CFeatureExtraction_common.cpp

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/* +---------------------------------------------------------------------------+
   |                     Mobile Robot Programming Toolkit (MRPT)               |
   |                          http://www.mrpt.org/                             |
   |                                                                           |
   | Copyright (c) 2005-2018, Individual contributors, see AUTHORS file        |
   | See: http://www.mrpt.org/Authors - All rights reserved.                   |
   | Released under BSD License. See details in http://www.mrpt.org/License    |
   +---------------------------------------------------------------------------+
   */
 
#include "vision-precomp.h"  // Precompiled headers
 
#include <mrpt/vision/CFeatureExtraction.h>
#include <mrpt/system/CTicTac.h>
#include <mrpt/serialization/CArchive.h>
 
using namespace mrpt;
using namespace mrpt::img;
using namespace mrpt::vision;
using namespace mrpt::img;
using namespace mrpt::system;
using namespace std;
 
CFeatureExtraction::~CFeatureExtraction() {}
struct sort_pred
{
        bool operator()(
                const std::vector<unsigned int>& left,
                const std::vector<unsigned int>& right)
        {
                return left[1] < right[1];
        }
};
 
/************************************************************************************************
*                                                               extractFeatures *
************************************************************************************************/
void CFeatureExtraction::detectFeatures(
        const CImage& img, CFeatureList& feats, const unsigned int init_ID,
        const unsigned int nDesiredFeatures, const TImageROI& ROI) const
{
        switch (options.featsType)
        {
                case featHarris:
                        MRPT_TODO(
                                "Refactor: check if OpenCV's tile method can be directly "
                                "called to save space here?")
                        if (options.harrisOptions.tile_image)
                        {
                                mrpt::system::CTicTac tictac;
 
                                if (!(ROI.xMax == 0 && ROI.xMin == 0 && ROI.yMax == 0 &&
                                          ROI.yMin == 0))  // ROI must be not active for this option
                                        std::cout << "Warning: Image ROI is not taken into "
                                                                 "account, as harrisOptions.tile is set to YES"
                                                          << std::endl;
 
                                TImageROI newROI;
 
                                unsigned int wd = img.getWidth();
                                unsigned int hg = img.getHeight();
 
                                unsigned int tt =
                                        0;  // Total number of features detected in the whole image
                                std::vector<std::vector<unsigned int>> tam(8);
                                std::vector<CFeatureList> aux_feats(
                                        8);  // 2x4 tiles into the image -> 8 sets of features
 
                                for (unsigned int k = 0; k < 4;
                                         k++)  // Search over the 2x4 tiled image
                                {
                                        // Resize the inner vector
                                        tam[k].resize(2);
                                        tam[k + 4].resize(2);
 
                                        // First row
                                        newROI.xMin = k * wd / 4.f;
                                        newROI.yMin = 0;
                                        newROI.xMax = wd / 4.f + k * wd / 4.f - 1;
                                        newROI.yMax = hg / 2.f - 1;
 
                                        tictac.Tic();
                                        extractFeaturesKLT(
                                                img, aux_feats[k], init_ID, nDesiredFeatures, newROI);
                                        cout << "Tiempo en extraer una tile: "
                                                 << tictac.Tac() * 1000.0f << endl;
 
                                        tam[k][0] = k;
                                        tam[k][1] = aux_feats[k].size();
 
                                        // Second row
                                        newROI.xMin = k * wd / 4;
                                        newROI.yMin = hg / 2;
                                        newROI.xMax = wd / 4 + k * wd / 4 - 1;
                                        newROI.yMax = hg - 1;
 
                                        tictac.Tic();
                                        extractFeaturesKLT(
                                                img, aux_feats[k + 4], init_ID, nDesiredFeatures,
                                                newROI);
                                        cout << "Tiempo en extraer una tile: "
                                                 << tictac.Tac() * 1000.0f << endl;
 
                                        tam[k + 4][0] = k + 4;
                                        tam[k + 4][1] = aux_feats[k + 4].size();
 
