OpenCV  3.4.7-dev
Open Source Computer Vision
Line Features Tutorial

In this tutorial it will be shown how to:

Lines extraction and descriptors computation

In the following snippet of code, it is shown how to detect lines from an image. The LSD extractor is initialized with LSD_REFINE_ADV option; remaining parameters are left to their default values. A mask of ones is used in order to accept all extracted lines, which, at the end, are displayed using random colors for octave 0.

1 /*M///////////////////////////////////////////////////////////////////////////////////////
2  //
3  // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
4  //
5  // By downloading, copying, installing or using the software you agree to this license.
6  // If you do not agree to this license, do not download, install,
7  // copy or use the software.
8  //
9  //
10  // License Agreement
11  // For Open Source Computer Vision Library
12  //
13  // Copyright (C) 2014, Biagio Montesano, all rights reserved.
14  // Third party copyrights are property of their respective owners.
15  //
16  // Redistribution and use in source and binary forms, with or without modification,
17  // are permitted provided that the following conditions are met:
18  //
19  // * Redistribution's of source code must retain the above copyright notice,
20  // this list of conditions and the following disclaimer.
21  //
22  // * Redistribution's in binary form must reproduce the above copyright notice,
23  // this list of conditions and the following disclaimer in the documentation
24  // and/or other materials provided with the distribution.
25  //
26  // * The name of the copyright holders may not be used to endorse or promote products
27  // derived from this software without specific prior written permission.
28  //
29  // This software is provided by the copyright holders and contributors "as is" and
30  // any express or implied warranties, including, but not limited to, the implied
31  // warranties of merchantability and fitness for a particular purpose are disclaimed.
32  // In no event shall the Intel Corporation or contributors be liable for any direct,
33  // indirect, incidental, special, exemplary, or consequential damages
34  // (including, but not limited to, procurement of substitute goods or services;
35  // loss of use, data, or profits; or business interruption) however caused
36  // and on any theory of liability, whether in contract, strict liability,
37  // or tort (including negligence or otherwise) arising in any way out of
38  // the use of this software, even if advised of the possibility of such damage.
39  //
40  //M*/
41 
42 #include <iostream>
43 #include <opencv2/opencv_modules.hpp>
44 
45 #ifdef HAVE_OPENCV_FEATURES2D
46 
48 #include <opencv2/core/utility.hpp>
49 #include <opencv2/imgproc.hpp>
50 #include <opencv2/features2d.hpp>
51 #include <opencv2/highgui.hpp>
52 
53 using namespace cv;
54 using namespace cv::line_descriptor;
55 using namespace std;
56 
57 static const char* keys =
58 { "{@image_path | | Image path }" };
59 
60 static void help()
61 {
62  cout << "\nThis example shows the functionalities of lines extraction " << "furnished by BinaryDescriptor class\n"
63  << "Please, run this sample using a command in the form\n" << "./example_line_descriptor_lines_extraction <path_to_input_image>" << endl;
64 }
65 
66 int main( int argc, char** argv )
67 {
68  /* get parameters from comand line */
69  CommandLineParser parser( argc, argv, keys );
