text: /*
   *  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 std;
  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, IMREAD_GRAYSCALE);
      Mat img2 = imread(img2_name, IMREAD_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;
  }
  