                                        tt += aux_feats[k].size() + aux_feats[k + 4].size();
                                }
 
                                // Merge all the features
                                unsigned int new_nDesiredFeatures =
                                        nDesiredFeatures <= 0 ? 300 : nDesiredFeatures;
                                unsigned int o_n_per_tile = floor(new_nDesiredFeatures / 8.0f);
                                feats.clear();
                                if (tt > new_nDesiredFeatures)  // We have found too many
                                // features, we have to select
                                // them
                                {
                                        // Order the size vector
                                        std::sort(tam.begin(), tam.end(), sort_pred());
 
                                        if (tam[0][1] > o_n_per_tile)  // The smallest subset
                                        {
                                                // Everything goes right -> Get o_n_per_tile features
                                                // from each tile.
                                                for (unsigned int m = 0; m < 8; m++)
                                                        for (unsigned int k = 0; k < o_n_per_tile; k++)
                                                                feats.push_back(aux_feats[m][k]);
                                        }
                                        else
                                        {
                                                std::vector<std::vector<unsigned int>>::iterator
                                                        itVector;
                                                unsigned int n_per_tile = o_n_per_tile;
 
                                                for (itVector = tam.begin(); itVector != tam.end();
                                                         itVector++)
                                                {
                                                        if ((*itVector)[1] <
                                                                n_per_tile)  // Size of the subset
                                                        {
                                                                // We have to distribute the features among the
                                                                // tiles
                                                                for (unsigned int k = 0; k < (*itVector)[1];
                                                                         k++)
                                                                {
                                                                        feats.push_back(
                                                                                aux_feats[(*itVector)[0]][k]);
                                                                        n_per_tile += (n_per_tile - (*itVector)[1]);
                                                                }  // end for
                                                        }  // end if
                                                        else
                                                        {
                                                                for (unsigned int k = 0; k < n_per_tile; k++)
                                                                {
                                                                        feats.push_back(
                                                                                aux_feats[(*itVector)[0]][k]);
                                                                        n_per_tile = o_n_per_tile;
                                                                }  // end for
                                                        }  // end else
                                                }  // end for 'itVector'
                                        }  // end else
                                }  // end if tt > nDesiredFeatures
                                else  // We have found less features than the desired
                                {
                                        CFeatureList::iterator itList;
                                        for (unsigned int m = 0; m < 8; m++)
                                                for (itList = aux_feats[m].begin();
                                                         itList != aux_feats[m].end(); itList++)
                                                        feats.push_back(*itList);
                                        ;
                                }
 
                        }  // end if
 
                        else
                                extractFeaturesKLT(img, feats, init_ID, nDesiredFeatures, ROI);
                        break;
 
                case featKLT:
                        extractFeaturesKLT(img, feats, init_ID, nDesiredFeatures, ROI);
                        break;
 
                case featSIFT:
                        extractFeaturesSIFT(img, feats, init_ID, nDesiredFeatures, ROI);
                        break;
 
                case featBCD:
                        extractFeaturesBCD(img, feats, init_ID, nDesiredFeatures, ROI);
                        break;
 
                case featSURF:
                        extractFeaturesSURF(img, feats, init_ID, nDesiredFeatures, ROI);
                        break;
 
                case featFAST:
                        extractFeaturesFAST(img, feats, init_ID, nDesiredFeatures, ROI);
                        break;
 
                case featFASTER9:
                        extractFeaturesFASTER_N(
                                9, img, feats, init_ID, nDesiredFeatures, ROI);
                        break;
                case featFASTER10:
                        extractFeaturesFASTER_N(
                                10, img, feats, init_ID, nDesiredFeatures, ROI);
                        break;
                case featFASTER12:
                        extractFeaturesFASTER_N(
                                12, img, feats, init_ID, nDesiredFeatures, ROI);
                        break;
 
                case featORB:
                        extractFeaturesORB(img, feats, init_ID, nDesiredFeatures, ROI);
                        break;
 