70  String image_path = parser.get<String>( 0 );
71 
72  if( image_path.empty() )
73  {
74  help();
75  return -1;
76  }
77 
78  /* load image */
79  cv::Mat imageMat = imread( image_path, 1 );
80  if( imageMat.data == NULL )
81  {
82  std::cout << "Error, image could not be loaded. Please, check its path" << std::endl;
83  return -1;
84  }
85 
86  /* create a random binary mask */
87  cv::Mat mask = Mat::ones( imageMat.size(), CV_8UC1 );
88 
89  /* create a pointer to a BinaryDescriptor object with deafult parameters */
91 
92  /* create a structure to store extracted lines */
93  vector<KeyLine> lines;
94 
95  /* extract lines */
96  cv::Mat output = imageMat.clone();
97  bd->detect( imageMat, lines, 2, 1, mask );
98 
99  /* draw lines extracted from octave 0 */
100  if( output.channels() == 1 )
101  cvtColor( output, output, COLOR_GRAY2BGR );
102  for ( size_t i = 0; i < lines.size(); i++ )
103  {
104  KeyLine kl = lines[i];
105  if( kl.octave == 0)
106  {
107  /* get a random color */
108  int R = ( rand() % (int) ( 255 + 1 ) );
109  int G = ( rand() % (int) ( 255 + 1 ) );
110  int B = ( rand() % (int) ( 255 + 1 ) );
111 
112  /* get extremes of line */
113  Point pt1 = Point2f( kl.startPointX, kl.startPointY );
114  Point pt2 = Point2f( kl.endPointX, kl.endPointY );
115 
116  /* draw line */
117  line( output, pt1, pt2, Scalar( B, G, R ), 3 );
118  }
119 
120  }
121 
122  /* show lines on image */
123  imshow( "LSD lines", output );
124  waitKey();
125 }
126 
127 #else
128 
129 int main()
130 {
131  std::cerr << "OpenCV was built without features2d module" << std::endl;
132  return 0;
133 }
134 
135 #endif // HAVE_OPENCV_FEATURES2D
float startPointX
Definition: descriptor.hpp:126
Scalar_< double > Scalar
Definition: types.hpp:657
static Ptr< LSDDetector > createLSDDetector()
Creates ad LSDDetector object, using smart pointers.
Mat imread(const String &filename, int flags=IMREAD_COLOR)
Loads an image from a file.
static MatExpr ones(int rows, int cols, int type)
Returns an array of all 1&#39;s of the specified size and type.
Definition: imgproc.hpp:544
uchar * data
pointer to the data
Definition: mat.hpp:2116
STL namespace.
bool empty() const
void imshow(const String &winname, InputArray mat)
Displays an image in the specified window.
float startPointY
Definition: descriptor.hpp:127
Definition: affine.hpp:51
Designed for command line parsing.
Definition: utility.hpp:862
void cvtColor(InputArray src, OutputArray dst, int code, int dstCn=0)
Converts an image from one color space to another.
int octave
Definition: descriptor.hpp:112
float endPointX
Definition: descriptor.hpp:128
void line(InputOutputArray img, Point pt1, Point pt2, const Scalar &color, int thickness=1, int lineType=LINE_8, int shift=0)
Draws a line segment connecting two points.
Point_< float > Point2f
Definition: types.hpp:190
MatSize size
Definition: mat.hpp:2136
Definition: descriptor.hpp:74
Template class for smart pointers with shared ownership.
Definition: cvstd.hpp:261
A class to represent a line.
Definition: descriptor.hpp:102
int rand()
Definition: random.h:43
Mat clone() const CV_NODISCARD
Creates a full copy of the array and the underlying data.
#define CV_8UC1
Definition: interface.h:86
Definition: cvstd.hpp:458
n-dimensional dense array class
Definition: mat.hpp:804
int channels() const
Returns the number of matrix channels.
float endPointY
Definition: descriptor.hpp:129
int waitKey(int delay=0)
Waits for a pressed key.

