Fixed FernDescriptorMatch and undid change of FernClassifier

modules/features2d/src/descriptors.cpp

@@ -549,15 +549,15 @@ void FernDescriptorMatch::trainFernClassifier()
         assert( params.filename.empty() );
 
         vector<Point2f> points;
-        vector<Ptr<Mat> > refimgs( collection.images.size() );
+        vector<Ptr<Mat> > refimgs;
         vector<int> labels;
         for( size_t imageIdx = 0; imageIdx < collection.images.size(); imageIdx++ )
         {
-            refimgs[imageIdx] = new Mat (collection.images[imageIdx]);
             for( size_t pointIdx = 0; pointIdx < collection.points[imageIdx].size(); pointIdx++ )
             {
+                refimgs.push_back(new Mat (collection.images[imageIdx]));
                 points.push_back(collection.points[imageIdx][pointIdx].pt);
-                labels.push_back(imageIdx);
+                labels.push_back(pointIdx);
             }
         }
 
@@ -572,7 +572,7 @@ void FernDescriptorMatch::calcBestProbAndMatchIdx( const Mat& image, const Point
 {
     (*classifier)( image, pt, signature);
 
-    bestProb = 0;
+    bestProb = -FLT_MAX;
     bestMatchIdx = -1;
     for( size_t ci = 0; ci < (size_t)classifier->getClassCount(); ci++ )
     {

modules/features2d/src/planardetect.cpp

@@ -853,7 +853,7 @@ void FernClassifier::train(const vector<Point2f>& points,
     for( i = 0; i < nsamples; i++ )
     {
         Point2f pt = points[i];
-        const Mat& src = labels.empty() ? *refimgs[i] : *refimgs[labels[i]];
+        const Mat& src = *refimgs[i];
         int classId = labels.empty() ? i : labels[i];
         if( verbose && (i+1)*progressBarSize/nsamples != i*progressBarSize/nsamples )
             putchar('.');