    // Copyright (C) 2011  Davis E. King (davis@dlib.net)
    // License: Boost Software License   See LICENSE.txt for the full license.
    #undef DLIB_SCAN_iMAGE_ABSTRACT_Hh_
    #ifdef DLIB_SCAN_iMAGE_ABSTRACT_Hh_

    #include <vector>
    #include <utility>
    #include "../algs.h"
    #include "../image_processing/generic_image.h"

    namespace dlib
    {

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

        template <
            typename image_array_type
            >
        bool all_images_same_size (
            const image_array_type& images
        );
        /*!
            requires
                - image_array_type       == an implementation of array/array_kernel_abstract.h
                - image_array_type::type == an image object that implements the interface
                  defined in dlib/image_processing/generic_image.h
            ensures
                - if (all elements of images have the same dimensions (i.e.
                  for all i and j: get_rect(images[i]) == get_rect(images[j]))) then
                    - returns true
                - else
                    - returns false
        !*/

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

        template <
            typename image_array_type
            >
        double sum_of_rects_in_images (
            const image_array_type& images,
            const std::vector<std::pair<unsigned int, rectangle> >& rects,
            const point& position
        );
        /*!
            requires
                - image_array_type             == an implementation of array/array_kernel_abstract.h
                - image_array_type::type       == an image object that implements the interface
                  defined in dlib/image_processing/generic_image.h.  Moreover, these objects must
                  contain a scalar pixel type (e.g. int rather than rgb_pixel)
                - all_images_same_size(images) == true
                - for all valid i: rects[i].first < images.size()
                  (i.e. all the rectangles must reference valid elements of images)
            ensures
                - returns the sum of the pixels inside the given rectangles.  To be precise,
                  let RECT_SUM[i] = sum of pixels inside the rectangle translate_rect(rects[i].second, position)
                  from the image images[rects[i].first].  Then this function returns the
                  sum of RECT_SUM[i] for all the valid values of i.
        !*/

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

        template <
            typename image_array_type
            >
        double sum_of_rects_in_images_movable_parts (
            const image_array_type& images,
            const rectangle& window,
            const std::vector<std::pair<unsigned int, rectangle> >& fixed_rects,
            const std::vector<std::pair<unsigned int, rectangle> >& movable_rects,
            const point& position
        );
        /*!
            requires
                - image_array_type             == an implementation of array/array_kernel_abstract.h
                - image_array_type::type       == an image object that implements the interface
                  defined in dlib/image_processing/generic_image.h.  Moreover, these objects must
                  contain a scalar pixel type (e.g. int rather than rgb_pixel)
                - all_images_same_size(images) == true
                - center(window) == point(0,0)
                - for all valid i:
                    - fixed_rects[i].first < images.size()
                      (i.e. all the rectangles must reference valid elements of images)
                - for all valid i:
                    - movable_rects[i].first < images.size()
                      (i.e. all the rectangles must reference valid elements of images)
                    - center(movable_rects[i].second) == point(0,0)
            ensures
                - returns the sum of the pixels inside fixed_rects as well as the sum of the pixels
                  inside movable_rects when these latter rectangles are placed at their highest
                  scoring locations inside the given window.  To be precise:
                    - let RECT_SUM(r,x) = sum of pixels inside the rectangle translate_rect(r.second, x)
                      from the image images[r.first].
                    - let WIN_MAX(i) = The maximum value of RECT_SUM(movable_rects[i],X) when maximizing
                      over all the X such that translate_rect(window,position).contains(X) == true.

                    - let TOTAL_FIXED   == sum over all elements R in fixed_rects of: RECT_SUM(R,position)
                    - let TOTAL_MOVABLE == sum over all valid i of: max(WIN_MAX(i), 0)

                  Then this function returns TOTAL_FIXED + TOTAL_MOVABLE.
        !*/

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

        template <
            typename image_type
            >
        void find_points_above_thresh (
            std::vector<std::pair<double, point> >& dets,
            const image_type& img,
            const double thresh,
            const unsigned long max_dets
        );
        /*!
            requires
                - image_type == an image object that implements the interface defined in
                  dlib/image_processing/generic_image.h.  Moreover, these it must contain a
                  scalar pixel type (e.g. int rather than rgb_pixel)
            ensures
                - #dets == a list of points from img which had pixel values >= thresh.
                - Specifically, we have:
                    - #dets.size() <= max_dets
                      (note that dets is cleared before new detections are added by find_points_above_thresh())
                    - for all valid i:
                        - #dets[i].first == img[#dets[i].second.y()][#dets[i].second.x()]
                          (i.e. the first field contains the value of the pixel at this detection location)
                        - #dets[i].first >= thresh
                - if (there are more than max_dets locations that pass the above threshold test) then
                    - #dets == a random subsample of all the locations which passed the threshold
                      test.
                - else
                    - #dets == all the points which passed the threshold test.
        !*/