This is the result obtained for famous cameraman image:

lines_cameraman_edl.png
alternate text

Another way to extract lines is using LSDDetector class; such class uses the LSD extractor to compute lines. To obtain this result, it is sufficient to use the snippet code seen above, just modifying it by the rows

// create a pointer to an LSDDetector object
Ptr<LSDDetector> lsd = LSDDetector::createLSDDetector();
// compute lines
std::vector<KeyLine> keylines;
lsd->detect( imageMat, keylines, mask );

Here's the result returned by LSD detector again on cameraman picture:

cameraman_lines2.png
alternate text

Once keylines have been detected, it is possible to compute their descriptors as shown in the following:

1 /*M///////////////////////////////////////////////////////////////////////////////////////
2  //
3  // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
4  //
5  // By downloading, copying, installing or using the software you agree to this license.
6  // If you do not agree to this license, do not download, install,
7  // copy or use the software.
8  //
9  //
10  // License Agreement
11  // For Open Source Computer Vision Library
12  //
13  // Copyright (C) 2014, Biagio Montesano, all rights reserved.
14  // Third party copyrights are property of their respective owners.
15  //
16  // Redistribution and use in source and binary forms, with or without modification,
17  // are permitted provided that the following conditions are met:
18  //
19  // * Redistribution's of source code must retain the above copyright notice,
20  // this list of conditions and the following disclaimer.
21  //
22  // * Redistribution's in binary form must reproduce the above copyright notice,
23  // this list of conditions and the following disclaimer in the documentation
24  // and/or other materials provided with the distribution.
25  //
26  // * The name of the copyright holders may not be used to endorse or promote products
27  // derived from this software without specific prior written permission.
28  //
29  // This software is provided by the copyright holders and contributors "as is" and
30  // any express or implied warranties, including, but not limited to, the implied
31  // warranties of merchantability and fitness for a particular purpose are disclaimed.
32  // In no event shall the Intel Corporation or contributors be liable for any direct,
33  // indirect, incidental, special, exemplary, or consequential damages
34  // (including, but not limited to, procurement of substitute goods or services;
35  // loss of use, data, or profits; or business interruption) however caused
36  // and on any theory of liability, whether in contract, strict liability,
37  // or tort (including negligence or otherwise) arising in any way out of
38  // the use of this software, even if advised of the possibility of such damage.
39  //
40  //M*/
41 
42 #include <iostream>
43 #include <opencv2/opencv_modules.hpp>
44 
45 #ifdef HAVE_OPENCV_FEATURES2D
46 
48 #include <opencv2/core/utility.hpp>
49 #include <opencv2/imgproc.hpp>
50 #include <opencv2/features2d.hpp>
51 #include <opencv2/highgui.hpp>
52 
53 using namespace cv;
54 using namespace cv::line_descriptor;
55 
56 
57 static const char* keys =
58 { "{@image_path | | Image path }" };
59 
60 static void help()
61 {
62  std::cout << "\nThis example shows the functionalities of lines extraction " << "and descriptors computation furnished by BinaryDescriptor class\n"
63  << "Please, run this sample using a command in the form\n" << "./example_line_descriptor_compute_descriptors <path_to_input_image>"
64  << std::endl;
65 }
66 
67 int main( int argc, char** argv )
68 {
69  /* get parameters from command line */
70  CommandLineParser parser( argc, argv, keys );
71  String image_path = parser.get<String>( 0 );
72 
73  if( image_path.empty() )
74  {
75  help();
76  return -1;
77  }
78 
79  /* load image */
80  cv::Mat imageMat = imread( image_path, 1 );
81  if( imageMat.data == NULL )
82  {
83  std::cout << "Error, image could not be loaded. Please, check its path" << std::endl;
84  }
85 
86  /* create a binary mask */
87  cv::Mat mask = Mat::ones( imageMat.size(), CV_8UC1 );
88 
89  /* create a pointer to a BinaryDescriptor object with default parameters */
91 
92  /* compute lines */
93  std::vector<KeyLine> keylines;
94  bd->detect( imageMat, keylines, mask );
95 
96  /* compute descriptors */
97  cv::Mat descriptors;
98 
99  bd->compute( imageMat, keylines, descriptors);
100 
101 }
102 
103 #else
104 
105 int main()
106 {
107  std::cerr << "OpenCV was built without features2d module" << std::endl;
108  return 0;
109 }
110 
111 #endif // HAVE_OPENCV_FEATURES2D
static Ptr< BinaryDescriptor > createBinaryDescriptor()
Create a BinaryDescriptor object with default parameters (or with the ones provided) and return a sma...
Mat imread(const String &filename, int flags=IMREAD_COLOR)
Loads an image from a file.
static MatExpr ones(int rows, int cols, int type)
Returns an array of all 1&#39;s of the specified size and type.
uchar * data
pointer to the data
Definition: mat.hpp:2116
bool empty() const
Definition: affine.hpp:51
Designed for command line parsing.
Definition: utility.hpp:862
MatSize size
Definition: mat.hpp:2136
Definition: descriptor.hpp:74
Template class for smart pointers with shared ownership.
Definition: cvstd.hpp:261
#define CV_8UC1
Definition: interface.h:86
Definition: cvstd.hpp:458
n-dimensional dense array class
Definition: mat.hpp:804

