    // Copyright (C) 2009  Davis E. King (davis@dlib.net)
    // License: Boost Software License   See LICENSE.txt for the full license.
    #ifndef DLIB_HESSIAN_PYRAMId_Hh_
    #define DLIB_HESSIAN_PYRAMId_Hh_

    #include "hessian_pyramid_abstract.h"
    #include "../algs.h"
    #include "../image_transforms/integral_image.h"
    #include "../array.h"
    #include "../array2d.h"
    #include "../noncopyable.h"
    #include "../matrix.h"
    #include "../stl_checked.h"
    #include <algorithm>
    #include <vector>

    namespace dlib
    {

    // ----------------------------------------------------------------------------------------

        struct interest_point
        {
            interest_point() : scale(0), score(0), laplacian(0) {}

            dlib::vector<double,2> center;
            double scale;
            double score;
            double laplacian;

            bool operator < (const interest_point& p) const { return score < p.score; }
        };

    // ----------------------------------------------------------------------------------------

        inline void serialize(
            const interest_point& item,
            std::ostream& out
        )
        {
            try
            {
                serialize(item.center,out);
                serialize(item.scale,out);
                serialize(item.score,out);
                serialize(item.laplacian,out);
            }
            catch (serialization_error& e)
            {
                throw serialization_error(e.info + "\n   while serializing object of type interest_point");
            }
        }

    // ----------------------------------------------------------------------------------------

        inline void deserialize(
            interest_point& item,
            std::istream& in
        )
        {
            try
            {
                deserialize(item.center,in);
                deserialize(item.scale,in);
                deserialize(item.score,in);
                deserialize(item.laplacian,in);
            }
            catch (serialization_error& e)
            {
                throw serialization_error(e.info + "\n   while deserializing object of type interest_point");
            }
        }

    // ----------------------------------------------------------------------------------------

        class hessian_pyramid : noncopyable
        {
        public:
            hessian_pyramid()
            {
                num_octaves = 0;
                num_intervals = 0;
                initial_step_size = 0;
            }

            template <typename integral_image_type>
            void build_pyramid (
                const integral_image_type& img,
                long num_octaves,
                long num_intervals,
                long initial_step_size
            )
            {
                DLIB_ASSERT(num_octaves > 0 && num_intervals > 0 && initial_step_size > 0,
                    "\tvoid build_pyramid()"
                    << "\n\tAll arguments to this function must be > 0"
                    << "\n\t this:              " << this
                    << "\n\t num_octaves:       " << num_octaves
                    << "\n\t num_intervals:     " << num_intervals
                    << "\n\t initial_step_size: " << initial_step_size
                );

                this->num_octaves = num_octaves;
                this->num_intervals = num_intervals;
                this->initial_step_size = initial_step_size;

                // allocate space for the pyramid
                pyramid.resize(num_octaves*num_intervals);
                for (long o = 0; o < num_octaves; ++o)
                {
                    const long step_size = get_step_size(o);
                    for (long i = 0; i < num_intervals; ++i)
                    {
                        pyramid[num_intervals*o + i].set_size(img.nr()/step_size, img.nc()/step_size);
                    }
                }

                // now fill out the pyramid with data
                for (long o = 0; o < num_octaves; ++o)
                {
                    const long step_size = get_step_size(o);

                    for (long i = 0; i < num_intervals; ++i)
                    {
                        const long border_size = get_border_size(i)*step_size;
                        const long lobe_size = static_cast<long>(std::pow(2.0, o+1.0)+0.5)*(i+1) + 1;
                        const double area_inv = 1.0/std::pow(3.0*lobe_size, 2.0);

                        const long lobe_offset = lobe_size/2+1;
                        const point tl(-lobe_offset,-lobe_offset);
                        const point tr(lobe_offset,-lobe_offset);
                        const point bl(-lobe_offset,lobe_offset);
                        const point br(lobe_offset,lobe_offset);

                        for (long r = border_size; r < img.nr() - border_size; r += step_size)
                        {
                            for (long c = border_size; c < img.nc() - border_size; c += step_size)
                            {
                                const point p(c,r);

