opencv/modules/contrib/src/retina.cpp

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/*#******************************************************************************
** 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.
**
**
** HVStools : interfaces allowing OpenCV users to integrate Human Vision System models. Presented models originate from Jeanny Herault's original research and have been reused and adapted by the author&collaborators for computed vision applications since his thesis with Alice Caplier at Gipsa-Lab.
** Use: extract still images & image sequences features, from contours details to motion spatio-temporal features, etc. for high level visual scene analysis. Also contribute to image enhancement/compression such as tone mapping.
**
** Maintainers : Listic lab (code author current affiliation & applications) and Gipsa Lab (original research origins & applications)
**
** Creation - enhancement process 2007-2011
** Author: Alexandre Benoit (benoit.alexandre.vision@gmail.com), LISTIC lab, Annecy le vieux, France
**
** Theses algorithm have been developped by Alexandre BENOIT since his thesis with Alice Caplier at Gipsa-Lab (www.gipsa-lab.inpg.fr) and the research he pursues at LISTIC Lab (www.listic.univ-savoie.fr).
** Refer to the following research paper for more information:
** Benoit A., Caplier A., Durette B., Herault, J., "USING HUMAN VISUAL SYSTEM MODELING FOR BIO-INSPIRED LOW LEVEL IMAGE PROCESSING", Elsevier, Computer Vision and Image Understanding 114 (2010), pp. 758-773, DOI: http://dx.doi.org/10.1016/j.cviu.2010.01.011
** This work have been carried out thanks to Jeanny Herault who's research and great discussions are the basis of all this work, please take a look at his book:
** Vision: Images, Signals and Neural Networks: Models of Neural Processing in Visual Perception (Progress in Neural Processing),By: Jeanny Herault, ISBN: 9814273686. WAPI (Tower ID): 113266891.
**
** The retina filter includes the research contributions of phd/research collegues from which code has been redrawn by the author :
** _take a look at the retinacolor.hpp module to discover Brice Chaix de Lavarene color mosaicing/demosaicing and the reference paper:
** ====> B. Chaix de Lavarene, D. Alleysson, B. Durette, J. Herault (2007). "Efficient demosaicing through recursive filtering", IEEE International Conference on Image Processing ICIP 2007
** _take a look at imagelogpolprojection.hpp to discover retina spatial log sampling which originates from Barthelemy Durette phd with Jeanny Herault. A Retina / V1 cortex projection is also proposed and originates from Jeanny's discussions.
