200字范文 > OpenCV环境配置：Ubuntu18.04编译OpenCV4.2.0和contrib模块记录

OpenCV环境配置：Ubuntu18.04编译OpenCV4.2.0和contrib模块记录

时间：2020-04-02 03:28:20

1.下载源码和安装依赖包2.解压源码文件和配置路径3.配置Cmake并编译OpenCV4.导入OpenCV到环境变量5.使用编译好的库6.在Qt工程下使用OpenCV

1.下载源码和安装依赖包

OpenCV4.2.0和contrib源码下载链接如下：

OpenCV源码下载: /opencv/opencv/tar.gz/4.2.0contrib模块源码下载: /opencv/opencv_contrib/tar.gz/4.2.0

首先在终端中输入如下命令来安装依赖包：

sudo apt install cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev sudo apt install python-dev python-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libdc1394-22-dev sudo apt install build-essential qt5-default ccache libv4l-dev libavresample-dev libgphoto2-dev libopenblas-base libopenblas-dev doxygen openjdk-8-jdk pylint libvtk6-dev

Tips:在之前几次编译OpenCV的过程中我发现安装上面的依赖包的时候基本都会出现一些问题，这次我的Ubuntu软件源用的是南邮源，输入上面的命令安装包时居然一点问题没有报，因此如果出现问题的时候，可以尝试将你的Ubuntu软件源切换到NJUPT试试。

2.解压源码文件和配置路径

使用如下命令解压源码文件:

tar -zxvf opencv-4.2.0.tar.gz.gztar -zxvf opencv_contrib-4.2.0.tar.gz.gz

将解压后的opencv_contrib-4.2.0复制到opencv-4.2.0目录下，并且在opencv-4.2.0目录下新建build目录并进入：

cp opencv_contrib-4.2.0 -rf opencv-4.2.0cd opencv-4.2.0/ && mkdir buildcd build

最终opencv-4.2.0目录内如下：

3.配置Cmake并编译OpenCV

在build目录内执行以下命令(注意contrib路径换成自己的)：

cmake -D CMAKE_BUILD_TYPE=Release \-D CMAKE_INSTALL_PREFIX=/usr/local \-D OPENCV_EXTRA_MODULES_PATH=../opencv_contrib-4.2.0/modules \-D OPENCV_GENERATE_PKGCONFIG=YES \ ..

其中CMAKE_INSTALL_PREFIX指定了编译好的库的目录，也就是说编译完成的OpenCV库文件会在该目录下，OPENCV_GENERATE_PKGCONFIG指定了生成pkgconfig配置文件，这个文件在后续创建OpenCV工程的时会很有用。

完成后结果如下：

-- ------------------------------------------------------------------- -- Configuring done-- Generating done-- Build files have been written to: /home/peco/Documents/opencv-4.2.0/build

这个时候在执行：

sudo make -j4

就开始编译了，编译时间较长，但是会有进度提示，所以等着就好了。

如果报错：

fatal error: features2d/test/test_detectors_regression.impl.hpp: No such file or directory#include "features2d/test/test_detectors_regression.impl.hpp"

只需在该文件中将

#include "features2d/test/test_detectors_regression.impl.hpp"

改成：

#include "../../../../modules/features2d/test/test_detectors_invariance.impl.hpp

其他头文件缺失解决方法与此类似，其实上面的features2d目录就在opencv-4.2.0/modules/目录下，重新指定一下就行，编译完成输出如下：

[100%] Built target opencv_python2[100%] Building CXX object modules/optflow/CMakeFiles/opencv_perf_optflow.dir/perf/perf_rlof.cpp.o[100%] Building CXX object modules/optflow/CMakeFiles/opencv_perf_optflow.dir/perf/perf_tvl1optflow.cpp.o[100%] Linking CXX executable ../../bin/opencv_test_xfeatures2d[100%] Built target opencv_test_xfeatures2d[100%] Building CXX object modules/superres/CMakeFiles/opencv_perf_superres.dir/perf/perf_superres.cpp.o[100%] Linking CXX executable ../../bin/opencv_perf_optflow[100%] Built target opencv_perf_optflow[100%] Linking CXX executable ../../bin/opencv_perf_superres[100%] Built target opencv_perf_superres

安装编译好的库：

sudo make install

4.导入OpenCV到环境变量

还记得之前的-D OPENCV_GENERATE_PKGCONFIG=YES \吗，该选项可以帮助我们导出库的信息方便引用，该过程主要有两步：

sudo vim /etc/ld.so.conf

首先编辑ld.so.conf文件，在末尾加上：

include /usr/loacal/lib

然后终端执行命令:

sudo ldconfig

然后修改.bashrc文件：

sudo vim ~/.bashrc

输入：

PKG_CONFIG_PATH=$PKG_CONFIG_PATH:/usr/local/lib/pkgconfigexport PKG_CONFIG_PATH

最后source一下，让更改立即生效：

source ~/.bashrc

5.使用编译好的库

输入如下命令：

pkg-config --cflags --libs opencv4

-I/usr/local/include/opencv4/opencv -I/usr/local/include/opencv4 -L/usr/local/lib -lopencv_gapi -lopencv_stitching -lopencv_aruco -lopencv_bgsegm -lopencv_bioinspired -lopencv_ccalib -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_stereo -lopencv_structured_light -lopencv_phase_unwrapping -lopencv_superres -lopencv_optflow -lopencv_surface_matching -lopencv_tracking -lopencv_datasets -lopencv_text -lopencv_dnn -lopencv_plot -lopencv_videostab -lopencv_videoio -lopencv_viz -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_imgproc -lopencv_core

该输出可以作为g++等编译器指定头文件,库文件等目录参数。

写一个简单的测试代码test_opencv.cpp：

#include<iostream>#include<opencv2/opencv.hpp>using namespace std;using namespace cv;int main(int argc,char**argv){Mat input = imread("test.jpg");imshow("input",input);waitKey(0);return 0;}

使用如下命令编译该文件：

g++ test_opencv.cpp -I/usr/local/include/opencv4/opencv -I/usr/local/include/opencv4 -L/usr/local/lib -lopencv_gapi -lopencv_stitching -lopencv_aruco -lopencv_bgsegm -lopencv_bioinspired -lopencv_ccalib -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_stereo -lopencv_structured_light -lopencv_phase_unwrapping -lopencv_superres -lopencv_optflow -lopencv_surface_matching -lopencv_tracking -lopencv_datasets -lopencv_text -lopencv_dnn -lopencv_plot -lopencv_videostab -lopencv_videoio -lopencv_viz -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_imgproc -lopencv_core

编译命令比较长比较冗余，但是此处仅仅是为了测试，一般也没有谁会这么来编译C++代码。编译过程没有问题，生成a.out可执行文件，运行该文件显示出该目录下名为test.jpg的图片，说明至此整个编译安装完成。