コード例 #1
0
void getMatches(cv::BFMatcher &m_matcher, const cv::Mat &trainDescriptors, const cv::Mat& queryDescriptors,  std::vector<cv::DMatch>& good_matches)
{
    std::vector<std::vector<cv::DMatch> > m_knnMatches;
    good_matches.clear();

    // To avoid NaNs when best match has
    // zero distance we will use inverse ratio.
    const float minRatio =1.f / 1.5f;
    // KNN match will return 2 nearest
    // matches for each query descriptor
    m_matcher.knnMatch(trainDescriptors, queryDescriptors, m_knnMatches,10);
    for (size_t i=0; i < m_knnMatches.size(); i++)
    {
        const cv::DMatch& bestMatch = m_knnMatches[i][0];
        const cv::DMatch& betterMatch = m_knnMatches[i][1];
        float distanceRatio = bestMatch.distance /
            betterMatch.distance;
        // Pass only matches where distance ratio between
        // nearest matches is greater than 1.5
        // (distinct criteria)
        if (distanceRatio < minRatio)
        {
            good_matches.push_back(bestMatch);
        }
    }
}
コード例 #2
0
ファイル: estimate_kalman.cpp プロジェクト: Pold87/cpp-sift
  cv::Point2f calcLocation(cv::Mat query_img) {

    std::vector<cv::KeyPoint> kp_query; // Keypoints of the query image
    cv::Mat des_query;
    cv::Mat query_img_gray;
    
    cv::cvtColor(query_img,
                 query_img_gray,
                 cv::COLOR_BGR2GRAY);


    detector->detectAndCompute(query_img_gray, 
                               cv::noArray(), 
                               kp_query,
                               des_query);


    std::vector< std::vector<cv::DMatch> > matches;
   
    matcher.knnMatch(des_ref, 
                     des_query, 
                     matches,
                     2);


    std::vector<cv::KeyPoint> matched_query, matched_ref, inliers_query, inliers_ref;
    std::vector<cv::DMatch> good_matches;

   //-- Localize the object
    std::vector<cv::Point2f> pts_query;
    std::vector<cv::Point2f> pts_ref;
    
  for(size_t i = 0; i < matches.size(); i++) {
    
    cv::DMatch first = matches[i][0];
    float dist_query = matches[i][0].distance;
    float dist_ref = matches[i][1].distance;
    
    if (dist_query < match_ratio * dist_ref) {
      
      matched_query.push_back(kp_query[first.queryIdx]);
      matched_ref.push_back(kp_ref[first.trainIdx]);
      
      pts_query.push_back(kp_query[first.queryIdx].pt);
      pts_ref.push_back(kp_ref[first.trainIdx].pt);
      
    }
  }


  cv::Mat mask; 

  // Homograpy
  cv::Mat homography;
  
  homography = cv::findHomography(pts_query, 
				  pts_ref,
				  cv::RANSAC,
				  5,
				  mask);


  // Input Quadilateral or Image plane coordinates
  std::vector<cv::Point2f> centers(1), centers_transformed(1);

  cv::Point2f center(query_img_gray.rows / 2,
                     query_img_gray.cols / 2);
  
  cv::Point2f center_transformed(query_img.rows / 2,
                                 query_img.cols / 2);
  
  centers[0] = center; // Workaround for using perspective transform
  
  cv::perspectiveTransform(centers,
                           centers_transformed,
                           homography);

  center_transformed = centers_transformed[0];

  return center_transformed;
  
  }