OpenCV - Windows(win10)编译opencv + opencv_contrib

  在之前的几篇文章中,我提到了在Android、Linux中编译opencv + opencv_contrib,这篇文章主要讲在Windows中编译opencv + opencv_contrib。

首先需要准备的环境有:

  将下载得到的OpenCV Windows包解压,目录为opencv,然后将下载的OpenCV_Contrib包解压放入opencv目录下,新建new_build文件夹(用来放编译之后结果):

    OpenCV - Windows(win10)编译opencv + opencv_contrib

使用cmake生成OpenCV.sln:

  打开安装之后的cmake,在where is the source code中选择openCV的源代码目录:F:\opencv\sources;在where to build the binaries中选择编译为Visual Studio项目的目录:F:\opencv\new_build(这里我选择刚刚特地建立的new_build目录),如下图所示:

    OpenCV - Windows(win10)编译opencv + opencv_contrib

  点击Configure按钮后,弹出对话框,选择编译器,根据本地计算机的CPU架构,这里特别要注意的是,自己机器上是否装有相应的VS版本,如果没有装,还是要编译就会出错,可能是找不到对应的工具原因,以及选择X86和X64),这里用的是VS 2015。

    OpenCV - Windows(win10)编译opencv + opencv_contrib

  设置完成之后点击“Generate”开始生成工程,.第一次编译完成之后,我们需要将额外的opencv_contrib加到工程中进行第二次编译,在配置表中找到“OPENCV_EXTRA_MODULES_PATH”,设置其参数值为open_contrib源码包中的modles目录,我的目录是“F:\opencv\opencv_contrib\modules”:

    OpenCV - Windows(win10)编译opencv + opencv_contrib

  再次点击“Generate”进行第二次编译:

    OpenCV - Windows(win10)编译opencv + opencv_contrib

  这时候我们已经可以看见用cmake工具编译得到的OpenCV.sln:

    OpenCV - Windows(win10)编译opencv + opencv_contrib

用VS打开OpenCV.sln工程,编译生成Debug和Release库:

  用VS 2015打开OpenCV.sln工程,在解决方案中可以查看工程目录:

    OpenCV - Windows(win10)编译opencv + opencv_contrib

  编译生成debug版本的库,记得在此之前要选择编译的平台信息,这就是编译生成debug版本和release版本的区别,也可以选择release,因为自己的工程可能要用到相应的动态链接库:

    OpenCV - Windows(win10)编译opencv + opencv_contrib

  在解决方案中选中工程,右键选择重新生成解决方案:

    OpenCV - Windows(win10)编译opencv + opencv_contrib

  编译成功:

    OpenCV - Windows(win10)编译opencv + opencv_contrib

  .找到CMakeTargets中的INSTALL,然后右键选择“仅限于项目”-->“仅生成INSTALL”:

    OpenCV - Windows(win10)编译opencv + opencv_contrib

  完成编译后,Release模式下同理。此时,有了install目录。该目录包含了我们需要的头文件、库文件。

    OpenCV - Windows(win10)编译opencv + opencv_contrib

把新的库文件配置到到项目中:

  VC++目录-->包含目录,添加:

    E:\OpenCV320\opencv\new_build\install\include

  VC++目录-->库目录,添加:

    E:\OpenCV320\opencv\new_build\install\x64\vc14\lib

  链接器-->输入-->附加依赖项,添加: (注意添加的库与编译选项要一致,需要注意debug比release的文件名多了个d)

    opencv_aruco320.lib

    opencv_aruco320d.lib

    opencv_bgsegm320.lib
    opencv_bgsegm320d.lib
    opencv_bioinspired320.lib
    opencv_bioinspired320d.lib
    opencv_calib3d320.lib
    opencv_calib3d320d.lib
    opencv_ccalib320.lib
    opencv_ccalib320d.lib
    opencv_core320.lib
    opencv_core320d.lib
    opencv_datasets320.lib
    opencv_datasets320d.lib
    opencv_dnn320.lib
    opencv_dnn320d.lib
    opencv_dpm320.lib
    opencv_dpm320d.lib
    opencv_face320.lib
    opencv_face320d.lib
    opencv_features2d320.lib
    opencv_features2d320d.lib
    opencv_flann320.lib
    opencv_flann320d.lib
    opencv_fuzzy320.lib
    opencv_fuzzy320d.lib
    opencv_highgui320.lib
    opencv_highgui320d.lib
    opencv_imgcodecs320.lib
    opencv_imgcodecs320d.lib
    opencv_line_descriptor320.lib
    opencv_line_descriptor320d.lib
    opencv_ml320.lib
    opencv_ml320d.lib
    opencv_objdetect320.lib
    opencv_objdetect320d.lib
    opencv_optflow320.lib
    opencv_optflow320d.lib
    opencv_phase_unwrapping320.lib
    opencv_phase_unwrapping320d.lib
    opencv_photo320.lib
    opencv_photo320d.lib
    opencv_plot320.lib
    opencv_plot320d.lib
    opencv_reg320.lib
    opencv_reg320d.lib
    opencv_rgbd320.lib
    opencv_rgbd320d.lib
    opencv_saliency320.lib
    opencv_saliency320d.lib
    opencv_shape320.lib
    opencv_shape320d.lib
    opencv_stereo320.lib
    opencv_stereo320d.lib
    opencv_stitching320.lib
    opencv_stitching320d.lib
    opencv_structured_light320.lib
    opencv_structured_light320d.lib
    opencv_superres320.lib
    opencv_superres320d.lib
    opencv_surface_matching320.lib
    opencv_surface_matching320d.lib
    opencv_text320.lib
    opencv_text320d.lib
    opencv_tracking320.lib
    opencv_tracking320d.lib
    opencv_video320.lib
    opencv_video320d.lib
    opencv_videoio320.lib
    opencv_videoio320d.lib
    opencv_videostab320.lib
    opencv_videostab320d.lib
    opencv_xfeatures2d320.lib
    opencv_xfeatures2d320d.lib
    opencv_ximgproc320.lib
    opencv_ximgproc320d.lib
    opencv_xobjdetect320.lib
    opencv_xobjdetect320d.lib
    opencv_xphoto320.lib
    opencv_xphoto320d.lib
    kernel32.lib
    user32.lib
    gdi32.lib
    winspool.lib
    comdlg32.lib
    advapi32.lib
    shell32.lib
    ole32.lib
    oleaut32.lib
    uuid.lib
    odbc32.lib
    odbccp32.lib

  这样,我们就可以在VS中使用OpenCV了。

  需要提到的一个点,所需要使用Sift等算法,需要引入xfeatures2d命名空间:

using namespace xfeatures2d;

  

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