OpenCV3.3+contrib+VS2017+CMake+Win10

OpenCV3.3: http://opencv.org/releases.html 下载源文件

CMake：https://cmake.org/download/ 我下载的是3.9.2版本64位
contrib：https://github.com/opencv/opencv_contrib/tree/3.3.0

下载完成后解压OpenCV3.3和contrib到D:\openCV （路径可以自己决定） ,安装CMake

打开刚刚安装的CMake

按照图中的序号进行
1.选取opencv3.3的解压文件，我的是D:\openCV\opencv-3.3.0
2新建一个文件存放opencv编译后的文件，我的是D:\openCV\OpenCV
3.在第三步中选取“visual studio 15 2017 Win64”，然后确定即可。

然后等将近十分钟或者更慢，当完成之后将contrib的解压文件中的modules文件路径填到如下图所示的位置（我填的路径是D:\openCV\opencv_contrib-3.3.0\modules）

然后点击Generate即可。
稍等。。。。。。
完成之后，到刚刚新建的文件夹中，我的是D:\openCV\OpenCV
在其中用VS2017的方式打开OPENCV.sln

如上图右键“解决方案”选择重新生成解决方案
稍等。。。。。。

上一步完成后，右键INSTALL，选择“仅用于项目”，选择“仅生成INSTALL”
opencv编译好了，但由于在Release环境下所以生成的是仅用于Release环境的DLL文件，如果想在Debug模式下使用，需要在在VS下将Release改成Debug，然后重复在VS2017的步骤，这样就生成了可以在Debug模式下使用的DLL文件了。

VS2017配置opencv3.3并配置

打开小娜，查找“系统环境”点击“编辑系统环境变量”

如上图，点击“环境变量”

如上图，选择“系统变量”中的“Path”编辑

如上图，添加编译后生成的opencv文件中install文件的x64\vc15\bin文件路径，我的如图。

添加完后，重启计算机，使环境生效。

打开VS2017，
文件–>新建–>项目
选择“Windows控制台应用程序”

解决方案配置为debug（或Release），解决方案平台为x64

项目–>属性–>VC++目录–>包含目录

如上图，添加编译后在OpenCV目录中生成的install\include的路径 。 我的如图

在点击“库目录”，添加编译后在OpenCV中生成的install\x64\vc15\lib的目录。我的是 D:\openCV\OpenCV\install\x64\vc15\lib

完成后，点击右栏的“连接器”–>”输入”–>添加左栏的”附加依赖项”
Debug下，附加依赖项：
opencv_aruco330d.lib
opencv_bgsegm330d.lib
opencv_bioinspired330d.lib
opencv_calib3d330d.lib
opencv_ccalib330d.lib
opencv_core330d.lib
opencv_datasets330d.lib
opencv_dnn330d.lib
opencv_dpm330d.lib
opencv_face330d.lib
opencv_features2d330d.lib
opencv_flann330d.lib
opencv_fuzzy330d.lib
opencv_highgui330d.lib
opencv_img_hash330d.lib
opencv_imgcodecs330d.lib
opencv_imgproc330d.lib
opencv_line_descriptor330d.lib
opencv_ml330d.lib
opencv_objdetect330d.lib
opencv_optflow330d.lib
opencv_phase_unwrapping330d.lib
opencv_photo330d.lib
opencv_plot330d.lib
opencv_reg330d.lib
opencv_rgbd330d.lib
opencv_saliency330d.lib
opencv_shape330d.lib
opencv_stereo330d.lib
opencv_stitching330d.lib
opencv_structured_light330d.lib
opencv_superres330d.lib
opencv_surface_matching330d.lib
opencv_text330d.lib
opencv_tracking330d.lib
opencv_video330d.lib
opencv_videoio330d.lib
opencv_videostab330d.lib
opencv_viz330d.lib
opencv_xfeatures2d330d.lib
opencv_ximgproc330d.lib
opencv_xobjdetect330d.lib
opencv_xphoto330d.lib

Release下，附加依赖项;
opencv_aruco330.lib
opencv_bgsegm330.lib
opencv_bioinspired330.lib
opencv_calib3d330.lib
opencv_ccalib330.lib
opencv_core330.lib
opencv_datasets330.lib
opencv_dnn330.lib
opencv_dpm330.lib
opencv_face330.lib
opencv_features2d330.lib
opencv_flann330.lib
opencv_fuzzy330.lib
opencv_highgui330.lib
opencv_img_hash330.lib
opencv_imgcodecs330.lib
opencv_imgproc330.lib
opencv_line_descriptor330.lib
opencv_ml330.lib
opencv_objdetect330.lib
opencv_optflow330.lib
opencv_phase_unwrapping330.lib
opencv_photo330.lib
opencv_plot330.lib
opencv_reg330.lib
opencv_rgbd330.lib
opencv_saliency330.lib
opencv_shape330.lib
opencv_stereo330.lib
opencv_stitching330.lib
opencv_structured_light330.lib
opencv_superres330.lib
opencv_surface_matching330.lib
opencv_text330.lib
opencv_tracking330.lib
opencv_video330.lib
opencv_videoio330.lib
opencv_videostab330.lib
opencv_viz330.lib
opencv_xfeatures2d330.lib
opencv_ximgproc330.lib
opencv_xobjdetect330.lib
opencv_xphoto330.lib

程序测试：

#include <opencv2/opencv.hpp>

using namespace cv;

int main()
{
    Mat img = imread("2.jpg");
    imshow("1",img);
    waitKey(0);
    //getchar();
    return 0;
}

将一幅图片放入有main.c文件的文件夹中，重命名为“2.jpg”

运行！

结果：

完成！