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/*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) 2010-2013, Multicoreware, Inc., all rights reserved.
// Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// @Authors
// Peng Xiao, pengxiao@multicorewareinc.com
//
// 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 oclMaterials 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 __OCL_RETINA_HPP__
#define __OCL_RETINA_HPP__
#include "precomp.hpp"
#include "opencv2/bioinspired/retina.hpp"
#ifdef HAVE_OPENCL
// please refer to c++ headers for API comments
namespace cv
{
namespace bioinspired
{
namespace ocl
{
void normalizeGrayOutputCentredSigmoide(const float meanValue, const float sensitivity, UMat &in, UMat &out, const float maxValue = 255.f);
void normalizeGrayOutput_0_maxOutputValue(UMat &inputOutputBuffer, const float maxOutputValue = 255.0);
void normalizeGrayOutputNearZeroCentreredSigmoide(UMat &inputPicture, UMat &outputBuffer, const float sensitivity = 40, const float maxOutputValue = 255.0f);
void centerReductImageLuminance(UMat &inputOutputBuffer);
class BasicRetinaFilter
{
public:
BasicRetinaFilter(const unsigned int NBrows, const unsigned int NBcolumns, const unsigned int parametersListSize = 1, const bool useProgressiveFilter = false);
~BasicRetinaFilter();
inline void clearOutputBuffer()
{
_filterOutput = 0;
}
inline void clearSecondaryBuffer()
{
_localBuffer = 0;
}
inline void clearAllBuffers()
{
clearOutputBuffer();
clearSecondaryBuffer();
}
void resize(const unsigned int NBrows, const unsigned int NBcolumns);
const UMat &runFilter_LPfilter(const UMat &inputFrame, const unsigned int filterIndex = 0);
void runFilter_LPfilter(const UMat &inputFrame, UMat &outputFrame, const unsigned int filterIndex = 0);
void runFilter_LPfilter_Autonomous(UMat &inputOutputFrame, const unsigned int filterIndex = 0);
const UMat &runFilter_LocalAdapdation(const UMat &inputOutputFrame, const UMat &localLuminance);
void runFilter_LocalAdapdation(const UMat &inputFrame, const UMat &localLuminance, UMat &outputFrame);
const UMat &runFilter_LocalAdapdation_autonomous(const UMat &inputFrame);
void runFilter_LocalAdapdation_autonomous(const UMat &inputFrame, UMat &outputFrame);
void setLPfilterParameters(const float beta, const float tau, const float k, const unsigned int filterIndex = 0);
inline void setV0CompressionParameter(const float v0, const float maxInputValue, const float)
{
_v0 = v0 * maxInputValue;
_localLuminanceFactor = v0;
_localLuminanceAddon = maxInputValue * (1.0f - v0);
_maxInputValue = maxInputValue;
}
inline void setV0CompressionParameter(const float v0, const float meanLuminance)
{
this->setV0CompressionParameter(v0, _maxInputValue, meanLuminance);
}
inline void setV0CompressionParameter(const float v0)
{
_v0 = v0 * _maxInputValue;
_localLuminanceFactor = v0;
_localLuminanceAddon = _maxInputValue * (1.0f - v0);
}
inline void setV0CompressionParameterToneMapping(const float v0, const float maxInputValue, const float meanLuminance = 128.0f)
{
_v0 = v0 * maxInputValue;
_localLuminanceFactor = 1.0f;
_localLuminanceAddon = meanLuminance * _v0;
_maxInputValue = maxInputValue;
}
inline void updateCompressionParameter(const float meanLuminance)
{
_localLuminanceFactor = 1;
_localLuminanceAddon = meanLuminance * _v0;
}
inline float getV0CompressionParameter()
{
return _v0 / _maxInputValue;
}
inline const UMat &getOutput() const
{
return _filterOutput;
}
inline unsigned int getNBrows()
{
return _filterOutput.rows;
}
inline unsigned int getNBcolumns()
{
return _filterOutput.cols;
}
