Prepare KAZE and AKAZE sources for integration

modules/features2d/src/akaze/AKAZE.cpp

@@ -33,7 +33,7 @@ using namespace cv;
  * @param options AKAZE configuration options
  * @note This constructor allocates memory for the nonlinear scale space
 */
-AKAZE::AKAZE(const AKAZEOptions& options) {
+AKAZEFeatures::AKAZEFeatures(const AKAZEOptions& options) {
 
   soffset_ = options.soffset;
   factor_size_ = DEFAULT_FACTOR_SIZE;
@@ -75,7 +75,7 @@ AKAZE::AKAZE(const AKAZEOptions& options) {
 /**
  * @brief AKAZE destructor
 */
-AKAZE::~AKAZE(void) {
+AKAZEFeatures::~AKAZEFeatures(void) {
 
   evolution_.clear();
 }
@@ -86,7 +86,7 @@ AKAZE::~AKAZE(void) {
 /**
  * @brief This method allocates the memory for the nonlinear diffusion evolution
 */
-void AKAZE::Allocate_Memory_Evolution(void) {
+void AKAZEFeatures::Allocate_Memory_Evolution(void) {
 
   float rfactor = 0.0;
   int level_height = 0, level_width = 0;
@@ -145,7 +145,7 @@ void AKAZE::Allocate_Memory_Evolution(void) {
  * @param img Input image for which the nonlinear scale space needs to be created
  * @return 0 if the nonlinear scale space was created successfully, -1 otherwise
 */
-int AKAZE::Create_Nonlinear_Scale_Space(const cv::Mat &img) {
+int AKAZEFeatures::Create_Nonlinear_Scale_Space(const cv::Mat &img) {
 
   double t1 = 0.0, t2 = 0.0;
 
@@ -222,7 +222,7 @@ int AKAZE::Create_Nonlinear_Scale_Space(const cv::Mat &img) {
  * @brief This method selects interesting keypoints through the nonlinear scale space
  * @param kpts Vector of detected keypoints
 */
-void AKAZE::Feature_Detection(std::vector<cv::KeyPoint>& kpts) {
+void AKAZEFeatures::Feature_Detection(std::vector<cv::KeyPoint>& kpts) {
 
   double t1 = 0.0, t2 = 0.0;
 
@@ -242,7 +242,7 @@ void AKAZE::Feature_Detection(std::vector<cv::KeyPoint>& kpts) {
 /**
  * @brief This method computes the multiscale derivatives for the nonlinear scale space
 */
-void AKAZE::Compute_Multiscale_Derivatives(void) {
+void AKAZEFeatures::Compute_Multiscale_Derivatives(void) {
 
   double t1 = 0.0, t2 = 0.0;
 
@@ -279,7 +279,7 @@ void AKAZE::Compute_Multiscale_Derivatives(void) {
  * @brief This method computes the feature detector response for the nonlinear scale space
  * @note We use the Hessian determinant as the feature detector response
 */
-void AKAZE::Compute_Determinant_Hessian_Response(void) {
+void AKAZEFeatures::Compute_Determinant_Hessian_Response(void) {
 
   // Firstly compute the multiscale derivatives
   Compute_Multiscale_Derivatives();
@@ -307,7 +307,7 @@ void AKAZE::Compute_Determinant_Hessian_Response(void) {
  * @brief This method finds extrema in the nonlinear scale space
  * @param kpts Vector of detected keypoints
 */
-void AKAZE::Find_Scale_Space_Extrema(std::vector<cv::KeyPoint>& kpts) {
+void AKAZEFeatures::Find_Scale_Space_Extrema(std::vector<cv::KeyPoint>& kpts) {
 
   double t1 = 0.0, t2 = 0.0;
   float value = 0.0;
@@ -418,7 +418,7 @@ void AKAZE::Find_Scale_Space_Extrema(std::vector<cv::KeyPoint>& kpts) {
  * @brief This method performs subpixel refinement of the detected keypoints
  * @param kpts Vector of detected keypoints
 */
-void AKAZE::Do_Subpixel_Refinement(std::vector<cv::KeyPoint>& kpts) {
+void AKAZEFeatures::Do_Subpixel_Refinement(std::vector<cv::KeyPoint>& kpts) {
 
