Merge pull request #1797 from moodoki:bugfix_3344

diff --cc doc/tutorials/features2d/feature_flann_matcher/feature_flann_matcher.rst
index 27431e0,1257f1c..e4630c9
--- 1/doc/tutorials/features2d/feature_flann_matcher/feature_flann_matcher.rst
--- 2/doc/tutorials/features2d/feature_flann_matcher/feature_flann_matcher.rst
+++ b/doc/tutorials/features2d/feature_flann_matcher/feature_flann_matcher.rst
@@@ -19,97 -19,10 +19,10 @@@ Theor
  Code
  ====
  
 -This tutorial code's is shown lines below. You can also download it from `here <http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/cpp/tutorial_code/features2D/SURF_FlannMatcher.cpp>`_
 +This tutorial code's is shown lines below. You can also download it from `here <https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/features2D/SURF_FlannMatcher.cpp>`_
  
- .. code-block:: cpp
- 
-    #include <stdio.h>
-    #include <iostream>
-    #include "opencv2/core/core.hpp"
-    #include "opencv2/features2d/features2d.hpp"
-    #include "opencv2/highgui/highgui.hpp"
-    #include "opencv2/nonfree/nonfree.hpp"
- 
-    using namespace cv;
- 
-    void readme();
- 
-    /** @function main */
-    int main( int argc, char** argv )
-    {
-      if( argc != 3 )
-      { readme(); return -1; }
- 
-      Mat img_1 = imread( argv[1], CV_LOAD_IMAGE_GRAYSCALE );
-      Mat img_2 = imread( argv[2], CV_LOAD_IMAGE_GRAYSCALE );
- 
-      if( !img_1.data || !img_2.data )
-      { std::cout<< " --(!) Error reading images " << std::endl; return -1; }
- 
-      //-- Step 1: Detect the keypoints using SURF Detector
-      int minHessian = 400;
- 
-      SurfFeatureDetector detector( minHessian );
- 
-      std::vector<KeyPoint> keypoints_1, keypoints_2;
- 
-      detector.detect( img_1, keypoints_1 );
-      detector.detect( img_2, keypoints_2 );
- 
-      //-- Step 2: Calculate descriptors (feature vectors)
-      SurfDescriptorExtractor extractor;
- 
-      Mat descriptors_1, descriptors_2;
- 
-      extractor.compute( img_1, keypoints_1, descriptors_1 );
-      extractor.compute( img_2, keypoints_2, descriptors_2 );
- 
-      //-- Step 3: Matching descriptor vectors using FLANN matcher
-      FlannBasedMatcher matcher;
-      std::vector< DMatch > matches;
-      matcher.match( descriptors_1, descriptors_2, matches );
- 
-      double max_dist = 0; double min_dist = 100;
- 
-      //-- Quick calculation of max and min distances between keypoints
-      for( int i = 0; i < descriptors_1.rows; i++ )
-      { double dist = matches[i].distance;
-        if( dist < min_dist ) min_dist = dist;
-        if( dist > max_dist ) max_dist = dist;
-      }
- 
-      printf("-- Max dist : %f \n", max_dist );
-      printf("-- Min dist : %f \n", min_dist );
- 
-      //-- Draw only "good" matches (i.e. whose distance is less than 2*min_dist )
-      //-- PS.- radiusMatch can also be used here.
-      std::vector< DMatch > good_matches;
- 
-      for( int i = 0; i < descriptors_1.rows; i++ )
-      { if( matches[i].distance <= 2*min_dist )
-        { good_matches.push_back( matches[i]); }
-      }
- 
-      //-- Draw only "good" matches
-      Mat img_matches;
-      drawMatches( img_1, keypoints_1, img_2, keypoints_2,
-                   good_matches, img_matches, Scalar::all(-1), Scalar::all(-1),
-                   vector<char>(), DrawMatchesFlags::NOT_DRAW_SINGLE_POINTS );
- 
-      //-- Show detected matches
-      imshow( "Good Matches", img_matches );
- 
-      for( int i = 0; i < good_matches.size(); i++ )
-      { printf( "-- Good Match [%d] Keypoint 1: %d  -- Keypoint 2: %d  \n", i, good_matches[i].queryIdx, good_matches[i].trainIdx ); }
- 
-      waitKey(0);
- 
-      return 0;
-     }
- 
-     /** @function readme */
-     void readme()
-     { std::cout << " Usage: ./SURF_FlannMatcher <img1> <img2>" << std::endl; }
+ .. literalinclude:: ../../../../samples/cpp/tutorial_code/features2D/SURF_FlannMatcher.cpp
+    :language: cpp
  
  Explanation
  ============