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#ifndef __OPENCV_CUDABGSEGM_HPP__
#define __OPENCV_CUDABGSEGM_HPP__

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

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

namespace cv { namespace cuda {

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

class CV_EXPORTS BackgroundSubtractorMOG : public cv::BackgroundSubtractor
{
public:

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

    using cv::BackgroundSubtractor::getBackgroundImage;
    virtual void getBackgroundImage(OutputArray backgroundImage, Stream& stream) const = 0;

    virtual int getHistory() const = 0;
    virtual void setHistory(int nframes) = 0;

    virtual int getNMixtures() const = 0;
    virtual void setNMixtures(int nmix) = 0;

    virtual double getBackgroundRatio() const = 0;
    virtual void setBackgroundRatio(double backgroundRatio) = 0;

    virtual double getNoiseSigma() const = 0;
    virtual void setNoiseSigma(double noiseSigma) = 0;
};

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

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

class CV_EXPORTS BackgroundSubtractorGMG : public cv::BackgroundSubtractor
{
public:
    using cv::BackgroundSubtractor::apply;
    virtual void apply(InputArray image, OutputArray fgmask, double learningRate, Stream& stream) = 0;

    virtual int getMaxFeatures() const = 0;
    virtual void setMaxFeatures(int maxFeatures) = 0;

    virtual double getDefaultLearningRate() const = 0;
    virtual void setDefaultLearningRate(double lr) = 0;

    virtual int getNumFrames() const = 0;
    virtual void setNumFrames(int nframes) = 0;

    virtual int getQuantizationLevels() const = 0;
    virtual void setQuantizationLevels(int nlevels) = 0;

    virtual double getBackgroundPrior() const = 0;
    virtual void setBackgroundPrior(double bgprior) = 0;

    virtual int getSmoothingRadius() const = 0;
    virtual void setSmoothingRadius(int radius) = 0;

    virtual double getDecisionThreshold() const = 0;
    virtual void setDecisionThreshold(double thresh) = 0;

    virtual bool getUpdateBackgroundModel() const = 0;
    virtual void setUpdateBackgroundModel(bool update) = 0;

    virtual double getMinVal() const = 0;
    virtual void setMinVal(double val) = 0;

    virtual double getMaxVal() const = 0;
    virtual void setMaxVal(double val) = 0;
};

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

////////////////////////////////////////////////////
// FGD

/**
 * 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 BackgroundSubtractorFGD : public cv::BackgroundSubtractor
{
public:
    virtual void getForegroundRegions(OutputArrayOfArrays foreground_regions) = 0;
};

struct CV_EXPORTS FGDParams
{
    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
    FGDParams();
};

CV_EXPORTS Ptr<cuda::BackgroundSubtractorFGD>
    createBackgroundSubtractorFGD(const FGDParams& params = FGDParams());

}} // namespace cv { namespace cuda {

#endif /* __OPENCV_CUDABGSEGM_HPP__ */