   double t1 = 0.0, t2 = 0.0;
   float Dx = 0.0, Dy = 0.0, ratio = 0.0;
@@ -493,7 +493,7 @@ void AKAZE::Do_Subpixel_Refinement(std::vector<cv::KeyPoint>& kpts) {
  * @param kpts Vector of keypoints
  * @param mdist Maximum distance in pixels
 */
-void AKAZE::Feature_Suppression_Distance(std::vector<cv::KeyPoint>& kpts, float mdist) {
+void AKAZEFeatures::Feature_Suppression_Distance(std::vector<cv::KeyPoint>& kpts, float mdist) {
 
   vector<KeyPoint> aux;
   vector<int> to_delete;
@@ -545,7 +545,7 @@ void AKAZE::Feature_Suppression_Distance(std::vector<cv::KeyPoint>& kpts, float
  * @param kpts Vector of detected keypoints
  * @param desc Matrix to store the descriptors
 */
-void AKAZE::Compute_Descriptors(std::vector<cv::KeyPoint>& kpts, cv::Mat& desc) {
+void AKAZEFeatures::Compute_Descriptors(std::vector<cv::KeyPoint>& kpts, cv::Mat& desc) {
 
   double t1 = 0.0, t2 = 0.0;
 
@@ -653,7 +653,7 @@ void AKAZE::Compute_Descriptors(std::vector<cv::KeyPoint>& kpts, cv::Mat& desc)
  * @note The orientation is computed using a similar approach as described in the
  * original SURF method. See Bay et al., Speeded Up Robust Features, ECCV 2006
 */
-void AKAZE::Compute_Main_Orientation_SURF(cv::KeyPoint& kpt) {
+void AKAZEFeatures::Compute_Main_Orientation_SURF(cv::KeyPoint& kpt) {
 
   int ix = 0, iy = 0, idx = 0, s = 0, level = 0;
   float xf = 0.0, yf = 0.0, gweight = 0.0, ratio = 0.0;
@@ -728,7 +728,7 @@ void AKAZE::Compute_Main_Orientation_SURF(cv::KeyPoint& kpt) {
  * Gaussian weighting is performed. The descriptor is inspired from Bay et al.,
  * Speeded Up Robust Features, ECCV, 2006
 */
-void AKAZE::Get_SURF_Descriptor_Upright_64(const cv::KeyPoint& kpt, float *desc) {
+void AKAZEFeatures::Get_SURF_Descriptor_Upright_64(const cv::KeyPoint& kpt, float *desc) {
 
   float dx = 0.0, dy = 0.0, mdx = 0.0, mdy = 0.0;
   float rx = 0.0, ry = 0.0, len = 0.0, xf = 0.0, yf = 0.0;
@@ -819,7 +819,7 @@ void AKAZE::Get_SURF_Descriptor_Upright_64(const cv::KeyPoint& kpt, float *desc)
  * Gaussian weighting is performed. The descriptor is inspired from Bay et al.,
  * Speeded Up Robust Features, ECCV, 2006
 */
-void AKAZE::Get_SURF_Descriptor_64(const cv::KeyPoint& kpt, float *desc) {
+void AKAZEFeatures::Get_SURF_Descriptor_64(const cv::KeyPoint& kpt, float *desc) {
 
   float dx = 0.0, dy = 0.0, mdx = 0.0, mdy = 0.0;
   float rx = 0.0, ry = 0.0, rrx = 0.0, rry = 0.0, len = 0.0, xf = 0.0, yf = 0.0;
@@ -918,7 +918,7 @@ void AKAZE::Get_SURF_Descriptor_64(const cv::KeyPoint& kpt, float *desc) {
  * from Agrawal et al., CenSurE: Center Surround Extremas for Realtime Feature Detection and Matching,
  * ECCV 2008
 */
-void AKAZE::Get_MSURF_Upright_Descriptor_64(const cv::KeyPoint& kpt, float *desc) {
+void AKAZEFeatures::Get_MSURF_Upright_Descriptor_64(const cv::KeyPoint& kpt, float *desc) {
 