Matching among descriptors

If we have extracted descriptors from two different images, it is possible to search for matches among them. One way of doing it is matching exactly a descriptor to each input query descriptor, choosing the one at closest distance:

1 /*M///////////////////////////////////////////////////////////////////////////////////////
2  //
3  // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
4  //
5  // By downloading, copying, installing or using the software you agree to this license.
6  // If you do not agree to this license, do not download, install,
7  // copy or use the software.
8  //
9  //
10  // License Agreement
11  // For Open Source Computer Vision Library
12  //
13  // Copyright (C) 2014, Biagio Montesano, all rights reserved.
14  // Third party copyrights are property of their respective owners.
15  //
16  // Redistribution and use in source and binary forms, with or without modification,
17  // are permitted provided that the following conditions are met:
18  //
19  // * Redistribution's of source code must retain the above copyright notice,
20  // this list of conditions and the following disclaimer.
21  //
22  // * Redistribution's in binary form must reproduce the above copyright notice,
23  // this list of conditions and the following disclaimer in the documentation
24  // and/or other materials provided with the distribution.
25  //
26  // * The name of the copyright holders may not be used to endorse or promote products
27  // derived from this software without specific prior written permission.
28  //
29  // This software is provided by the copyright holders and contributors "as is" and
30  // any express or implied warranties, including, but not limited to, the implied
31  // warranties of merchantability and fitness for a particular purpose are disclaimed.
32  // In no event shall the Intel Corporation or contributors be liable for any direct,
33  // indirect, incidental, special, exemplary, or consequential damages
34  // (including, but not limited to, procurement of substitute goods or services;
35  // loss of use, data, or profits; or business interruption) however caused
36  // and on any theory of liability, whether in contract, strict liability,
37  // or tort (including negligence or otherwise) arising in any way out of
38  // the use of this software, even if advised of the possibility of such damage.
39  //
40  //M*/
41 
42 #include <iostream>
43 #include <opencv2/opencv_modules.hpp>
44 
45 #ifdef HAVE_OPENCV_FEATURES2D
46 
48 #include <opencv2/core/utility.hpp>
49 #include <opencv2/imgproc.hpp>
50 #include <opencv2/features2d.hpp>
51 #include <opencv2/highgui.hpp>
52 
53 #define MATCHES_DIST_THRESHOLD 25
54 
55 using namespace cv;
56 using namespace cv::line_descriptor;
57 
58 static const char* keys =
59 { "{@image_path1 | | Image path 1 }"
60  "{@image_path2 | | Image path 2 }" };
61 
62 static void help()
63 {
64  std::cout << "\nThis example shows the functionalities of lines extraction " << "and descriptors computation furnished by BinaryDescriptor class\n"
65  << "Please, run this sample using a command in the form\n" << "./example_line_descriptor_compute_descriptors <path_to_input_image 1>"
66  << "<path_to_input_image 2>" << std::endl;
67 
68 }
69 
70 int main( int argc, char** argv )
71 {
72  /* get parameters from command line */
73  CommandLineParser parser( argc, argv, keys );
74  String image_path1 = parser.get<String>( 0 );