inline unsigned int getNBpixels()
{
return _filterOutput.size().area();
}
inline void normalizeGrayOutput_0_maxOutputValue(const float maxValue)
{
ocl::normalizeGrayOutput_0_maxOutputValue(_filterOutput, maxValue);
}
inline void normalizeGrayOutputCentredSigmoide()
{
ocl::normalizeGrayOutputCentredSigmoide(0.0, 2.0, _filterOutput, _filterOutput);
}
inline void centerReductImageLuminance()
{
ocl::centerReductImageLuminance(_filterOutput);
}
inline float getMaxInputValue()
{
return this->_maxInputValue;
}
inline void setMaxInputValue(const float newMaxInputValue)
{
this->_maxInputValue = newMaxInputValue;
}
protected:
int _NBrows;
int _NBcols;
unsigned int _halfNBrows;
unsigned int _halfNBcolumns;
UMat _filterOutput;
UMat _localBuffer;
std::valarray <float>_filteringCoeficientsTable;
float _v0;
float _maxInputValue;
float _meanInputValue;
float _localLuminanceFactor;
float _localLuminanceAddon;
float _a;
float _tau;
float _gain;
void _spatiotemporalLPfilter(const UMat &inputFrame, UMat &LPfilterOutput, const unsigned int coefTableOffset = 0);
void _spatiotemporalLPfilter_h(const UMat &inputFrame, UMat &LPfilterOutput, const unsigned int coefTableOffset = 0);
void _spatiotemporalLPfilter_v(UMat &LPfilterOutput, const unsigned int multichannel = 0);
float _squaringSpatiotemporalLPfilter(const UMat &inputFrame, UMat &outputFrame, const unsigned int filterIndex = 0);
void _spatiotemporalLPfilter_Irregular(const UMat &inputFrame, UMat &outputFrame, const unsigned int filterIndex = 0);
void _localSquaringSpatioTemporalLPfilter(const UMat &inputFrame, UMat &LPfilterOutput, const unsigned int *integrationAreas, const unsigned int filterIndex = 0);
void _localLuminanceAdaptation(const UMat &inputFrame, const UMat &localLuminance, UMat &outputFrame, const bool updateLuminanceMean = true);
void _localLuminanceAdaptation(UMat &inputOutputFrame, const UMat &localLuminance);
void _localLuminanceAdaptationPosNegValues(const UMat &inputFrame, const UMat &localLuminance, float *outputFrame);
void _horizontalCausalFilter_addInput(const UMat &inputFrame, UMat &outputFrame);
void _verticalCausalFilter(UMat &outputFrame);
void _verticalCausalFilter_multichannel(UMat &outputFrame);
void _verticalCausalFilter_Irregular(UMat &outputFrame, const UMat &spatialConstantBuffer);
};
class MagnoRetinaFilter: public BasicRetinaFilter
{
public:
MagnoRetinaFilter(const unsigned int NBrows, const unsigned int NBcolumns);
virtual ~MagnoRetinaFilter();
void clearAllBuffers();
void resize(const unsigned int NBrows, const unsigned int NBcolumns);
void setCoefficientsTable(const float parasolCells_beta, const float parasolCells_tau, const float parasolCells_k, const float amacrinCellsTemporalCutFrequency, const float localAdaptIntegration_tau, const float localAdaptIntegration_k);
const UMat &runFilter(const UMat &OPL_ON, const UMat &OPL_OFF);
inline const UMat &getMagnoON() const
{
return _magnoXOutputON;
}
inline const UMat &getMagnoOFF() const
{
return _magnoXOutputOFF;
}
inline const UMat &getMagnoYsaturated() const
{
return _magnoYsaturated;
}
inline void normalizeGrayOutputNearZeroCentreredSigmoide()
{
ocl::normalizeGrayOutputNearZeroCentreredSigmoide(_magnoYOutput, _magnoYsaturated);
}
inline float getTemporalConstant()
{
return this->_filteringCoeficientsTable[2];
}
private:
UMat _previousInput_ON;
UMat _previousInput_OFF;
UMat _amacrinCellsTempOutput_ON;
UMat _amacrinCellsTempOutput_OFF;
UMat _magnoXOutputON;
UMat _magnoXOutputOFF;
UMat _localProcessBufferON;
UMat _localProcessBufferOFF;
UMat _magnoYOutput;
UMat _magnoYsaturated;