                // # added by Raghavender Sahdev
                case featAKAZE:
                        extractFeaturesAKAZE(img, feats, init_ID, nDesiredFeatures, ROI);
                        break;
                case featLSD:
                        extractFeaturesLSD(img, feats, init_ID, nDesiredFeatures, ROI);
                        break;
 
                default:
                        THROW_EXCEPTION("options.method has an invalid value!");
                        break;
        }
}
 
/************************************************************************************************
                                                                computeDescriptors
************************************************************************************************/
void CFeatureExtraction::computeDescriptors(
        const CImage& in_img, CFeatureList& inout_features,
        TDescriptorType in_descriptor_list) const
{
        MRPT_START
 
        int nDescComputed = 0;
 
        if ((in_descriptor_list & descSIFT) != 0)
        {
                this->internal_computeSiftDescriptors(in_img, inout_features);
                ++nDescComputed;
        }
        if ((in_descriptor_list & descSURF) != 0)
        {
                this->internal_computeSurfDescriptors(in_img, inout_features);
                ++nDescComputed;
        }
        if ((in_descriptor_list & descSpinImages) != 0)
        {
                this->internal_computeSpinImageDescriptors(in_img, inout_features);
                ++nDescComputed;
        }
        if ((in_descriptor_list & descPolarImages) != 0)
        {
                this->internal_computePolarImageDescriptors(in_img, inout_features);
                ++nDescComputed;
        }
        if ((in_descriptor_list & descLogPolarImages) != 0)
        {
                this->internal_computeLogPolarImageDescriptors(in_img, inout_features);
                ++nDescComputed;
        }
        if ((in_descriptor_list & descORB) != 0)
        {
                this->internal_computeORBDescriptors(in_img, inout_features);
                ++nDescComputed;
        }
        // # added by Raghavender Sahdev
        if ((in_descriptor_list & descBLD) != 0)
        {
                this->internal_computeBLDLineDescriptors(in_img, inout_features);
                ++nDescComputed;
        }
        if ((in_descriptor_list & descLATCH) != 0)
        {
                this->internal_computeLATCHDescriptors(in_img, inout_features);
                ++nDescComputed;
        }
        if (!nDescComputed)
                THROW_EXCEPTION_FMT(
                        "No known descriptor value found in in_descriptor_list=%u",
                        (unsigned)in_descriptor_list)
 
        MRPT_END
}
 
/************************************************************************************************
*                                                               extractFeaturesBCD *
************************************************************************************************/
void CFeatureExtraction::extractFeaturesBCD(
        const CImage& img, CFeatureList& feats, unsigned int init_ID,
        unsigned int nDesiredFeatures, const TImageROI& ROI) const
{
        MRPT_UNUSED_PARAM(img);
        MRPT_UNUSED_PARAM(feats);
        MRPT_UNUSED_PARAM(init_ID);
        MRPT_UNUSED_PARAM(nDesiredFeatures);
        MRPT_UNUSED_PARAM(ROI);
 
        THROW_EXCEPTION("Not implemented yet!");
}  // end extractFeaturesBCD
 
/*------------------------------------------------------------
                                        TOptions()
-------------------------------------------------------------*/
CFeatureExtraction::TOptions::TOptions(const TFeatureType _featsType)
        : featsType(_featsType)  // Default Method: Kanade-Lucas-Tomasi
{
        // General options
        patchSize = 21;  // Patch size
        FIND_SUBPIXEL = true;  // Find subpixel
        useMask = false;  // Use mask for finding features
        addNewFeatures = false;  // Add to existing feature list
 
        // Harris Options
        harrisOptions.k = 0.04f;
        harrisOptions.radius = 3;  // 15;
        harrisOptions.threshold =
                0.005f;  // 0.01f; The lower this is, more features will be found
        harrisOptions.sigma = 3.0f;
        harrisOptions.min_distance = 5;  // 10;
        harrisOptions.tile_image = false;
 