   float dx = 0.0, dy = 0.0, mdx = 0.0, mdy = 0.0, gauss_s1 = 0.0, gauss_s2 = 0.0;
   float rx = 0.0, ry = 0.0, len = 0.0, xf = 0.0, yf = 0.0, ys = 0.0, xs = 0.0;
@@ -1041,7 +1041,7 @@ void AKAZE::Get_MSURF_Upright_Descriptor_64(const cv::KeyPoint& kpt, float *desc
  * from Agrawal et al., CenSurE: Center Surround Extremas for Realtime Feature Detection and Matching,
  * ECCV 2008
 */
-void AKAZE::Get_MSURF_Descriptor_64(const cv::KeyPoint& kpt, float *desc) {
+void AKAZEFeatures::Get_MSURF_Descriptor_64(const cv::KeyPoint& kpt, float *desc) {
 
   float dx = 0.0, dy = 0.0, mdx = 0.0, mdy = 0.0, gauss_s1 = 0.0, gauss_s2 = 0.0;
   float rx = 0.0, ry = 0.0, rrx = 0.0, rry = 0.0, len = 0.0, xf = 0.0, yf = 0.0, ys = 0.0, xs = 0.0;
@@ -1165,7 +1165,7 @@ void AKAZE::Get_MSURF_Descriptor_64(const cv::KeyPoint& kpt, float *desc) {
  * @param kpt Input keypoint
  * @param desc Descriptor vector
 */
-void AKAZE::Get_Upright_MLDB_Full_Descriptor(const cv::KeyPoint& kpt, unsigned char *desc) {
+void AKAZEFeatures::Get_Upright_MLDB_Full_Descriptor(const cv::KeyPoint& kpt, unsigned char *desc) {
 
   float di = 0.0, dx = 0.0, dy = 0.0;
   float ri = 0.0, rx = 0.0, ry = 0.0, xf = 0.0, yf = 0.0;
@@ -1378,7 +1378,7 @@ void AKAZE::Get_Upright_MLDB_Full_Descriptor(const cv::KeyPoint& kpt, unsigned c
  * @param kpt Input keypoint
  * @param desc Descriptor vector
 */
-void AKAZE::Get_MLDB_Full_Descriptor(const cv::KeyPoint& kpt, unsigned char *desc) {
+void AKAZEFeatures::Get_MLDB_Full_Descriptor(const cv::KeyPoint& kpt, unsigned char *desc) {
 
   float di = 0.0, dx = 0.0, dy = 0.0, ratio = 0.0;
   float ri = 0.0, rx = 0.0, ry = 0.0, rrx = 0.0, rry = 0.0, xf = 0.0, yf = 0.0;
@@ -1680,7 +1680,7 @@ void AKAZE::Get_MLDB_Full_Descriptor(const cv::KeyPoint& kpt, unsigned char *des
  * @param kpt Input keypoint
  * @param desc Descriptor vector
 */
-void AKAZE::Get_MLDB_Descriptor_Subset(const cv::KeyPoint& kpt, unsigned char *desc) {
+void AKAZEFeatures::Get_MLDB_Descriptor_Subset(const cv::KeyPoint& kpt, unsigned char *desc) {
 
   float di, dx, dy;
   float  rx, ry;
@@ -1772,7 +1772,7 @@ void AKAZE::Get_MLDB_Descriptor_Subset(const cv::KeyPoint& kpt, unsigned char *d
  * @param kpt Input keypoint
  * @param desc Descriptor vector
 */
-void AKAZE::Get_Upright_MLDB_Descriptor_Subset(const cv::KeyPoint& kpt, unsigned char *desc) {
+void AKAZEFeatures::Get_Upright_MLDB_Descriptor_Subset(const cv::KeyPoint& kpt, unsigned char *desc) {
 
   float di = 0.0f, dx = 0.0f, dy = 0.0f;
   float rx = 0.0f, ry = 0.0f;
@@ -1851,22 +1851,6 @@ void AKAZE::Get_Upright_MLDB_Descriptor_Subset(const cv::KeyPoint& kpt, unsigned
 //*************************************************************************************
 //*************************************************************************************
 
-/**
- * @brief This method displays the computation times
-*/
-void AKAZE::Show_Computation_Times(void) {
-
-  cout << "(*) Time Scale Space: " << tscale_ << endl;
-  cout << "(*) Time Detector: " << tdetector_ << endl;
-  cout << "   - Time Derivatives: " << tderivatives_ << endl;
-  cout << "   - Time Extrema: " << textrema_ << endl;
-  cout << "   - Time Subpixel: " << tsubpixel_ << endl;
-  cout << "(*) Time Descriptor: " << tdescriptor_ << endl;
-}
-
-//*************************************************************************************
-//*************************************************************************************
-
 /**
  * @brief This function computes a (quasi-random) list of bits to be taken
  * from the full descriptor. To speed the extraction, the function creates

modules/features2d/src/akaze/AKAZE.h

@@ -22,7 +22,7 @@
 //*************************************************************************************
 
