凯里市建设局网站,腾讯微信公众号,长春seo网站建设费用,李贤威wordpress建站教程目录opencv_contrib的获取主要工具编译 opencv编译 opencv_contribVisual Studio 编译配置新项目的环境添加包含目录添加库目录配置调试环境添加依赖项测试平台#xff1a;Windows 10 20H2 Visual Studio 2015 opencv_contrib-3.4.12 参考文章#xff1a; 添加OpenCV_contr…
目录opencv_contrib的获取主要工具编译 opencv编译 opencv_contribVisual Studio 编译配置新项目的环境添加包含目录添加库目录配置调试环境添加依赖项测试平台Windows 10 20H2 Visual Studio 2015 opencv_contrib-3.4.12 参考文章 添加OpenCV_contrib库至OpenCV3.1.0中Windows 64位 环境下编译OpenCV3.1.0和OpenCV_contrib—— MICHAEL_LIU opencv_contrib安装笔记 —— weijifen000 Releases - OpenCV上的OpenCV所包含的库只有基础内容而人脸识别、matlab调用、RGB加工、深层神经网络等内容则需要安装opencv_contrib。
opencv_contrib的获取 Githubopencv/opencv_contrib
主要工具
Cmake我下载的安装包是cmake-3.21.2-windows-x86_64.msi。opencv 和 opencv_contrib版本要一致我安装的版本是3.4.12。Visual Studio我所用的版本是2015。
编译 opencv 使用cmake的时候需使用python 2.7否则之后貌似会有警告。 使用Anaconda3建立环境后进入python 2.7环境。 在python 2.7环境下打开cmake Where is the source code内填入opencv解压目录下的 sources 文件夹路径 Where to build the binaries内填入输出路径 点击Configure 选择所用的Visual Studio版本和系统平台 确认下方框内无红色警告 若有警告打开警告位置的日志文件 查找cmake_download字符串其后第一个路径是文件放置位置第二个网址是下载地址 缺的文件会由于下载失败变成0kb的文件 下载后改成相同的名字将其替换 之后再次点击Configure确认上下方都没红色警告且提示Configuring done 之后点击Generate出现Generating done
编译 opencv_contrib 在 search 对话框中输入 OPENCV_EXTRA_MODULES_PATH找到OPENCV_EXTRA_MODULES_PATH后在value中填入opencv_contrib解压目录下的modules路径反斜杠\要改成正斜杠/ 在 search 对话框中输入 OPENCV_ENABLE_NONFREE 在value值中勾选以允许使用已申请专利的算法之后再次点击Configure。 出现Configuring done后点击Generate 等待出现Generating done
Visual Studio 编译
点击 Open Project 选择 生成-批生成 勾选ALL_BUILD和INSTALL的Debug和Release配置之后点击生成 等待编译完成最终生成的文件不小 此后该文件夹也可移动到别的地方
配置新项目的环境
新建要用的项目 配置项目的属性 配置选为所有配置平台为之前所选的平台
添加包含目录
VC目录-包含目录 添加输出文件夹下install\include文件夹及其子文件夹的路径 添加库目录
VC目录-库目录 其路径为输出文件夹下/install/x64/vc14/lib文件夹的路径 点击应用
配置调试环境
调试-环境 添加 PATHD:\Work\OpenCV\opencv-3.4.12_build\install\x64\vc14\bin;%PATH% 路径为输出文件夹下\install\x64\vc14\bin文件夹的路径 点击应用 添加依赖项
分别配置Debug、Release下的 链接器-输入-附加依赖项 加入lib文件夹下的以.lib结尾的库文件名 其中以d.dll结尾的为Debug时需要的库 不带’d’的则为Release时需要的库
这些文件名可用如下python脚本提取filePath为lib文件夹的路径
import os
filePath rD:\Work\OpenCV\opencv-3.4.12_build\install\x64\vc14\libDebugLibList []
ReleaseLibList []for _ in os.listdir(filePath):if _.endswith(d.lib):DebugLibList.append(_)elif _.endswith(.lib):ReleaseLibList.append(_)print(DebugLibList:\n)
for _ in DebugLibList:print(_)print(\nReleaseLibList:\n)
for _ in ReleaseLibList:print(_)在本例中 Debug的库为
opencv_aruco3412d.lib
opencv_bgsegm3412d.lib
opencv_bioinspired3412d.lib
opencv_calib3d3412d.lib
opencv_ccalib3412d.lib
opencv_core3412d.lib
opencv_datasets3412d.lib
opencv_dnn3412d.lib
opencv_dnn_objdetect3412d.lib
opencv_dpm3412d.lib
opencv_face3412d.lib
opencv_features2d3412d.lib
opencv_flann3412d.lib
opencv_fuzzy3412d.lib
opencv_hdf3412d.lib
opencv_hfs3412d.lib
opencv_highgui3412d.lib
opencv_imgcodecs3412d.lib
opencv_imgproc3412d.lib
