mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
263 lines
10 KiB
263 lines
10 KiB
/*M/////////////////////////////////////////////////////////////////////////////////////// |
|
// |
|
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. |
|
// |
|
// By downloading, copying, installing or using the software you agree to this license. |
|
// If you do not agree to this license, do not download, install, |
|
// copy or use the software. |
|
// |
|
// |
|
// License Agreement |
|
// For Open Source Computer Vision Library |
|
// |
|
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. |
|
// Copyright (C) 2009, Willow Garage Inc., all rights reserved. |
|
// Third party copyrights are property of their respective owners. |
|
// |
|
// Redistribution and use in source and binary forms, with or without modification, |
|
// are permitted provided that the following conditions are met: |
|
// |
|
// * Redistribution's of source code must retain the above copyright notice, |
|
// this list of conditions and the following disclaimer. |
|
// |
|
// * Redistribution's in binary form must reproduce the above copyright notice, |
|
// this list of conditions and the following disclaimer in the documentation |
|
// and/or other materials provided with the distribution. |
|
// |
|
// * The name of the copyright holders may not be used to endorse or promote products |
|
// derived from this software without specific prior written permission. |
|
// |
|
// This software is provided by the copyright holders and contributors "as is" and |
|
// any express or implied warranties, including, but not limited to, the implied |
|
// warranties of merchantability and fitness for a particular purpose are disclaimed. |
|
// In no event shall the Intel Corporation or contributors be liable for any direct, |
|
// indirect, incidental, special, exemplary, or consequential damages |
|
// (including, but not limited to, procurement of substitute goods or services; |
|
// loss of use, data, or profits; or business interruption) however caused |
|
// and on any theory of liability, whether in contract, strict liability, |
|
// or tort (including negligence or otherwise) arising in any way out of |
|
// the use of this software, even if advised of the possibility of such damage. |
|
// |
|
//M*/ |
|
|
|
#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" |
|
|
|
/** |
|
@addtogroup cuda |
|
@{ |
|
@defgroup cudabgsegm Background Segmentation |
|
@} |
|
*/ |
|
|
|
namespace cv { namespace cuda { |
|
|
|
//! @addtogroup cudabgsegm |
|
//! @{ |
|
|
|
//////////////////////////////////////////////////// |
|
// MOG |
|
|
|
/** @brief Gaussian Mixture-based Background/Foreground Segmentation Algorithm. |
|
|
|
The class discriminates between foreground and background pixels by building and maintaining a model |
|
of the background. Any pixel which does not fit this model is then deemed to be foreground. The |
|
class implements algorithm described in @cite MOG2001. |
|
|
|
@sa BackgroundSubtractorMOG |
|
|
|
@note |
|
- An example on gaussian mixture based background/foreground segmantation can be found at |
|
opencv_source_code/samples/gpu/bgfg_segm.cpp |
|
*/ |
|
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; |
|
}; |
|
|
|
/** @brief Creates mixture-of-gaussian background subtractor |
|
|
|
@param history Length of the history. |
|
@param nmixtures Number of Gaussian mixtures. |
|
@param backgroundRatio Background ratio. |
|
@param noiseSigma Noise strength (standard deviation of the brightness or each color channel). 0 |
|
means some automatic value. |
|
*/ |
|
CV_EXPORTS Ptr<cuda::BackgroundSubtractorMOG> |
|
createBackgroundSubtractorMOG(int history = 200, int nmixtures = 5, |
|
double backgroundRatio = 0.7, double noiseSigma = 0); |
|
|
|
//////////////////////////////////////////////////// |
|
// MOG2 |
|
|
|
/** @brief Gaussian Mixture-based Background/Foreground Segmentation Algorithm. |
|
|
|
The class discriminates between foreground and background pixels by building and maintaining a model |
|
of the background. Any pixel which does not fit this model is then deemed to be foreground. The |
|
class implements algorithm described in @cite MOG2004. |
|
|
|
@sa BackgroundSubtractorMOG2 |
|
*/ |
|
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; |
|
}; |
|
|
|
/** @brief Creates MOG2 Background Subtractor |
|
|
|
@param history Length of the history. |
|
@param varThreshold Threshold on the squared Mahalanobis distance between the pixel and the model |
|
to decide whether a pixel is well described by the background model. This parameter does not |
|
affect the background update. |
|
@param detectShadows If true, the algorithm will detect shadows and mark them. It decreases the |
|
speed a bit, so if you do not need this feature, set the parameter to false. |
|
*/ |
|
CV_EXPORTS Ptr<cuda::BackgroundSubtractorMOG2> |
|
createBackgroundSubtractorMOG2(int history = 500, double varThreshold = 16, |
|
bool detectShadows = true); |
|
|
|
//////////////////////////////////////////////////// |
|
// GMG |
|
|
|
/** @brief Background/Foreground Segmentation Algorithm. |
|
|
|
The class discriminates between foreground and background pixels by building and maintaining a model |
|
of the background. Any pixel which does not fit this model is then deemed to be foreground. The |
|
class implements algorithm described in @cite GMG2012. |
|
*/ |
|
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; |
|
}; |
|
|
|
/** @brief Creates GMG Background Subtractor |
|
|
|
@param initializationFrames Number of frames of video to use to initialize histograms. |
|
@param decisionThreshold Value above which pixel is determined to be FG. |
|
*/ |
|
CV_EXPORTS Ptr<cuda::BackgroundSubtractorGMG> |
|
createBackgroundSubtractorGMG(int initializationFrames = 120, double decisionThreshold = 0.8); |
|
|
|
//////////////////////////////////////////////////// |
|
// FGD |
|
|
|
/** @brief The class discriminates between foreground and background pixels by building and maintaining a model |
|
of the background. |
|
|
|
Any pixel which does not fit this model is then deemed to be foreground. The class implements |
|
algorithm described in @cite FGD2003. |
|
@sa BackgroundSubtractor |
|
*/ |
|
class CV_EXPORTS BackgroundSubtractorFGD : public cv::BackgroundSubtractor |
|
{ |
|
public: |
|
/** @brief Returns the output foreground regions calculated by findContours. |
|
|
|
@param foreground_regions Output array (CPU memory). |
|
*/ |
|
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(); |
|
}; |
|
|
|
/** @brief Creates FGD Background Subtractor |
|
|
|
@param params Algorithm's parameters. See @cite FGD2003 for explanation. |
|
*/ |
|
CV_EXPORTS Ptr<cuda::BackgroundSubtractorFGD> |
|
createBackgroundSubtractorFGD(const FGDParams& params = FGDParams()); |
|
|
|
//! @} |
|
|
|
}} // namespace cv { namespace cuda { |
|
|
|
#endif /* __OPENCV_CUDABGSEGM_HPP__ */
|
|
|