 // AKAZE Class Declaration
-class AKAZE {
+class AKAZEFeatures {
 
 private:
 
@@ -72,10 +72,10 @@ private:
 public:
 
   // Constructor
-  AKAZE(const AKAZEOptions &options);
+  AKAZEFeatures(const AKAZEOptions &options);
 
   // Destructor
-  ~AKAZE(void);
+  ~AKAZEFeatures(void);
 
   // Setters
   void Set_Octave_Max(const int& omax) {
@@ -144,11 +144,6 @@ public:
   void Get_MLDB_Full_Descriptor(const cv::KeyPoint& kpt, unsigned char *desc);
   void Get_Upright_MLDB_Descriptor_Subset(const cv::KeyPoint& kpt, unsigned char *desc);
   void Get_MLDB_Descriptor_Subset(const cv::KeyPoint& kpt, unsigned char *desc);
-
-  // Methods for saving some results and showing computation times
-  void Save_Scale_Space(void);
-  void Save_Detector_Responses(void);
-  void Show_Computation_Times(void);
 };
 
 //*************************************************************************************

modules/features2d/src/akaze/config.h

-#ifndef _CONFIG_H_
-#define _CONFIG_H_
+#ifndef __OPENCV_FEATURES_2D_AKAZE_CONFIG_HPP__
+#define __OPENCV_FEATURES_2D_AKAZE_CONFIG_HPP__
 
 // STL
 #include <string>
@@ -17,7 +17,7 @@
 #endif
 
 // Lookup table for 2d gaussian (sigma = 2.5) where (0,0) is top left and (6,6) is bottom right
-const float gauss25[7][7] = {
+static const float gauss25[7][7] = {
   {0.02546481f,	0.02350698f,	0.01849125f,	0.01239505f,	0.00708017f,	0.00344629f,	0.00142946f},
   {0.02350698f,	0.02169968f,	0.01706957f,	0.01144208f,	0.00653582f,	0.00318132f,	0.00131956f},
   {0.01849125f,	0.01706957f,	0.01342740f,	0.00900066f,	0.00514126f,	0.00250252f,	0.00103800f},
@@ -29,24 +29,24 @@ const float gauss25[7][7] = {
 
 
 // Scale Space parameters
-const float DEFAULT_SCALE_OFFSET = 1.60f;    // Base scale offset (sigma units)
-const float DEFAULT_FACTOR_SIZE = 1.5f;      // Factor for the multiscale derivatives
-const int DEFAULT_OCTAVE_MIN = 0;            // Initial octave level (-1 means that the size of the input image is duplicated)
-const int DEFAULT_OCTAVE_MAX = 4;            // Maximum octave evolution of the image 2^sigma (coarsest scale sigma units)
-const int DEFAULT_NSUBLEVELS = 4;            // Default number of sublevels per scale level
-const int DEFAULT_DIFFUSIVITY_TYPE = 1;
-const float KCONTRAST_PERCENTILE = 0.7f;
-const int KCONTRAST_NBINS = 300;
-const float DEFAULT_SIGMA_SMOOTHING_DERIVATIVES = 1.0f;
-const float DEFAULT_KCONTRAST = .01f;
+static const float DEFAULT_SCALE_OFFSET = 1.60f;    // Base scale offset (sigma units)
+static const float DEFAULT_FACTOR_SIZE = 1.5f;      // Factor for the multiscale derivatives
+static const int DEFAULT_OCTAVE_MIN = 0;            // Initial octave level (-1 means that the size of the input image is duplicated)
+static const int DEFAULT_OCTAVE_MAX = 4;            // Maximum octave evolution of the image 2^sigma (coarsest scale sigma units)
+static const int DEFAULT_NSUBLEVELS = 4;            // Default number of sublevels per scale level
+static const int DEFAULT_DIFFUSIVITY_TYPE = 1;
+static const float KCONTRAST_PERCENTILE = 0.7f;
+static const int KCONTRAST_NBINS = 300;
+static const float DEFAULT_SIGMA_SMOOTHING_DERIVATIVES = 1.0f;
+static const float DEFAULT_KCONTRAST = .01f;
 