float _temporalCoefficient;
void _amacrineCellsComputing(const UMat &OPL_ON, const UMat &OPL_OFF);
};
class ParvoRetinaFilter: public BasicRetinaFilter
{
public:
ParvoRetinaFilter(const unsigned int NBrows = 480, const unsigned int NBcolumns = 640);
virtual ~ParvoRetinaFilter();
void resize(const unsigned int NBrows, const unsigned int NBcolumns);
void clearAllBuffers();
void setOPLandParvoFiltersParameters(const float beta1, const float tau1, const float k1, const float beta2, const float tau2, const float k2);
inline void setGanglionCellsLocalAdaptationLPfilterParameters(const float tau, const float k)
{
BasicRetinaFilter::setLPfilterParameters(0, tau, k, 2);
}
const UMat &runFilter(const UMat &inputFrame, const bool useParvoOutput = true);
inline const UMat &getPhotoreceptorsLPfilteringOutput() const
{
return _photoreceptorsOutput;
}
inline const UMat &getHorizontalCellsOutput() const
{
return _horizontalCellsOutput;
}
inline const UMat &getParvoON() const
{
return _parvocellularOutputON;
}
inline const UMat &getParvoOFF() const
{
return _parvocellularOutputOFF;
}
inline const UMat &getBipolarCellsON() const
{
return _bipolarCellsOutputON;
}
inline const UMat &getBipolarCellsOFF() const
{
return _bipolarCellsOutputOFF;
}
inline float getPhotoreceptorsTemporalConstant()
{
return this->_filteringCoeficientsTable[2];
}
inline float getHcellsTemporalConstant()
{
return this->_filteringCoeficientsTable[5];
}
private:
UMat _photoreceptorsOutput;
UMat _horizontalCellsOutput;
UMat _parvocellularOutputON;
UMat _parvocellularOutputOFF;
UMat _bipolarCellsOutputON;
UMat _bipolarCellsOutputOFF;
UMat _localAdaptationOFF;
UMat _localAdaptationON;
UMat _parvocellularOutputONminusOFF;
void _OPL_OnOffWaysComputing();
};
class RetinaColor: public BasicRetinaFilter
{
public:
RetinaColor(const unsigned int NBrows, const unsigned int NBcolumns, const int samplingMethod = RETINA_COLOR_DIAGONAL);
virtual ~RetinaColor();
void clearAllBuffers();
void resize(const unsigned int NBrows, const unsigned int NBcolumns);
inline void runColorMultiplexing(const UMat &inputRGBFrame)
{
runColorMultiplexing(inputRGBFrame, _multiplexedFrame);
}
void runColorMultiplexing(const UMat &demultiplexedInputFrame, UMat &multiplexedFrame);
void runColorDemultiplexing(const UMat &multiplexedColorFrame, const bool adaptiveFiltering = false, const float maxInputValue = 255.0);
void setColorSaturation(const bool saturateColors = true, const float colorSaturationValue = 4.0)
{
_saturateColors = saturateColors;
_colorSaturationValue = colorSaturationValue;
}
void setChrominanceLPfilterParameters(const float beta, const float tau, const float k)
{
setLPfilterParameters(beta, tau, k);
}
bool applyKrauskopfLMS2Acr1cr2Transform(UMat &result);
bool applyLMS2LabTransform(UMat &result);
inline const UMat &getMultiplexedFrame() const
{
return _multiplexedFrame;
}
inline const UMat &getDemultiplexedColorFrame() const
{
return _demultiplexedColorFrame;
}
inline const UMat &getLuminance() const
{
return _luminance;
}
inline const UMat &getChrominance() const
{
return _chrominance;
}
void clipRGBOutput_0_maxInputValue(UMat &inputOutputBuffer, const float maxOutputValue = 255.0);
void normalizeRGBOutput_0_maxOutputValue(const float maxOutputValue = 255.0);
inline void setDemultiplexedColorFrame(const UMat &demultiplexedImage)
{
_demultiplexedColorFrame = demultiplexedImage;
}
protected:
inline unsigned int bayerSampleOffset(unsigned int index)
{
return index + ((index / getNBcolumns()) % 2) * getNBpixels() + ((index % getNBcolumns()) % 2) * getNBpixels();
}
