Merge pull request #1318 from sovrasov:bioinspired_improvement

modules/bioinspired/include/opencv2/bioinspired/retina.hpp

@@ -422,32 +422,30 @@ public:
     Retina::getParvo methods
      */
     CV_WRAP virtual void activateContoursProcessing(const bool activate)=0;
-};
-
-//! @relates bioinspired::Retina
-//! @{
 
-/** @overload */
-CV_EXPORTS_W Ptr<Retina> createRetina(Size inputSize);
-/** @brief Constructors from standardized interfaces : retreive a smart pointer to a Retina instance
-
-@param inputSize the input frame size
-@param colorMode the chosen processing mode : with or without color processing
-@param colorSamplingMethod specifies which kind of color sampling will be used :
--   cv::bioinspired::RETINA_COLOR_RANDOM: each pixel position is either R, G or B in a random choice
--   cv::bioinspired::RETINA_COLOR_DIAGONAL: color sampling is RGBRGBRGB..., line 2 BRGBRGBRG..., line 3, GBRGBRGBR...
--   cv::bioinspired::RETINA_COLOR_BAYER: standard bayer sampling
-@param useRetinaLogSampling activate retina log sampling, if true, the 2 following parameters can
-be used
-@param reductionFactor only usefull if param useRetinaLogSampling=true, specifies the reduction
-factor of the output frame (as the center (fovea) is high resolution and corners can be
-underscaled, then a reduction of the output is allowed without precision leak
-@param samplingStrenght only usefull if param useRetinaLogSampling=true, specifies the strenght of
-the log scale that is applied
+    /** @overload */
+    CV_WRAP static Ptr<Retina> create(Size inputSize);
+    /** @brief Constructors from standardized interfaces : retreive a smart pointer to a Retina instance
+
+    @param inputSize the input frame size
+    @param colorMode the chosen processing mode : with or without color processing
+    @param colorSamplingMethod specifies which kind of color sampling will be used :
+    -   cv::bioinspired::RETINA_COLOR_RANDOM: each pixel position is either R, G or B in a random choice
+    -   cv::bioinspired::RETINA_COLOR_DIAGONAL: color sampling is RGBRGBRGB..., line 2 BRGBRGBRG..., line 3, GBRGBRGBR...
+    -   cv::bioinspired::RETINA_COLOR_BAYER: standard bayer sampling
+    @param useRetinaLogSampling activate retina log sampling, if true, the 2 following parameters can
+    be used
+    @param reductionFactor only usefull if param useRetinaLogSampling=true, specifies the reduction
+    factor of the output frame (as the center (fovea) is high resolution and corners can be
+    underscaled, then a reduction of the output is allowed without precision leak
+    @param samplingStrenght only usefull if param useRetinaLogSampling=true, specifies the strenght of
+    the log scale that is applied
      */
-CV_EXPORTS_W Ptr<Retina> createRetina(Size inputSize, const bool colorMode, int colorSamplingMethod=RETINA_COLOR_BAYER, const bool useRetinaLogSampling=false, const float reductionFactor=1.0f, const float samplingStrenght=10.0f);
-
-//! @}
+    CV_WRAP static Ptr<Retina> create(Size inputSize, const bool colorMode,
+                                           int colorSamplingMethod=RETINA_COLOR_BAYER,
+                                           const bool useRetinaLogSampling=false,
+                                           const float reductionFactor=1.0f, const float samplingStrenght=10.0f);
+};
 
 //! @}
 

modules/bioinspired/include/opencv2/bioinspired/retinafasttonemapping.hpp

@@ -126,10 +126,10 @@ public:
     (default is 1, see reference paper)
      */
     CV_WRAP virtual void setup(const float photoreceptorsNeighborhoodRadius=3.f, const float ganglioncellsNeighborhoodRadius=1.f, const float meanLuminanceModulatorK=1.f)=0;
+
+    CV_WRAP static Ptr<RetinaFastToneMapping> create(Size inputSize);
 };
 
-//! @relates bioinspired::RetinaFastToneMapping
-CV_EXPORTS_W Ptr<RetinaFastToneMapping> createRetinaFastToneMapping(Size inputSize);
 
 //! @}
 

modules/bioinspired/include/opencv2/bioinspired/transientareassegmentationmodule.hpp