 
 // Detector Parameters
-const float DEFAULT_DETECTOR_THRESHOLD = 0.001f;           // Detector response threshold to accept point
-const float DEFAULT_MIN_DETECTOR_THRESHOLD = 0.00001f;     // Minimum Detector response threshold to accept point
-const int DEFAULT_LDB_DESCRIPTOR_SIZE = 0;  // Use 0 for the full descriptor, or the number of bits
-const int DEFAULT_LDB_PATTERN_SIZE = 10;    // Actual patch size is 2*pattern_size*point.scale;
-const int DEFAULT_LDB_CHANNELS = 3;
+static const float DEFAULT_DETECTOR_THRESHOLD = 0.001f;           // Detector response threshold to accept point
+static const float DEFAULT_MIN_DETECTOR_THRESHOLD = 0.00001f;     // Minimum Detector response threshold to accept point
+static const int DEFAULT_LDB_DESCRIPTOR_SIZE = 0;  // Use 0 for the full descriptor, or the number of bits
+static const int DEFAULT_LDB_PATTERN_SIZE = 10;    // Actual patch size is 2*pattern_size*point.scale;
+static const int DEFAULT_LDB_CHANNELS = 3;
 
 // Descriptor Parameters
 enum DESCRIPTOR_TYPE
@@ -59,13 +59,13 @@ enum DESCRIPTOR_TYPE
   MLDB = 5
 };
 
-const int DEFAULT_DESCRIPTOR = MLDB;
+static const int DEFAULT_DESCRIPTOR = MLDB;
 
 // Some debugging options
-const bool DEFAULT_SAVE_SCALE_SPACE = false; // For saving the scale space images
-const bool DEFAULT_VERBOSITY = false; // Verbosity level (0->no verbosity)
-const bool DEFAULT_SHOW_RESULTS = true; // For showing the output image with the detected features plus some ratios
-const bool DEFAULT_SAVE_KEYPOINTS = false; // For saving the list of keypoints
+static const bool DEFAULT_SAVE_SCALE_SPACE = false; // For saving the scale space images
+static const bool DEFAULT_VERBOSITY = false; // Verbosity level (0->no verbosity)
+static const bool DEFAULT_SHOW_RESULTS = true; // For showing the output image with the detected features plus some ratios
+static const bool DEFAULT_SAVE_KEYPOINTS = false; // For saving the list of keypoints
 
 // Options structure
 struct AKAZEOptions

modules/features2d/src/kaze/KAZE.h

@@ -23,7 +23,7 @@
 //*************************************************************************************
 
 // KAZE Class Declaration
-class KAZE {
+class KAZEFeatures {
 
 private:
 
@@ -69,10 +69,10 @@ private:
 public:
 
   // Constructor
-  KAZE(KAZEOptions& options);
+  KAZEFeatures(KAZEOptions& options);
 
   // Destructor
-  ~KAZE(void);
+  ~KAZEFeatures(void);
 
   // Public methods for KAZE interface
   void Allocate_Memory_Evolution(void);
@@ -80,11 +80,6 @@ public:
   void Feature_Detection(std::vector<cv::KeyPoint>& kpts);
   void Feature_Description(std::vector<cv::KeyPoint>& kpts, cv::Mat& desc);
 
-  // Methods for saving the scale space set of images and detector responses
-  void Save_Nonlinear_Scale_Space(void);
-  void Save_Detector_Responses(void);
-  void Save_Flow_Responses(void);
-
 private:
 
   // Feature Detection Methods

modules/features2d/src/kaze/config.h

@@ -6,8 +6,8 @@
  * @author Pablo F. Alcantarilla
  */
 
-#ifndef _CONFIG_H_
-#define _CONFIG_H_
+#ifndef __OPENCV_FEATURES_2D_KAZE_CONFIG_HPP__
+#define __OPENCV_FEATURES_2D_KAZE_CONFIG_HPP__
 
 //******************************************************************************
 //******************************************************************************
@@ -38,30 +38,30 @@
 #define NMAX_CHAR 400
 