                                double Dxx = img.get_sum_of_area(centered_rect(p, lobe_size*3, 2*lobe_size-1)) -
                                             img.get_sum_of_area(centered_rect(p, lobe_size,   2*lobe_size-1))*3.0;

                                double Dyy = img.get_sum_of_area(centered_rect(p, 2*lobe_size-1, lobe_size*3)) -
                                             img.get_sum_of_area(centered_rect(p, 2*lobe_size-1, lobe_size))*3.0;

                                double Dxy = img.get_sum_of_area(centered_rect(p+bl, lobe_size, lobe_size)) +
                                             img.get_sum_of_area(centered_rect(p+tr, lobe_size, lobe_size)) -
                                             img.get_sum_of_area(centered_rect(p+tl, lobe_size, lobe_size)) -
                                             img.get_sum_of_area(centered_rect(p+br, lobe_size, lobe_size));

                                // now we normalize the filter responses
                                Dxx *= area_inv;
                                Dyy *= area_inv;
                                Dxy *= area_inv;

                                double sign_of_laplacian = +1;
                                if (Dxx + Dyy < 0)
                                    sign_of_laplacian = -1;

                                double determinant = Dxx*Dyy - 0.81*Dxy*Dxy;

                                // If the determinant is negative then just blank it out by setting
                                // it to zero.
                                if (determinant < 0)
                                    determinant = 0;

                                // Save the determinant of the Hessian into our image pyramid.  Also
                                // pack the laplacian sign into the value so we can get it out later.
                                pyramid[o*num_intervals + i][r/step_size][c/step_size] = sign_of_laplacian*determinant;

                            }
                        }

                    }
                }
            }

            long get_border_size (
                long interval
            ) const
            {
                DLIB_ASSERT(0 <= interval && interval < intervals(),
                    "\tlong get_border_size(interval)"
                    << "\n\tInvalid interval value"
                    << "\n\t this:   " << this
                    << "\n\t interval: " << interval
                );

                const double lobe_size = 2.0*(interval+1) + 1;
                const double filter_size = 3*lobe_size;

                const long bs = static_cast<long>(std::ceil(filter_size/2.0));
                return bs;
            }

            long get_step_size (
                long octave
            ) const
            {
                DLIB_ASSERT(0 <= octave && octave < octaves(),
                    "\tlong get_step_size(octave)"
                    << "\n\tInvalid octave value"
                    << "\n\t this:   " << this
                    << "\n\t octave: " << octave
                );

                return initial_step_size*static_cast<long>(std::pow(2.0, (double)octave)+0.5);
            }

            long nr (
                long octave
            ) const
            {
                DLIB_ASSERT(0 <= octave && octave < octaves(),
                    "\tlong nr(octave)"
                    << "\n\tInvalid octave value"
                    << "\n\t this:   " << this
                    << "\n\t octave: " << octave
                );

                return pyramid[num_intervals*octave].nr();
            }

            long nc (
                long octave
            ) const
            {
                DLIB_ASSERT(0 <= octave && octave < octaves(),
                    "\tlong nc(octave)"
                    << "\n\tInvalid octave value"
                    << "\n\t this:   " << this
                    << "\n\t octave: " << octave
                );

                return pyramid[num_intervals*octave].nc();
            }

            double get_value (
                long octave,
                long interval,
                long r,
                long c
            ) const
            {
                DLIB_ASSERT(0 <= octave && octave < octaves() &&
                            0 <= interval && interval < intervals() &&
                            get_border_size(interval) <= r && r < nr(octave)-get_border_size(interval) &&
                            get_border_size(interval) <= c && c < nc(octave)-get_border_size(interval),
                    "\tdouble get_value(octave, interval, r, c)"
                    << "\n\tInvalid inputs to this function"
                    << "\n\t this:      " << this
                    << "\n\t octave:    " << octave
                    << "\n\t interval:  " << interval
                    << "\n\t octaves:   " << octaves()
                    << "\n\t intervals: " << intervals()
                    << "\n\t r:         " << r
                    << "\n\t c:         " << c
                    << "\n\t nr(octave): " << nr(octave)
                    << "\n\t nc(octave): " << nc(octave)
                    << "\n\t get_border_size(interval): " << get_border_size(interval)
                );