        // KLT Options
        KLTOptions.min_distance = 5;  // 10;
        KLTOptions.threshold = 0.1f;  // 0.005 ; 0.01f;
        KLTOptions.radius = 15;  // 3;
        KLTOptions.tile_image = false;
 
        // SIFT Options
        SIFTOptions.implementation = Hess;  // Default implementation: Hess
 
        // SURF Options
 
        // BCD Options
 
        // FAST:
        FASTOptions.threshold = 20;
        FASTOptions.nonmax_suppression = true;
        FASTOptions.use_KLT_response = false;
        FASTOptions.min_distance = 5;
 
        // ORB:
        ORBOptions.extract_patch = false;
        ORBOptions.min_distance = 0;
        ORBOptions.n_levels = 8;
        ORBOptions.scale_factor = 1.2f;
 
        // SpinImages Options:
        SpinImagesOptions.hist_size_distance = 10;
        SpinImagesOptions.hist_size_intensity = 10;
        SpinImagesOptions.radius = 20;
        SpinImagesOptions.std_dist = 0.4f;
        SpinImagesOptions.std_intensity = 10;
 
        // TPolarImagesOptions
        PolarImagesOptions.bins_angle = 8;
        PolarImagesOptions.bins_distance = 6;
        PolarImagesOptions.radius = 20;
 
        // LogPolarImagesOptions
        LogPolarImagesOptions.radius = 30;
        LogPolarImagesOptions.num_angles =
                16;  // Log-Polar image patch will have dimensions WxH, with:
        // W=num_angles,  H= rho_scale * log(radius)
        LogPolarImagesOptions.rho_scale = 5;
 
        // added by Raghavender Sahdev
        // AKAZEOptions
        AKAZEOptions.diffusivity = 1;  // KAZE::DIFF_PM_G2 maps to 1;
        // http://docs.opencv.org/trunk/d3/d61/classcv_1_1KAZE.html
        AKAZEOptions.nOctaveLayers = 4;
        AKAZEOptions.nOctaves = 4;
        AKAZEOptions.threshold = 0.001f;
        AKAZEOptions.descriptor_channels = 3;
        AKAZEOptions.descriptor_size = 0;
        AKAZEOptions.descriptor_type =
                5;  // AKAZE::DESCRIPTOR_MLDB maps to 5 in open cv;
        // http://docs.opencv.org/trunk/d8/d30/classcv_1_1AKAZE.html
 
        // LSD Options
        LSDOptions.scale = 2;
        LSDOptions.nOctaves = 1;
 
        // BLD Options
        // BLDOptions.ksize_ = 11;
        BLDOptions.numOfOctave = 1;
        BLDOptions.widthOfBand = 7;
        BLDOptions.reductionRatio = 2;
 
        LATCHOptions.bytes = 32;
        LATCHOptions.half_ssd_size = 3;
        LATCHOptions.rotationInvariance = true;
}
 
/*---------------------------------------------------------------
                                        dumpToTextStream
  ---------------------------------------------------------------*/
void CFeatureExtraction::TOptions::dumpToTextStream(std::ostream& out) const
{
        out << mrpt::format(
                "\n----------- [CFeatureExtraction::TOptions] ------------ \n\n");
 
        LOADABLEOPTS_DUMP_VAR(featsType, int)
        LOADABLEOPTS_DUMP_VAR(patchSize, int)
        LOADABLEOPTS_DUMP_VAR(FIND_SUBPIXEL, bool)
        LOADABLEOPTS_DUMP_VAR(useMask, bool)
        LOADABLEOPTS_DUMP_VAR(addNewFeatures, bool)
 
        LOADABLEOPTS_DUMP_VAR(harrisOptions.k, double)
        LOADABLEOPTS_DUMP_VAR(harrisOptions.radius, int)
        LOADABLEOPTS_DUMP_VAR(harrisOptions.threshold, float)
        LOADABLEOPTS_DUMP_VAR(harrisOptions.sigma, float)
        LOADABLEOPTS_DUMP_VAR(harrisOptions.min_distance, float)
 
