前言
本文主要介绍如何在linux系统安装使用opencv.
具体步骤可参考opencv官网here.
步骤
编译源码之前需要安装相关依赖库；
1.下载源码；
2.解压源码；
3.配置cmake；
注意将配置的错误文件删除，以及cmake目录；
4.编译链接；
编译过程涉及到opencv的编译选项；
cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_C_COMPILER=/usr/bin/gcc -D CMAKE_INSTALL_PREFIX=/usr/local -D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib/modules/ -D CUDA_CUDA_LIBRARY=/usr/local/cuda/lib64/stubs/libcuda.so -D CUDA_ARCH_BIN=6.1 -D CUDA_ARCH_PTX="" -D WITH_CUDA=ON -D WITH_TBB=ON -D WITH_FFMPEG=ON -D BUILD_PYTHON_SUPPORT=ON -D BUILD_NEW_PYTHON_SUPPORT=ON -D BUILD_OPENCV_PYTHON3=ON -D PYTHON_INCLUDE_DIR=/home/xxx/anaconda3/include/python3.8 -D PYTHON_PACKAGES_PATH=/home/xxx/anaconda3/lib/python3.8/site-packages -D WITH_V4L=ON -D INSTALL_C_EXAMPLES=ON -D INSTALL_PYTHON_EXAMPLES=ON -D BUILD_EXAMPLES=ON -D WITH_QT=ON -D WITH_GSTREAMER=ON -D WITH_OPENGL=ON -D ENABLE_FAST_MATH=1 -D CUDA_FAST_MATH=1 -D OPENCV_GENERATE_PKGCONFIG=ON -D OPENCV_PC_FILE_NAME=opencv.pc -D CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda -D CMAKE_LIBRARY_PATH=/usr/local/cuda/lib64/stubs -D WITH_CUBLAS=ON -D WITH_NVCUVID=ON -D BUILD_opencv_cudacodec=ON -D OPENCV_DNN_CUDA=ON -D WITH_CUDNN=ON -D OPENCV_ENABLE_NONFREE=ON -D WITH_GSTREAMER=ON -D BUILD_EXAMPLES=ON .. cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_C_COMPILER=/usr/bin/gcc -D CMAKE_INSTALL_PREFIX=/usr/local -D OPENCV_EXTRA_MODULES_PATH=../../opencv_contrib/modules/ -D CUDA_CUDA_LIBRARY=/usr/local/cuda/lib64/stubs/libcuda.so -D CUDA_ARCH_BIN=8.6 -D CUDA_ARCH_PTX="" -D WITH_CUDA=ON -D WITH_TBB=ON -D WITH_FFMPEG=ON -D BUILD_PYTHON_SUPPORT=ON -D BUILD_NEW_PYTHON_SUPPORT=ON -D BUILD_OPENCV_PYTHON3=ON -D PYTHON_INCLUDE_DIR=/usr/include/python3.8 -D PYTHON_LIBRARY=/usr/lib/python3.8/config-3.8-x86_64-linux-gnu/libpython3.8.so -D WITH_V4L=ON -D INSTALL_C_EXAMPLES=ON -D INSTALL_PYTHON_EXAMPLES=ON -D BUILD_EXAMPLES=ON -D WITH_QT=ON -D WITH_GSTREAMER=ON -D WITH_OPENGL=ON -D ENABLE_FAST_MATH=1 -D CUDA_FAST_MATH=1 -D OPENCV_GENERATE_PKGCONFIG=ON -D OPENCV_PC_FILE_NAME=opencv.pc -D CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda -D CMAKE_LIBRARY_PATH=/usr/local/cuda/lib64/stubs -D WITH_CUBLAS=ON -D WITH_NVCUVID=ON -D BUILD_opencv_cudacodec=ON -D OPENCV_DNN_CUDA=ON -D WITH_CUDNN=ON -D OPENCV_ENABLE_NONFREE=ON -D WITH_GSTREAMER=ON -D BUILD_EXAMPLES=ON .. cmake -DPYTHON_INCLUDE_DIR=/usr/include/python3.8 -DPYTHON_LIBRARY=/usr/lib/python3.8/config-3.8-x86_64-linux-gnu/libpython3.8.so
5.安装库；
Required Packages
[compiler] sudo apt-get install build-essential [required] sudo apt-get install cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev [optional] sudo apt-get install python-dev python-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libjasper-dev libdc1394-22-dev
Bash
/opt$ sudo unzip opencv-3.3.1.zip /opt$cd opencv-3.3.1 /opt/opencv-3.3.1$sudo mkdir build /opt/opencv-3.3.1$cd build /opt/opencv-3.3.1/build$sudo cmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_INSTALL_PREFIX=/usr/local .. /opt/opencv-3.3.1/build$sudo make -j8（wait long time） /opt/opencv-3.3.1/build$sudo make install
注意事项
1. 注意你要安装的opencv的版本以及cv12、cv14等；
2.首先需要安装opencv的依赖库，而且必须是在安装opencv之前优先安装依赖库，可参考here；
3.测试程序完成之后，需要CMakeLists.txt进行编译，可参考here；