inline Rect getROI(int idx)
{
return Rect(0, idx * _NBrows, _NBcols, _NBrows);
}
int _samplingMethod;
bool _saturateColors;
float _colorSaturationValue;
UMat _luminance;
UMat _multiplexedFrame;
UMat _RGBmosaic;
UMat _tempMultiplexedFrame;
UMat _demultiplexedTempBuffer;
UMat _demultiplexedColorFrame;
UMat _chrominance;
UMat _colorLocalDensity;
UMat _imageGradient;
float _pR, _pG, _pB;
bool _objectInit;
void _initColorSampling();
void _adaptiveSpatialLPfilter_h(const UMat &inputFrame, const UMat &gradient, UMat &outputFrame);
void _adaptiveSpatialLPfilter_v(const UMat &gradient, UMat &outputFrame);
void _adaptiveHorizontalCausalFilter_addInput(const UMat &inputFrame, const UMat &gradient, UMat &outputFrame);
void _computeGradient(const UMat &luminance, UMat &gradient);
void _normalizeOutputs_0_maxOutputValue(void);
void _applyImageColorSpaceConversion(const UMat &inputFrame, UMat &outputFrame, const float *transformTable);
};
class RetinaFilter
{
public:
RetinaFilter(const unsigned int sizeRows, const unsigned int sizeColumns, const bool colorMode = false, const int samplingMethod = RETINA_COLOR_BAYER, const bool useRetinaLogSampling = false, const double reductionFactor = 1.0, const double samplingStrenght = 10.0);
~RetinaFilter();
void clearAllBuffers();
void resize(const unsigned int NBrows, const unsigned int NBcolumns);
bool checkInput(const UMat &input, const bool colorMode);
bool runFilter(const UMat &imageInput, const bool useAdaptiveFiltering = true, const bool processRetinaParvoMagnoMapping = false, const bool useColorMode = false, const bool inputIsColorMultiplexed = false);
void setGlobalParameters(const float OPLspatialResponse1 = 0.7, const float OPLtemporalresponse1 = 1, const float OPLassymetryGain = 0, const float OPLspatialResponse2 = 5, const float OPLtemporalresponse2 = 1, const float LPfilterSpatialResponse = 5, const float LPfilterGain = 0, const float LPfilterTemporalresponse = 0, const float MovingContoursExtractorCoefficient = 5, const bool normalizeParvoOutput_0_maxOutputValue = false, const bool normalizeMagnoOutput_0_maxOutputValue = false, const float maxOutputValue = 255.0, const float maxInputValue = 255.0, const float meanValue = 128.0);
inline void setPhotoreceptorsLocalAdaptationSensitivity(const float V0CompressionParameter)
{
_photoreceptorsPrefilter.setV0CompressionParameter(1 - V0CompressionParameter);
_setInitPeriodCount();
}
inline void setParvoGanglionCellsLocalAdaptationSensitivity(const float V0CompressionParameter)
{
_ParvoRetinaFilter.setV0CompressionParameter(V0CompressionParameter);
_setInitPeriodCount();
}
inline void setGanglionCellsLocalAdaptationLPfilterParameters(const float spatialResponse, const float temporalResponse)
{
_ParvoRetinaFilter.setGanglionCellsLocalAdaptationLPfilterParameters(temporalResponse, spatialResponse);
_setInitPeriodCount();
};
inline void setMagnoGanglionCellsLocalAdaptationSensitivity(const float V0CompressionParameter)
{
_MagnoRetinaFilter.setV0CompressionParameter(V0CompressionParameter);
_setInitPeriodCount();
}
void setOPLandParvoParameters(const float beta1, const float tau1, const float k1, const float beta2, const float tau2, const float k2, const float V0CompressionParameter)
{
_ParvoRetinaFilter.setOPLandParvoFiltersParameters(beta1, tau1, k1, beta2, tau2, k2);
_ParvoRetinaFilter.setV0CompressionParameter(V0CompressionParameter);
_setInitPeriodCount();
}
void setMagnoCoefficientsTable(const float parasolCells_beta, const float parasolCells_tau, const float parasolCells_k, const float amacrinCellsTemporalCutFrequency, const float V0CompressionParameter, const float localAdaptintegration_tau, const float localAdaptintegration_k)
