minor changes of recall-precision output

diff --git a/modules/features2d/include/opencv2/features2d/features2d.hpp b/modules/features2d/include/opencv2/features2d/features2d.hpp
index a6ddd91..0844092 100644 (file)
--- a/modules/features2d/include/opencv2/features2d/features2d.hpp
+++ b/modules/features2d/include/opencv2/features2d/features2d.hpp
@@ -2720,7 +2720,9 @@ CV_EXPORTS void evaluateFeatureDetector( const Mat& img1, const Mat& img2, const
 CV_EXPORTS void computeRecallPrecisionCurve( const vector<vector<DMatch> >& matches1to2,
                                              const vector<vector<uchar> >& correctMatches1to2Mask,
                                              vector<Point2f>& recallPrecisionCurve );
+
 CV_EXPORTS float getRecall( const vector<Point2f>& recallPrecisionCurve, float l_precision );
+CV_EXPORTS int getNearestPoint( const vector<Point2f>& recallPrecisionCurve, float l_precision );
 
 CV_EXPORTS void evaluateGenericDescriptorMatcher( const Mat& img1, const Mat& img2, const Mat& H1to2,
                                                   vector<KeyPoint>& keypoints1, vector<KeyPoint>& keypoints2,

diff --git a/modules/features2d/src/evaluation.cpp b/modules/features2d/src/evaluation.cpp
index 6ab9412..0cf53a8 100644 (file)
--- a/modules/features2d/src/evaluation.cpp
+++ b/modules/features2d/src/evaluation.cpp
@@ -491,26 +491,35 @@ void cv::computeRecallPrecisionCurve( const vector<vector<DMatch> >& matches1to2
 
 float cv::getRecall( const vector<Point2f>& recallPrecisionCurve, float l_precision )
 {
-    float recall = -1;
+    int nearestPointIndex = getNearestPoint( recallPrecisionCurve, l_precision );
+
+    float recall = -1.f;
+
+    if( nearestPointIndex >= 0 )
+        recall = recallPrecisionCurve[nearestPointIndex].y;
+
+    return recall;
+}
+
+int cv::getNearestPoint( const vector<Point2f>& recallPrecisionCurve, float l_precision )
+{
+    int nearestPointIndex = -1;
 
     if( l_precision >= 0 && l_precision <= 1 )
     {
-        int bestIdx = -1;
         float minDiff = FLT_MAX;
         for( size_t i = 0; i < recallPrecisionCurve.size(); i++ )
         {
             float curDiff = std::fabs(l_precision - recallPrecisionCurve[i].x);
             if( curDiff <= minDiff )
             {
-                bestIdx = (int)i;
+                nearestPointIndex = (int)i;
                 minDiff = curDiff;
             }
         }
-
-        recall = recallPrecisionCurve[bestIdx].y;
     }
 
-    return recall;
+    return nearestPointIndex;
 }
 
 void cv::evaluateGenericDescriptorMatcher( const Mat& img1, const Mat& img2, const Mat& H1to2,

diff --git a/samples/cpp/descriptor_extractor_matcher.cpp b/samples/cpp/descriptor_extractor_matcher.cpp
index 834b401..a950582 100644 (file)
--- a/samples/cpp/descriptor_extractor_matcher.cpp
+++ b/samples/cpp/descriptor_extractor_matcher.cpp
@@ -13,17 +13,16 @@ void help(char** argv)
     cout << "\nThis program demonstrats keypoint finding and matching between 2 images using features2d framework.\n"
      << "   In one case, the 2nd image is synthesized by homography from the first, in the second case, there are 2 images\n"
      << "\n"
-     << "case1: second image is obtained from the first (given) image using random generated homography matrix\n"
+     << "Case1: second image is obtained from the first (given) image using random generated homography matrix\n"
      << argv[0] << " [detectorType] [descriptorType] [matcherType] [matcherFilterType] [image] [evaluate(0 or 1)]\n"
      << "Example of case1:\n"
      << "./descriptor_extractor_matcher SURF SURF FlannBased NoneFilter cola.jpg 0\n"
      << "\n"
-     << "case2: both images are given. If ransacReprojThreshold>=0 then homography matrix are calculated\n"
-     << "Example of case2:\n"
+     << "Case2: both images are given. If ransacReprojThreshold>=0 then homography matrix are calculated\n"
      << argv[0] << " [detectorType] [descriptorType] [matcherType] [matcherFilterType] [image1] [image2] [ransacReprojThreshold]\n"
      << "\n"
      << "Matches are filtered using homography matrix in case1 and case2 (if ransacReprojThreshold>=0)\n"
-     << "Example:\n"
+     << "Example of case2:\n"
      << "./descriptor_extractor_matcher SURF SURF BruteForce CrossCheckFilter cola1.jpg cola2.jpg 3\n"
      << "\n"
      << "Possible detectorType values: see in documentation on createFeatureDetector().\n"
@@ -151,12 +150,16 @@ void doIteration( const Mat& img1, Mat& img2, bool isWarpPerspective,
 
     if( !H12.empty() && eval )
     {
-        cout << "< Evaluate descriptor match..." << endl;
+        cout << "< Evaluate descriptor matcher..." << endl;
         vector<Point2f> curve;
         Ptr<GenericDescriptorMatcher> gdm = new VectorDescriptorMatcher( descriptorExtractor, descriptorMatcher );
         evaluateGenericDescriptorMatcher( img1, img2, H12, keypoints1, keypoints2, 0, 0, curve, gdm );
-        for( float l_p = 0; l_p < 1 - FLT_EPSILON; l_p+=0.1f )
-            cout << "1-precision = " << l_p << "; recall = " << getRecall( curve, l_p ) << endl;
+
+        for( float l_p = 0; l_p <= 1; l_p+=0.05f )
+        {
+            int nearest = getNearestPoint( curve, l_p );
+            cout << "1-precision = " << curve[nearest].x << "; recall = " << curve[nearest].y << endl;
+        }
         cout << ">" << endl;
     }