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Compatibility with core repos, pure virtual overload foreground masking
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‎modules/bgsegm/include/opencv2/bgsegm.hpp‎

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@@ -62,6 +62,32 @@ The class implements the algorithm described in @cite KB2001 .
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class CV_EXPORTS_W BackgroundSubtractorMOG : public BackgroundSubtractor
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{
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public:
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// BackgroundSubtractor interface
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/** @brief Computes a foreground mask.
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@param image Next video frame of type CV_8UC(n),CV_8SC(n),CV_16UC(n),CV_16SC(n),CV_32SC(n),CV_32FC(n),CV_64FC(n), where n is 1,2,3,4.
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@param fgmask The output foreground mask as an 8-bit binary image.
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@param learningRate The value between 0 and 1 that indicates how fast the background model is
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learnt. Negative parameter value makes the algorithm to use some automatically chosen learning
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rate. 0 means that the background model is not updated at all, 1 means that the background model
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is completely reinitialized from the last frame.
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*/
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CV_WRAP virtual void apply(InputArray image, OutputArray fgmask, double learningRate=-1) CV_OVERRIDE = 0;
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/** @brief Computes a foreground mask and skips known foreground in evaluation.
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@param image Next video frame of type CV_8UC(n),CV_8SC(n),CV_16UC(n),CV_16SC(n),CV_32SC(n),CV_32FC(n),CV_64FC(n), where n is 1,2,3,4.
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@param fgmask The output foreground mask as an 8-bit binary image.
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@param knownForegroundMask The mask for inputting already known foreground, allows model to ignore learning known pixels.
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@param learningRate The value between 0 and 1 that indicates how fast the background model is
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learnt. Negative parameter value makes the algorithm to use some automatically chosen learning
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rate. 0 means that the background model is not updated at all, 1 means that the background model
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is completely reinitialized from the last frame.
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*/
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CV_WRAP virtual void apply(InputArray image, InputArray knownForegroundMask, OutputArray fgmask, double learningRate=-1) CV_OVERRIDE = 0;
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CV_WRAP virtual int getHistory() const = 0;
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CV_WRAP virtual void setHistory(int nframes) = 0;
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@@ -110,6 +136,22 @@ class CV_EXPORTS_W BackgroundSubtractorGMG : public BackgroundSubtractor
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is completely reinitialized from the last frame.
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*/
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CV_WRAP virtual void apply(InputArray image, OutputArray fgmask, double learningRate=-1) CV_OVERRIDE = 0;
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/** @brief Computes a foreground mask with known foreground mask input.
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@param image Next video frame.
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@param fgmask The output foreground mask as an 8-bit binary image.
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@param knownForegroundMask The mask for inputting already known foreground.
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@param learningRate The value between 0 and 1 that indicates how fast the background model is
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learnt. Negative parameter value makes the algorithm to use some automatically chosen learning
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rate. 0 means that the background model is not updated at all, 1 means that the background model
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is completely reinitialized from the last frame.
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@note This method has a default virtual implementation that throws a "not impemented" error.
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Foreground masking may not be supported by all background subtractors.
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*/
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CV_WRAP virtual void apply(InputArray image, InputArray knownForegroundMask, OutputArray fgmask, double learningRate=-1);
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CV_WRAP virtual void getBackgroundImage(OutputArray backgroundImage) const CV_OVERRIDE = 0;
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/** @brief Returns total number of distinct colors to maintain in histogram.
@@ -210,6 +252,22 @@ class CV_EXPORTS_W BackgroundSubtractorCNT : public BackgroundSubtractor
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public:
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// BackgroundSubtractor interface
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CV_WRAP virtual void apply(InputArray image, OutputArray fgmask, double learningRate=-1) CV_OVERRIDE = 0;
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/** @brief Computes a foreground mask with known foreground mask input.
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@param image Next video frame.
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@param knownForegroundMask The mask for inputting already known foreground.
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@param fgmask The output foreground mask as an 8-bit binary image.
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@param learningRate The value between 0 and 1 that indicates how fast the background model is
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learnt. Negative parameter value makes the algorithm to use some automatically chosen learning
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rate. 0 means that the background model is not updated at all, 1 means that the background model
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is completely reinitialized from the last frame.
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@note This method has a default virtual implementation that throws a "not impemented" error.
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Foreground masking may not be supported by all background subtractors.
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*/
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CV_WRAP virtual void apply(InputArray image, InputArray knownForegroundMask, OutputArray fgmask, double learningRate=-1) CV_OVERRIDE = 0;
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CV_WRAP virtual void getBackgroundImage(OutputArray backgroundImage) const CV_OVERRIDE = 0;
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/** @brief Returns number of frames with same pixel color to consider stable.
@@ -269,6 +327,7 @@ class CV_EXPORTS_W BackgroundSubtractorGSOC : public BackgroundSubtractor
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public:
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// BackgroundSubtractor interface
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CV_WRAP virtual void apply(InputArray image, OutputArray fgmask, double learningRate=-1) CV_OVERRIDE = 0;
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CV_WRAP virtual void apply(InputArray image, InputArray knownForegroundMask, OutputArray fgmask, double learningRate=-1) CV_OVERRIDE = 0;
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CV_WRAP virtual void getBackgroundImage(OutputArray backgroundImage) const CV_OVERRIDE = 0;
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};
@@ -280,6 +339,7 @@ class CV_EXPORTS_W BackgroundSubtractorLSBP : public BackgroundSubtractor
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public:
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// BackgroundSubtractor interface
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CV_WRAP virtual void apply(InputArray image, OutputArray fgmask, double learningRate=-1) CV_OVERRIDE = 0;
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CV_WRAP virtual void apply(InputArray image, InputArray knownForegroundMask, OutputArray fgmask, double learningRate=-1) CV_OVERRIDE = 0;
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CV_WRAP virtual void getBackgroundImage(OutputArray backgroundImage) const CV_OVERRIDE = 0;
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};