** ====> more informations in the above cited Jeanny Heraults's book.
**
** License Agreement
** For Open Source Computer Vision Library
**
** Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
** Copyright (C) 2008-2011, Willow Garage Inc., all rights reserved.
**
** For Human Visual System tools (hvstools)
** Copyright (C) 2007-2011, LISTIC Lab, Annecy le Vieux and GIPSA Lab, Grenoble, France, all rights reserved.
**
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** Redistribution and use in source and binary forms, with or without modification,
** are permitted provided that the following conditions are met:
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** 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
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*******************************************************************************/
/*
* Retina.cpp
*
* Created on: Jul 19, 2011
* Author: Alexandre Benoit
*/
#include "precomp.hpp"
#include "retinafilter.hpp"
#include <iostream>
namespace cv
{
Retina::Retina(const cv::Size inputSize)
{
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_retinaFilter = 0;
_init(inputSize, true, RETINA_COLOR_BAYER, false);
}
Retina::Retina(const cv::Size inputSize, const bool colorMode, RETINA_COLORSAMPLINGMETHOD colorSamplingMethod, const bool useRetinaLogSampling, const double reductionFactor, const double samplingStrenght)
{
_retinaFilter = 0;
_init(inputSize, colorMode, colorSamplingMethod, useRetinaLogSampling, reductionFactor, samplingStrenght);
};
Retina::~Retina()
{
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if (_retinaFilter)
delete _retinaFilter;
}
void Retina::setColorSaturation(const bool saturateColors, const float colorSaturationValue)
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{
_retinaFilter->setColorSaturation(saturateColors, colorSaturationValue);
}
struct Retina::RetinaParameters Retina::getParameters(){return _retinaParameters;}
void Retina::setup(std::string retinaParameterFile, const bool applyDefaultSetupOnFailure)
{
try
{
// opening retinaParameterFile in read mode
cv::FileStorage fs(retinaParameterFile, cv::FileStorage::READ);
setup(fs, applyDefaultSetupOnFailure);
}catch(Exception &e)
{
std::cout<<"Retina::setup: wrong/unappropriate xml parameter file : error report :`n=>"<<e.what()<<std::endl;
if (applyDefaultSetupOnFailure)
{
std::cout<<"Retina::setup: resetting retina with default parameters"<<std::endl;
setupOPLandIPLParvoChannel();
setupIPLMagnoChannel();
}
else
{
std::cout<<"=> keeping current parameters"<<std::endl;
}
}
}
void Retina::setup(cv::FileStorage &fs, const bool applyDefaultSetupOnFailure)
{
try
{
// read parameters file if it exists or apply default setup if asked for
if (!fs.isOpened())
{
std::cout<<"Retina::setup: provided parameters file could not be open... skeeping configuration"<<std::endl;
return;
// implicit else case : retinaParameterFile could be open (it exists at least)
}
// OPL and Parvo init first... update at the same time the parameters structure and the retina core
cv::FileNode rootFn = fs.root(), currFn=rootFn["OPLandIPLparvo"];
currFn["colorMode"]>>_retinaParameters.OPLandIplParvo.colorMode;
currFn["normaliseOutput"]>>_retinaParameters.OPLandIplParvo.normaliseOutput;
currFn["photoreceptorsLocalAdaptationSensitivity"]>>_retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity;
currFn["photoreceptorsTemporalConstant"]>>_retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant;
currFn["photoreceptorsSpatialConstant"]>>_retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant;
currFn["horizontalCellsGain"]>>_retinaParameters.OPLandIplParvo.horizontalCellsGain;
currFn["hcellsTemporalConstant"]>>_retinaParameters.OPLandIplParvo.hcellsTemporalConstant;
currFn["hcellsSpatialConstant"]>>_retinaParameters.OPLandIplParvo.hcellsSpatialConstant;
currFn["ganglionCellsSensitivity"]>>_retinaParameters.OPLandIplParvo.ganglionCellsSensitivity;