@@ -187,13 +187,12 @@ public:
     /** @brief cleans all the buffers of the instance
     */
     CV_WRAP virtual void clearAllBuffers()=0;
-};
 
-/** @brief allocator
-@param inputSize : size of the images input to segment (output will be the same size)
-@relates bioinspired::TransientAreasSegmentationModule
+    /** @brief allocator
+    @param inputSize : size of the images input to segment (output will be the same size)
      */
-CV_EXPORTS_W Ptr<TransientAreasSegmentationModule> createTransientAreasSegmentationModule(Size inputSize);
+    CV_WRAP static Ptr<TransientAreasSegmentationModule> create(Size inputSize);
+};
 
 //! @}
 

modules/bioinspired/perf/opencl/perf_retina.ocl.cpp

@@ -29,7 +29,7 @@ OCL_PERF_TEST_P(RetinaFixture, Retina,
     UMat ocl_parvo, ocl_magno;
 
     {
-        Ptr<cv::bioinspired::Retina> retina = cv::bioinspired::createRetina(
+        Ptr<cv::bioinspired::Retina> retina = cv::bioinspired::Retina::create(
             input.size(), colorMode, colorSamplingMethod, useLogSampling,
             reductionFactor, samplingStrength);
 

modules/bioinspired/samples/OpenEXRimages_HDR_Retina_toneMapping.cpp

@@ -220,10 +220,10 @@ int main(int argc, char* argv[])
 		 */
 		if (useLogSampling)
 		{
-			retina = cv::bioinspired::createRetina(inputImage.size(),true, cv::bioinspired::RETINA_COLOR_BAYER, true, 2.0, 10.0);
+            retina = cv::bioinspired::Retina::create(inputImage.size(),true, cv::bioinspired::RETINA_COLOR_BAYER, true, 2.0, 10.0);
 		}
 		else// -> else allocate "classical" retina :
-			retina = cv::bioinspired::createRetina(inputImage.size());
+            retina = cv::bioinspired::Retina::create(inputImage.size());
 
 		// create a fast retina tone mapper (Meyla&al algorithm)
 		std::cout<<"Allocating fast tone mapper..."<<std::endl;

modules/bioinspired/samples/basicRetina.cpp

-//============================================================================
-// Name        : retinademo.cpp
-// Author      : Alexandre Benoit, benoit.alexandre.vision@gmail.com
-// Version     : 0.1
-// Copyright   : LISTIC/GIPSA French Labs, May 2015
-// Description : Gipsa/LISTIC Labs quick retina demo in C++, Ansi-style
-//============================================================================
-
-// include bioinspired module and OpenCV core utilities
-#include "opencv2/bioinspired.hpp"
-#include "opencv2/imgcodecs.hpp"
-#include "opencv2/videoio.hpp"
-#include "opencv2/highgui.hpp"
-#include <iostream>
-#include <cstring>
-
-// main function
-int main(int argc, char* argv[]) {
-
-  // basic input arguments checking
-  if (argc>1)
-  {
-        std::cout<<"****************************************************"<<std::endl;
-	std::cout<<"* Retina demonstration : demonstrates the use of is a wrapper class of the Gipsa/Listic Labs retina model."<<std::endl;
-	std::cout<<"* This retina model allows spatio-temporal image processing (applied on a webcam sequences)."<<std::endl;
-	std::cout<<"* As a summary, these are the retina model properties:"<<std::endl;
-	std::cout<<"* => It applies a spectral whithening (mid-frequency details enhancement)"<<std::endl;
-	std::cout<<"* => high frequency spatio-temporal noise reduction"<<std::endl;
-	std::cout<<"* => low frequency luminance to be reduced (luminance range compression)"<<std::endl;
-	std::cout<<"* => local logarithmic luminance compression allows details to be enhanced in low light conditions\n"<<std::endl;
-	std::cout<<"* for more information, reer to the following papers :"<<std::endl;
-	std::cout<<"* 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"<<std::endl;
-	std::cout<<"* 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."<<std::endl;
-	std::cout<<"* => reports comments/remarks at benoit.alexandre.vision@gmail.com"<<std::endl;
-	std::cout<<"* => more informations and papers at : http://sites.google.com/site/benoitalexandrevision/"<<std::endl;
-	std::cout<<"****************************************************"<<std::endl;
-	std::cout<<" NOTE : this program generates the default retina parameters file 'RetinaDefaultParameters.xml'"<<std::endl;
-	std::cout<<" => you can use this to fine tune parameters and load them if you save to file 'RetinaSpecificParameters.xml'"<<std::endl;
-       
-        if (strcmp(argv[1],  "help")==0){
-	    std::cout<<"No help provided for now, please test the retina Demo for a more complete program"<<std::endl;
-        }
-  }
-
-  std::string inputMediaType=argv[1];
-  // declare the retina input buffer.
-  cv::Mat inputFrame;
-  // setup webcam reader and grab a first frame to get its size
-  cv::VideoCapture videoCapture(0); 
-  videoCapture>>inputFrame;
-
-  // allocate a retina instance with input size equal to the one of the loaded image
-  cv::Ptr<cv::bioinspired::Retina> myRetina = cv::bioinspired::createRetina(inputFrame.size());
-
-  /* retina parameters management methods use sample
-     -> save current (here default) retina parameters to a xml file (you may use it only one time to get the file and modify it)
-  */
-  myRetina->write("RetinaDefaultParameters.xml");
-
-  // -> load parameters if file exists
-  myRetina->setup("RetinaSpecificParameters.xml");
-
-  // reset all retina buffers (open your eyes)  
-  myRetina->clearBuffers();
-
-  // declare retina output buffers
-  cv::Mat retinaOutput_parvo;
-  cv::Mat retinaOutput_magno;
-
-  //main processing loop
-  bool stillProcess=true;
-  while(stillProcess){
-	
-	// if using video stream, then, grabbing a new frame, else, input remains the same
-	if (videoCapture.isOpened())
-		videoCapture>>inputFrame;
-        else
-		stillProcess=false;
-	// run retina filter
-	myRetina->run(inputFrame);
-	// Retrieve and display retina output
-	myRetina->getParvo(retinaOutput_parvo);
-	myRetina->getMagno(retinaOutput_magno);
-	cv::imshow("retina input", inputFrame);
-	cv::imshow("Retina Parvo", retinaOutput_parvo);
-	cv::imshow("Retina Magno", retinaOutput_magno);
-
-	cv::waitKey(5);
-  }
-
-}