‎modules/bgsegm/src/bgfg_gaussmix.cpp‎

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@@ -104,6 +104,8 @@ class BackgroundSubtractorMOGImpl CV_FINAL : public BackgroundSubtractorMOG
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//! the update operator
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virtual void apply(InputArray image, OutputArray fgmask, double learningRate=0) CV_OVERRIDE;
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virtual void apply(InputArray image, InputArray knownForegroundMask, OutputArray fgmask, double learningRate) CV_OVERRIDE;
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//! re-initiaization method
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virtual void initialize(Size _frameSize, int _frameType)
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{
@@ -461,6 +463,15 @@ void BackgroundSubtractorMOGImpl::apply(InputArray _image, OutputArray _fgmask,
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CV_Error( Error::StsUnsupportedFormat, "Only 1- and 3-channel 8-bit images are supported in BackgroundSubtractorMOG" );
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}
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void BackgroundSubtractorMOGImpl::apply(InputArray _image, InputArray _knownForegroundMask, OutputArray _fgmask, double learningRate){
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Mat knownForegroundMask = _knownForegroundMask.getMat();
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if(!_knownForegroundMask.empty())
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{
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CV_Error( Error::StsNotImplemented, "Known Foreground Masking has not been implemented for this specific background subtractor, falling back to subtraction without known foreground");
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}
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apply(_image, _fgmask, learningRate);
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}
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Ptr<BackgroundSubtractorMOG> createBackgroundSubtractorMOG(int history, int nmixtures,
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double backgroundRatio, double noiseSigma)
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{

‎modules/bgsegm/src/bgfg_gmg.cpp‎

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@@ -97,6 +97,7 @@ class BackgroundSubtractorGMGImpl CV_FINAL : public BackgroundSubtractorGMG
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* @param fgmask Output mask image representing foreground and background pixels
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*/
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virtual void apply(InputArray image, OutputArray fgmask, double learningRate=-1.0) CV_OVERRIDE;
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virtual void apply(InputArray image, InputArray knownForegroundMask, OutputArray fgmask, double learningRate) CV_OVERRIDE;
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/**
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* Releases all inner buffers.
@@ -473,6 +474,15 @@ void BackgroundSubtractorGMGImpl::apply(InputArray _frame, OutputArray _fgmask,
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++frameNum_;
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}
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void BackgroundSubtractorGMGImpl::apply(InputArray _image, InputArray _knownForegroundMask, OutputArray _fgmask, double newLearningRate){
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Mat knownForegroundMask = _knownForegroundMask.getMat();
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if(!_knownForegroundMask.empty())
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{
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CV_Error( Error::StsNotImplemented, "Known Foreground Masking has not been implemented for this specific background subtractor, falling back to subtraction without known foreground");
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}
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apply(_image, _fgmask, newLearningRate);
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}
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void BackgroundSubtractorGMGImpl::release()
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{
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frameSize_ = Size();

