OpenCV4.2.0和contrib源码下载链接如下：
OpenCV源码下载: https://codeload.github.com/opencv/opencv/tar.gz/4.2.0contrib模块源码下载: https://codeload.github.com/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。使用如下命令解压源码文件:
tar -zxvf opencv-4.2.0.tar.gz.gz tar -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-4.2.0 cd opencv-4.2.0/ && mkdir build cd build最终opencv-4.2.0目录内如下：
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/pkgconfig export PKG_CONFIG_PATH最后source一下，让更改立即生效：
source ~/.bashrc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。
要问Ubuntu下好用的C++ IDE有哪些，Qt是我最推荐的，因为整个Qt在Ubuntu下也就一个多G，相比Windows下VS 动辄十几二十个G，Qt使用起来真的很清爽，而且Qt也可以创建纯C和纯C++项目，因此非常推荐。
在Qt中使用OpenCV，其实只要配置.pro文件就可以了，只需要在.pro文件中添加上库的路径就可以：
## opencv lib INCLUDEPATH+=/usr/local/include/opencv4/ \ /usr/local/include/ \ /usr/local/include/opencv4/opencv2 LIBS+=/usr/locao/lib/*.so.*