modules/bioinspired/src/basicretinafilter.hpp

@@ -498,8 +498,8 @@ namespace bioinspired
 #endif
                 for (int IDrow=r.start; IDrow!=r.end; ++IDrow)
                 {
-                    register float* outputPTR=outputFrame+(IDrowEnd-IDrow)*(nbColumns)-1;
-                    register float result=0;
+                    float* outputPTR=outputFrame+(IDrowEnd-IDrow)*(nbColumns)-1;
+                    float result=0;
                     for (unsigned int index=0; index<nbColumns; ++index)
                     {
                         result = *(outputPTR)+  filterParam_a* result;
@@ -523,9 +523,9 @@ namespace bioinspired
             virtual void operator()( const Range& r ) const {
                 for (int IDrow=r.start; IDrow!=r.end; ++IDrow)
                 {
-                    register float* outputPTR=outputFrame+(IDrowStart+IDrow)*nbColumns;
-                    register const float* inputPTR=inputFrame+(IDrowStart+IDrow)*nbColumns;
-                    register float result=0;
+                    float* outputPTR=outputFrame+(IDrowStart+IDrow)*nbColumns;
+                    const float* inputPTR=inputFrame+(IDrowStart+IDrow)*nbColumns;
+                    float result=0;
                     for (unsigned int index=0; index<nbColumns; ++index)
                     {
                         result = *(inputPTR++) + filterParam_tau**(outputPTR)+  filterParam_a* result;
@@ -548,8 +548,8 @@ namespace bioinspired
             virtual void operator()( const Range& r ) const {
                 for (int IDcolumn=r.start; IDcolumn!=r.end; ++IDcolumn)
                 {
-                    register float result=0;
-                    register float *outputPTR=outputFrame+IDcolumn;
+                    float result=0;
+                    float *outputPTR=outputFrame+IDcolumn;
 
                     for (unsigned int index=0; index<nbRows; ++index)
                     {
@@ -576,8 +576,8 @@ namespace bioinspired
                 float* offset=outputFrame+nbColumns*nbRows-nbColumns;
                 for (int IDcolumn=r.start; IDcolumn!=r.end; ++IDcolumn)
                 {
-                    register float result=0;
-                    register float *outputPTR=offset+IDcolumn;
+                    float result=0;
+                    float *outputPTR=offset+IDcolumn;
 