75  String image_path2 = parser.get<String>( 1 );
76 
77  if( image_path1.empty() || image_path2.empty() )
78  {
79  help();
80  return -1;
81  }
82 
83  /* load image */
84  cv::Mat imageMat1 = imread( image_path1, 1 );
85  cv::Mat imageMat2 = imread( image_path2, 1 );
86 
87  if( imageMat1.data == NULL || imageMat2.data == NULL )
88  {
89  std::cout << "Error, images could not be loaded. Please, check their path" << std::endl;
90  }
91 
92  /* create binary masks */
93  cv::Mat mask1 = Mat::ones( imageMat1.size(), CV_8UC1 );
94  cv::Mat mask2 = Mat::ones( imageMat2.size(), CV_8UC1 );
95 
96  /* create a pointer to a BinaryDescriptor object with default parameters */
98 
99  /* compute lines and descriptors */
100  std::vector<KeyLine> keylines1, keylines2;
101  cv::Mat descr1, descr2;
102 
103  ( *bd )( imageMat1, mask1, keylines1, descr1, false, false );
104  ( *bd )( imageMat2, mask2, keylines2, descr2, false, false );
105 
106  /* select keylines from first octave and their descriptors */
107  std::vector<KeyLine> lbd_octave1, lbd_octave2;
108  Mat left_lbd, right_lbd;
109  for ( int i = 0; i < (int) keylines1.size(); i++ )
110  {
111  if( keylines1[i].octave == 0 )
112  {
113  lbd_octave1.push_back( keylines1[i] );
114  left_lbd.push_back( descr1.row( i ) );
115  }
116  }
117 
118  for ( int j = 0; j < (int) keylines2.size(); j++ )
119  {
120  if( keylines2[j].octave == 0 )
121  {
122  lbd_octave2.push_back( keylines2[j] );
123  right_lbd.push_back( descr2.row( j ) );
124  }
125  }
126 
127  /* create a BinaryDescriptorMatcher object */
129 
130  /* require match */
131  std::vector<DMatch> matches;
132  bdm->match( left_lbd, right_lbd, matches );
133 
134  /* select best matches */
135  std::vector<DMatch> good_matches;
136  for ( int i = 0; i < (int) matches.size(); i++ )
137  {
138  if( matches[i].distance < MATCHES_DIST_THRESHOLD )
139  good_matches.push_back( matches[i] );
140  }
141 
142  /* plot matches */
143  cv::Mat outImg;
144  cv::Mat scaled1, scaled2;
145  std::vector<char> mask( matches.size(), 1 );
146  drawLineMatches( imageMat1, lbd_octave1, imageMat2, lbd_octave2, good_matches, outImg, Scalar::all( -1 ), Scalar::all( -1 ), mask,
148 
149  imshow( "Matches", outImg );
150  waitKey();
151  imwrite("/home/ubisum/Desktop/images/env_match/matches.jpg", outImg);
152  /* create an LSD detector */
154 
155  /* detect lines */
156  std::vector<KeyLine> klsd1, klsd2;
157  Mat lsd_descr1, lsd_descr2;
158  lsd->detect( imageMat1, klsd1, 2, 2, mask1 );
159  lsd->detect( imageMat2, klsd2, 2, 2, mask2 );
160 
161  /* compute descriptors for lines from first octave */
162  bd->compute( imageMat1, klsd1, lsd_descr1 );
163  bd->compute( imageMat2, klsd2, lsd_descr2 );
164 
165  /* select lines and descriptors from first octave */
166  std::vector<KeyLine> octave0_1, octave0_2;
167  Mat leftDEscr, rightDescr;
168  for ( int i = 0; i < (int) klsd1.size(); i++ )
169  {
170  if( klsd1[i].octave == 1 )
171  {
172  octave0_1.push_back( klsd1[i] );
173  leftDEscr.push_back( lsd_descr1.row( i ) );
174  }
175  }
176 
177  for ( int j = 0; j < (int) klsd2.size(); j++ )
178  {
179  if( klsd2[j].octave == 1 )
180  {
181  octave0_2.push_back( klsd2[j] );
182  rightDescr.push_back( lsd_descr2.row( j ) );
183  }
184  }
185 
186  /* compute matches */
187  std::vector<DMatch> lsd_matches;
188  bdm->match( leftDEscr, rightDescr, lsd_matches );
189 
190  /* select best matches */
191  good_matches.clear();
