Refactor of KAZE and AKAZE:
1) Clean-up from the unused code 2) Remove of SURF extraction method 3) Enabled threading for KAZE extraction 4) Exposed new properties for runtime configuration
This commit is contained in:
Ievgen Khvedchenia
@@ -5,92 +5,81 @@
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* @author Pablo F. Alcantarilla
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*/
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#ifndef __OPENCV_FEATURES_2D_KAZE_CONFIG_HPP__
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#define __OPENCV_FEATURES_2D_KAZE_CONFIG_HPP__
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//******************************************************************************
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//******************************************************************************
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#pragma once
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// OpenCV Includes
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#include "precomp.hpp"
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#include <opencv2/features2d.hpp>
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//*************************************************************************************
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//*************************************************************************************
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// Some defines
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#define NMAX_CHAR 400
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// Some default options
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static const float DEFAULT_SCALE_OFFSET = 1.60f; // Base scale offset (sigma units)
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static const float DEFAULT_OCTAVE_MAX = 4.0f; // Maximum octave evolution of the image 2^sigma (coarsest scale sigma units)
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static const int DEFAULT_NSUBLEVELS = 4; // Default number of sublevels per scale level
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static const float DEFAULT_DETECTOR_THRESHOLD = 0.001f; // Detector response threshold to accept point
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static const float DEFAULT_MIN_DETECTOR_THRESHOLD = 0.00001f; // Minimum Detector response threshold to accept point
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static const int DEFAULT_DESCRIPTOR_MODE = 1; // Descriptor Mode 0->SURF, 1->M-SURF
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static const bool DEFAULT_USE_FED = true; // 0->AOS, 1->FED
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static const bool DEFAULT_UPRIGHT = false; // Upright descriptors, not invariant to rotation
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static const bool DEFAULT_EXTENDED = false; // Extended descriptor, dimension 128
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// Some important configuration variables
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static const float DEFAULT_SIGMA_SMOOTHING_DERIVATIVES = 1.0f;
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static const float DEFAULT_KCONTRAST = 0.01f;
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static const float KCONTRAST_PERCENTILE = 0.7f;
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static const int KCONTRAST_NBINS = 300;
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static const bool COMPUTE_KCONTRAST = true;
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static const int DEFAULT_DIFFUSIVITY_TYPE = 1; // 0 -> PM G1, 1 -> PM G2, 2 -> Weickert
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static const bool USE_CLIPPING_NORMALIZATION = false;
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static const float CLIPPING_NORMALIZATION_RATIO = 1.6f;
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static const int CLIPPING_NORMALIZATION_NITER = 5;
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//*************************************************************************************
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//*************************************************************************************
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struct KAZEOptions {
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KAZEOptions() {
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// Load the default options
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soffset = DEFAULT_SCALE_OFFSET;
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omax = static_cast<int>(DEFAULT_OCTAVE_MAX);
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nsublevels = DEFAULT_NSUBLEVELS;
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dthreshold = DEFAULT_DETECTOR_THRESHOLD;
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use_fed = DEFAULT_USE_FED;
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upright = DEFAULT_UPRIGHT;
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extended = DEFAULT_EXTENDED;
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descriptor = DEFAULT_DESCRIPTOR_MODE;
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diffusivity = DEFAULT_DIFFUSIVITY_TYPE;
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sderivatives = DEFAULT_SIGMA_SMOOTHING_DERIVATIVES;
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}
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enum DIFFUSIVITY_TYPE {
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PM_G1 = 0,
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PM_G2 = 1,
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WEICKERT = 2
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};
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float soffset;
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int omax;
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int nsublevels;
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int img_width;
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int img_height;
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int diffusivity;
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float sderivatives;
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float dthreshold;
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bool use_fed;
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bool upright;
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bool extended;
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int descriptor;
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KAZEOptions()
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: descriptor(cv::KAZE::DESCRIPTOR_MSURF)
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, diffusivity(PM_G2)
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, soffset(1.60f)
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, omax(4)
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, nsublevels(4)
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, img_width(0)
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, img_height(0)
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, sderivatives(1.0f)
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, dthreshold(0.001f)
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, kcontrast(0.01f)
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, kcontrast_percentille(0.7f)
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, kcontrast_bins(300)
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, use_fed(true)
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, upright(false)
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, extended(false)
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, use_clipping_normalilzation(false)
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, clipping_normalization_ratio(1.6f)
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, clipping_normalization_niter(5)
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{