 // Some default options
-const float DEFAULT_SCALE_OFFSET = 1.60; // Base scale offset (sigma units)
-const float DEFAULT_OCTAVE_MAX = 4.0; // Maximum octave evolution of the image 2^sigma (coarsest scale sigma units)
-const int DEFAULT_NSUBLEVELS = 4; // Default number of sublevels per scale level
-const float DEFAULT_DETECTOR_THRESHOLD = 0.001; // Detector response threshold to accept point
-const float DEFAULT_MIN_DETECTOR_THRESHOLD = 0.00001;     // Minimum Detector response threshold to accept point
-const int DEFAULT_DESCRIPTOR_MODE = 1; // Descriptor Mode 0->SURF, 1->M-SURF
-const bool DEFAULT_USE_FED = true;  // 0->AOS, 1->FED
-const bool DEFAULT_UPRIGHT = false;  // Upright descriptors, not invariant to rotation
-const bool DEFAULT_EXTENDED = false; // Extended descriptor, dimension 128
-const bool DEFAULT_SAVE_SCALE_SPACE = false; // For saving the scale space images
-const bool DEFAULT_VERBOSITY = false; // Verbosity level (0->no verbosity)
-const bool DEFAULT_SHOW_RESULTS = true; // For showing the output image with the detected features plus some ratios
-const bool DEFAULT_SAVE_KEYPOINTS = false; // For saving the list of keypoints
+static const float DEFAULT_SCALE_OFFSET = 1.60; // Base scale offset (sigma units)
+static const float DEFAULT_OCTAVE_MAX = 4.0; // Maximum octave evolution of the image 2^sigma (coarsest scale sigma units)
+static const int DEFAULT_NSUBLEVELS = 4; // Default number of sublevels per scale level
+static const float DEFAULT_DETECTOR_THRESHOLD = 0.001; // Detector response threshold to accept point
+static const float DEFAULT_MIN_DETECTOR_THRESHOLD = 0.00001;     // Minimum Detector response threshold to accept point
+static const int DEFAULT_DESCRIPTOR_MODE = 1; // Descriptor Mode 0->SURF, 1->M-SURF
+static const bool DEFAULT_USE_FED = true;  // 0->AOS, 1->FED
+static const bool DEFAULT_UPRIGHT = false;  // Upright descriptors, not invariant to rotation
+static const bool DEFAULT_EXTENDED = false; // Extended descriptor, dimension 128
+static const bool DEFAULT_SAVE_SCALE_SPACE = false; // For saving the scale space images
+static const bool DEFAULT_VERBOSITY = false; // Verbosity level (0->no verbosity)
+static const bool DEFAULT_SHOW_RESULTS = true; // For showing the output image with the detected features plus some ratios
+static const bool DEFAULT_SAVE_KEYPOINTS = false; // For saving the list of keypoints
 
 // Some important configuration variables
-const float DEFAULT_SIGMA_SMOOTHING_DERIVATIVES = 1.0;
-const float DEFAULT_KCONTRAST = .01;
-const float KCONTRAST_PERCENTILE = 0.7;
-const int KCONTRAST_NBINS = 300;
-const bool COMPUTE_KCONTRAST = true;
-const int DEFAULT_DIFFUSIVITY_TYPE = 1;  // 0 -> PM G1, 1 -> PM G2, 2 -> Weickert
-const bool USE_CLIPPING_NORMALIZATION = false;
-const float CLIPPING_NORMALIZATION_RATIO = 1.6;
-const int CLIPPING_NORMALIZATION_NITER = 5;
+static const float DEFAULT_SIGMA_SMOOTHING_DERIVATIVES = 1.0;
+static const float DEFAULT_KCONTRAST = .01;
+static const float KCONTRAST_PERCENTILE = 0.7;
+static const int KCONTRAST_NBINS = 300;
+static const bool COMPUTE_KCONTRAST = true;
+static const int DEFAULT_DIFFUSIVITY_TYPE = 1;  // 0 -> PM G1, 1 -> PM G2, 2 -> Weickert
+static const bool USE_CLIPPING_NORMALIZATION = false;
+static const float CLIPPING_NORMALIZATION_RATIO = 1.6;
+static const int CLIPPING_NORMALIZATION_NITER = 5;
 
 //*************************************************************************************
 //*************************************************************************************