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/*
* one_way_sample.cpp
* outlet_detection
*
* Created by Victor Eruhimov on 8/5/09.
* Copyright 2009 Argus Corp. All rights reserved.
*
*/
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/features2d/features2d.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/nonfree/nonfree.hpp"
#include "opencv2/legacy/legacy.hpp"
#include "opencv2/legacy/compat.hpp"
#include <string>
#include <stdio.h>
static void help()
{
printf("\nThis program demonstrates the one way interest point descriptor found in features2d.hpp\n"
"Correspondences are drawn\n");
printf("Format: \n./one_way_sample <path_to_samples> <image1> <image2>\n");
printf("For example: ./one_way_sample . ../c/scene_l.bmp ../c/scene_r.bmp\n");
}
using namespace cv;
Mat DrawCorrespondences(const Mat& img1, const vector<KeyPoint>& features1, const Mat& img2,
const vector<KeyPoint>& features2, const vector<int>& desc_idx);
int main(int argc, char** argv)
{
const char images_list[] = "one_way_train_images.txt";
const CvSize patch_size = cvSize(24, 24);
const int pose_count = 50;
if (argc != 4)
{
help();
return 0;
}
std::string path_name = argv[1];
std::string img1_name = path_name + "/" + std::string(argv[2]);
std::string img2_name = path_name + "/" + std::string(argv[3]);
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...\n", (int)keypoints1.size());
printf("Training one way descriptors... \n");
// create descriptors
OneWayDescriptorBase descriptors(patch_size, pose_count, OneWayDescriptorBase::GetPCAFilename(), path_name,
images_list);
IplImage img1_c = img1;
IplImage img2_c = img2;
descriptors.CreateDescriptorsFromImage(&img1_c, keypoints1);
printf("done\n");
// extract keypoints from the second image
vector<KeyPoint> keypoints2;
surf_extractor(img2, Mat(), keypoints2);
printf("Extracted %d keypoints from the second image...\n", (int)keypoints2.size());
printf("Finding nearest neighbors...");
// find NN for each of keypoints2 in keypoints1
vector<int> desc_idx;
desc_idx.resize(keypoints2.size());
for (size_t i = 0; i < keypoints2.size(); i++)
{
int pose_idx = 0;
float distance = 0;
descriptors.FindDescriptor(&img2_c, keypoints2[i].pt, desc_idx[i], pose_idx, distance);
}
printf("done\n");
Mat img_corr = DrawCorrespondences(img1, keypoints1, img2, keypoints2, desc_idx);
imshow("correspondences", img_corr);
waitKey(0);
}
Mat DrawCorrespondences(const Mat& img1, const vector<KeyPoint>& features1, const Mat& img2,
const vector<KeyPoint>& features2, const vector<int>& 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((int)features2[i].pt.x + img1.cols, (int)features2[i].pt.y);
circle(img_corr, pt, 3, Scalar(0, 0, 255));
line(img_corr, features1[desc_idx[i]].pt, pt, Scalar(0, 255, 0));
}
return img_corr;
}
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