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438 lines
22 KiB
C++
438 lines
22 KiB
C++
/*#******************************************************************************
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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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** 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.
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** 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.
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**
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** Maintainers : Listic lab (code author current affiliation & applications) and Gipsa Lab (original research origins & applications)
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**
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** Creation - enhancement process 2007-2011
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** Author: Alexandre Benoit (benoit.alexandre.vision@gmail.com), LISTIC lab, Annecy le vieux, France
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**
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** 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).
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** Refer to the following research paper for more information:
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** 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
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** 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:
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** 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.
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**
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** The retina filter includes the research contributions of phd/research collegues from which code has been redrawn by the author :
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** _take a look at the retinacolor.hpp module to discover Brice Chaix de Lavarene color mosaicing/demosaicing and the reference paper:
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** ====> B. Chaix de Lavarene, D. Alleysson, B. Durette, J. Herault (2007). "Efficient demosaicing through recursive filtering", IEEE International Conference on Image Processing ICIP 2007
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** _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.
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** ====> more informations in the above cited Jeanny Heraults's book.
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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) 2008-2011, Willow Garage Inc., all rights reserved.
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**
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** For Human Visual System tools (hvstools)
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** Copyright (C) 2007-2011, LISTIC Lab, Annecy le Vieux and GIPSA Lab, Grenoble, France, all rights reserved.
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**
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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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** * Redistributions 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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** * Redistributions 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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/*
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* Retina.cpp
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*
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* Created on: Jul 19, 2011
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* Author: Alexandre Benoit
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*/
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#include "precomp.hpp"
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#include "retinafilter.hpp"
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#include <iostream>
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namespace cv
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{
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Retina::Retina(const std::string parametersSaveFile, const cv::Size inputSize)
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{
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_retinaFilter = 0;
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_init(parametersSaveFile, inputSize, true, RETINA_COLOR_BAYER, false);
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}
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Retina::Retina(const std::string parametersSaveFile, const cv::Size inputSize, const bool colorMode, RETINA_COLORSAMPLINGMETHOD colorSamplingMethod, const bool useRetinaLogSampling, const double reductionFactor, const double samplingStrenght)
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{
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_retinaFilter = 0;
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_init(parametersSaveFile, inputSize, colorMode, colorSamplingMethod, useRetinaLogSampling, reductionFactor, samplingStrenght);
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};
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Retina::~Retina()
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{
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if (_retinaFilter)
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delete _retinaFilter;
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}
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void Retina::setColorSaturation(const bool saturateColors, const float colorSaturationValue)
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{
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_retinaFilter->setColorSaturation(saturateColors, colorSaturationValue);
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}
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void Retina::setup(std::string retinaParameterFile, const bool applyDefaultSetupOnFailure)
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{
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// open specified parameters file
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std::cout<<"Retina::setup: setting up retina from parameter file : "<<retinaParameterFile<<std::endl;
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// very UGLY cases processing... to be updated...
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try
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{
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// rewriting a new parameter file...
