moved nonfree and a part of features2d to opencv_contrib/xfeatures2d

doc/tutorials/features2d/feature_description/feature_description.rst

@@ -23,7 +23,7 @@ Theory
 Code
 ====
 
-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_descriptor.cpp>`_
+This tutorial code's is shown lines below.
 
 .. code-block:: cpp
 
@@ -32,9 +32,10 @@ This tutorial code's is shown lines below. You can also download it from `here <
    #include "opencv2/core.hpp"
    #include "opencv2/features2d.hpp"
    #include "opencv2/highgui.hpp"
-   #include "opencv2/nonfree.hpp"
+   #include "opencv2/xfeatures2d.hpp"
 
    using namespace cv;
+   using namespace cv::xfeatures2d;
 
    void readme();
 
@@ -50,25 +51,19 @@ This tutorial code's is shown lines below. You can also download it from `here <
      if( !img_1.data || !img_2.data )
       { return -1; }
 
-     //-- Step 1: Detect the keypoints using SURF Detector
+     //-- Step 1: Detect the keypoints using SURF Detector, compute the descriptors
      int minHessian = 400;
 
-     SurfFeatureDetector detector( minHessian );
+     Ptr<SURF> detector = SURF::create();
+     detector->setMinHessian(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 );
+     detector->detectAndCompute( img_1, keypoints_1, descriptors_1 );
+     detector->detectAndCompute( img_2, keypoints_2, descriptors_2 );
 
-     //-- Step 3: Matching descriptor vectors with a brute force matcher
+     //-- Step 2: Matching descriptor vectors with a brute force matcher
      BFMatcher matcher(NORM_L2);
      std::vector< DMatch > matches;
      matcher.match( descriptors_1, descriptors_2, matches );

doc/tutorials/features2d/feature_detection/feature_detection.rst

@@ -22,7 +22,7 @@ Theory
 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_detector.cpp>`_
+This tutorial code's is shown lines below.
 
 .. code-block:: cpp
 
@@ -30,11 +30,11 @@ This tutorial code's is shown lines below. You can also download it from `here <
    #include <iostream>
    #include "opencv2/core.hpp"
    #include "opencv2/features2d.hpp"
-   #include "opencv2/nonfree/features2d.hpp"
+   #include "opencv2/xfeatures2d.hpp"
    #include "opencv2/highgui.hpp"
-   #include "opencv2/nonfree.hpp"
 
    using namespace cv;
+   using namespace cv::xfeatures2d;
 
    void readme();
 
@@ -53,12 +53,12 @@ This tutorial code's is shown lines below. You can also download it from `here <
      //-- Step 1: Detect the keypoints using SURF Detector
      int minHessian = 400;
 
-     SurfFeatureDetector detector( minHessian );
+     Ptr<SURF> detector = SURF::create( minHessian );
 
      std::vector<KeyPoint> keypoints_1, keypoints_2;
 
-     detector.detect( img_1, keypoints_1 );
-     detector.detect( img_2, keypoints_2 );
+     detector->detect( img_1, keypoints_1 );
+     detector->detect( img_2, keypoints_2 );
 
      //-- Draw keypoints
      Mat img_keypoints_1; Mat img_keypoints_2;

doc/tutorials/features2d/feature_flann_matcher/feature_flann_matcher.rst

@@ -19,10 +19,116 @@ Theory
 Code
 ====
 
-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>`_
+This tutorial code's is shown lines below.
+
+.. code-block:: cpp
+
+    /**
+     * @file SURF_FlannMatcher
+     * @brief SURF detector + descriptor + FLANN Matcher
+     * @author A. Huaman
+     */
+
+    #include <stdio.h>
+    #include <iostream>
+    #include <stdio.h>
+    #include <iostream>
+    #include "opencv2/core.hpp"
+    #include "opencv2/features2d.hpp"
+    #include "opencv2/imgcodecs.hpp"
+    #include "opencv2/highgui.hpp"
+    #include "opencv2/xfeatures2d.hpp"
+
+    using namespace std;
+    using namespace cv;
+    using namespace cv::xfeatures2d;
+
+    void readme();
+
+    /**
+     * @function main
+     * @brief Main function
+     */
+    int main( int argc, char** argv )
+    {
+      if( argc != 3 )
+      { readme(); return -1; }
+
+      Mat img_1 = imread( argv[1], IMREAD_GRAYSCALE );
+      Mat img_2 = imread( argv[2], IMREAD_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,
+      //-- or a small arbitary value ( 0.02 ) in the event that min_dist is very
+      //-- small)
+      //-- 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 <= max(2*min_dist, 0.02) )
+        { 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 < (int)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
 ============

doc/tutorials/features2d/feature_homography/feature_homography.rst

@@ -20,7 +20,7 @@ Theory
 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_Homography.cpp>`_
+This tutorial code's is shown lines below.
 
 .. code-block:: cpp
 
@@ -30,9 +30,10 @@ This tutorial code's is shown lines below. You can also download it from `here <
    #include "opencv2/features2d.hpp"
    #include "opencv2/highgui.hpp"
    #include "opencv2/calib3d.hpp"
-   #include "opencv2/nonfree.hpp"
+   #include "opencv2/xfeatures2d.hpp"
 
    using namespace cv;
+   using namespace cv::xfeatures2d;
 
    void readme();