setupOPLandIPLParvoChannel(_retinaParameters.OPLandIplParvo.colorMode, _retinaParameters.OPLandIplParvo.normaliseOutput, _retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity, _retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant, _retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant, _retinaParameters.OPLandIplParvo.horizontalCellsGain, _retinaParameters.OPLandIplParvo.hcellsTemporalConstant, _retinaParameters.OPLandIplParvo.hcellsSpatialConstant, _retinaParameters.OPLandIplParvo.ganglionCellsSensitivity);
// init retina IPL magno setup... update at the same time the parameters structure and the retina core
currFn=rootFn["IPLmagno"];
currFn["normaliseOutput"]>>_retinaParameters.IplMagno.normaliseOutput;
currFn["parasolCells_beta"]>>_retinaParameters.IplMagno.parasolCells_beta;
currFn["parasolCells_tau"]>>_retinaParameters.IplMagno.parasolCells_tau;
currFn["parasolCells_k"]>>_retinaParameters.IplMagno.parasolCells_k;
currFn["amacrinCellsTemporalCutFrequency"]>>_retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency;
currFn["V0CompressionParameter"]>>_retinaParameters.IplMagno.V0CompressionParameter;
currFn["localAdaptintegration_tau"]>>_retinaParameters.IplMagno.localAdaptintegration_tau;
currFn["localAdaptintegration_k"]>>_retinaParameters.IplMagno.localAdaptintegration_k;
setupIPLMagnoChannel(_retinaParameters.IplMagno.normaliseOutput, _retinaParameters.IplMagno.parasolCells_beta, _retinaParameters.IplMagno.parasolCells_tau, _retinaParameters.IplMagno.parasolCells_k, _retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency,_retinaParameters.IplMagno.V0CompressionParameter, _retinaParameters.IplMagno.localAdaptintegration_tau, _retinaParameters.IplMagno.localAdaptintegration_k);
}catch(Exception &e)
{
std::cout<<"Retina::setup: resetting retina with default parameters"<<std::endl;
if (applyDefaultSetupOnFailure)
{
setupOPLandIPLParvoChannel();
setupIPLMagnoChannel();
}
std::cout<<"Retina::setup: wrong/unappropriate xml parameter file : error report :`n=>"<<e.what()<<std::endl;
std::cout<<"=> keeping current parameters"<<std::endl;
}
// report current configuration
std::cout<<printSetup()<<std::endl;
}
void Retina::setup(cv::Retina::RetinaParameters newConfiguration)
{
// simply copy structures
memcpy(&_retinaParameters, &newConfiguration, sizeof(cv::Retina::RetinaParameters));
// apply setup
setupOPLandIPLParvoChannel(_retinaParameters.OPLandIplParvo.colorMode, _retinaParameters.OPLandIplParvo.normaliseOutput, _retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity, _retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant, _retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant, _retinaParameters.OPLandIplParvo.horizontalCellsGain, _retinaParameters.OPLandIplParvo.hcellsTemporalConstant, _retinaParameters.OPLandIplParvo.hcellsSpatialConstant, _retinaParameters.OPLandIplParvo.ganglionCellsSensitivity);
setupIPLMagnoChannel(_retinaParameters.IplMagno.normaliseOutput, _retinaParameters.IplMagno.parasolCells_beta, _retinaParameters.IplMagno.parasolCells_tau, _retinaParameters.IplMagno.parasolCells_k, _retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency,_retinaParameters.IplMagno.V0CompressionParameter, _retinaParameters.IplMagno.localAdaptintegration_tau, _retinaParameters.IplMagno.localAdaptintegration_k);
}
const std::string Retina::printSetup()
{
std::stringstream outmessage;
// displaying OPL and IPL parvo setup
outmessage<<"Current Retina instance setup :"
<<"\nOPLandIPLparvo"<<"{"
<< "\n==> colorMode : " << _retinaParameters.OPLandIplParvo.colorMode
<< "\n==> normalizeParvoOutput :" << _retinaParameters.OPLandIplParvo.normaliseOutput
<< "\n==> photoreceptorsLocalAdaptationSensitivity : " << _retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity
<< "\n==> photoreceptorsTemporalConstant : " << _retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant
<< "\n==> photoreceptorsSpatialConstant : " << _retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant
<< "\n==> horizontalCellsGain : " << _retinaParameters.OPLandIplParvo.horizontalCellsGain
<< "\n==> hcellsTemporalConstant : " << _retinaParameters.OPLandIplParvo.hcellsTemporalConstant
<< "\n==> hcellsSpatialConstant : " << _retinaParameters.OPLandIplParvo.hcellsSpatialConstant