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if (_parametersSaveFile.isOpened())
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_parametersSaveFile.release();
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_parametersSaveFile.open(_parametersSaveFileName, cv::FileStorage::WRITE);
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// opening retinaParameterFile in read mode
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cv::FileStorage fs(retinaParameterFile, cv::FileStorage::READ);
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// read parameters file if it exists or apply default setup if asked for
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if (!fs.isOpened())
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{
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std::cout<<"Retina::setup: provided parameters file could not be open... skeeping configuration"<<std::endl;
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return;
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// implicit else case : retinaParameterFile could be open (it exists at least)
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}
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// preparing parameter setup
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bool colorMode, normaliseOutput;
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float photoreceptorsLocalAdaptationSensitivity, photoreceptorsTemporalConstant, photoreceptorsSpatialConstant, horizontalCellsGain, hcellsTemporalConstant, hcellsSpatialConstant, ganglionCellsSensitivity;
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// OPL and Parvo init first
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cv::FileNode rootFn = fs.root(), currFn=rootFn["OPLandIPLparvo"];
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currFn["colorMode"]>>colorMode;
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currFn["normaliseOutput"]>>normaliseOutput;
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currFn["photoreceptorsLocalAdaptationSensitivity"]>>photoreceptorsLocalAdaptationSensitivity;
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currFn["photoreceptorsTemporalConstant"]>>photoreceptorsTemporalConstant;
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currFn["photoreceptorsSpatialConstant"]>>photoreceptorsSpatialConstant;
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currFn["horizontalCellsGain"]>>horizontalCellsGain;
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currFn["hcellsTemporalConstant"]>>hcellsTemporalConstant;
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currFn["hcellsSpatialConstant"]>>hcellsSpatialConstant;
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currFn["ganglionCellsSensitivity"]>>ganglionCellsSensitivity;
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setupOPLandIPLParvoChannel(colorMode, normaliseOutput, photoreceptorsLocalAdaptationSensitivity, photoreceptorsTemporalConstant, photoreceptorsSpatialConstant, horizontalCellsGain, hcellsTemporalConstant, hcellsSpatialConstant, ganglionCellsSensitivity);
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// init retina IPL magno setup
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currFn=rootFn["IPLmagno"];
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currFn["normaliseOutput"]>>normaliseOutput;
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float parasolCells_beta, parasolCells_tau, parasolCells_k, amacrinCellsTemporalCutFrequency, V0CompressionParameter, localAdaptintegration_tau, localAdaptintegration_k;
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currFn["parasolCells_beta"]>>parasolCells_beta;
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currFn["parasolCells_tau"]>>parasolCells_tau;
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currFn["parasolCells_k"]>>parasolCells_k;
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currFn["amacrinCellsTemporalCutFrequency"]>>amacrinCellsTemporalCutFrequency;
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currFn["V0CompressionParameter"]>>V0CompressionParameter;
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currFn["localAdaptintegration_tau"]>>localAdaptintegration_tau;
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currFn["localAdaptintegration_k"]>>localAdaptintegration_k;
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setupIPLMagnoChannel(normaliseOutput, parasolCells_beta, parasolCells_tau, parasolCells_k, amacrinCellsTemporalCutFrequency,
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V0CompressionParameter, localAdaptintegration_tau, localAdaptintegration_k);
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}catch(Exception &e)
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{
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std::cout<<"Retina::setup: resetting retina with default parameters"<<std::endl;
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if (applyDefaultSetupOnFailure)
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{
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setupOPLandIPLParvoChannel();
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setupIPLMagnoChannel();
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}
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std::cout<<"Retina::setup: wrong/unappropriate xml parameter file : error report :`n=>"<<e.what()<<std::endl;
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std::cout<<"=> keeping current parameters"<<std::endl;
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}
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_parametersSaveFile.release(); // close file after setup
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// report current configuration
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std::cout<<printSetup()<<std::endl;
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}
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const std::string Retina::printSetup()
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{
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std::stringstream outmessage;
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try
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{
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cv::FileStorage parametersReader(_parametersSaveFileName, cv::FileStorage::READ);
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if (!parametersReader.isOpened())
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{
