#include "opencv2\opencv.hpp"
#include <stdio.h>
#include <opencv2/legacy/legacy.hpp>
#include <opencv2/objdetect/objdetect.hpp>
#include <opencv2/nonfree/nonfree.hpp>
#include <opencv2/nonfree/features2d.hpp>
using namespace std;
using namespace cv;
//
int main( )
{
//source image
char* img1_file = "C:/images/box.png";
char* img2_file = "C:/images/box.png";
// image read
Mat tmp = cv::imread( img1_file, 1 );
Mat in = cv::imread( img2_file, 1 );
/* threshold = 0.04;
edge_threshold = 10.0;
magnification = 3.0; */
// SIFT feature detector and feature extractor
cv::SiftFeatureDetector detector( 0.05, 5.0 );
cv::SiftDescriptorExtractor extractor( 3.0 );
/* In case of SURF, you apply the below two lines
cv::SurfFeatureDetector detector();
cv::SurfDescriptorExtractor extractor();
*/
// Feature detection
std::vector keypoints1, keypoints2;
detector.detect( tmp, keypoints1 );
detector.detect( in, keypoints2 );
// Feature display
Mat feat1,feat2;
drawKeypoints(tmp,keypoints1,feat1,Scalar(255, 255, 255),DrawMatchesFlags::DRAW_RICH_KEYPOINTS);
drawKeypoints(in,keypoints2,feat2,Scalar(255, 255, 255),DrawMatchesFlags::DRAW_RICH_KEYPOINTS);
imwrite( "feat1.bmp", feat1 );
imwrite( "feat2.bmp", feat2 );
int key1 = keypoints1.size();
int key2 = keypoints2.size();
printf("Keypoint1=%d \nKeypoint2=%d", key1, key2);
// Feature descriptor computation
Mat descriptor1,descriptor2;
extractor.compute( tmp, keypoints1, descriptor1 );
extractor.compute( in, keypoints2, descriptor2 );
/*int desc1 = descriptor1.size;
int desc2 = descriptor2.size;
printf("Descriptor1=%d \nDescriptor2=%d", desc1, desc2);*/
// corresponded points
std::vector matches;
// L2 distance based matching. Brute Force Matching
BruteForceMatcher<L2 > matcher;
// Flann-based matching
//FlannBasedMatcher matcher;
// display of corresponding points
matcher.match( descriptor1, descriptor2, matches );
// matching result
Mat result;
drawMatches( tmp, keypoints1, in, keypoints2, matches, result );
// output file
imwrite( "result.bmp", result );
// display the result
namedWindow("SIFT", CV_WINDOW_AUTOSIZE );
imshow("SIFT", result);
waitKey(0); //press any key to quit
return 0;
}
Input image:
Result:
Catatan Fahmi 
Posted by SURF-based Image Recognition « Catatan Fahmi on December 11, 2012 at 10:23 am
[…] [OpenCV] SIFT implementation in OpenCV 2.4 […]
Posted by mezguich med amine on December 14, 2012 at 10:50 am
I tried the code in code blocks but it does not work
C:\Users\hp\Desktop\Test IMPL\Test6\main.cpp:37: error: missing template arguments before ‘keypoints1’
Posted by Daniel on May 1, 2013 at 12:42 pm
I had the same error code… problema with std::vector
Posted by Daniel on May 1, 2013 at 1:07 pm
Note: I am using Opencv 2.4.5
Correct code:
————————————–
#include “opencv2\opencv.hpp”
#include
#include
#include
#include
#include
using namespace std;
using namespace cv;
//
int main( )
{
//source image
//modify!!!!
char* img1_file = “D:\\CodeBlocks\\Fotos\\fachada-do-predio.jpg”;
char* img2_file = “D:\\CodeBlocks\\Fotos\\fachada-do-predio.jpg”;
// image read
Mat tmp = cv::imread( img1_file, 1 );
Mat in = cv::imread( img2_file, 1 );
/* threshold = 0.04;
edge_threshold = 10.0;
magnification = 3.0; */
// SIFT feature detector and feature extractor
cv::SiftFeatureDetector detector( 0.05, 5.0 );
cv::SiftDescriptorExtractor extractor( 3.0 );
//In case of SURF, you apply the below two lines
//cv::SurfFeatureDetector detector();
//cv::SurfDescriptorExtractor extractor();
// Feature detection
std::vector keypoints1, keypoints2;
detector.detect( tmp, keypoints1 );
detector.detect( in, keypoints2 );
// Feature display
Mat feat1,feat2;
drawKeypoints(tmp,keypoints1,feat1,Scalar(255, 255, 255),DrawMatchesFlags::DRAW_RICH_KEYPOINTS);
drawKeypoints(in,keypoints2,feat2,Scalar(255, 255, 255),DrawMatchesFlags::DRAW_RICH_KEYPOINTS);
//modify!!!!
imwrite( “D:\\CodeBlocks\\Fotos\\template_matching2.jpg”, feat1 ); //modify to use your img
imwrite( “D:\\CodeBlocks\\Fotos\\template_matching2.jpg”, feat2 ); //modify to use your img
int key1 = keypoints1.size();
int key2 = keypoints2.size();
printf(“Keypoint1=%d \nKeypoint2=%d”, key1, key2);
// Feature descriptor computation
Mat descriptor1,descriptor2;
extractor.compute( tmp, keypoints1, descriptor1 );
extractor.compute( in, keypoints2, descriptor2 );
/*int desc1 = descriptor1.size;
int desc2 = descriptor2.size;
printf(“Descriptor1=%d \nDescriptor2=%d”, desc1, desc2);*/
// corresponded points
std::vector matches;
// L2 distance based matching. Brute Force Matching
BruteForceMatcher<L2 > matcher;
// Flann-based matching
//FlannBasedMatcher matcher;
// display of corresponding points
matcher.match( descriptor1, descriptor2, matches );
// matching result
Mat result;
drawMatches( tmp, keypoints1, in, keypoints2, matches, result );
// output file
//modify!!!!