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}
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cv::KAZE::DESCRIPTOR_TYPE descriptor;
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DIFFUSIVITY_TYPE diffusivity;
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float soffset;
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int omax;
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int nsublevels;
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int img_width;
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int img_height;
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float sderivatives;
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float dthreshold;
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float kcontrast;
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float kcontrast_percentille;
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int kcontrast_bins;
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bool use_fed;
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bool upright;
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bool extended;
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bool use_clipping_normalilzation;
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float clipping_normalization_ratio;
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int clipping_normalization_niter;
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};
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struct TEvolution {
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cv::Mat Lx, Ly; // First order spatial derivatives
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cv::Mat Lxx, Lxy, Lyy; // Second order spatial derivatives
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cv::Mat Lflow; // Diffusivity image
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cv::Mat Lt; // Evolution image
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cv::Mat Lsmooth; // Smoothed image
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cv::Mat Lstep; // Evolution step update
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cv::Mat Ldet; // Detector response
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float etime; // Evolution time
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float esigma; // Evolution sigma. For linear diffusion t = sigma^2 / 2
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float octave; // Image octave
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float sublevel; // Image sublevel in each octave
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int sigma_size; // Integer esigma. For computing the feature detector responses
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cv::Mat Lx, Ly; // First order spatial derivatives
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cv::Mat Lxx, Lxy, Lyy; // Second order spatial derivatives
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cv::Mat Lflow; // Diffusivity image
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cv::Mat Lt; // Evolution image
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cv::Mat Lsmooth; // Smoothed image
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cv::Mat Lstep; // Evolution step update
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cv::Mat Ldet; // Detector response
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float etime; // Evolution time
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float esigma; // Evolution sigma. For linear diffusion t = sigma^2 / 2
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float octave; // Image octave
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float sublevel; // Image sublevel in each octave
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int sigma_size; // Integer esigma. For computing the feature detector responses
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};
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//*************************************************************************************
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//*************************************************************************************
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#endif
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File diff suppressed because it is too large
Load Diff
@@ -26,97 +26,52 @@ class KAZEFeatures {
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private:
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// Parameters of the Nonlinear diffusion class
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float soffset_; // Base scale offset
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float sderivatives_; // Standard deviation of the Gaussian for the nonlinear diff. derivatives
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int omax_; // Maximum octave level
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int nsublevels_; // Number of sublevels per octave level
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int img_width_; // Width of the original image
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int img_height_; // Height of the original image
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std::vector<TEvolution> evolution_; // Vector of nonlinear diffusion evolution
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float kcontrast_; // The contrast parameter for the scalar nonlinear diffusion
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float dthreshold_; // Feature detector threshold response
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int diffusivity_; // Diffusivity type, 0->PM G1, 1->PM G2, 2-> Weickert
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int descriptor_mode_; // Descriptor mode
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bool use_fed_; // Set to true in case we want to use FED for the nonlinear diffusion filtering. Set false for using AOS
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bool use_upright_; // Set to true in case we want to use the upright version of the descriptors
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bool use_extended_; // Set to true in case we want to use the extended version of the descriptors
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bool use_normalization;
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KAZEOptions options;
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// Vector of keypoint vectors for finding extrema in multiple threads
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std::vector<std::vector<cv::KeyPoint> > kpts_par_;
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// Parameters of the Nonlinear diffusion class
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std::vector<TEvolution> evolution_; // Vector of nonlinear diffusion evolution
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// FED parameters
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int ncycles_; // Number of cycles
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bool reordering_; // Flag for reordering time steps
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std::vector<std::vector<float > > tsteps_; // Vector of FED dynamic time steps
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std::vector<int> nsteps_; // Vector of number of steps per cycle
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// Vector of keypoint vectors for finding extrema in multiple threads
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std::vector<std::vector<cv::KeyPoint> > kpts_par_;
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// Computation times variables in ms
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//double tkcontrast_; // Kcontrast factor computation
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//double tnlscale_; // Nonlinear Scale space generation
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//double tdetector_; // Feature detector