192  for ( int i = 0; i < (int) lsd_matches.size(); i++ )
193  {
194  if( lsd_matches[i].distance < MATCHES_DIST_THRESHOLD )
195  good_matches.push_back( lsd_matches[i] );
196  }
197 
198  /* plot matches */
199  cv::Mat lsd_outImg;
200  resize( imageMat1, imageMat1, Size( imageMat1.cols / 2, imageMat1.rows / 2 ), 0, 0, INTER_LINEAR_EXACT );
201  resize( imageMat2, imageMat2, Size( imageMat2.cols / 2, imageMat2.rows / 2 ), 0, 0, INTER_LINEAR_EXACT );
202  std::vector<char> lsd_mask( matches.size(), 1 );
203  drawLineMatches( imageMat1, octave0_1, imageMat2, octave0_2, good_matches, lsd_outImg, Scalar::all( -1 ), Scalar::all( -1 ), lsd_mask,
205 
206  imshow( "LSD matches", lsd_outImg );
207  waitKey();
208 
209 
210 }
211 
212 #else
213 
214 int main()
215 {
216  std::cerr << "OpenCV was built without features2d module" << std::endl;
217  return 0;
218 }
219 
220 #endif // HAVE_OPENCV_FEATURES2D
void detect(const Mat &image, std::vector< KeyLine > &keypoints, int scale, int numOctaves, const Mat &mask=Mat())
Detect lines inside an image.
bool imwrite(const String &filename, InputArray img, const std::vector< int > &params=std::vector< int >())
Saves an image to a specified file.
static Ptr< LSDDetector > createLSDDetector()
Creates ad LSDDetector object, using smart pointers.
static Ptr< BinaryDescriptor > createBinaryDescriptor()
Create a BinaryDescriptor object with default parameters (or with the ones provided) and return a sma...
void push_back(const _Tp &elem)
Adds elements to the bottom of the matrix.
Mat imread(const String &filename, int flags=IMREAD_COLOR)
Loads an image from a file.
static MatExpr ones(int rows, int cols, int type)
Returns an array of all 1&#39;s of the specified size and type.
uchar * data
pointer to the data
Definition: mat.hpp:2116
bool empty() const
void imshow(const String &winname, InputArray mat)
Displays an image in the specified window.
Definition: affine.hpp:51
void resize(InputArray src, OutputArray dst, Size dsize, double fx=0, double fy=0, int interpolation=INTER_LINEAR)
Resizes an image.
Designed for command line parsing.
Definition: utility.hpp:862
MatSize size
Definition: mat.hpp:2136
void drawLineMatches(const Mat &img1, const std::vector< KeyLine > &keylines1, const Mat &img2, const std::vector< KeyLine > &keylines2, const std::vector< DMatch > &matches1to2, Mat &outImg, const Scalar &matchColor=Scalar::all(-1), const Scalar &singleLineColor=Scalar::all(-1), const std::vector< char > &matchesMask=std::vector< char >(), int flags=DrawLinesMatchesFlags::DEFAULT)
Draws the found matches of keylines from two images.
Definition: descriptor.hpp:74
Template class for smart pointers with shared ownership.
Definition: cvstd.hpp:261
Size2i Size
Definition: types.hpp:343
Mat row(int y) const
Creates a matrix header for the specified matrix row.
void match(const Mat &queryDescriptors, const Mat &trainDescriptors, std::vector< DMatch > &matches, const Mat &mask=Mat()) const
For every input query descriptor, retrieve the best matching one from a dataset provided from user or...
#define CV_8UC1
Definition: interface.h:86
static Scalar_< double > all(double v0)
returns a scalar with all elements set to v0
Definition: cvstd.hpp:458
n-dimensional dense array class
Definition: mat.hpp:804
static Ptr< BinaryDescriptorMatcher > createBinaryDescriptorMatcher()
Create a BinaryDescriptorMatcher object and return a smart pointer to it.
int waitKey(int delay=0)
Waits for a pressed key.
Definition: imgproc.hpp:254