                return std::abs(pyramid[num_intervals*octave + interval][r][c]);
            }

            double get_laplacian (
                long octave,
                long interval,
                long r,
                long c
            ) const
            {
                DLIB_ASSERT(0 <= octave && octave < octaves() &&
                            0 <= interval && interval < intervals() &&
                            get_border_size(interval) <= r && r < nr(octave)-get_border_size(interval) &&
                            get_border_size(interval) <= c && c < nc(octave)-get_border_size(interval),
                    "\tdouble get_laplacian(octave, interval, r, c)"
                    << "\n\tInvalid inputs to this function"
                    << "\n\t this:      " << this
                    << "\n\t octave:    " << octave
                    << "\n\t interval:  " << interval
                    << "\n\t octaves:   " << octaves()
                    << "\n\t intervals: " << intervals()
                    << "\n\t r:         " << r
                    << "\n\t c:         " << c
                    << "\n\t nr(octave): " << nr(octave)
                    << "\n\t nc(octave): " << nc(octave)
                    << "\n\t get_border_size(interval): " << get_border_size(interval)
                );

                // return the sign of the laplacian
                if (pyramid[num_intervals*octave + interval][r][c] > 0)
                    return +1;
                else
                    return -1;
            }

            long octaves (
            ) const { return num_octaves; }

            long intervals (
            ) const { return num_intervals; }

        private:

            long num_octaves;
            long num_intervals;
            long initial_step_size;

            typedef array2d<double> image_type;
            typedef array<image_type> pyramid_type;

            pyramid_type pyramid;
        };

    // ----------------------------------------------------------------------------------------
    // ----------------------------------------------------------------------------------------
    // ----------------------------------------------------------------------------------------

        namespace hessian_pyramid_helpers
        {
            inline bool is_maximum_in_region(
                const hessian_pyramid& pyr,
                long o,
                long i,
                long r,
                long c
            )
            {
                // First check if this point is near the edge of the octave
                // If it is then we say it isn't a maximum as these points are
                // not as reliable.
                if (i <= 0 || i+1 >= pyr.intervals())
                {
                    return false;
                }

                const double val = pyr.get_value(o,i,r,c);

                // now check if there are any bigger values around this guy
                for (long ii = i-1; ii <= i+1; ++ii)
                {
                    for (long rr = r-1; rr <= r+1; ++rr)
                    {
                        for (long cc = c-1; cc <= c+1; ++cc)
                        {
                            if (pyr.get_value(o,ii,rr,cc) > val)
                                return false;
                        }
                    }
                }

                return true;
            }

        // ------------------------------------------------------------------------------------

            inline const matrix<double,3,1> get_hessian_gradient (
                const hessian_pyramid& pyr,
                long o,
                long i,
                long r,
                long c
            )
            {
                matrix<double,3,1> grad;
                grad(0) = (pyr.get_value(o,i,r,c+1) - pyr.get_value(o,i,r,c-1))/2.0;
                grad(1) = (pyr.get_value(o,i,r+1,c) - pyr.get_value(o,i,r-1,c))/2.0;
                grad(2) = (pyr.get_value(o,i+1,r,c) - pyr.get_value(o,i-1,r,c))/2.0;
                return grad;
            }

        // ------------------------------------------------------------------------------------

            inline const matrix<double,3,3> get_hessian_hessian (
                const hessian_pyramid& pyr,
                long o,
                long i,
                long r,
                long c
            )
            {
                matrix<double,3,3> hess;
                const double val = pyr.get_value(o,i,r,c);

                double Dxx = (pyr.get_value(o,i,r,c+1) + pyr.get_value(o,i,r,c-1)) - 2*val;
                double Dyy = (pyr.get_value(o,i,r+1,c) + pyr.get_value(o,i,r-1,c)) - 2*val;
                double Dss = (pyr.get_value(o,i+1,r,c) + pyr.get_value(o,i-1,r,c)) - 2*val;

                double Dxy = (pyr.get_value(o,i,r+1,c+1) + pyr.get_value(o,i,r-1,c-1) -
                              pyr.get_value(o,i,r-1,c+1) - pyr.get_value(o,i,r+1,c-1)) / 4.0;

