基于TLD算法和GOTURN算法的多摄像头目标跟踪.zip

"# MultiCameraTargetTracking" # 使用前务必仔细阅读此文件！ ## 开发环境 - 操作系统：Ubuntu 16.04 - OpenCV版本：OpenCV-3.4.5 ## 一、安装OpenCV     由于只有OpenCV 3.0以后的版本才有目标跟踪的功能，自从进入3.X时代以后，OpenCV将代码库分成了两部分，分别是稳定的核心功能库和试验性质的contrib库。下面是OpenCV + Contrib的编译与安装过程。 ### 1.下载OpenCV和Contrib：     Contrib没有在OpenCV的官网发布，而是发布在了OpenCV的github上，需要注意的是OpenCV和Contrib的版本要对应，不然无法编译安装。OpenCV和Contrib的源代码都可以在OpenCV的github上下载到，下载连接： - [OpenCV](https://github.com/opencv/opencv/archive/3.4.5.zip) - [Contrib](https://github.com/opencv/opencv_contrib/archive/3.4.5.zip) ### 2.编译安装： 准备，先安装以下依赖包： ``` bash sudo apt-get install build-essential sudo apt-get install cmake git libgtk2.0-dev pkg-config libavcodec-dev libavformat-dev libswscale-dev sudo apt-get install python-dev python-numpy libtbb2 libtbb-dev libjpeg-dev libpng-dev libtiff-dev libjasper-dev libdc1394-22-dev sudo apt-get install build-essential qt5-default ccache libv4l-dev libavresample-dev libgphoto2-dev libopenblas-base libopenblas-dev doxygen openjdk-8-jdk pylint libvtk6-dev sudo apt-get install pkg-config ``` 编译： （1）解压下载好的源代码： ``` bash sudo unzip opencv-3.3.1.zip sudo unzip opencv_contrib-3.3.1.zip ``` （2）解压完后需要将opencv_contrib.zip提取到opencv目录下，同时在该目录下新建一个文件夹build： ``` bash sudo cp -r opencv_contrib-3.3.1 opencv-3.3.1 #复制opencv_contrib到opencv目录下 cd opencv-3.3.1 sudo mkdir build #新建文件夹build ``` （3）进入build目录，并且执行cmake生成makefile文件： ``` bash sudo cmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_INSTALL_PREFIX=/usr/local -D OPENCV_EXTRA_MODULES_PATH=/home/user_name/opencv-3.4.3/opencv_contrib-3.4.3/modules/ .. ``` 注意：OPENCV_EXTRA_MODULES_PATH就是 opencv_contrib-3.3.1下面的modules目录，请按照自己的实际目录修改地址。接下来就是漫长的等待了…… （4）在cmake成功之后，就可以在build文件下make了： ``` bash make ``` 接下来就是更漫长的等待了……make成功后再执行`make install`就ok了！ （5）链接库共享： 编译安装完毕之后，为了让你的链接库被系统共享，让编译器发现，需要执行管理命令ldconfig： ``` bash sudo ldconfig -v ``` Ubuntu16.04会报错： ``` Scanning dependencies of target opencv_test_superres //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `TIFFReadDirectory@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `TIFFGetFieldDefaulted@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `TIFFNumberOfDirectories@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `TIFFIsTiled@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `TIFFOpen@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `TIFFDefaultStripSize@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `TIFFReadRGBAImage@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `TIFFReadTile@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `TIFFSetField@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `TIFFWriteScanline@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `_TIFFfree@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `TIFFGetField@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `TIFFScanlineSize@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `TIFFSetWarningHandler@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `TIFFTileSize@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `_TIFFmalloc@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `TIFFSetErrorHandler@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `TIFFSetDirectory@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `TIFFReadScanline@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `TIFFClose@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `TIFFNumberOfTiles@LIBTIFF_4.0' //usr/lib/x86_64-linux-gnu/libvtkIOImage-6.2.so.6.2: undefined reference to `TIFFClientOpen@LIBTIFF_4.0' [ 74%] Building CXX object modules/imgcodecs/CMakeFiles/opencv_perf_imgcodecs.dir/perf/perf_main.cpp.o [ 74%] Building CXX object modules/shape/CMakeFiles/opencv_test_shape.dir/test/test_main.cpp.o [ 74%] Building CXX object modules/highgui/CMakeFiles/opencv_test_highgui.dir/test/test_main.cpp.o [ 75%] Building CXX object modules/superres/CMakeFiles/opencv_test_superres.dir/test/test_main.cpp.o [ 75%] Building CXX object modules/videoio/CMakeFiles/opencv_perf_videoio.dir/perf/perf_main.cpp.o [ 75%] Building CXX object modules/videoio/CMakeFiles/opencv_test_videoio.dir/test/test_main.cpp.o collect2: error: ld returned 1 exit status modules/viz/CMakeFiles/opencv_test_viz.dir/build.make:233: recipe for target 'bin/opencv_test_viz' failed make[2]: *** [bin/opencv_test_viz] Error 1 CMakeFiles/Makefile2:5627: recipe for target 'modules/viz/CMakeFiles/opencv_test_viz.dir/all' failed make[1]: *** [modules/viz/CMakeFiles/opencv_test_viz.dir/all] Error 2 make[1]: *** Waiting for unfinished jobs... ``` 解决办法： ``` bash sudo apt-get autoremove libtiff5-dev sudo apt-get install libtiff5-dev ``` ### 3.测试 ``` bash # 进入opencv-2.4.13/samples/c/example_cmake cd opencv-2.4.13/samples/c/example_cmake # 编译 cmake make # 编译之后会生成可执行文件opencv_example，运行 ./opencv_example # 运行结果为摄像头拍摄并在画布上显示hello opencv ``` ## 二、编译源代码     首先下载源代码，并解压，进入解压后的目录。新建build目录并进入build： ``` bash mkdir build cd build ```     然后用cmake进行编译： ``` bash cmake ../src/ make ```     make命令执行成功后会在build目录下生成bin文件夹，进入bin文件夹就可以运行可执行文件了。 首先要下载已经训练好的caffe模型，并放在bin目录下，已经下训练好的模型链接如下： 链接：https://pan.baidu.com/s/1nq9g4l3ttNm5qBU0pJA64Q 提取码：j3td 同时，这个链接中也包含了两个演示视频。 然后运行以下命令运行程序： ``` bash ./run -p ../parameters.yml -s ../datasets/06_car/car.mpg # -p用来指定tld算法的参数文件 -s选项用来选择传入的视频文件，可以连续输入多个视频做跨摄像头目标跟踪 ``` ### 三、联系方式 - 邮箱：[email protected] - QQ：1725805106