Sometimes, we could be interested in searching for the closest k descriptors, given an input one. This requires to modify slightly previous code:

// prepare a structure to host matches
std::vector<std::vector<DMatch> > matches;
// require knn match
bdm->knnMatch( descr1, descr2, matches, 6 );

In the above example, the closest 6 descriptors are returned for every query. In some cases, we could have a search radius and look for all descriptors distant at the most r from input query. Previous code must me modified:

// prepare a structure to host matches
std::vector<std::vector<DMatch> > matches;
// compute matches
bdm->radiusMatch( queries, matches, 30 );

Here's an example om matching among descriptors extratced from original cameraman image and its downsampled (and blurred) version:

matching2.png
alternate text

Querying internal database

The BynaryDescriptorMatcher class, owns an internal database that can be populated with descriptors extracted from different images and queried using one of the modalities described in previous section. Population of internal dataset can be done using the add function; such function doesn't directly add new data to database, but it just stores it them locally. The real update happens when function train is invoked or when any querying function is executed, since each of them invokes train before querying. When queried, internal database not only returns required descriptors, but, for every returned match, it is able to tell which image matched descriptor was extracted from. An example of internal dataset usage is described in the following code; after adding locally new descriptors, a radius search is invoked. This provokes local data to be transferred to dataset, which, in turn, is then queried.