                     for (unsigned int index=0; index<nbRows; ++index)
                     {
@@ -604,7 +604,7 @@ namespace bioinspired
                 const float *localLuminancePTR=localLuminance+r.start;
                 const float *inputFramePTR=inputFrame+r.start;
                 float *outputFramePTR=outputFrame+r.start;
-                for (register int IDpixel=r.start ; IDpixel!=r.end ; ++IDpixel, ++inputFramePTR, ++outputFramePTR)
+                for (int IDpixel=r.start ; IDpixel!=r.end ; ++IDpixel, ++inputFramePTR, ++outputFramePTR)
                 {
                     float X0=*(localLuminancePTR++)*localLuminanceFactor+localLuminanceAddon;
                     // TODO : the following line can lead to a divide by zero ! A small offset is added, take care if the offset is too large in case of High Dynamic Range images which can use very small values...
@@ -630,9 +630,9 @@ namespace bioinspired
 
                 for (int IDrow=r.start; IDrow!=r.end; ++IDrow)
                 {
-                    register float* outputPTR=outputFrame+(IDrowEnd-IDrow)*(nbColumns)-1;
-                    register const float* spatialConstantPTR=spatialConstantBuffer+(IDrowEnd-IDrow)*(nbColumns)-1;
-                    register float result=0;
+                    float* outputPTR=outputFrame+(IDrowEnd-IDrow)*(nbColumns)-1;
+                    const float* spatialConstantPTR=spatialConstantBuffer+(IDrowEnd-IDrow)*(nbColumns)-1;
+                    float result=0;
                     for (unsigned int index=0; index<nbColumns; ++index)
                     {
                         result = *(outputPTR)+  *(spatialConstantPTR--)* result;
@@ -655,9 +655,9 @@ namespace bioinspired
             virtual void operator()( const Range& r ) const {
                 for (int IDcolumn=r.start; IDcolumn!=r.end; ++IDcolumn)
                 {
-                    register float result=0;
-                    register float *outputPTR=outputFrame+IDcolumn;
-                    register const float* spatialConstantPTR=spatialConstantBuffer+IDcolumn;
+                    float result=0;
+                    float *outputPTR=outputFrame+IDcolumn;
+                    const float* spatialConstantPTR=spatialConstantBuffer+IDcolumn;
                     for (unsigned int index=0; index<nbRows; ++index)
                     {
                         result = *(outputPTR) +  *(spatialConstantPTR) * result;

modules/bioinspired/src/imagelogpolprojection.cpp

@@ -410,7 +410,7 @@ std::valarray<float> &ImageLogPolProjection::runProjection(const std::valarray<f
         _spatiotemporalLPfilter_Irregular(&_irregularLPfilteredFrame[0], &_tempBuffer[0]+_filterOutput.getNBpixels()*2);
 
         // applying image projection/resampling
-        register unsigned int *transformTablePTR=&_transformTable[0];
+        unsigned int *transformTablePTR=&_transformTable[0];
         for (unsigned int i=0 ; i<_usefullpixelIndex ; i+=2, transformTablePTR+=2)
         {
 #ifdef IMAGELOGPOLPROJECTION_DEBUG
@@ -430,7 +430,7 @@ std::valarray<float> &ImageLogPolProjection::runProjection(const std::valarray<f
         _spatiotemporalLPfilter_Irregular(get_data(inputFrame), &_irregularLPfilteredFrame[0]);
         _spatiotemporalLPfilter_Irregular(&_irregularLPfilteredFrame[0], &_irregularLPfilteredFrame[0]);
         // applying image projection/resampling
-        register unsigned int *transformTablePTR=&_transformTable[0];
+        unsigned int *transformTablePTR=&_transformTable[0];
         for (unsigned int i=0 ; i<_usefullpixelIndex ; i+=2, transformTablePTR+=2)
         {
 #ifdef IMAGELOGPOLPROJECTION_DEBUG