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

        template <
            typename image_type
            >
        std::vector<point> find_peaks (
            const image_type& img,
            const double non_max_suppression_radius,
            const typename pixel_traits<typename image_traits<image_type>::pixel_type>::basic_pixel_type& thresh
        );
        /*!
            requires
                - image_type == an image object that implements the interface defined in
                  dlib/image_processing/generic_image.h.  Moreover, these it must contain a
                  scalar pixel type (e.g. int rather than rgb_pixel)
                - non_max_suppression_radius >= 0
            ensures
                - Scans the given image and finds all pixels with values >= thresh that are
                  also local maximums within their 8-connected neighborhood of the image.  Such
                  pixels are collected, sorted in decreasing order of their pixel values, and
                  then non-maximum suppression is applied to this list of points using the
                  given non_max_suppression_radius.  The final list of peaks is then returned.

                  Therefore, the returned list, V, will have these properties:
                    - V.size() == the number of peaks found in the image.
                    - When measured in image coordinates, no elements of V are within
                      non_max_suppression_radius distance of each other.  That is, for all valid i!=j
                      it is true that length(V[i]-V[j]) > non_max_suppression_radius.
                    - For each element of V, that element has the maximum pixel value of all
                      pixels in the ball centered on that pixel with radius
                      non_max_suppression_radius.
        !*/

        template <
            typename image_type
            >
        std::vector<point> find_peaks (
            const image_type& img
        );
        /*!
            ensures
                - performs: return find_peaks(img, 0, partition_pixels(img))
        !*/

        template <
            typename image_type
            >
        std::vector<point> find_peaks (
            const image_type& img,
            const double non_max_suppression_radius
        );
        /*!
            ensures
                - performs: return find_peaks(img, non_max_suppression_radius, partition_pixels(img))
        !*/

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

        template <
            typename image_array_type
            >
        void scan_image (
            std::vector<std::pair<double, point> >& dets,
            const image_array_type& images,
            const std::vector<std::pair<unsigned int, rectangle> >& rects,
            const double thresh,
            const unsigned long max_dets
        );
        /*!
            requires
                - image_array_type             == an implementation of array/array_kernel_abstract.h
                - image_array_type::type       == an image object that implements the interface
                  defined in dlib/image_processing/generic_image.h.  Moreover, these objects must
                  contain a scalar pixel type (e.g. int rather than rgb_pixel)
                - images.size() > 0
                - rects.size() > 0
                - all_images_same_size(images) == true
                - for all valid i: rects[i].first < images.size()
                  (i.e. all the rectangles must reference valid elements of images)
            ensures
                - slides the set of rectangles over the image space and reports the locations
                  which give a sum bigger than thresh.
                - Specifically, we have:
                    - #dets.size() <= max_dets
                      (note that dets is cleared before new detections are added by scan_image())
                    - for all valid i:
                        - #dets[i].first == sum_of_rects_in_images(images,rects,#dets[i].second) >= thresh
                - if (there are more than max_dets locations that pass the threshold test) then
                    - #dets == a random subsample of all the locations which passed the threshold
                      test.
        !*/

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

        template <
            typename image_array_type
            >
        void scan_image_movable_parts (
            std::vector<std::pair<double, point> >& dets,
            const image_array_type& images,
            const rectangle& window,
            const std::vector<std::pair<unsigned int, rectangle> >& fixed_rects,
            const std::vector<std::pair<unsigned int, rectangle> >& movable_rects,
            const double thresh,
            const unsigned long max_dets
        );
        /*!
            requires
                - image_array_type             == an implementation of array/array_kernel_abstract.h
                - image_array_type::type       == an image object that implements the interface
                  defined in dlib/image_processing/generic_image.h.  Moreover, these objects must
                  contain a scalar pixel type (e.g. int rather than rgb_pixel)
                - images.size() > 0
                - all_images_same_size(images) == true
                - center(window) == point(0,0)
                - window.area() > 0
                - for all valid i:
                    - fixed_rects[i].first < images.size()
                      (i.e. all the rectangles must reference valid elements of images)
                - for all valid i:
                    - movable_rects[i].first < images.size()
                      (i.e. all the rectangles must reference valid elements of images)
                    - center(movable_rects[i].second) == point(0,0)
                    - movable_rects[i].second.area() > 0
            ensures
                - Scans the given window over the images and reports the locations with a score bigger
                  than thresh.
                - Specifically, we have:
                    - #dets.size() <= max_dets
                      (note that dets is cleared before new detections are added by scan_image_movable_parts())
                    - for all valid i:
                        - #dets[i].first == sum_of_rects_in_images_movable_parts(images,
                                                                                 window,
                                                                                 fixed_rects,
                                                                                 movable_rects,
                                                                                 #dets[i].second) >= thresh
                - if (there are more than max_dets locations that pass the above threshold test) then
                    - #dets == a random subsample of all the locations which passed the threshold
                      test.
        !*/

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

    }

    #endif // DLIB_SCAN_iMAGE_ABSTRACT_Hh_