opencv/samples/cpp/generic_descriptor_match.cpp

93 lines
3.3 KiB
C++

#include "opencv2/core/core.hpp"
#include "opencv2/calib3d/calib3d.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/features2d/features2d.hpp"
#include <highgui.h>
#include <cstdio>
using namespace cv;
IplImage* DrawCorrespondences(IplImage* img1, const vector<KeyPoint>& features1, IplImage* img2,
const vector<KeyPoint>& features2, const vector<DMatch>& desc_idx);
int main(int argc, char** argv)
{
if (argc != 5)
{
printf("Format: \n./generic_descriptor_match [image1] [image2] [algorithm] [XML params]\n");
printf("For example: ./generic_descriptor_match scene_l.bmp scene_r.bmp FERN fern_params.xml\n");
return 0;
}
std::string img1_name = std::string(argv[1]);
std::string img2_name = std::string(argv[2]);
std::string alg_name = std::string(argv[3]);
std::string params_filename = std::string(argv[4]);
Ptr<GenericDescriptorMatcher> descriptorMatcher = createGenericDescriptorMatcher(alg_name, params_filename);
if( descriptorMatcher == 0 )
{
printf ("Cannot create descriptor\n");
return 0;
}
//printf("Reading the images...\n");
IplImage* img1 = cvLoadImage(img1_name.c_str(), CV_LOAD_IMAGE_GRAYSCALE);
IplImage* img2 = cvLoadImage(img2_name.c_str(), CV_LOAD_IMAGE_GRAYSCALE);
// extract keypoints from the first image
SURF surf_extractor(5.0e3);
vector<KeyPoint> keypoints1;
// printf("Extracting keypoints\n");
surf_extractor(img1, Mat(), keypoints1);
printf("Extracted %d keypoints from the first image\n", (int)keypoints1.size());
vector<KeyPoint> keypoints2;
surf_extractor(img2, Mat(), keypoints2);
printf("Extracted %d keypoints from the second image\n", (int)keypoints2.size());
printf("Finding nearest neighbors... \n");
// find NN for each of keypoints2 in keypoints1
vector<DMatch> matches2to1;
descriptorMatcher->match( img2, keypoints2, img1, keypoints1, matches2to1 );
printf("Done\n");
IplImage* img_corr = DrawCorrespondences(img1, keypoints1, img2, keypoints2, matches2to1);
cvNamedWindow("correspondences", 1);
cvShowImage("correspondences", img_corr);
cvWaitKey(0);
cvReleaseImage(&img1);
cvReleaseImage(&img2);
cvReleaseImage(&img_corr);
}
IplImage* DrawCorrespondences(IplImage* img1, const vector<KeyPoint>& features1, IplImage* img2,
const vector<KeyPoint>& features2, const vector<DMatch>& desc_idx)
{
IplImage* img_corr = cvCreateImage(cvSize(img1->width + img2->width, MAX(img1->height, img2->height)),
IPL_DEPTH_8U, 3);
cvSetImageROI(img_corr, cvRect(0, 0, img1->width, img1->height));
cvCvtColor(img1, img_corr, CV_GRAY2RGB);
cvSetImageROI(img_corr, cvRect(img1->width, 0, img2->width, img2->height));
cvCvtColor(img2, img_corr, CV_GRAY2RGB);
cvResetImageROI(img_corr);
for (size_t i = 0; i < features1.size(); i++)
{
cvCircle(img_corr, features1[i].pt, 3, CV_RGB(255, 0, 0));
}
for (size_t i = 0; i < features2.size(); i++)
{
CvPoint pt = cvPoint(cvRound(features2[i].pt.x + img1->width), cvRound(features2[i].pt.y));
cvCircle(img_corr, pt, 3, CV_RGB(255, 0, 0));
cvLine(img_corr, features1[desc_idx[i].trainIdx].pt, pt, CV_RGB(0, 255, 0));
}
return img_corr;
}