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https://github.com/opencv/opencv.git
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2a6fb2867e
Made all STL usages explicit to be able automatically find all usages of particular class or function.
95 lines
3.2 KiB
C++
95 lines
3.2 KiB
C++
#include "opencv2/calib3d/calib3d.hpp"
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#include "opencv2/features2d/features2d.hpp"
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#include "opencv2/highgui/highgui.hpp"
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#include "opencv2/imgproc/imgproc.hpp"
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#include "opencv2/nonfree/nonfree.hpp"
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#include <cstdio>
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using namespace std;
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using namespace cv;
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static void help()
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{
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printf("Use the SURF descriptor for matching keypoints between 2 images\n");
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printf("Format: \n./generic_descriptor_match <image1> <image2> <algorithm> <XML params>\n");
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printf("For example: ./generic_descriptor_match ../c/scene_l.bmp ../c/scene_r.bmp FERN fern_params.xml\n");
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}
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Mat DrawCorrespondences(const Mat& img1, const vector<KeyPoint>& features1, const Mat& img2,
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const vector<KeyPoint>& features2, const vector<DMatch>& desc_idx);
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int main(int argc, char** argv)
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{
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if (argc != 5)
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{
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help();
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return 0;
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}
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std::string img1_name = std::string(argv[1]);
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std::string img2_name = std::string(argv[2]);
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std::string alg_name = std::string(argv[3]);
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std::string params_filename = std::string(argv[4]);
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Ptr<GenericDescriptorMatcher> descriptorMatcher = GenericDescriptorMatcher::create(alg_name, params_filename);
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if( descriptorMatcher.empty() )
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{
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printf ("Cannot create descriptor\n");
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return 0;
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}
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//printf("Reading the images...\n");
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Mat img1 = imread(img1_name, CV_LOAD_IMAGE_GRAYSCALE);
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Mat img2 = imread(img2_name, CV_LOAD_IMAGE_GRAYSCALE);
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// extract keypoints from the first image
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SURF surf_extractor(5.0e3);
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vector<KeyPoint> keypoints1;
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// printf("Extracting keypoints\n");
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surf_extractor(img1, Mat(), keypoints1);
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printf("Extracted %d keypoints from the first image\n", (int)keypoints1.size());
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vector<KeyPoint> keypoints2;
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surf_extractor(img2, Mat(), keypoints2);
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printf("Extracted %d keypoints from the second image\n", (int)keypoints2.size());
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printf("Finding nearest neighbors... \n");
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// find NN for each of keypoints2 in keypoints1
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vector<DMatch> matches2to1;
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descriptorMatcher->match( img2, keypoints2, img1, keypoints1, matches2to1 );
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printf("Done\n");
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Mat img_corr = DrawCorrespondences(img1, keypoints1, img2, keypoints2, matches2to1);
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imshow("correspondences", img_corr);
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waitKey(0);
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}
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Mat DrawCorrespondences(const Mat& img1, const vector<KeyPoint>& features1, const Mat& img2,
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const vector<KeyPoint>& features2, const vector<DMatch>& desc_idx)
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{
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Mat part, img_corr(Size(img1.cols + img2.cols, MAX(img1.rows, img2.rows)), CV_8UC3);
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img_corr = Scalar::all(0);
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part = img_corr(Rect(0, 0, img1.cols, img1.rows));
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cvtColor(img1, part, COLOR_GRAY2RGB);
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part = img_corr(Rect(img1.cols, 0, img2.cols, img2.rows));
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cvtColor(img1, part, COLOR_GRAY2RGB);
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for (size_t i = 0; i < features1.size(); i++)
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{
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circle(img_corr, features1[i].pt, 3, CV_RGB(255, 0, 0));
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}
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for (size_t i = 0; i < features2.size(); i++)
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{
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Point pt(cvRound(features2[i].pt.x + img1.cols), cvRound(features2[i].pt.y));
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circle(img_corr, pt, 3, Scalar(0, 0, 255));
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line(img_corr, features1[desc_idx[i].trainIdx].pt, pt, Scalar(0, 255, 0));
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}
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return img_corr;
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}
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