資源簡介
基于OpenCV的圖像分類技術,非監督分類中常用方法,簡單實用

代碼片段和文件信息
//?Classify.cpp?:?定義控制臺應用程序的入口點。
//
#include?“stdafx.h“
#include?
#include?“opencv2/core/core.hpp“
#include?“opencv2/imgproc/imgproc.hpp“
#include?“opencv2/highgui/highgui.hpp“
#include?“opencv2/ml/ml.hpp“
#include?
using?namespace?std;
using?namespace?cv;
int?main(int?argc?_TCHAR*?argv[])
{
char?*?path?=?_T(“lena.jpg“);
int?i?=?_access(path?0);
Mat?src_img?=?imread(path?CV_LOAD_IMAGE_UNCHANGED);//讀圖像
int?width_src?=?src_img.cols;
int?height_src?=?src_img.rows;
Mat?samples?=?Mat::zeros(width_src*height_src?1?CV_32FC3);//創建樣本矩陣,CV_32FC3代表32位浮點3通道(彩色圖像)
Mat?clusters;//類別標記矩陣
int?k?=?0;
for?(int?i?=?0;?i {
for?(int?j?=?0;?j {
//將像素點三通道的值按順序排入樣本矩陣
samples.at(k?0)[0]?=?(float)src_img.at(i?j)[0];
samples.at(k?0)[1]?=?(float)src_img.at(i?j)[1];
samples.at(k?0)[2]?=?(float)src_img.at(i?j)[2];
}
}
int?nCuster?=?10;//聚類類別數,自己修改。
//聚類,KMEANS?PP?CENTERS?Use?kmeans++?center?initialization?by?Arthur?and?Vassilvitskii
kmeans(samples?nCuster?clusters?TermCriteria(CV_TERMCRIT_EPS?+?CV_TERMCRIT_ITER?10?1.0)?1?KMEANS_PP_CENTERS);
//顯示聚類結果
Mat?result?=?Mat::zeros(height_src?width_src?CV_8UC1);
k?=?0;
int?val?=?0;
float?step?=?255?/?(nCuster?-?1);
for?(int?i?=?0;?i {
for?(int?j?=?0;?j {
val?=?255?-?clusters.at(k?0)*step;//int
result.at(i?j)?=?val;
}
}
imshow(“原始圖像“?src_img);
imshow(“聚類結果“?result);
waitKey(0);
return?0;
}
?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----
?????文件??????87040??2019-01-05?16:43??ImageClassify\Debug\ImageClassify.exe
?????文件?????558420??2019-01-05?16:43??ImageClassify\Debug\ImageClassify.ilk
?????文件????2101248??2019-01-05?16:43??ImageClassify\Debug\ImageClassify.pdb
?????文件????????416??2019-01-05?16:04??ImageClassify\ImageClassify\Debug\ImageClassify.Build.CppClean.log
?????文件???????1822??2019-01-05?16:43??ImageClassify\ImageClassify\Debug\ImageClassify.log
?????文件?????289376??2019-01-05?16:43??ImageClassify\ImageClassify\Debug\ImageClassify.obj
?????文件????????606??2019-01-05?16:43??ImageClassify\ImageClassify\Debug\ImageClassify.tlog\cl.command.1.tlog
?????文件??????32548??2019-01-05?16:43??ImageClassify\ImageClassify\Debug\ImageClassify.tlog\CL.read.1.tlog
?????文件????????568??2019-01-05?16:43??ImageClassify\ImageClassify\Debug\ImageClassify.tlog\CL.write.1.tlog
?????文件????????170??2019-01-05?16:43??ImageClassify\ImageClassify\Debug\ImageClassify.tlog\ImageClassify.lastbuildstate
?????文件???????1368??2019-01-05?16:43??ImageClassify\ImageClassify\Debug\ImageClassify.tlog\li
?????文件???????2940??2019-01-05?16:43??ImageClassify\ImageClassify\Debug\ImageClassify.tlog\li
?????文件????????528??2019-01-05?16:43??ImageClassify\ImageClassify\Debug\ImageClassify.tlog\li
?????文件?????871424??2019-01-05?16:43??ImageClassify\ImageClassify\Debug\vc120.idb
?????文件?????708608??2019-01-05?16:43??ImageClassify\ImageClassify\Debug\vc120.pdb
?????文件???????1699??2019-01-05?16:43??ImageClassify\ImageClassify\ImageClassify.cpp
?????文件???????3942??2019-01-05?16:38??ImageClassify\ImageClassify\ImageClassify.vcxproj
?????文件???????1278??2019-01-05?16:07??ImageClassify\ImageClassify\ImageClassify.vcxproj.filters
?????文件??????91814??2010-12-05?06:13??ImageClassify\ImageClassify\lena.jpg
?????文件????2010624??2010-12-05?10:38??ImageClassify\ImageClassify\opencv_core220.dll
?????文件????3589632??2010-12-05?10:37??ImageClassify\ImageClassify\opencv_core220d.dll
?????文件?????776192??2010-12-05?10:38??ImageClassify\ImageClassify\opencv_highgui220.dll
?????文件????1716224??2010-12-05?08:45??ImageClassify\ImageClassify\opencv_highgui220d.dll
?????文件?????????80??2019-01-05?16:04??ImageClassify\ImageClassify\stdafx.h
?????文件????????234??2019-01-05?16:04??ImageClassify\ImageClassify\targetver.h
?????文件???37552128??2019-01-05?17:09??ImageClassify\ImageClassify.sdf
?????文件????????985??2019-01-05?15:59??ImageClassify\ImageClassify.sln
????..A..H.?????23040??2019-01-05?17:09??ImageClassify\ImageClassify.v12.suo
?????目錄??????????0??2019-01-05?16:43??ImageClassify\ImageClassify\Debug\ImageClassify.tlog
?????目錄??????????0??2019-01-05?16:43??ImageClassify\ImageClassify\Debug
............此處省略6個文件信息
評論
共有 條評論