<< "\n==> parvoGanglionCellsSensitivity : " << _retinaParameters.OPLandIplParvo.ganglionCellsSensitivity
<<"}\n";
// displaying IPL magno setup
outmessage<<"Current Retina instance setup :"
<<"\nIPLmagno"<<"{"
<< "\n==> normaliseOutput : " << _retinaParameters.IplMagno.normaliseOutput
<< "\n==> parasolCells_beta : " << _retinaParameters.IplMagno.parasolCells_beta
<< "\n==> parasolCells_tau : " << _retinaParameters.IplMagno.parasolCells_tau
<< "\n==> parasolCells_k : " << _retinaParameters.IplMagno.parasolCells_k
<< "\n==> amacrinCellsTemporalCutFrequency : " << _retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency
<< "\n==> V0CompressionParameter : " << _retinaParameters.IplMagno.V0CompressionParameter
<< "\n==> localAdaptintegration_tau : " << _retinaParameters.IplMagno.localAdaptintegration_tau
<< "\n==> localAdaptintegration_k : " << _retinaParameters.IplMagno.localAdaptintegration_k
<<"}";
return outmessage.str();
}
void Retina::write( std::string fs ) const
{
FileStorage parametersSaveFile(fs, cv::FileStorage::WRITE );
write(parametersSaveFile);
}
void Retina::write( FileStorage& fs ) const
{
if (!fs.isOpened())
return; // basic error case
fs<<"OPLandIPLparvo"<<"{";
fs << "colorMode" << _retinaParameters.OPLandIplParvo.colorMode;
fs << "normaliseOutput" << _retinaParameters.OPLandIplParvo.normaliseOutput;
fs << "photoreceptorsLocalAdaptationSensitivity" << _retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity;
fs << "photoreceptorsTemporalConstant" << _retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant;
fs << "photoreceptorsSpatialConstant" << _retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant;
fs << "horizontalCellsGain" << _retinaParameters.OPLandIplParvo.horizontalCellsGain;
fs << "hcellsTemporalConstant" << _retinaParameters.OPLandIplParvo.hcellsTemporalConstant;
fs << "hcellsSpatialConstant" << _retinaParameters.OPLandIplParvo.hcellsSpatialConstant;
fs << "ganglionCellsSensitivity" << _retinaParameters.OPLandIplParvo.ganglionCellsSensitivity;
fs << "}";
fs<<"IPLmagno"<<"{";
fs << "normaliseOutput" << _retinaParameters.IplMagno.normaliseOutput;
fs << "parasolCells_beta" << _retinaParameters.IplMagno.parasolCells_beta;
fs << "parasolCells_tau" << _retinaParameters.IplMagno.parasolCells_tau;
fs << "parasolCells_k" << _retinaParameters.IplMagno.parasolCells_k;
fs << "amacrinCellsTemporalCutFrequency" << _retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency;
fs << "V0CompressionParameter" << _retinaParameters.IplMagno.V0CompressionParameter;
fs << "localAdaptintegration_tau" << _retinaParameters.IplMagno.localAdaptintegration_tau;
fs << "localAdaptintegration_k" << _retinaParameters.IplMagno.localAdaptintegration_k;
fs<<"}";
}
void Retina::setupOPLandIPLParvoChannel(const bool colorMode, const bool normaliseOutput, const float photoreceptorsLocalAdaptationSensitivity, const float photoreceptorsTemporalConstant, const float photoreceptorsSpatialConstant, const float horizontalCellsGain, const float HcellsTemporalConstant, const float HcellsSpatialConstant, const float ganglionCellsSensitivity)
{
// retina core parameters setup
_retinaFilter->setColorMode(colorMode);
_retinaFilter->setPhotoreceptorsLocalAdaptationSensitivity(photoreceptorsLocalAdaptationSensitivity);
_retinaFilter->setOPLandParvoParameters(0, photoreceptorsTemporalConstant, photoreceptorsSpatialConstant, horizontalCellsGain, HcellsTemporalConstant, HcellsSpatialConstant, ganglionCellsSensitivity);
_retinaFilter->setParvoGanglionCellsLocalAdaptationSensitivity(ganglionCellsSensitivity);
_retinaFilter->activateNormalizeParvoOutput_0_maxOutputValue(normaliseOutput);
// update parameters struture
_retinaParameters.OPLandIplParvo.colorMode = colorMode;
_retinaParameters.OPLandIplParvo.normaliseOutput = normaliseOutput;
_retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity = photoreceptorsLocalAdaptationSensitivity;
_retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant = photoreceptorsTemporalConstant;
_retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant = photoreceptorsSpatialConstant;
