mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
93 lines
3.1 KiB
93 lines
3.1 KiB
#include "opencv2/calib3d/calib3d.hpp" |
|
#include "opencv2/features2d/features2d.hpp" |
|
#include "opencv2/highgui/highgui.hpp" |
|
#include "opencv2/imgproc/imgproc.hpp" |
|
#include "opencv2/nonfree/nonfree.hpp" |
|
|
|
#include <cstdio> |
|
|
|
using namespace cv; |
|
|
|
static void help() |
|
{ |
|
printf("Use the SURF descriptor for matching keypoints between 2 images\n"); |
|
printf("Format: \n./generic_descriptor_match <image1> <image2> <algorithm> <XML params>\n"); |
|
printf("For example: ./generic_descriptor_match ../c/scene_l.bmp ../c/scene_r.bmp FERN fern_params.xml\n"); |
|
} |
|
|
|
Mat DrawCorrespondences(const Mat& img1, const vector<KeyPoint>& features1, const Mat& img2, |
|
const vector<KeyPoint>& features2, const vector<DMatch>& desc_idx); |
|
|
|
int main(int argc, char** argv) |
|
{ |
|
if (argc != 5) |
|
{ |
|
help(); |
|
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 = GenericDescriptorMatcher::create(alg_name, params_filename); |
|
if( descriptorMatcher.empty() ) |
|
{ |
|
printf ("Cannot create descriptor\n"); |
|
return 0; |
|
} |
|
|
|
//printf("Reading the images...\n"); |
|
Mat img1 = imread(img1_name, CV_LOAD_IMAGE_GRAYSCALE); |
|
Mat img2 = imread(img2_name, 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"); |
|
|
|
Mat img_corr = DrawCorrespondences(img1, keypoints1, img2, keypoints2, matches2to1); |
|
|
|
imshow("correspondences", img_corr); |
|
waitKey(0); |
|
} |
|
|
|
Mat DrawCorrespondences(const Mat& img1, const vector<KeyPoint>& features1, const Mat& img2, |
|
const vector<KeyPoint>& features2, const vector<DMatch>& desc_idx) |
|
{ |
|
Mat part, img_corr(Size(img1.cols + img2.cols, MAX(img1.rows, img2.rows)), CV_8UC3); |
|
img_corr = Scalar::all(0); |
|
part = img_corr(Rect(0, 0, img1.cols, img1.rows)); |
|
cvtColor(img1, part, COLOR_GRAY2RGB); |
|
part = img_corr(Rect(img1.cols, 0, img2.cols, img2.rows)); |
|
cvtColor(img1, part, COLOR_GRAY2RGB); |
|
|
|
for (size_t i = 0; i < features1.size(); i++) |
|
{ |
|
circle(img_corr, features1[i].pt, 3, CV_RGB(255, 0, 0)); |
|
} |
|
|
|
for (size_t i = 0; i < features2.size(); i++) |
|
{ |
|
Point pt(cvRound(features2[i].pt.x + img1.cols), cvRound(features2[i].pt.y)); |
|
circle(img_corr, pt, 3, Scalar(0, 0, 255)); |
|
line(img_corr, features1[desc_idx[i].trainIdx].pt, pt, Scalar(0, 255, 0)); |
|
} |
|
|
|
return img_corr; |
|
}
|
|
|