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#ifndef __OPENCV_GPUBGSEGM_HPP__
#define __OPENCV_GPUBGSEGM_HPP__

#ifndef __cplusplus
#  error gpubgsegm.hpp header must be compiled as C++
#endif

#include "opencv2/core/gpu.hpp"
#include "opencv2/video/background_segm.hpp"

#include <memory>
#include "opencv2/gpufilters.hpp"

namespace cv { namespace gpu {

////////////////////////////////////////////////////
// MOG

class CV_EXPORTS BackgroundSubtractorMOG : public cv::BackgroundSubtractorMOG
{
public:
    using cv::BackgroundSubtractorMOG::apply;
    using cv::BackgroundSubtractorMOG::getBackgroundImage;

    virtual void apply(InputArray image, OutputArray fgmask, double learningRate, Stream& stream) = 0;

    virtual void getBackgroundImage(OutputArray backgroundImage, Stream& stream) const = 0;
};

CV_EXPORTS Ptr<gpu::BackgroundSubtractorMOG>
    createBackgroundSubtractorMOG(int history = 200, int nmixtures = 5,
                                  double backgroundRatio = 0.7, double noiseSigma = 0);

////////////////////////////////////////////////////
// MOG2

class CV_EXPORTS BackgroundSubtractorMOG2 : public cv::BackgroundSubtractorMOG2
{
public:
    using cv::BackgroundSubtractorMOG2::apply;
    using cv::BackgroundSubtractorMOG2::getBackgroundImage;

    virtual void apply(InputArray image, OutputArray fgmask, double learningRate, Stream& stream) = 0;

    virtual void getBackgroundImage(OutputArray backgroundImage, Stream& stream) const = 0;
};

CV_EXPORTS Ptr<gpu::BackgroundSubtractorMOG2>
    createBackgroundSubtractorMOG2(int history = 500, double varThreshold = 16,
                                   bool detectShadows = true);

////////////////////////////////////////////////////
// GMG

class CV_EXPORTS BackgroundSubtractorGMG : public cv::BackgroundSubtractorGMG
{
public:
    using cv::BackgroundSubtractorGMG::apply;

    virtual void apply(InputArray image, OutputArray fgmask, double learningRate, Stream& stream) = 0;
};

CV_EXPORTS Ptr<gpu::BackgroundSubtractorGMG>
    createBackgroundSubtractorGMG(int initializationFrames = 120, double decisionThreshold = 0.8);









// Foreground Object Detection from Videos Containing Complex Background.
// Liyuan Li, Weimin Huang, Irene Y.H. Gu, and Qi Tian.
// ACM MM2003 9p
class CV_EXPORTS FGDStatModel
{
public:
    struct CV_EXPORTS Params
    {
        int Lc;  // Quantized levels per 'color' component. Power of two, typically 32, 64 or 128.
        int N1c; // Number of color vectors used to model normal background color variation at a given pixel.
        int N2c; // Number of color vectors retained at given pixel.  Must be > N1c, typically ~ 5/3 of N1c.
        // Used to allow the first N1c vectors to adapt over time to changing background.

        int Lcc;  // Quantized levels per 'color co-occurrence' component.  Power of two, typically 16, 32 or 64.
        int N1cc; // Number of color co-occurrence vectors used to model normal background color variation at a given pixel.
        int N2cc; // Number of color co-occurrence vectors retained at given pixel.  Must be > N1cc, typically ~ 5/3 of N1cc.
        // Used to allow the first N1cc vectors to adapt over time to changing background.

        bool is_obj_without_holes; // If TRUE we ignore holes within foreground blobs. Defaults to TRUE.
        int perform_morphing;     // Number of erode-dilate-erode foreground-blob cleanup iterations.
        // These erase one-pixel junk blobs and merge almost-touching blobs. Default value is 1.

        float alpha1; // How quickly we forget old background pixel values seen. Typically set to 0.1.
        float alpha2; // "Controls speed of feature learning". Depends on T. Typical value circa 0.005.
        float alpha3; // Alternate to alpha2, used (e.g.) for quicker initial convergence. Typical value 0.1.

        float delta;   // Affects color and color co-occurrence quantization, typically set to 2.
        float T;       // A percentage value which determines when new features can be recognized as new background. (Typically 0.9).
        float minArea; // Discard foreground blobs whose bounding box is smaller than this threshold.

        // default Params
        Params();
    };

    // out_cn - channels count in output result (can be 3 or 4)
    // 4-channels require more memory, but a bit faster
    explicit FGDStatModel(int out_cn = 3);
    explicit FGDStatModel(const cv::gpu::GpuMat& firstFrame, const Params& params = Params(), int out_cn = 3);

    ~FGDStatModel();

    void create(const cv::gpu::GpuMat& firstFrame, const Params& params = Params());
    void release();

    int update(const cv::gpu::GpuMat& curFrame);

    //8UC3 or 8UC4 reference background image
    cv::gpu::GpuMat background;

    //8UC1 foreground image
    cv::gpu::GpuMat foreground;

    std::vector< std::vector<cv::Point> > foreground_regions;

private:
    FGDStatModel(const FGDStatModel&);
    FGDStatModel& operator=(const FGDStatModel&);

    class Impl;
    std::auto_ptr<Impl> impl_;
};

}} // namespace cv { namespace gpu {

#endif /* __OPENCV_GPUBGSEGM_HPP__ */