opencv_img_hash3412d.lib
opencv_line_descriptor3412d.lib
opencv_ml3412d.lib
opencv_objdetect3412d.lib
opencv_optflow3412d.lib
opencv_phase_unwrapping3412d.lib
opencv_photo3412d.lib
opencv_plot3412d.lib
opencv_reg3412d.lib
opencv_rgbd3412d.lib
opencv_saliency3412d.lib
opencv_shape3412d.lib
opencv_stereo3412d.lib
opencv_stitching3412d.lib
opencv_structured_light3412d.lib
opencv_superres3412d.lib
opencv_surface_matching3412d.lib
opencv_text3412d.lib
opencv_tracking3412d.lib
opencv_video3412d.lib
opencv_videoio3412d.lib
opencv_videostab3412d.lib
opencv_xfeatures2d3412d.lib
opencv_ximgproc3412d.lib
opencv_xobjdetect3412d.lib
opencv_xphoto3412d.libRelease的库为
opencv_aruco3412.lib
opencv_bgsegm3412.lib
opencv_bioinspired3412.lib
opencv_calib3d3412.lib
opencv_ccalib3412.lib
opencv_core3412.lib
opencv_datasets3412.lib
opencv_dnn3412.lib
opencv_dnn_objdetect3412.lib
opencv_dpm3412.lib
opencv_face3412.lib
opencv_features2d3412.lib
opencv_flann3412.lib
opencv_fuzzy3412.lib
opencv_hdf3412.lib
opencv_hfs3412.lib
opencv_highgui3412.lib
opencv_imgcodecs3412.lib
opencv_imgproc3412.lib
opencv_img_hash3412.lib
opencv_line_descriptor3412.lib
opencv_ml3412.lib
opencv_objdetect3412.lib
opencv_optflow3412.lib
opencv_phase_unwrapping3412.lib
opencv_photo3412.lib
opencv_plot3412.lib
opencv_reg3412.lib
opencv_rgbd3412.lib
opencv_saliency3412.lib
opencv_shape3412.lib
opencv_stereo3412.lib
opencv_stitching3412.lib
opencv_structured_light3412.lib
opencv_superres3412.lib
opencv_surface_matching3412.lib
opencv_text3412.lib
opencv_tracking3412.lib
opencv_video3412.lib
opencv_videoio3412.lib
opencv_videostab3412.lib
opencv_xfeatures2d3412.lib
opencv_ximgproc3412.lib
opencv_xobjdetect3412.lib
opencv_xphoto3412.lib测试
来自Opencv3.1.0opencv_contrib配置及使用SIFT测试 —— 陈纪建
opencv 3中SIFT匹配是在opencv_contrib库中的这里我们就用它来做一个简单的测试。
#include iostream
#include opencv2/opencv.hpp //头文件
#include opencv2/xfeatures2d.hppusing namespace cv; //包含cv命名空间
using namespace std;
using namespace xfeatures2d;int main()
{//Create SIFT class pointerPtrFeature2D f2d SIFT::create();//读入图片Mat img_1 imread(D:/Work/OpenCV/Workplace/Robot/Robot/1.jpg);Mat img_2 imread(D:/Work/OpenCV/Workplace/Robot/Robot/2.jpg);//Detect the keypointsvectorKeyPoint keypoints_1, keypoints_2;f2d-detect(img_1, keypoints_1);f2d-detect(img_2, keypoints_2);//Calculate descriptors (feature vectors)Mat descriptors_1, descriptors_2;f2d-compute(img_1, keypoints_1, descriptors_1);f2d-compute(img_2, keypoints_2, descriptors_2);//Matching descriptor vector using BFMatcherBFMatcher matcher;vectorDMatch matches;matcher.match(descriptors_1, descriptors_2, matches);//绘制匹配出的关键点Mat img_matches;drawMatches(img_1, keypoints_1, img_2, keypoints_2, matches, img_matches);imshow(match图, img_matches);//等待任意按键按下waitKey(0);
}测试结果如下