_retinaParameters.OPLandIplParvo.horizontalCellsGain = horizontalCellsGain;
_retinaParameters.OPLandIplParvo.hcellsTemporalConstant = HcellsTemporalConstant;
_retinaParameters.OPLandIplParvo.hcellsSpatialConstant = HcellsSpatialConstant;
_retinaParameters.OPLandIplParvo.ganglionCellsSensitivity = ganglionCellsSensitivity;
}
void Retina::setupIPLMagnoChannel(const bool normaliseOutput, 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)
{
_retinaFilter->setMagnoCoefficientsTable(parasolCells_beta, parasolCells_tau, parasolCells_k, amacrinCellsTemporalCutFrequency, V0CompressionParameter, localAdaptintegration_tau, localAdaptintegration_k);
_retinaFilter->activateNormalizeMagnoOutput_0_maxOutputValue(normaliseOutput);
// update parameters struture
_retinaParameters.IplMagno.normaliseOutput = normaliseOutput;
_retinaParameters.IplMagno.parasolCells_beta = parasolCells_beta;
_retinaParameters.IplMagno.parasolCells_tau = parasolCells_tau;
_retinaParameters.IplMagno.parasolCells_k = parasolCells_k;
_retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency = amacrinCellsTemporalCutFrequency;
_retinaParameters.IplMagno.V0CompressionParameter = V0CompressionParameter;
_retinaParameters.IplMagno.localAdaptintegration_tau = localAdaptintegration_tau;
_retinaParameters.IplMagno.localAdaptintegration_k = localAdaptintegration_k;
}
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void Retina::run(const cv::Mat &inputMatToConvert)
{
// first convert input image to the compatible format : std::valarray<float>
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const bool colorMode = _convertCvMat2ValarrayBuffer(inputMatToConvert, _inputBuffer);
// process the retina
if (!_retinaFilter->runFilter(_inputBuffer, colorMode, false, _retinaParameters.OPLandIplParvo.colorMode && colorMode, false))
throw cv::Exception(-1, "Retina cannot be applied, wrong input buffer size", "Retina::run", "Retina.h", 0);
}
void Retina::getParvo(cv::Mat &retinaOutput_parvo)
{
if (_retinaFilter->getColorMode())
{
// reallocate output buffer (if necessary)
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_convertValarrayBuffer2cvMat(_retinaFilter->getColorOutput(), _retinaFilter->getOutputNBrows(), _retinaFilter->getOutputNBcolumns(), true, retinaOutput_parvo);
}else
{
// reallocate output buffer (if necessary)
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_convertValarrayBuffer2cvMat(_retinaFilter->getContours(), _retinaFilter->getOutputNBrows(), _retinaFilter->getOutputNBcolumns(), false, retinaOutput_parvo);
}
//retinaOutput_parvo/=255.0;
}
void Retina::getMagno(cv::Mat &retinaOutput_magno)
{
// reallocate output buffer (if necessary)
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_convertValarrayBuffer2cvMat(_retinaFilter->getMovingContours(), _retinaFilter->getOutputNBrows(), _retinaFilter->getOutputNBcolumns(), false, retinaOutput_magno);
//retinaOutput_magno/=255.0;
}
// original API level data accessors : copy buffers if size matches
void Retina::getMagno(std::valarray<float> &magnoOutputBufferCopy){if (magnoOutputBufferCopy.size()==_retinaFilter->getMovingContours().size()) magnoOutputBufferCopy = _retinaFilter->getMovingContours();}
void Retina::getParvo(std::valarray<float> &parvoOutputBufferCopy){if (parvoOutputBufferCopy.size()==_retinaFilter->getContours().size()) parvoOutputBufferCopy = _retinaFilter->getContours();}
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// private method called by constructirs
void Retina::_init(const cv::Size inputSize, const bool colorMode, RETINA_COLORSAMPLINGMETHOD colorSamplingMethod, const bool useRetinaLogSampling, const double reductionFactor, const double samplingStrenght)
{
// basic error check
if (inputSize.height*inputSize.width <= 0)
throw cv::Exception(-1, "Bad retina size setup : size height and with must be superior to zero", "Retina::setup", "Retina.h", 0);
unsigned int nbPixels=inputSize.height*inputSize.width;
// resize buffers if size does not match
_inputBuffer.resize(nbPixels*3); // buffer supports gray images but also 3 channels color buffers... (larger is better...)