1 /*M///////////////////////////////////////////////////////////////////////////////////////
2  //
3  // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
4  //
5  // By downloading, copying, installing or using the software you agree to this license.
6  // If you do not agree to this license, do not download, install,
7  // copy or use the software.
8  //
9  //
10  // License Agreement
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40  //M*/
41 
42 #include <iostream>
43 #include <opencv2/opencv_modules.hpp>
44 
45 #ifdef HAVE_OPENCV_FEATURES2D
46 
48 #include <opencv2/core/utility.hpp>
49 #include <opencv2/imgproc.hpp>
50 #include <opencv2/features2d.hpp>
51 #include <opencv2/highgui.hpp>
52 
53 #include <vector>
54 
55 using namespace cv;
56 using namespace cv::line_descriptor;
57 
58 static const std::string images[] =
59 { "cameraman.jpg", "church.jpg", "church2.png", "einstein.jpg", "stuff.jpg" };
60 
61 static const char* keys =
62 { "{@image_path | | Image path }" };
63 
64 static void help()
65 {
66  std::cout << "\nThis example shows the functionalities of radius matching " << "Please, run this sample using a command in the form\n"
67  << "./example_line_descriptor_radius_matching <path_to_input_images>/" << std::endl;
68 }
69 
70 int main( int argc, char** argv )
71 {
72  /* get parameters from comand line */
73  CommandLineParser parser( argc, argv, keys );
74  String pathToImages = parser.get < String > ( 0 );
75 
76  /* create structures for hosting KeyLines and descriptors */
77  int num_elements = sizeof ( images ) / sizeof ( images[0] );
78  std::vector < Mat > descriptorsMat;
79  std::vector < std::vector<KeyLine> > linesMat;
80 
81  /*create a pointer to a BinaryDescriptor object */
83 
84  /* compute lines and descriptors */
85  for ( int i = 0; i < num_elements; i++ )
86  {
87  /* get path to image */
88  std::stringstream image_path;
89  image_path << pathToImages << images[i];
90  std::cout << image_path.str().c_str() << std::endl;
91 
92  /* load image */
93  Mat loadedImage = imread( image_path.str().c_str(), 1 );
94  if( loadedImage.data == NULL )
95  {
96  std::cout << "Could not load images." << std::endl;
97  help();
98  exit( -1 );
99  }
100 
101  /* compute lines and descriptors */
102  std::vector < KeyLine > lines;
103  Mat computedDescr;
104  bd->detect( loadedImage, lines );
105  bd->compute( loadedImage, lines, computedDescr );
106 
107  descriptorsMat.push_back( computedDescr );
108  linesMat.push_back( lines );
109 
110  }
111 
112  /* compose a queries matrix */
113  Mat queries;
114  for ( size_t j = 0; j < descriptorsMat.size(); j++ )
115  {
116  if( descriptorsMat[j].rows >= 5 )
117  queries.push_back( descriptorsMat[j].rowRange( 0, 5 ) );
118 
119  else if( descriptorsMat[j].rows > 0 && descriptorsMat[j].rows < 5 )
120  queries.push_back( descriptorsMat[j] );
121  }
122 
123  std::cout << "It has been generated a matrix of " << queries.rows << " descriptors" << std::endl;
124 
125  /* create a BinaryDescriptorMatcher object */
127 
128  /* populate matcher */
129  bdm->add( descriptorsMat );
130 
131  /* compute matches */
132  std::vector < std::vector<DMatch> > matches;
133  bdm->radiusMatch( queries, matches, 30 );
134  std::cout << "size matches sample " << matches.size() << std::endl;
135 
136  for ( int i = 0; i < (int) matches.size(); i++ )
137  {
138  for ( int j = 0; j < (int) matches[i].size(); j++ )
139  {
140  std::cout << "match: " << matches[i][j].queryIdx << " " << matches[i][j].trainIdx << " " << matches[i][j].distance << std::endl;
141  }
142 
143  }
144 
145 }
146 
147 #else
148 
149 int main()
150 {
151  std::cerr << "OpenCV was built without features2d module" << std::endl;
152  return 0;
153 }
154 
155 #endif // HAVE_OPENCV_FEATURES2D
static Ptr< BinaryDescriptor > createBinaryDescriptor()
Create a BinaryDescriptor object with default parameters (or with the ones provided) and return a sma...
int rows
the number of rows and columns or (-1, -1) when the matrix has more than 2 dimensions ...
Definition: mat.hpp:2114
void compute(const Mat &image, std::vector< KeyLine > &keylines, Mat &descriptors, bool returnFloatDescr=false) const
Requires descriptors computation.
void push_back(const _Tp &elem)
Adds elements to the bottom of the matrix.
Mat imread(const String &filename, int flags=IMREAD_COLOR)
Loads an image from a file.
uchar * data
pointer to the data
Definition: mat.hpp:2116
Definition: affine.hpp:51
Designed for command line parsing.
Definition: utility.hpp:862
void add(const std::vector< Mat > &descriptors)
Store locally new descriptors to be inserted in dataset, without updating dataset.
const char * c_str() const
void radiusMatch(const Mat &queryDescriptors, const Mat &trainDescriptors, std::vector< std::vector< DMatch > > &matches, float maxDistance, const Mat &mask=Mat(), bool compactResult=false) const
For every input query descriptor, retrieve, from a dataset provided from user or from the one interna...
Definition: descriptor.hpp:74
Template class for smart pointers with shared ownership.
Definition: cvstd.hpp:261
void detect(const Mat &image, std::vector< KeyLine > &keypoints, const Mat &mask=Mat())
Requires line detection.
Definition: cvstd.hpp:458
n-dimensional dense array class
Definition: mat.hpp:804
static Ptr< BinaryDescriptorMatcher > createBinaryDescriptorMatcher()
Create a BinaryDescriptorMatcher object and return a smart pointer to it.