{
_MagnoRetinaFilter.setCoefficientsTable(parasolCells_beta, parasolCells_tau, parasolCells_k, amacrinCellsTemporalCutFrequency, localAdaptintegration_tau, localAdaptintegration_k);
_MagnoRetinaFilter.setV0CompressionParameter(V0CompressionParameter);
_setInitPeriodCount();
}
inline void activateNormalizeParvoOutput_0_maxOutputValue(const bool normalizeParvoOutput_0_maxOutputValue)
{
_normalizeParvoOutput_0_maxOutputValue = normalizeParvoOutput_0_maxOutputValue;
}
inline void activateNormalizeMagnoOutput_0_maxOutputValue(const bool normalizeMagnoOutput_0_maxOutputValue)
{
_normalizeMagnoOutput_0_maxOutputValue = normalizeMagnoOutput_0_maxOutputValue;
}
inline void setMaxOutputValue(const float maxOutputValue)
{
_maxOutputValue = maxOutputValue;
}
void setColorMode(const bool desiredColorMode)
{
_useColorMode = desiredColorMode;
}
inline void setColorSaturation(const bool saturateColors = true, const float colorSaturationValue = 4.0)
{
_colorEngine.setColorSaturation(saturateColors, colorSaturationValue);
}
inline const UMat &getLocalAdaptation() const
{
return _photoreceptorsPrefilter.getOutput();
}
inline const UMat &getPhotoreceptors() const
{
return _ParvoRetinaFilter.getPhotoreceptorsLPfilteringOutput();
}
inline const UMat &getHorizontalCells() const
{
return _ParvoRetinaFilter.getHorizontalCellsOutput();
}
inline bool areContoursProcessed()
{
return _useParvoOutput;
}
bool getParvoFoveaResponse(UMat &parvoFovealResponse);
inline void activateContoursProcessing(const bool useParvoOutput)
{
_useParvoOutput = useParvoOutput;
}
const UMat &getContours();
inline const UMat &getContoursON() const
{
return _ParvoRetinaFilter.getParvoON();
}
inline const UMat &getContoursOFF() const
{
return _ParvoRetinaFilter.getParvoOFF();
}
inline bool areMovingContoursProcessed()
{
return _useMagnoOutput;
}
inline void activateMovingContoursProcessing(const bool useMagnoOutput)
{
_useMagnoOutput = useMagnoOutput;
}
inline const UMat &getMovingContours() const
{
return _MagnoRetinaFilter.getOutput();
}
inline const UMat &getMovingContoursSaturated() const
{
return _MagnoRetinaFilter.getMagnoYsaturated();
}
inline const UMat &getMovingContoursON() const
{
return _MagnoRetinaFilter.getMagnoON();
}
inline const UMat &getMovingContoursOFF() const
{
return _MagnoRetinaFilter.getMagnoOFF();
}
inline const UMat &getRetinaParvoMagnoMappedOutput() const
{
return _retinaParvoMagnoMappedFrame;
}
inline const UMat &getParvoContoursChannel() const
{
return _colorEngine.getLuminance();
}
inline const UMat &getParvoChrominance() const
{
return _colorEngine.getChrominance();
}
inline const UMat &getColorOutput() const
{
return _colorEngine.getDemultiplexedColorFrame();
}
inline bool isColorMode()
{
return _useColorMode;
}
bool getColorMode()
{
return _useColorMode;
}
inline bool isInitTransitionDone()
{
if (_ellapsedFramesSinceLastReset < _globalTemporalConstant)
{
return false;
}
return true;
}
inline float getRetinaSamplingBackProjection(const float projectedRadiusLength)
{
return projectedRadiusLength;
}
inline unsigned int getInputNBrows()
{
return _photoreceptorsPrefilter.getNBrows();
}
inline unsigned int getInputNBcolumns()
{
return _photoreceptorsPrefilter.getNBcolumns();
}
inline unsigned int getInputNBpixels()
{
return _photoreceptorsPrefilter.getNBpixels();
}
inline unsigned int getOutputNBrows()
{
return _photoreceptorsPrefilter.getNBrows();
}
inline unsigned int getOutputNBcolumns()
{