// allocate the retina model
if (_retinaFilter)
delete _retinaFilter;
_retinaFilter = new RetinaFilter(inputSize.height, inputSize.width, colorMode, colorSamplingMethod, useRetinaLogSampling, reductionFactor, samplingStrenght);
// prepare the default parameter XML file with default setup
setup(_retinaParameters);
// init retina
_retinaFilter->clearAllBuffers();
// report current configuration
std::cout<<printSetup()<<std::endl;
}
void Retina::_convertValarrayBuffer2cvMat(const std::valarray<float> &grayMatrixToConvert, const unsigned int nbRows, const unsigned int nbColumns, const bool colorMode, cv::Mat &outBuffer)
{
// fill output buffer with the valarray buffer
const float *valarrayPTR=get_data(grayMatrixToConvert);
if (!colorMode)
{
outBuffer.create(cv::Size(nbColumns, nbRows), CV_8U);
for (unsigned int i=0;i<nbRows;++i)
{
for (unsigned int j=0;j<nbColumns;++j)
{
cv::Point2d pixel(j,i);
outBuffer.at<unsigned char>(pixel)=(unsigned char)*(valarrayPTR++);
}
}
}else
{
const unsigned int doubleNBpixels=_retinaFilter->getOutputNBpixels()*2;
outBuffer.create(cv::Size(nbColumns, nbRows), CV_8UC3);
for (unsigned int i=0;i<nbRows;++i)
{
for (unsigned int j=0;j<nbColumns;++j,++valarrayPTR)
{
cv::Point2d pixel(j,i);
cv::Vec3b pixelValues;
pixelValues[2]=(unsigned char)*(valarrayPTR);
pixelValues[1]=(unsigned char)*(valarrayPTR+_retinaFilter->getOutputNBpixels());
pixelValues[0]=(unsigned char)*(valarrayPTR+doubleNBpixels);
outBuffer.at<cv::Vec3b>(pixel)=pixelValues;
}
}
}
}
const bool Retina::_convertCvMat2ValarrayBuffer(const cv::Mat inputMatToConvert, std::valarray<float> &outputValarrayMatrix)
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{
// first check input consistency
if (inputMatToConvert.empty())
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throw cv::Exception(-1, "Retina cannot be applied, input buffer is empty", "Retina::run", "Retina.h", 0);
// retreive color mode from image input
int imageNumberOfChannels = inputMatToConvert.channels();
// convert to float AND fill the valarray buffer
typedef float T; // define here the target pixel format, here, float
const int dsttype = DataType<T>::depth; // output buffer is float format
if(imageNumberOfChannels==4)
{
// create a cv::Mat table (for RGBA planes)
cv::Mat planes[] =
{
cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[_retinaFilter->getInputNBpixels()*2]),
cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[_retinaFilter->getInputNBpixels()]),
cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[0]),
cv::Mat(inputMatToConvert.size(), dsttype) // last channel (alpha) does not point on the valarray (not usefull in our case)
};
// split color cv::Mat in 4 planes... it fills valarray directely
cv::split(cv::Mat_<Vec<T, 4> >(inputMatToConvert), planes);
}else if (imageNumberOfChannels==3)
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{
// create a cv::Mat table (for RGB planes)
cv::Mat planes[] =
{
cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[_retinaFilter->getInputNBpixels()*2]),
cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[_retinaFilter->getInputNBpixels()]),
cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[0])
};
// split color cv::Mat in 3 planes... it fills valarray directely
cv::split(cv::Mat_<Vec<T, 3> >(inputMatToConvert), planes);
}else if(imageNumberOfChannels==1)
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{
// create a cv::Mat header for the valarray
cv::Mat dst(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[0]);
inputMatToConvert.convertTo(dst, dsttype);
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}
else
CV_Error(CV_StsUnsupportedFormat, "input image must be single channel (gray levels), bgr format (color) or bgra (color with transparency which won't be considered");
return imageNumberOfChannels>1; // return bool : false for gray level image processing, true for color mode
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}
void Retina::clearBuffers() {_retinaFilter->clearAllBuffers();}
void Retina::activateMovingContoursProcessing(const bool activate){_retinaFilter->activateMovingContoursProcessing(activate);}
void Retina::activateContoursProcessing(const bool activate){_retinaFilter->activateContoursProcessing(activate);}
} // end of namespace cv