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outmessage<<"Retina is not already settled up";
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}
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else
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{
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// accessing xml parameters nodes
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cv::FileNode rootFn = parametersReader.root();
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cv::FileNode currFn=rootFn["OPLandIPLparvo"];
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// displaying OPL and IPL parvo setup
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outmessage<<"Current Retina instance setup :"
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<<"\nOPLandIPLparvo"<<"{"
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<< "\n==> colorMode : " << currFn["colorMode"].operator int()
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<< "\n==> normalizeParvoOutput :" << currFn["normaliseOutput"].operator int()
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<< "\n==> photoreceptorsLocalAdaptationSensitivity : " << currFn["photoreceptorsLocalAdaptationSensitivity"].operator float()
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<< "\n==> photoreceptorsTemporalConstant : " << currFn["photoreceptorsTemporalConstant"].operator float()
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<< "\n==> photoreceptorsSpatialConstant : " << currFn["photoreceptorsSpatialConstant"].operator float()
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<< "\n==> horizontalCellsGain : " << currFn["horizontalCellsGain"].operator float()
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<< "\n==> hcellsTemporalConstant : " << currFn["hcellsTemporalConstant"].operator float()
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<< "\n==> hcellsSpatialConstant : " << currFn["hcellsSpatialConstant"].operator float()
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<< "\n==> parvoGanglionCellsSensitivity : " << currFn["ganglionCellsSensitivity"].operator float()
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<<"}\n";
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// displaying IPL magno setup
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currFn=rootFn["IPLmagno"];
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outmessage<<"Current Retina instance setup :"
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<<"\nIPLmagno"<<"{"
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<< "\n==> normaliseOutput : " << currFn["normaliseOutput"].operator int()
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<< "\n==> parasolCells_beta : " << currFn["parasolCells_beta"].operator float()
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<< "\n==> parasolCells_tau : " << currFn["parasolCells_tau"].operator float()
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<< "\n==> parasolCells_k : " << currFn["parasolCells_k"].operator float()
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<< "\n==> amacrinCellsTemporalCutFrequency : " << currFn["amacrinCellsTemporalCutFrequency"].operator float()
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<< "\n==> V0CompressionParameter : " << currFn["V0CompressionParameter"].operator float()
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<< "\n==> localAdaptintegration_tau : " << currFn["localAdaptintegration_tau"].operator float()
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<< "\n==> localAdaptintegration_k : " << currFn["localAdaptintegration_k"].operator float()
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<<"}";
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}
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}catch(cv::Exception &e)
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{
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outmessage<<"Error reading parameters configuration file : "<<e.what()<<std::endl;
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}
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return outmessage.str();
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}
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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)
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{
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// parameters setup (default setup)
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_retinaFilter->setColorMode(colorMode);
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_retinaFilter->setPhotoreceptorsLocalAdaptationSensitivity(photoreceptorsLocalAdaptationSensitivity);
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_retinaFilter->setOPLandParvoParameters(0, photoreceptorsTemporalConstant, photoreceptorsSpatialConstant, horizontalCellsGain, HcellsTemporalConstant, HcellsSpatialConstant, ganglionCellsSensitivity);
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_retinaFilter->setParvoGanglionCellsLocalAdaptationSensitivity(ganglionCellsSensitivity);
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_retinaFilter->activateNormalizeParvoOutput_0_maxOutputValue(normaliseOutput);
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// save parameters in the xml parameters tree... if parameters file is already open
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if (!_parametersSaveFile.isOpened())
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return;
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_parametersSaveFile<<"OPLandIPLparvo"<<"{";
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_parametersSaveFile << "colorMode" << colorMode;
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_parametersSaveFile << "normaliseOutput" << normaliseOutput;
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_parametersSaveFile << "photoreceptorsLocalAdaptationSensitivity" << photoreceptorsLocalAdaptationSensitivity;
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_parametersSaveFile << "photoreceptorsTemporalConstant" << photoreceptorsTemporalConstant;
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_parametersSaveFile << "photoreceptorsSpatialConstant" << photoreceptorsSpatialConstant;
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_parametersSaveFile << "horizontalCellsGain" << horizontalCellsGain;
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_parametersSaveFile << "hcellsTemporalConstant" << HcellsTemporalConstant;
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_parametersSaveFile << "hcellsSpatialConstant" << HcellsSpatialConstant;