return _photoreceptorsPrefilter.getNBcolumns();
}
inline unsigned int getOutputNBpixels()
{
return _photoreceptorsPrefilter.getNBpixels();
}
private:
bool _useParvoOutput;
bool _useMagnoOutput;
unsigned int _ellapsedFramesSinceLastReset;
unsigned int _globalTemporalConstant;
UMat _retinaParvoMagnoMappedFrame;
BasicRetinaFilter _photoreceptorsPrefilter;
ParvoRetinaFilter _ParvoRetinaFilter;
MagnoRetinaFilter _MagnoRetinaFilter;
RetinaColor _colorEngine;
bool _useMinimalMemoryForToneMappingONLY;
bool _normalizeParvoOutput_0_maxOutputValue;
bool _normalizeMagnoOutput_0_maxOutputValue;
float _maxOutputValue;
bool _useColorMode;
void _setInitPeriodCount();
void _processRetinaParvoMagnoMapping();
void _runGrayToneMapping(const UMat &grayImageInput, UMat &grayImageOutput , const float PhotoreceptorsCompression = 0.6, const float ganglionCellsCompression = 0.6);
};
class RetinaOCLImpl : public Retina
{
public:
RetinaOCLImpl(Size getInputSize);
RetinaOCLImpl(Size getInputSize, const bool colorMode, int colorSamplingMethod = RETINA_COLOR_BAYER, const bool useRetinaLogSampling = false, const double reductionFactor = 1.0, const double samplingStrenght = 10.0);
virtual ~RetinaOCLImpl();
Size getInputSize();
Size getOutputSize();
void setup(String retinaParameterFile = "", const bool applyDefaultSetupOnFailure = true);
void setup(cv::FileStorage &fs, const bool applyDefaultSetupOnFailure = true);
void setup(RetinaParameters newParameters);
RetinaParameters getParameters();
const String printSetup();
virtual void write(String fs) const;
virtual void write(FileStorage& fs) const;
void setupOPLandIPLParvoChannel(const bool colorMode = true, const bool normaliseOutput = true, const float photoreceptorsLocalAdaptationSensitivity = 0.7, const float photoreceptorsTemporalConstant = 0.5, const float photoreceptorsSpatialConstant = 0.53, const float horizontalCellsGain = 0, const float HcellsTemporalConstant = 1, const float HcellsSpatialConstant = 7, const float ganglionCellsSensitivity = 0.7);
void setupIPLMagnoChannel(const bool normaliseOutput = true, const float parasolCells_beta = 0, const float parasolCells_tau = 0, const float parasolCells_k = 7, const float amacrinCellsTemporalCutFrequency = 1.2, const float V0CompressionParameter = 0.95, const float localAdaptintegration_tau = 0, const float localAdaptintegration_k = 7);
void run(InputArray inputImage);
void getParvo(OutputArray retinaOutput_parvo);
void getMagno(OutputArray retinaOutput_magno);
void setColorSaturation(const bool saturateColors = true, const float colorSaturationValue = 4.0);
void clearBuffers();
void activateMovingContoursProcessing(const bool activate);
void activateContoursProcessing(const bool activate);
// unimplemented interfaces:
void applyFastToneMapping(InputArray /*inputImage*/, OutputArray /*outputToneMappedImage*/);
void getParvoRAW(OutputArray /*retinaOutput_parvo*/);
void getMagnoRAW(OutputArray /*retinaOutput_magno*/);
const Mat getMagnoRAW() const;
const Mat getParvoRAW() const;
protected:
RetinaParameters _retinaParameters;
UMat _inputBuffer;
RetinaFilter* _retinaFilter;
bool convertToColorPlanes(const UMat& input, UMat &output);
void convertToInterleaved(const UMat& input, bool colorMode, UMat &output);
void _init(const Size getInputSize, const bool colorMode, int colorSamplingMethod = RETINA_COLOR_BAYER, const bool useRetinaLogSampling = false, const double reductionFactor = 1.0, const double samplingStrenght = 10.0);
};
} /* namespace ocl */
} /* namespace bioinspired */
} /* namespace cv */
#endif /* HAVE_OPENCL */
#endif /* __OCL_RETINA_HPP__ */