                double Dxs = (pyr.get_value(o,i+1,r,c+1) + pyr.get_value(o,i-1,r,c-1) -
                              pyr.get_value(o,i-1,r,c+1) - pyr.get_value(o,i+1,r,c-1)) / 4.0;

                double Dys = (pyr.get_value(o,i+1,r+1,c) + pyr.get_value(o,i-1,r-1,c) -
                              pyr.get_value(o,i-1,r+1,c) - pyr.get_value(o,i+1,r-1,c)) / 4.0;

                hess = Dxx, Dxy, Dxs,
                Dxy, Dyy, Dys,
                Dxs, Dys, Dss;

                return hess;
            }

        // ------------------------------------------------------------------------------------

            inline const interest_point interpolate_point (
                const hessian_pyramid& pyr,
                long o,
                long i,
                long r,
                long c
            )
            {
                dlib::vector<double,2> p(c,r);

                dlib::vector<double,3> start_point(c,r,i);
                dlib::vector<double,3> interpolated_point = -inv(get_hessian_hessian(pyr,o,i,r,c))*get_hessian_gradient(pyr,o,i,r,c);

                //cout << "inter: " <<  trans(interpolated_point);

                interest_point temp;
                if (max(abs(interpolated_point)) < 0.5)
                {
                    p = (start_point+interpolated_point)*pyr.get_step_size(o);
                    const double lobe_size = std::pow(2.0, o+1.0)*(i+interpolated_point.z()+1) + 1;
                    const double filter_size = 3*lobe_size;
                    const double scale = 1.2/9.0 * filter_size;

                    temp.center = p;
                    temp.scale = scale;
                    temp.score = pyr.get_value(o,i,r,c);
                    temp.laplacian = pyr.get_laplacian(o,i,r,c);
                }
                else
                {
                    // this indicates to the caller that no interest point was found.
                    temp.score = -1;
                }

                return temp;
            }

        }

    // ----------------------------------------------------------------------------------------

        template <typename Alloc>
        void get_interest_points (
            const hessian_pyramid& pyr,
            double threshold,
            std::vector<interest_point,Alloc>& result_points
        )
        {
            DLIB_ASSERT(threshold >= 0,
                "\tvoid get_interest_points()"
                << "\n\t Invalid arguments to this function"
                << "\n\t threshold: " << threshold
            );
            using namespace std;
            using namespace hessian_pyramid_helpers;

            result_points.clear();

            for (long o = 0; o < pyr.octaves(); ++o)
            {
                const long nr = pyr.nr(o);
                const long nc = pyr.nc(o);

                // do non-maximum suppression on all the intervals in the current octave and
                // accumulate the results in result_points
                for (long i = 1; i < pyr.intervals()-1;  i += 1)
                {
                    const long border_size = pyr.get_border_size(i+1);
                    for (long r = border_size+1; r < nr - border_size-1; r += 1)
                    {
                        for (long c = border_size+1; c < nc - border_size-1; c += 1)
                        {
                            double max_val = pyr.get_value(o,i,r,c);
                            long max_i = i;
                            long max_r = r;
                            long max_c = c;

                            // If the max point we found is really a maximum in its own region and
                            // is big enough then add it to the results.
                            if (max_val >= threshold && is_maximum_in_region(pyr, o, max_i, max_r, max_c))
                            {
                                //cout << max_val << endl;
                                interest_point sp = interpolate_point (pyr, o, max_i, max_r, max_c);
                                if (sp.score >= threshold)
                                {
                                    result_points.push_back(sp);
                                }
                            }

                        }
                    }
                }
            }

        }

    // ----------------------------------------------------------------------------------------

        template <typename Alloc>
        void get_interest_points (
            const hessian_pyramid& pyr,
            double threshold,
            std_vector_c<interest_point,Alloc>& result_points
        )
        /*!
            This function is just an overload that automatically casts std_vector_c objects
            into std::vector objects.  (Usually this is automatic but the template argument
            there messes up the conversion so we have to do it explicitly)
        !*/
        {
            std::vector<interest_point,Alloc>& v = result_points;
            get_interest_points(pyr, threshold, v);
        }

    // ----------------------------------------------------------------------------------------

    }

    #endif  // DLIB_HESSIAN_PYRAMId_Hh_