‎modules/bgsegm/src/bgfg_gsoc.cpp‎

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@@ -494,6 +494,7 @@ class BackgroundSubtractorGSOCImpl CV_FINAL : public BackgroundSubtractorGSOC {
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float noiseRemovalThresholdFacFG);
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CV_WRAP virtual void apply(InputArray image, OutputArray fgmask, double learningRate = -1) CV_OVERRIDE;
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CV_WRAP virtual void apply(InputArray image, InputArray knownForegroundMask, OutputArray fgmask, double learningRate) CV_OVERRIDE;
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CV_WRAP virtual void getBackgroundImage(OutputArray backgroundImage) const CV_OVERRIDE;
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@@ -542,6 +543,7 @@ class BackgroundSubtractorLSBPImpl CV_FINAL : public BackgroundSubtractorLSBP {
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);
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CV_WRAP virtual void apply(InputArray image, OutputArray fgmask, double learningRate = -1) CV_OVERRIDE;
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CV_WRAP virtual void apply(InputArray image, InputArray knownForegroundMask, OutputArray fgmask, double learningRate) CV_OVERRIDE;
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CV_WRAP virtual void getBackgroundImage(OutputArray backgroundImage) const CV_OVERRIDE;
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@@ -793,6 +795,15 @@ void BackgroundSubtractorGSOCImpl::apply(InputArray _image, OutputArray _fgmask,
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this->postprocessing(fgMask);
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}
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void BackgroundSubtractorGSOCImpl::apply(InputArray _image, InputArray _knownForegroundMask, OutputArray _fgmask, double learningRate){
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Mat knownForegroundMask = _knownForegroundMask.getMat();
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if(!_knownForegroundMask.empty())
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{
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CV_Error( Error::StsNotImplemented, "Known Foreground Masking has not been implemented for this specific background subtractor, falling back to subtraction without known foreground");
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}
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apply(_image, _fgmask, learningRate);
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}
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void BackgroundSubtractorGSOCImpl::getBackgroundImage(OutputArray _backgroundImage) const {
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CV_Assert(!backgroundModel.empty());
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const Size sz = backgroundModel->getSize();
@@ -928,6 +939,15 @@ void BackgroundSubtractorLSBPImpl::apply(InputArray _image, OutputArray _fgmask,
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this->postprocessing(fgMask);
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}
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void BackgroundSubtractorLSBPImpl::apply(InputArray _image, InputArray _knownForegroundMask, OutputArray _fgmask, double learningRate){
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Mat knownForegroundMask = _knownForegroundMask.getMat();
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if(!_knownForegroundMask.empty())
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{
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CV_Error( Error::StsNotImplemented, "Known Foreground Masking has not been implemented for this specific background subtractor, falling back to subtraction without known foreground");
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}
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apply(_image, _fgmask, learningRate);
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}
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void BackgroundSubtractorLSBPImpl::getBackgroundImage(OutputArray _backgroundImage) const {
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CV_Assert(!backgroundModel.empty());
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const Size sz = backgroundModel->getSize();

‎modules/bgsegm/src/bgfg_subcnt.cpp‎

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@@ -61,6 +61,8 @@ class BackgroundSubtractorCNTImpl CV_FINAL : public BackgroundSubtractorCNT
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// BackgroundSubtractor interface
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virtual void apply(InputArray image, OutputArray fgmask, double learningRate) CV_OVERRIDE;
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virtual void apply(InputArray image, InputArray knownForegroundMask, OutputArray fgmask, double learningRate) CV_OVERRIDE;
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virtual void getBackgroundImage(OutputArray backgroundImage) const CV_OVERRIDE;
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int getMinPixelStability() const CV_OVERRIDE;
@@ -409,6 +411,14 @@ void BackgroundSubtractorCNTImpl::apply(InputArray image, OutputArray _fgmask, d
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prevFrame = frame;
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}
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void BackgroundSubtractorCNTImpl::apply(InputArray _image, InputArray _knownForegroundMask, OutputArray _fgmask, double learningRate){
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Mat knownForegroundMask = _knownForegroundMask.getMat();
416+
if(!_knownForegroundMask.empty())
417+
{
418+
CV_Error( Error::StsNotImplemented, "Known Foreground Masking has not been implemented for this specific background subtractor, falling back to subtraction without known foreground");
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}
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apply(_image, _fgmask, learningRate);
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}
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Ptr<BackgroundSubtractorCNT> createBackgroundSubtractorCNT(int minPixelStability, bool useHistory, int maxStability, bool isParallel)
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{

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