imwrite( “D:\\CodeBlocks\\Fotos\\result.bmp”, result );
// display the result
namedWindow(“SIFT”, CV_WINDOW_AUTOSIZE );
imshow(“SIFT”, result);
waitKey(0); //press any key to quit
return 0;
}
————————————–
Posted by Daniel on May 1, 2013 at 1:10 pm
OPS… Wrong Code…
Here’s the correct one:
#include “opencv2\opencv.hpp”
#include
#include
#include
#include
#include
using namespace std;
using namespace cv;
//
int main( )
{
//source image
char* img1_file = “D:\\CodeBlocks\\Fotos\\fachada-do-predio.jpg”;
char* img2_file = “D:\\CodeBlocks\\Fotos\\fachada-do-predio.jpg”;
// image read
Mat tmp = cv::imread( img1_file, 1 );
Mat in = cv::imread( img2_file, 1 );
/* threshold = 0.04;
edge_threshold = 10.0;
magnification = 3.0; */
// SIFT feature detector and feature extractor
cv::SiftFeatureDetector detector( 0.05, 5.0 );
cv::SiftDescriptorExtractor extractor( 3.0 );
//In case of SURF, you apply the below two lines
//cv::SurfFeatureDetector detector();
//cv::SurfDescriptorExtractor extractor();
// Feature detection
std::vector keypoints1, keypoints2;
detector.detect( tmp, keypoints1 );
detector.detect( in, keypoints2 );
// Feature display
Mat feat1,feat2;
drawKeypoints(tmp,keypoints1,feat1,Scalar(255, 255, 255),DrawMatchesFlags::DRAW_RICH_KEYPOINTS);
drawKeypoints(in,keypoints2,feat2,Scalar(255, 255, 255),DrawMatchesFlags::DRAW_RICH_KEYPOINTS);
imwrite( “D:\\CodeBlocks\\Fotos\\template_matching2.jpg”, feat1 );
imwrite( “D:\\CodeBlocks\\Fotos\\template_matching2.jpg”, feat2 );
int key1 = keypoints1.size();
int key2 = keypoints2.size();
printf(“Keypoint1=%d \nKeypoint2=%d”, key1, key2);
// Feature descriptor computation
Mat descriptor1,descriptor2;
extractor.compute( tmp, keypoints1, descriptor1 );
extractor.compute( in, keypoints2, descriptor2 );
/*int desc1 = descriptor1.size;
int desc2 = descriptor2.size;
printf(“Descriptor1=%d \nDescriptor2=%d”, desc1, desc2);*/
// corresponded points
std::vector matches;
// L2 distance based matching. Brute Force Matching
BruteForceMatcher<L2 > matcher;
// Flann-based matching
//FlannBasedMatcher matcher;
// display of corresponding points
matcher.match( descriptor1, descriptor2, matches );
// matching result
Mat result;
drawMatches( tmp, keypoints1, in, keypoints2, matches, result );
// output file
imwrite( “D:\\CodeBlocks\\Fotos\\result.bmp”, result );
// display the result
namedWindow(“SIFT”, CV_WINDOW_AUTOSIZE );
imshow(“SIFT”, result);
waitKey(0); //press any key to quit
return 0;
}
Posted by sookang on January 2, 2015 at 6:08 am
It is also failed
That’s why there are errors that part b’cuz of vector keypoint1,keypoint2; and vector matches and BruteForceMatcher<L2 > matcher; This is correct code
Posted by Bala on March 1, 2013 at 2:04 am
Where can I find a perfectly working SIFT or SURF code for object detection/identification?
I need the code to work like shown in http://www.aishack.in/2010/05/sift-scale-invariant-feature-transform/
Posted by fahmifahim on March 7, 2013 at 11:10 pm
You may refer to the Robhess and VLFeat implementation on SIFT:
Robhess= http://robwhess.github.com/opensift/
VLFeat= http://www.vlfeat.org/overview/sift.html
(the code there are carefully written by the authors)
Or, you may find other sources from the below links:
http://stackoverflow.com/questions/5461148/sift-implementation-with-opencv-2-2/8529111#8529111
Posted by Zara on August 26, 2013 at 11:16 am
hello, if i want to use this for a nos. of images than what changes i have to do as in to call .xml file as input
plz help
thnk you
Posted by Nick on November 22, 2013 at 1:21 am
First of all, make sure your code is correct before posting it.
Line 37 should be std::vector keypoints1, keypoints2;
Line 60 should be std::vector matches;
Secondly, when I tried your code I got 734 keypoints and not 263 as it shows on your screenshots. Clearly, there are no bad matches to filter out as both images are the same. Technically each keypoint in the first image is matched with its identical keypoint in the second so there are no false positives, true negatives and unmatched keypoints. Could you please clarify what’s going on? I am a bit confused.
Posted by r on June 18, 2014 at 4:57 pm
thanks
Posted by Sheikha Nazreen on March 16, 2017 at 2:14 am
can i get python code of same . please help