資源簡(jiǎn)介
論文《Distinctive Image Features from Scale-Invariant Keypoints》和《Object Recognition from Local Scale-Invariant Features》及SIFT源代碼,代碼里附有詳細(xì)注釋。

代碼片段和文件信息
//vs2010+opencv2.2
//zdd
//Just?For?Fun
//zddmail@gmail.com
//2012年5月17日16:16:11
#include?
#include?
using?namespace?std;
#include?
#include?
#include?
using?namespace?cv;
#include?“sift.h“
int?main(int?argc?char?**argv)
{
Mat?src?=?imread(“jobs.jpg“);
Vector?features;
Sift(src?features?1.6);
DrawKeyPoints(src?features);
DrawSiftFeatures(src?features);
write_features(features?“descriptor1.txt“);
imshow(“src“?src);
waitKey();
return?0;
}
/*
int?main(int?argc?char?**argv)
{
Mat?src?=?imread(“l(fā)ena.jpg“);
Mat?gray?dst;
Mat?small;
ConvertToGray(src?gray);
DownSample(gray?dst);
// DownSample(dst?small);
Mat?up?up1;
// UpSample(small?up);
// Size?sz(gray.size().width/2?gray.size().height/2);
//resize(src?small?sz);
// resize(small?up1?small.size()*2);
// imshow(“up1“?up1);
// imshow(“up“?up);
Mat?gau?gau1;
int?start?=?GetTickCount();
GaussianBlur(src?gau?Size(00)?16);?
cout?<“GaussianBlur:?“< imshow(“gau“?gau);
// cvSmooth(gray?gau1?2?00?0.0?0.0);
// GaussianBlur(gray?gau1?Size(00)?0.0);?
// imshow(“gau1“?gau1);
Mat?gauss;
start?=?GetTickCount();
GaussianTemplateSmooth(gray?gauss?0.0);
cout?<“GaussianTemplateSmooth:?“< imshow(“gauss“?gauss);
// imwrite(“dst.jpg“?dst);
// imwrite(“gauss.jpg“?gauss);
//0.84089642
Mat?gs;
start?=?GetTickCount();
GaussianSmooth(src?gs?16);
cout?<“GaussianSmooth:?“< imshow(“gs“?gs);
// imwrite(“small.jpg“?small);
// imwrite(“gs.jpg“?gs);
Mat?g1;
start?=?GetTickCount();
GaussianSmooth2D(gray?g1?16);
cout?<“GaussianSmooth2D:?“< imshow(“g1“?g1);
// imwrite(“g1.jpg“?g1);
if(src.empty()?||?gray.empty()?||?dst.empty())
return?-1;
// imshow(“src“?src);
imshow(“gray“?gray);
imshow(“dst“?dst);
waitKey();
return?0;
}
*/
?屬性????????????大小?????日期????時(shí)間???名稱
-----------?---------??----------?-----??----
?????文件?????515656??2017-11-04?21:40??SIFT\Distinctive?Image?Features.pdf
?????文件?????231933??2017-11-04?21:35??SIFT\ob
?????文件?????174080??2018-02-06?18:49??SIFT\sift\Debug\sift.exe
?????文件?????918400??2018-02-06?18:49??SIFT\sift\Debug\sift.ilk
?????文件????2437120??2018-02-06?18:49??SIFT\sift\Debug\sift.pdb
?????文件???????6504??2012-05-16?21:55??SIFT\sift\exe\aa.jpg
?????文件??????40557??2012-05-17?16:21??SIFT\sift\exe\desc
?????文件?????159232??2012-05-17?16:17??SIFT\sift\exe\sift.exe
?????文件????????242??2012-05-17?16:23??SIFT\sift\readme.txt
?????文件???????6504??2012-05-16?21:55??SIFT\sift\sift\aa.jpg
?????文件???????5764??2012-04-28?16:04??SIFT\sift\sift\bbb.jpg
?????文件?????786486??2006-05-10?11:04??SIFT\sift\sift\dd.jpg
?????文件?????228655??2018-02-06?18:14??SIFT\sift\sift\Debug\main.obj
?????文件???????4444??2018-02-06?18:49??SIFT\sift\sift\Debug\sift.log
?????文件?????606283??2018-02-06?18:49??SIFT\sift\sift\Debug\sift.obj
?????文件???????1362??2018-02-06?18:49??SIFT\sift\sift\Debug\sift.tlog\cl.command.1.tlog
?????文件??????56268??2018-02-06?18:49??SIFT\sift\sift\Debug\sift.tlog\CL.read.1.tlog
?????文件???????1762??2018-02-06?18:49??SIFT\sift\sift\Debug\sift.tlog\CL.write.1.tlog
?????文件???????2984??2018-02-06?18:49??SIFT\sift\sift\Debug\sift.tlog\li
?????文件???????7744??2018-02-06?18:49??SIFT\sift\sift\Debug\sift.tlog\li
?????文件????????612??2018-02-06?18:49??SIFT\sift\sift\Debug\sift.tlog\li
?????文件????????195??2018-02-06?18:49??SIFT\sift\sift\Debug\sift.tlog\sift.lastbuildstate
?????文件????1141760??2018-02-06?18:49??SIFT\sift\sift\Debug\vc120.idb
?????文件????1339392??2018-02-06?18:49??SIFT\sift\sift\Debug\vc120.pdb
?????文件??????65968??2017-12-22?17:46??SIFT\sift\sift\desc
?????文件??????65968??2018-02-06?18:49??SIFT\sift\sift\desc
?????文件??????82187??2018-02-06?18:49??SIFT\sift\sift\dogpyramid\0.jpg
?????文件??????78112??2018-02-06?18:49??SIFT\sift\sift\dogpyramid\1.jpg
?????文件???????8944??2018-02-06?18:49??SIFT\sift\sift\dogpyramid\10.jpg
?????文件???????8628??2018-02-06?18:49??SIFT\sift\sift\dogpyramid\11.jpg
............此處省略120個(gè)文件信息
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