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//double tmderivatives_; // Multiscale derivatives computation
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//double tdresponse_; // Detector response computation
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//double tdescriptor_; // Feature descriptor
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//double tsubpixel_; // Subpixel refinement
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// FED parameters
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int ncycles_; // Number of cycles
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bool reordering_; // Flag for reordering time steps
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std::vector<std::vector<float > > tsteps_; // Vector of FED dynamic time steps
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std::vector<int> nsteps_; // Vector of number of steps per cycle
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// Some auxiliary variables used in the AOS step
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cv::Mat Ltx_, Lty_, px_, py_, ax_, ay_, bx_, by_, qr_, qc_;
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// Some auxiliary variables used in the AOS step
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cv::Mat Ltx_, Lty_, px_, py_, ax_, ay_, bx_, by_, qr_, qc_;
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public:
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// Constructor
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KAZEFeatures(KAZEOptions& options);
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// Constructor
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KAZEFeatures(KAZEOptions& options);
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// Public methods for KAZE interface
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void Allocate_Memory_Evolution(void);
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int Create_Nonlinear_Scale_Space(const cv::Mat& img);
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void Feature_Detection(std::vector<cv::KeyPoint>& kpts);
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void Feature_Description(std::vector<cv::KeyPoint>& kpts, cv::Mat& desc);
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// Public methods for KAZE interface
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void Allocate_Memory_Evolution(void);
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int Create_Nonlinear_Scale_Space(const cv::Mat& img);
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void Feature_Detection(std::vector<cv::KeyPoint>& kpts);
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void Feature_Description(std::vector<cv::KeyPoint>& kpts, cv::Mat& desc);
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static void Compute_Main_Orientation(cv::KeyPoint& kpt, const std::vector<TEvolution>& evolution_, const KAZEOptions& options);
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private:
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// Feature Detection Methods
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void Compute_KContrast(const cv::Mat& img, const float& kper);
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void Compute_Multiscale_Derivatives(void);
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void Compute_Detector_Response(void);
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void Determinant_Hessian_Parallel(std::vector<cv::KeyPoint>& kpts);
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void Find_Extremum_Threading(const int& level);
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void Do_Subpixel_Refinement(std::vector<cv::KeyPoint>& kpts);
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// Feature Detection Methods
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void Compute_KContrast(const cv::Mat& img, const float& kper);
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void Compute_Multiscale_Derivatives(void);
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void Compute_Detector_Response(void);
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void Determinant_Hessian_Parallel(std::vector<cv::KeyPoint>& kpts);
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void Find_Extremum_Threading(const int& level);
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void Do_Subpixel_Refinement(std::vector<cv::KeyPoint>& kpts);
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// AOS Methods
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void AOS_Step_Scalar(cv::Mat &Ld, const cv::Mat &Ldprev, const cv::Mat &c, const float& stepsize);
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void AOS_Rows(const cv::Mat &Ldprev, const cv::Mat &c, const float& stepsize);
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void AOS_Columns(const cv::Mat &Ldprev, const cv::Mat &c, const float& stepsize);
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void Thomas(const cv::Mat &a, const cv::Mat &b, const cv::Mat &Ld, cv::Mat &x);
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// AOS Methods
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void AOS_Step_Scalar(cv::Mat &Ld, const cv::Mat &Ldprev, const cv::Mat &c, const float& stepsize);
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void AOS_Rows(const cv::Mat &Ldprev, const cv::Mat &c, const float& stepsize);
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void AOS_Columns(const cv::Mat &Ldprev, const cv::Mat &c, const float& stepsize);
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void Thomas(const cv::Mat &a, const cv::Mat &b, const cv::Mat &Ld, cv::Mat &x);
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// Feature Description methods
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void Compute_Main_Orientation_SURF(cv::KeyPoint& kpt);
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// Descriptor Mode -> 0 SURF 64
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void Get_SURF_Upright_Descriptor_64(const cv::KeyPoint& kpt, float* desc);
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void Get_SURF_Descriptor_64(const cv::KeyPoint& kpt, float* desc);
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// Descriptor Mode -> 0 SURF 128
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void Get_SURF_Upright_Descriptor_128(const cv::KeyPoint& kpt, float* desc);
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void Get_SURF_Descriptor_128(const cv::KeyPoint& kpt, float* desc);
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// Descriptor Mode -> 1 M-SURF 64
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void Get_MSURF_Upright_Descriptor_64(const cv::KeyPoint& kpt, float* desc);
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void Get_MSURF_Descriptor_64(const cv::KeyPoint& kpt, float* desc);
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// Descriptor Mode -> 1 M-SURF 128
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void Get_MSURF_Upright_Descriptor_128(const cv::KeyPoint& kpt, float* desc);
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void Get_MSURF_Descriptor_128(const cv::KeyPoint& kpt, float *desc);
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// Descriptor Mode -> 2 G-SURF 64
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void Get_GSURF_Upright_Descriptor_64(const cv::KeyPoint& kpt, float* desc);
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void Get_GSURF_Descriptor_64(const cv::KeyPoint& kpt, float *desc);
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// Descriptor Mode -> 2 G-SURF 128
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void Get_GSURF_Upright_Descriptor_128(const cv::KeyPoint& kpt, float* desc);
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void Get_GSURF_Descriptor_128(const cv::KeyPoint& kpt, float* desc);
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};
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//*************************************************************************************
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