root/modules/features2d/src/akaze.cpp

DEFINITIONS

1. diffusivity
2. setDescriptorType
3. getDescriptorType
4. setDescriptorSize
5. getDescriptorSize
6. setDescriptorChannels
7. getDescriptorChannels
8. setThreshold
9. getThreshold
10. setNOctaves
11. getNOctaves
12. setNOctaveLayers
13. getNOctaveLayers
14. setDiffusivity
15. getDiffusivity
16. descriptorSize
17. descriptorType
18. defaultNorm
19. detectAndCompute
20. write
21. read
22. create

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/*
OpenCV wrapper of reference implementation of
[1] Fast Explicit Diffusion for Accelerated Features in Nonlinear Scale Spaces.
Pablo F. Alcantarilla, J. Nuevo and Adrien Bartoli.
In British Machine Vision Conference (BMVC), Bristol, UK, September 2013
http://www.robesafe.com/personal/pablo.alcantarilla/papers/Alcantarilla13bmvc.pdf
@author Eugene Khvedchenya <ekhvedchenya@gmail.com>
*/

#include "precomp.hpp"
#include "kaze/AKAZEFeatures.h"

#include <iostream>

namespace cv
{
    using namespace std;

    class AKAZE_Impl : public AKAZE
    {
    public:
        AKAZE_Impl(int _descriptor_type, int _descriptor_size, int _descriptor_channels,
                 float _threshold, int _octaves, int _sublevels, int _diffusivity)
        : descriptor(_descriptor_type)
        , descriptor_channels(_descriptor_channels)
        , descriptor_size(_descriptor_size)
        , threshold(_threshold)
        , octaves(_octaves)
        , sublevels(_sublevels)
        , diffusivity(_diffusivity)
        {
        }

        virtual ~AKAZE_Impl()
        {

        }

        void setDescriptorType(int dtype) { descriptor = dtype; }
        int getDescriptorType() const { return descriptor; }

        void setDescriptorSize(int dsize) { descriptor_size = dsize; }
        int getDescriptorSize() const { return descriptor_size; }

        void setDescriptorChannels(int dch) { descriptor_channels = dch; }
        int getDescriptorChannels() const { return descriptor_channels; }

        void setThreshold(double threshold_) { threshold = (float)threshold_; }
        double getThreshold() const { return threshold; }

        void setNOctaves(int octaves_) { octaves = octaves_; }
        int getNOctaves() const { return octaves; }

        void setNOctaveLayers(int octaveLayers_) { sublevels = octaveLayers_; }
        int getNOctaveLayers() const { return sublevels; }

        void setDiffusivity(int diff_) { diffusivity = diff_; }
        int getDiffusivity() const { return diffusivity; }

        // returns the descriptor size in bytes
        int descriptorSize() const
        {
            switch (descriptor)
            {
            case DESCRIPTOR_KAZE:
            case DESCRIPTOR_KAZE_UPRIGHT:
                return 64;

            case DESCRIPTOR_MLDB:
            case DESCRIPTOR_MLDB_UPRIGHT:
                // We use the full length binary descriptor -> 486 bits
                if (descriptor_size == 0)
                {
                    int t = (6 + 36 + 120) * descriptor_channels;
                    return (int)ceil(t / 8.);
                }
                else
                {
                    // We use the random bit selection length binary descriptor
                    return (int)ceil(descriptor_size / 8.);
                }

            default:
                return -1;
            }
        }

        // returns the descriptor type
        int descriptorType() const
        {
            switch (descriptor)
            {
            case DESCRIPTOR_KAZE:
            case DESCRIPTOR_KAZE_UPRIGHT:
                    return CV_32F;

            case DESCRIPTOR_MLDB:
            case DESCRIPTOR_MLDB_UPRIGHT:
                    return CV_8U;

                default:
                    return -1;
            }
        }

        // returns the default norm type
        int defaultNorm() const
        {
            switch (descriptor)
            {
            case DESCRIPTOR_KAZE:
            case DESCRIPTOR_KAZE_UPRIGHT:
                return NORM_L2;

            case DESCRIPTOR_MLDB:
            case DESCRIPTOR_MLDB_UPRIGHT:
                return NORM_HAMMING;

            default:
                return -1;
            }
        }

        void detectAndCompute(InputArray image, InputArray mask,
                              std::vector<KeyPoint>& keypoints,
                              OutputArray descriptors,
                              bool useProvidedKeypoints)
        {
            Mat img = image.getMat();
            if (img.type() != CV_8UC1)
                cvtColor(image, img, COLOR_BGR2GRAY);

            Mat img1_32;
            if ( img.depth() == CV_32F )
                img1_32 = img;
            else if ( img.depth() == CV_8U )
                img.convertTo(img1_32, CV_32F, 1.0 / 255.0, 0);
            else if ( img.depth() == CV_16U )
                img.convertTo(img1_32, CV_32F, 1.0 / 65535.0, 0);

            CV_Assert( ! img1_32.empty() );

            AKAZEOptions options;
            options.descriptor = descriptor;
            options.descriptor_channels = descriptor_channels;
            options.descriptor_size = descriptor_size;
            options.img_width = img.cols;
            options.img_height = img.rows;
            options.dthreshold = threshold;
            options.omax = octaves;
            options.nsublevels = sublevels;
            options.diffusivity = diffusivity;

            AKAZEFeatures impl(options);
            impl.Create_Nonlinear_Scale_Space(img1_32);

            if (!useProvidedKeypoints)
            {
                impl.Feature_Detection(keypoints);
            }

            if (!mask.empty())
            {
                KeyPointsFilter::runByPixelsMask(keypoints, mask.getMat());
            }

            if( descriptors.needed() )
            {
                Mat& desc = descriptors.getMatRef();
                impl.Compute_Descriptors(keypoints, desc);

                CV_Assert((!desc.rows || desc.cols == descriptorSize()));
                CV_Assert((!desc.rows || (desc.type() == descriptorType())));
            }
        }

        void write(FileStorage& fs) const
        {
            fs << "descriptor" << descriptor;
            fs << "descriptor_channels" << descriptor_channels;
            fs << "descriptor_size" << descriptor_size;
            fs << "threshold" << threshold;
            fs << "octaves" << octaves;
            fs << "sublevels" << sublevels;
            fs << "diffusivity" << diffusivity;
        }

        void read(const FileNode& fn)
        {
            descriptor = (int)fn["descriptor"];
            descriptor_channels = (int)fn["descriptor_channels"];
            descriptor_size = (int)fn["descriptor_size"];
            threshold = (float)fn["threshold"];
            octaves = (int)fn["octaves"];
            sublevels = (int)fn["sublevels"];
            diffusivity = (int)fn["diffusivity"];
        }

        int descriptor;
        int descriptor_channels;
        int descriptor_size;
        float threshold;
        int octaves;
        int sublevels;
        int diffusivity;
    };

    Ptr<AKAZE> AKAZE::create(int descriptor_type,
                             int descriptor_size, int descriptor_channels,
                             float threshold, int octaves,
                             int sublevels, int diffusivity)
    {
        return makePtr<AKAZE_Impl>(descriptor_type, descriptor_size, descriptor_channels,
                                   threshold, octaves, sublevels, diffusivity);
    }
}