        LOADABLEOPTS_DUMP_VAR(KLTOptions.min_distance, float)
        LOADABLEOPTS_DUMP_VAR(KLTOptions.threshold, float)
        LOADABLEOPTS_DUMP_VAR(KLTOptions.radius, int)
 
        LOADABLEOPTS_DUMP_VAR(SIFTOptions.implementation, int)
 
        LOADABLEOPTS_DUMP_VAR(SURFOptions.rotation_invariant, bool)
        LOADABLEOPTS_DUMP_VAR(SURFOptions.hessianThreshold, int)
        LOADABLEOPTS_DUMP_VAR(SURFOptions.nOctaves, int)
        LOADABLEOPTS_DUMP_VAR(SURFOptions.nLayersPerOctave, int)
 
        LOADABLEOPTS_DUMP_VAR(FASTOptions.threshold, int)
        LOADABLEOPTS_DUMP_VAR(FASTOptions.nonmax_suppression, bool)
        LOADABLEOPTS_DUMP_VAR(FASTOptions.min_distance, float)
        LOADABLEOPTS_DUMP_VAR(FASTOptions.use_KLT_response, bool)
 
        LOADABLEOPTS_DUMP_VAR(ORBOptions.scale_factor, float)
        LOADABLEOPTS_DUMP_VAR(ORBOptions.min_distance, int)
        LOADABLEOPTS_DUMP_VAR(ORBOptions.n_levels, int)
        LOADABLEOPTS_DUMP_VAR(ORBOptions.extract_patch, bool)
 
        LOADABLEOPTS_DUMP_VAR(SpinImagesOptions.hist_size_distance, int)
        LOADABLEOPTS_DUMP_VAR(SpinImagesOptions.hist_size_intensity, int)
        LOADABLEOPTS_DUMP_VAR(SpinImagesOptions.radius, int)
        LOADABLEOPTS_DUMP_VAR(SpinImagesOptions.std_dist, float)
        LOADABLEOPTS_DUMP_VAR(SpinImagesOptions.std_intensity, float)
 
        LOADABLEOPTS_DUMP_VAR(PolarImagesOptions.bins_angle, int)
        LOADABLEOPTS_DUMP_VAR(PolarImagesOptions.bins_distance, int)
        LOADABLEOPTS_DUMP_VAR(PolarImagesOptions.radius, int)
 
        LOADABLEOPTS_DUMP_VAR(LogPolarImagesOptions.radius, int)
        LOADABLEOPTS_DUMP_VAR(LogPolarImagesOptions.num_angles, int)
        LOADABLEOPTS_DUMP_VAR(LogPolarImagesOptions.rho_scale, double)
 
        // # added by Raghavender Sahdev
        LOADABLEOPTS_DUMP_VAR(AKAZEOptions.descriptor_type, int)
        LOADABLEOPTS_DUMP_VAR(AKAZEOptions.descriptor_size, int)
        LOADABLEOPTS_DUMP_VAR(AKAZEOptions.descriptor_channels, int)
        LOADABLEOPTS_DUMP_VAR(AKAZEOptions.threshold, float)
        LOADABLEOPTS_DUMP_VAR(AKAZEOptions.nOctaves, int)
        LOADABLEOPTS_DUMP_VAR(AKAZEOptions.nOctaveLayers, int)
        LOADABLEOPTS_DUMP_VAR(AKAZEOptions.diffusivity, int)
 
        LOADABLEOPTS_DUMP_VAR(LSDOptions.nOctaves, int)
        LOADABLEOPTS_DUMP_VAR(LSDOptions.scale, int)
 
        LOADABLEOPTS_DUMP_VAR(BLDOptions.numOfOctave, int)
        LOADABLEOPTS_DUMP_VAR(BLDOptions.reductionRatio, int)
        LOADABLEOPTS_DUMP_VAR(BLDOptions.widthOfBand, int)
 
