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264 lines
10 KiB
C++
264 lines
10 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#ifndef __OPENCV_CUDABGSEGM_HPP__
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#define __OPENCV_CUDABGSEGM_HPP__
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#ifndef __cplusplus
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# error cudabgsegm.hpp header must be compiled as C++
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#endif
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#include "opencv2/core/cuda.hpp"
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#include "opencv2/video/background_segm.hpp"
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/**
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@addtogroup cuda
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@{
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@defgroup cudabgsegm Background Segmentation
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@}
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*/
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namespace cv { namespace cuda {
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//! @addtogroup cudabgsegm
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//! @{
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////////////////////////////////////////////////////
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// MOG
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/** @brief Gaussian Mixture-based Background/Foreground Segmentation Algorithm.
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The class discriminates between foreground and background pixels by building and maintaining a model
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of the background. Any pixel which does not fit this model is then deemed to be foreground. The
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class implements algorithm described in @cite MOG2001 .
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@sa BackgroundSubtractorMOG
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@note
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- An example on gaussian mixture based background/foreground segmantation can be found at
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opencv_source_code/samples/gpu/bgfg_segm.cpp
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*/
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class CV_EXPORTS BackgroundSubtractorMOG : public cv::BackgroundSubtractor
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{
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public:
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using cv::BackgroundSubtractor::apply;
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virtual void apply(InputArray image, OutputArray fgmask, double learningRate, Stream& stream) = 0;
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using cv::BackgroundSubtractor::getBackgroundImage;
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virtual void getBackgroundImage(OutputArray backgroundImage, Stream& stream) const = 0;
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virtual int getHistory() const = 0;
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virtual void setHistory(int nframes) = 0;
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virtual int getNMixtures() const = 0;
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virtual void setNMixtures(int nmix) = 0;
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virtual double getBackgroundRatio() const = 0;
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virtual void setBackgroundRatio(double backgroundRatio) = 0;
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virtual double getNoiseSigma() const = 0;
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virtual void setNoiseSigma(double noiseSigma) = 0;
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};
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/** @brief Creates mixture-of-gaussian background subtractor
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@param history Length of the history.
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@param nmixtures Number of Gaussian mixtures.
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@param backgroundRatio Background ratio.
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@param noiseSigma Noise strength (standard deviation of the brightness or each color channel). 0
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means some automatic value.
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*/
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CV_EXPORTS Ptr<cuda::BackgroundSubtractorMOG>
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createBackgroundSubtractorMOG(int history = 200, int nmixtures = 5,
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double backgroundRatio = 0.7, double noiseSigma = 0);
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////////////////////////////////////////////////////
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// MOG2
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/** @brief Gaussian Mixture-based Background/Foreground Segmentation Algorithm.
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The class discriminates between foreground and background pixels by building and maintaining a model
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of the background. Any pixel which does not fit this model is then deemed to be foreground. The
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class implements algorithm described in @cite Zivkovic2004 .
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@sa BackgroundSubtractorMOG2
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*/
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class CV_EXPORTS BackgroundSubtractorMOG2 : public cv::BackgroundSubtractorMOG2
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{
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public:
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using cv::BackgroundSubtractorMOG2::apply;
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using cv::BackgroundSubtractorMOG2::getBackgroundImage;
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virtual void apply(InputArray image, OutputArray fgmask, double learningRate, Stream& stream) = 0;
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virtual void getBackgroundImage(OutputArray backgroundImage, Stream& stream) const = 0;
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};
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/** @brief Creates MOG2 Background Subtractor
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@param history Length of the history.
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@param varThreshold Threshold on the squared Mahalanobis distance between the pixel and the model
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to decide whether a pixel is well described by the background model. This parameter does not
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affect the background update.
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@param detectShadows If true, the algorithm will detect shadows and mark them. It decreases the
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speed a bit, so if you do not need this feature, set the parameter to false.
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*/
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CV_EXPORTS Ptr<cuda::BackgroundSubtractorMOG2>
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createBackgroundSubtractorMOG2(int history = 500, double varThreshold = 16,
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bool detectShadows = true);
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////////////////////////////////////////////////////
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// GMG
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/** @brief Background/Foreground Segmentation Algorithm.
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The class discriminates between foreground and background pixels by building and maintaining a model
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of the background. Any pixel which does not fit this model is then deemed to be foreground. The
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class implements algorithm described in @cite Gold2012 .