CMAKE_MINIMUM_REQUIRED(VERSION 2.8) PROJECT(test_opencv) SET(OpenCV_DIR /lib/opencv2413/opencv-2.4.13.4/build) INCLUDE_DIRECTORIES(/lib/opencv2413/opencv-2.4.13.4/build/include) FIND_PACKAGE(OpenCV REQUIRED) ADD_EXECUTABLE(test_opencv test_opencv.cpp) TARGET_LINK_LIBRARIES(test_opencv ${OpenCV_LIBS})
FIND_PACKAGE可以设置为多个opencv版本之间的切换；
FIND_PACKAGE(OpenCV 3.3.1 REQUIRED)
example
find_package( OpenCV 3.1.0 REQUIRED ) include_directories( ${OpenCV_INCLUDE_DIRS} ) message("OpenCV_INCLUDE_DIRS: ${OpenCV_INCLUDE_DIRS}") message("OpenCV_LIBS: ${OpenCV_LIBS}") target_link_libraries( demo ${OpenCV_LIBS} )
4.其他多是调试代码；
如何卸载
cd build sudo make uninstall cd .. sudo rm -r build sudo rm -r /usr/local/include/opencv2 /usr/local/include/opencv /usr/include/opencv /usr/include/opencv2 /usr/local/share/opencv /usr/local/share/OpenCV /usr/share/opencv /usr/share/OpenCV /usr/local/bin/opencv* /usr/local/lib/libopencv* cd .. rm -r opencv3.3.1
添加opencv_contrib
to build with modules from opencv_contrib set OPENCV_EXTRA_MODULES_PATH to <path to opencv_contrib/modules/>
command
/opt/opencv-3.3.1/build$ sudo cmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_INSTALL_PREFIX=/usr/local -D OPENCV_EXTRA_MODULES_PATH=../opencv_contrib/modules/ ..
error
CMake Error at cmake/OpenCVModule.cmake:296 (add_subdirectory): The binary directory /opt/opencv-3.3.1/build/modules/cudaarithm/.cudaarithm is already used to build a source directory. It cannot be used to build source directory /opt/opencv-3.3.1/opencv_contrib/modules/cudaarithm Specify a unique binary directory name. Call Stack (most recent call first): modules/CMakeLists.txt:7 (ocv_glob_modules)
都是类似以上的错误，过程参考here和here，还没有解决。
最后发现是系统有些文件不合适，删除之后再编译就ok啦。。。。发现这个不能解决根本问题。
编译通过但是编译测试程序的时候还是有问题，没有找到对应的文件，个人觉得应该注意opencv_contrib的版本here问题，正在测试。
最后还是两者的版本问题，两个版本一定要一致。
还有就是cmake那个步骤，这次使用的是绝对路径，不知道使用相对路径是否会出问题，试过的童鞋可以回答一下这个问题。
后来使用相同的版本安装编译之后，使用opencv_contrib中的samples中的例程进行测试，可以正常运行，即说明安装成功。
如果还有问题，可能是本身程序有什么BUG引起的，可以进行调试。
test code
/*---------------------------------------------- * Usage: * ./test 0 *--------------------------------------------------*/ #include <opencv2/core/utility.hpp> #include <opencv2/tracking.hpp> #include <opencv2/videoio.hpp> #include <opencv2/highgui.hpp> #include <iostream> #include <cstring> #include "samples_utility.hpp" using namespace std; using namespace cv; int main( int argc, char** argv ){ // show help if(argc<2){ cout<< " Usage: example_tracking_kcf <video_name>\n" " examples:\n" " example_tracking_kcf Bolt/img/%04.jpg\n" " example_tracking_kcf faceocc2.webm\n" << endl; return 0; } // create the tracker Ptr<Tracker> tracker = TrackerKCF::create(); // set input video std::string video = argv[1]; VideoCapture cap(0); Mat frame; // get bounding box cap >> frame; Rect2d roi= selectROI("tracker", frame, true, false); //quit if ROI was not selected if(roi.width==0 || roi.height==0) return 0; // initialize the tracker tracker->init(frame,roi); // do the tracking printf("Start the tracking process, press ESC to quit.\n"); for ( ;; ){ // get frame from the video cap >> frame; // stop the program if no more images if(frame.rows==0 || frame.cols==0) break; // update the tracking result bool isfound = tracker->update(frame,roi); if(!isfound) { cout << "The target has been lost...\n"; waitKey(0); return 0; } // draw the tracked object rectangle( frame, roi, Scalar( 255, 0, 0 ), 2, 1 ); // show image with the tracked object imshow("tracker",frame); //quit on ESC button if(waitKey(1)==27)break; } }