99 lines
		
	
	
		
			2.6 KiB
		
	
	
	
		
			ReStructuredText
		
	
	
	
	
	
			
		
		
	
	
			99 lines
		
	
	
		
			2.6 KiB
		
	
	
	
		
			ReStructuredText
		
	
	
	
	
	
| .. _feature_detection:
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| 
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| Feature Detection
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| ******************
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| 
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| Goal
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| =====
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| 
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| In this tutorial you will learn how to:
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| 
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| .. container:: enumeratevisibleitemswithsquare
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| 
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|    * Use the :feature_detector:`FeatureDetector<>` interface in order to find interest points. Specifically:
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| 
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|      * Use the :surf_feature_detector:`SurfFeatureDetector<>` and its function :feature_detector_detect:`detect<>` to perform the detection process
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|      * Use the function :draw_keypoints:`drawKeypoints<>` to draw the detected keypoints
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| 
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| 
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| Theory
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| ======
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| 
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| Code
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| ====
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| 
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| 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>`_
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| 
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| .. code-block:: cpp
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| 
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|    #include <stdio.h>
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|    #include <iostream>
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|    #include "opencv2/core/core.hpp"
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|    #include "opencv2/features2d/features2d.hpp"
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|    #include "opencv2/nonfree/features2d.hpp"
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|    #include "opencv2/highgui/highgui.hpp"
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|    #include "opencv2/nonfree/nonfree.hpp"
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| 
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|    using namespace cv;
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| 
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|    void readme();
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| 
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|    /** @function main */
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|    int main( int argc, char** argv )
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|    {
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|      if( argc != 3 )
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|      { readme(); return -1; }
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| 
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|      Mat img_1 = imread( argv[1], CV_LOAD_IMAGE_GRAYSCALE );
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|      Mat img_2 = imread( argv[2], CV_LOAD_IMAGE_GRAYSCALE );
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| 
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|      if( !img_1.data || !img_2.data )
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|      { std::cout<< " --(!) Error reading images " << std::endl; return -1; }
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| 
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|      //-- Step 1: Detect the keypoints using SURF Detector
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|      int minHessian = 400;
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| 
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|      SurfFeatureDetector detector( minHessian );
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| 
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|      std::vector<KeyPoint> keypoints_1, keypoints_2;
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| 
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|      detector.detect( img_1, keypoints_1 );
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|      detector.detect( img_2, keypoints_2 );
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| 
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|      //-- Draw keypoints
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|      Mat img_keypoints_1; Mat img_keypoints_2;
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| 
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|      drawKeypoints( img_1, keypoints_1, img_keypoints_1, Scalar::all(-1), DrawMatchesFlags::DEFAULT );
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|      drawKeypoints( img_2, keypoints_2, img_keypoints_2, Scalar::all(-1), DrawMatchesFlags::DEFAULT );
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| 
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|      //-- Show detected (drawn) keypoints
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|      imshow("Keypoints 1", img_keypoints_1 );
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|      imshow("Keypoints 2", img_keypoints_2 );
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| 
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|      waitKey(0);
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| 
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|      return 0;
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|      }
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| 
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|      /** @function readme */
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|      void readme()
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|      { std::cout << " Usage: ./SURF_detector <img1> <img2>" << std::endl; }
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| 
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| Explanation
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| ============
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| 
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| Result
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| ======
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| 
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| #. Here is the result of the feature detection applied to the first image:
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| 
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|    .. image:: images/Feature_Detection_Result_a.jpg
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|       :align: center
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|       :height: 125pt
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| 
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| #. And here is the result for the second image:
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| 
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|    .. image:: images/Feature_Detection_Result_b.jpg
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|       :align: center
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|       :height: 200pt
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