv_flann -lopencv_xphoto -lopencv_photo -lopencv_cudaimgproc -lopencv_cudafilters -lopencv_imgproc -lopencv_cudaarithm -lopencv_core -lopencv_cudev
Libs.private: -lm -lpthread -L/usr/lib/x86_64-linux-gnu -lGL -lGLU -lcudart_static -ldl -lrt -lnppc -lnppial -lnppicc -lnppicom -lnppidei -lnppif -lnppig -lnppim -lnppist -lnppisu -lnppitc -lnpps -lcublas -lcudnn -lcufft -L-L/usr/local/cuda -llib64 -L-L/usr/lib -lx86_64-linux-gnu
Cflags: -I${includedir_old} -I${includedir_new}
注意:需要将第6行修改为:
includedir_old=${prefix}/include/opencv4/opencv2
如果没有自动生成,可以试着新建一个文件,将上述的内容复制进去,继续下一步;
Step 6: 在.bashrc
文件中添加PKG_CONFIG_PATH
执行:
sudo gedit ~/.bashrc
在文件最后添加:
PKG_CONFIG_PATH=$PKG_CONFIG_PATH:/usr/local/lib/pkgconfig
export PKG_CONFIG_PATH
退出后,执行
source ~/.bashrc
# 判断路径时候添加成功,返回:/usr/local/lib/pkgconfig即可
echo $PKG_CONFIG_PATH
Step 7: 使用C++代码进行验证
在任意目录下创建test.cpp
文件,加入下面内容:
#include "opencv.hpp"
using namespace cv;
using namespace std;
int main( int argc, char** argv )
{
cout << "OpenCV version : " << CV_VERSION << endl;
cout << "Major version : " << CV_MAJOR_VERSION << endl;
cout << "Minor version : " << CV_MINOR_VERSION << endl;
cout << "Subminor version : " << CV_SUBMINOR_VERSION << endl;
}
使用命令行在其文件夹下执行:
# 编译test.cpp程序,并生成可执行文件
g++ -std=c++11 test.cpp `pkg-config --libs --cflags opencv4` -o result
# 执行可执行文件
./result
输出以下内容,即表明配置成功
OpenCV version : 4.2.0
Major version : 4
Minor version : 2
Subminor version : 0
原文地址:https://www.cnblogs.com/chenzhen0530/p/12109868.html