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*/
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class CV_EXPORTS BackgroundSubtractorGMG : public cv::BackgroundSubtractor
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{
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public:
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using cv::BackgroundSubtractor::apply;
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virtual void apply(InputArray image, OutputArray fgmask, double learningRate, Stream& stream) = 0;
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virtual int getMaxFeatures() const = 0;
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virtual void setMaxFeatures(int maxFeatures) = 0;
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virtual double getDefaultLearningRate() const = 0;
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virtual void setDefaultLearningRate(double lr) = 0;
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virtual int getNumFrames() const = 0;
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virtual void setNumFrames(int nframes) = 0;
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virtual int getQuantizationLevels() const = 0;
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virtual void setQuantizationLevels(int nlevels) = 0;
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virtual double getBackgroundPrior() const = 0;
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virtual void setBackgroundPrior(double bgprior) = 0;
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virtual int getSmoothingRadius() const = 0;
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virtual void setSmoothingRadius(int radius) = 0;
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virtual double getDecisionThreshold() const = 0;
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virtual void setDecisionThreshold(double thresh) = 0;
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virtual bool getUpdateBackgroundModel() const = 0;
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virtual void setUpdateBackgroundModel(bool update) = 0;
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virtual double getMinVal() const = 0;
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virtual void setMinVal(double val) = 0;
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virtual double getMaxVal() const = 0;
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virtual void setMaxVal(double val) = 0;
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};
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/** @brief Creates GMG Background Subtractor
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@param initializationFrames Number of frames of video to use to initialize histograms.
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@param decisionThreshold Value above which pixel is determined to be FG.
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*/
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CV_EXPORTS Ptr<cuda::BackgroundSubtractorGMG>
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createBackgroundSubtractorGMG(int initializationFrames = 120, double decisionThreshold = 0.8);
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////////////////////////////////////////////////////
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// FGD
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/** @brief The class discriminates between foreground and background pixels by building and maintaining a model
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of the background.
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Any pixel which does not fit this model is then deemed to be foreground. The class implements
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algorithm described in @cite FGD2003 .
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@sa BackgroundSubtractor
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*/
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class CV_EXPORTS BackgroundSubtractorFGD : public cv::BackgroundSubtractor
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{
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public:
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/** @brief Returns the output foreground regions calculated by findContours.
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@param foreground_regions Output array (CPU memory).
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*/
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virtual void getForegroundRegions(OutputArrayOfArrays foreground_regions) = 0;
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};
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struct CV_EXPORTS FGDParams
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{
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int Lc; //!< Quantized levels per 'color' component. Power of two, typically 32, 64 or 128.
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int N1c; //!< Number of color vectors used to model normal background color variation at a given pixel.
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int N2c; //!< Number of color vectors retained at given pixel. Must be > N1c, typically ~ 5/3 of N1c.
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//!< Used to allow the first N1c vectors to adapt over time to changing background.
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int Lcc; //!< Quantized levels per 'color co-occurrence' component. Power of two, typically 16, 32 or 64.
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int N1cc; //!< Number of color co-occurrence vectors used to model normal background color variation at a given pixel.
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int N2cc; //!< Number of color co-occurrence vectors retained at given pixel. Must be > N1cc, typically ~ 5/3 of N1cc.
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//!< Used to allow the first N1cc vectors to adapt over time to changing background.
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bool is_obj_without_holes; //!< If TRUE we ignore holes within foreground blobs. Defaults to TRUE.
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int perform_morphing; //!< Number of erode-dilate-erode foreground-blob cleanup iterations.
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//!< These erase one-pixel junk blobs and merge almost-touching blobs. Default value is 1.
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float alpha1; //!< How quickly we forget old background pixel values seen. Typically set to 0.1.
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float alpha2; //!< "Controls speed of feature learning". Depends on T. Typical value circa 0.005.
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float alpha3; //!< Alternate to alpha2, used (e.g.) for quicker initial convergence. Typical value 0.1.
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float delta; //!< Affects color and color co-occurrence quantization, typically set to 2.
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float T; //!< A percentage value which determines when new features can be recognized as new background. (Typically 0.9).
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float minArea; //!< Discard foreground blobs whose bounding box is smaller than this threshold.
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//! default Params
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FGDParams();
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};
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/** @brief Creates FGD Background Subtractor
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@param params Algorithm's parameters. See @cite FGD2003 for explanation.
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*/
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CV_EXPORTS Ptr<cuda::BackgroundSubtractorFGD>
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createBackgroundSubtractorFGD(const FGDParams& params = FGDParams());
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//! @}
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}} // namespace cv { namespace cuda {
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#endif /* __OPENCV_CUDABGSEGM_HPP__ */
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