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_parametersSaveFile << "ganglionCellsSensitivity" << ganglionCellsSensitivity;
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_parametersSaveFile << "}";
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}
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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)
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{
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_retinaFilter->setMagnoCoefficientsTable(parasolCells_beta, parasolCells_tau, parasolCells_k, amacrinCellsTemporalCutFrequency, V0CompressionParameter, localAdaptintegration_tau, localAdaptintegration_k);
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_retinaFilter->activateNormalizeMagnoOutput_0_maxOutputValue(normaliseOutput);
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// save parameters in the xml parameters tree... if parameters file is already open
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if (!_parametersSaveFile.isOpened())
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return;
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_parametersSaveFile<<"IPLmagno"<<"{";
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_parametersSaveFile << "normaliseOutput" << normaliseOutput;
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_parametersSaveFile << "parasolCells_beta" << parasolCells_beta;
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_parametersSaveFile << "parasolCells_tau" << parasolCells_tau;
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_parametersSaveFile << "parasolCells_k" << parasolCells_k;
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_parametersSaveFile << "amacrinCellsTemporalCutFrequency" << amacrinCellsTemporalCutFrequency;
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_parametersSaveFile << "V0CompressionParameter" << V0CompressionParameter;
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_parametersSaveFile << "localAdaptintegration_tau" << localAdaptintegration_tau;
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_parametersSaveFile << "localAdaptintegration_k" << localAdaptintegration_k;
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_parametersSaveFile<<"}";
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}
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void Retina::run(const cv::Mat &inputMatToConvert)
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{
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// first convert input image to the compatible format : std::valarray<float>
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const bool colorMode = _convertCvMat2ValarrayBuffer(inputMatToConvert, _inputBuffer);
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// process the retina
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if (!_retinaFilter->runFilter(_inputBuffer, colorMode, false, colorMode, false))
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throw cv::Exception(-1, "Retina cannot be applied, wrong input buffer size", "Retina::run", "Retina.h", 0);
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}
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void Retina::getParvo(cv::Mat &retinaOutput_parvo)
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{
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if (_retinaFilter->getColorMode())
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{
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// reallocate output buffer (if necessary)
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_convertValarrayBuffer2cvMat(_retinaFilter->getColorOutput(), _retinaFilter->getOutputNBrows(), _retinaFilter->getOutputNBcolumns(), true, retinaOutput_parvo);
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}else
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{
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// reallocate output buffer (if necessary)
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_convertValarrayBuffer2cvMat(_retinaFilter->getContours(), _retinaFilter->getOutputNBrows(), _retinaFilter->getOutputNBcolumns(), false, retinaOutput_parvo);
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}
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//retinaOutput_parvo/=255.0;
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}
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void Retina::getMagno(cv::Mat &retinaOutput_magno)
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{
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// reallocate output buffer (if necessary)
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_convertValarrayBuffer2cvMat(_retinaFilter->getMovingContours(), _retinaFilter->getOutputNBrows(), _retinaFilter->getOutputNBcolumns(), false, retinaOutput_magno);
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//retinaOutput_magno/=255.0;
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}
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// original API level data accessors
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void Retina::getMagno(std::valarray<float> &){_retinaFilter->getMovingContours();}
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void Retina::getParvo(std::valarray<float> &){_retinaFilter->getContours();}
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// private method called by constructirs
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void Retina::_init(const std::string parametersSaveFile, const cv::Size inputSize, const bool colorMode, RETINA_COLORSAMPLINGMETHOD colorSamplingMethod, const bool useRetinaLogSampling, const double reductionFactor, const double samplingStrenght)
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{
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_parametersSaveFileName = parametersSaveFile;
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// basic error check
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if (inputSize.height*inputSize.width <= 0)
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throw cv::Exception(-1, "Bad retina size setup : size height and with must be superior to zero", "Retina::setup", "Retina.h", 0);
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unsigned int nbPixels=inputSize.height*inputSize.width;
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// resize buffers if size does not match
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_inputBuffer.resize(nbPixels*3); // buffer supports gray images but also 3 channels color buffers... (larger is better...)