        LOADABLEOPTS_DUMP_VAR(LATCHOptions.bytes, int)
        LOADABLEOPTS_DUMP_VAR(LATCHOptions.half_ssd_size, int)
        LOADABLEOPTS_DUMP_VAR(LATCHOptions.rotationInvariance, bool)
 
        out << mrpt::format("\n");
}
 
/*---------------------------------------------------------------
                                        loadFromConfigFile
  ---------------------------------------------------------------*/
void CFeatureExtraction::TOptions::loadFromConfigFile(
        const mrpt::config::CConfigFileBase& iniFile, const std::string& section)
{
        featsType = iniFile.read_enum(section, "featsType", featsType);
 
        MRPT_LOAD_CONFIG_VAR(patchSize, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(FIND_SUBPIXEL, bool, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(useMask, bool, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(addNewFeatures, bool, iniFile, section)
 
        // string sect = section;
        MRPT_LOAD_CONFIG_VAR(harrisOptions.k, double, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(harrisOptions.radius, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(harrisOptions.threshold, float, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(harrisOptions.sigma, float, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(harrisOptions.min_distance, float, iniFile, section)
 
        MRPT_LOAD_CONFIG_VAR(KLTOptions.min_distance, float, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(KLTOptions.threshold, float, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(KLTOptions.radius, int, iniFile, section)
 
        MRPT_LOAD_CONFIG_VAR_CAST(
                SIFTOptions.implementation, int, TSIFTImplementation, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(SIFTOptions.threshold, double, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(SIFTOptions.edgeThreshold, double, iniFile, section)
 
        MRPT_LOAD_CONFIG_VAR(SURFOptions.rotation_invariant, bool, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(SURFOptions.hessianThreshold, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(SURFOptions.nOctaves, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(SURFOptions.nLayersPerOctave, int, iniFile, section)
 
        MRPT_LOAD_CONFIG_VAR(FASTOptions.threshold, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(FASTOptions.nonmax_suppression, bool, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(FASTOptions.min_distance, float, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(FASTOptions.use_KLT_response, bool, iniFile, section)
 
        MRPT_LOAD_CONFIG_VAR(ORBOptions.extract_patch, bool, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(ORBOptions.min_distance, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(ORBOptions.n_levels, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(ORBOptions.scale_factor, float, iniFile, section)
 
        MRPT_LOAD_CONFIG_VAR(
                SpinImagesOptions.hist_size_distance, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(
                SpinImagesOptions.hist_size_intensity, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(SpinImagesOptions.radius, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(SpinImagesOptions.std_dist, float, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(
                SpinImagesOptions.std_intensity, float, iniFile, section)
 
        MRPT_LOAD_CONFIG_VAR(PolarImagesOptions.bins_angle, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(
                PolarImagesOptions.bins_distance, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(PolarImagesOptions.radius, int, iniFile, section)
 
        MRPT_LOAD_CONFIG_VAR(LogPolarImagesOptions.radius, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(
                LogPolarImagesOptions.num_angles, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(
                LogPolarImagesOptions.rho_scale, double, iniFile, section)
 
        // #added by Raghavender Sahdev
        MRPT_LOAD_CONFIG_VAR(AKAZEOptions.descriptor_type, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(AKAZEOptions.descriptor_size, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(
                AKAZEOptions.descriptor_channels, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(AKAZEOptions.threshold, float, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(AKAZEOptions.nOctaves, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(AKAZEOptions.nOctaveLayers, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(AKAZEOptions.diffusivity, int, iniFile, section)
 
        MRPT_LOAD_CONFIG_VAR(LSDOptions.nOctaves, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(LSDOptions.scale, int, iniFile, section)
 
        MRPT_LOAD_CONFIG_VAR(BLDOptions.numOfOctave, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(BLDOptions.widthOfBand, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(BLDOptions.reductionRatio, int, iniFile, section)
 
        MRPT_LOAD_CONFIG_VAR(LATCHOptions.bytes, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(LATCHOptions.half_ssd_size, int, iniFile, section)
        MRPT_LOAD_CONFIG_VAR(
                LATCHOptions.rotationInvariance, bool, iniFile, section)
}