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// allocate the retina model
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if (_retinaFilter)
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delete _retinaFilter;
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_retinaFilter = new RetinaFilter(inputSize.height, inputSize.width, colorMode, colorSamplingMethod, useRetinaLogSampling, reductionFactor, samplingStrenght);
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// prepare the parameter XML tree
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_parametersSaveFile.open(parametersSaveFile, cv::FileStorage::WRITE );
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_parametersSaveFile<<"InputSize"<<"{";
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_parametersSaveFile<<"height"<<inputSize.height;
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_parametersSaveFile<<"width"<<inputSize.width;
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_parametersSaveFile<<"}";
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// clear all retina buffers
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// apply default setup
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setupOPLandIPLParvoChannel();
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setupIPLMagnoChannel();
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// write current parameters to params file
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_parametersSaveFile.release();
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// init retina
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_retinaFilter->clearAllBuffers();
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// report current configuration
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std::cout<<printSetup()<<std::endl;
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}
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void Retina::_convertValarrayBuffer2cvMat(const std::valarray<float> &grayMatrixToConvert, const unsigned int nbRows, const unsigned int nbColumns, const bool colorMode, cv::Mat &outBuffer)
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{
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// fill output buffer with the valarray buffer
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const float *valarrayPTR=get_data(grayMatrixToConvert);
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if (!colorMode)
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{
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outBuffer.create(cv::Size(nbColumns, nbRows), CV_8U);
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for (unsigned int i=0;i<nbRows;++i)
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{
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for (unsigned int j=0;j<nbColumns;++j)
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{
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cv::Point2d pixel(j,i);
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outBuffer.at<unsigned char>(pixel)=(unsigned char)*(valarrayPTR++);
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}
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}
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}else
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{
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const unsigned int doubleNBpixels=_retinaFilter->getOutputNBpixels()*2;
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outBuffer.create(cv::Size(nbColumns, nbRows), CV_8UC3);
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for (unsigned int i=0;i<nbRows;++i)
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{
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for (unsigned int j=0;j<nbColumns;++j,++valarrayPTR)
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{
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cv::Point2d pixel(j,i);
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cv::Vec3b pixelValues;
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pixelValues[2]=(unsigned char)*(valarrayPTR);
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pixelValues[1]=(unsigned char)*(valarrayPTR+_retinaFilter->getOutputNBpixels());
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pixelValues[0]=(unsigned char)*(valarrayPTR+doubleNBpixels);
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outBuffer.at<cv::Vec3b>(pixel)=pixelValues;
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}
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}
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}
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}
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const bool Retina::_convertCvMat2ValarrayBuffer(const cv::Mat inputMatToConvert, std::valarray<float> &outputValarrayMatrix)
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{
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// first check input consistency
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if (inputMatToConvert.empty())
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throw cv::Exception(-1, "Retina cannot be applied, input buffer is empty", "Retina::run", "Retina.h", 0);
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// retreive color mode from image input
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int imageNumberOfChannels = inputMatToConvert.channels();
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// convert to float AND fill the valarray buffer
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typedef float T; // define here the target pixel format, here, float
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const int dsttype = DataType<T>::depth; // output buffer is float format
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if(imageNumberOfChannels==4)
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{
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// create a cv::Mat table (for RGBA planes)
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cv::Mat planes[] =
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{
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cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[_retinaFilter->getInputNBpixels()*2]),
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cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[_retinaFilter->getInputNBpixels()]),
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cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[0]),
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cv::Mat(inputMatToConvert.size(), dsttype) // last channel (alpha) does not point on the valarray (not usefull in our case)
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};
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// split color cv::Mat in 4 planes... it fills valarray directely
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cv::split(cv::Mat_<Vec<T, 4> >(inputMatToConvert), planes);
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}else if (imageNumberOfChannels==3)
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{
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// create a cv::Mat table (for RGB planes)
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cv::Mat planes[] =
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{
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cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[_retinaFilter->getInputNBpixels()*2]),
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cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[_retinaFilter->getInputNBpixels()]),
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cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[0])
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};
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// split color cv::Mat in 3 planes... it fills valarray directely
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cv::split(cv::Mat_<Vec<T, 3> >(inputMatToConvert), planes);
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}else if(imageNumberOfChannels==1)
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{
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// create a cv::Mat header for the valarray
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cv::Mat dst(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[0]);
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inputMatToConvert.convertTo(dst, dsttype);
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}
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else
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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");
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return imageNumberOfChannels>1; // return bool : false for gray level image processing, true for color mode
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}
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void Retina::clearBuffers() {_retinaFilter->clearAllBuffers();}
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void Retina::activateMovingContoursProcessing(const bool activate){_retinaFilter->activateMovingContoursProcessing(activate);}
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void Retina::activateContoursProcessing(const bool activate){_retinaFilter->activateMovingContoursProcessing(activate);}
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} // end of namespace cv
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