modules/bioinspired/src/magnoretinafilter.cpp

@@ -158,12 +158,12 @@ void MagnoRetinaFilter::_amacrineCellsComputing(const float *OPL_ON, const float
 #ifdef MAKE_PARALLEL
         cv::parallel_for_(cv::Range(0,_filterOutput.getNBpixels()), Parallel_amacrineCellsComputing(OPL_ON, OPL_OFF, &_previousInput_ON[0], &_previousInput_OFF[0], &_amacrinCellsTempOutput_ON[0], &_amacrinCellsTempOutput_OFF[0], _temporalCoefficient));
 #else
-    register const float *OPL_ON_PTR=OPL_ON;
-    register const float *OPL_OFF_PTR=OPL_OFF;
-    register float *previousInput_ON_PTR= &_previousInput_ON[0];
-    register float *previousInput_OFF_PTR= &_previousInput_OFF[0];
-    register float *amacrinCellsTempOutput_ON_PTR= &_amacrinCellsTempOutput_ON[0];
-    register float *amacrinCellsTempOutput_OFF_PTR= &_amacrinCellsTempOutput_OFF[0];
+    const float *OPL_ON_PTR=OPL_ON;
+    const float *OPL_OFF_PTR=OPL_OFF;
+    float *previousInput_ON_PTR= &_previousInput_ON[0];
+    float *previousInput_OFF_PTR= &_previousInput_OFF[0];
+    float *amacrinCellsTempOutput_ON_PTR= &_amacrinCellsTempOutput_ON[0];
+    float *amacrinCellsTempOutput_OFF_PTR= &_amacrinCellsTempOutput_OFF[0];
 
     for (unsigned int IDpixel=0 ; IDpixel<this->getNBpixels(); ++IDpixel)
     {
@@ -200,10 +200,10 @@ const std::valarray<float> &MagnoRetinaFilter::runFilter(const std::valarray<flo
     _localLuminanceAdaptation(&_magnoXOutputOFF[0], &_localProcessBufferOFF[0]);
 
     /* Compute MagnoY */
-    register float *magnoYOutput= &(*_magnoYOutput)[0];
-    register float *magnoXOutputON_PTR= &_magnoXOutputON[0];
-    register float *magnoXOutputOFF_PTR= &_magnoXOutputOFF[0];
-    for (register unsigned int IDpixel=0 ; IDpixel<_filterOutput.getNBpixels() ; ++IDpixel)
+    float *magnoYOutput= &(*_magnoYOutput)[0];
+    float *magnoXOutputON_PTR= &_magnoXOutputON[0];
+    float *magnoXOutputOFF_PTR= &_magnoXOutputOFF[0];
+    for (unsigned int IDpixel=0 ; IDpixel<_filterOutput.getNBpixels() ; ++IDpixel)
         *(magnoYOutput++)=*(magnoXOutputON_PTR++)+*(magnoXOutputOFF_PTR++);
 
     return (*_magnoYOutput);

modules/bioinspired/src/magnoretinafilter.hpp

@@ -212,12 +212,12 @@ namespace bioinspired
                 :OPL_ON(OPL_ON_PTR), OPL_OFF(OPL_OFF_PTR), previousInput_ON(previousInput_ON_PTR), previousInput_OFF(previousInput_OFF_PTR), amacrinCellsTempOutput_ON(amacrinCellsTempOutput_ON_PTR), amacrinCellsTempOutput_OFF(amacrinCellsTempOutput_OFF_PTR), temporalCoefficient(temporalCoefficientVal) {}
 
             virtual void operator()( const Range& r ) const {
-                register const float *OPL_ON_PTR=OPL_ON+r.start;
-                register const float *OPL_OFF_PTR=OPL_OFF+r.start;
-                register float *previousInput_ON_PTR= previousInput_ON+r.start;
-                register float *previousInput_OFF_PTR= previousInput_OFF+r.start;
-                register float *amacrinCellsTempOutput_ON_PTR= amacrinCellsTempOutput_ON+r.start;
-                register float *amacrinCellsTempOutput_OFF_PTR= amacrinCellsTempOutput_OFF+r.start;
+                const float *OPL_ON_PTR=OPL_ON+r.start;
+                const float *OPL_OFF_PTR=OPL_OFF+r.start;
+                float *previousInput_ON_PTR= previousInput_ON+r.start;
+                float *previousInput_OFF_PTR= previousInput_OFF+r.start;
+                float *amacrinCellsTempOutput_ON_PTR= amacrinCellsTempOutput_ON+r.start;
+                float *amacrinCellsTempOutput_OFF_PTR= amacrinCellsTempOutput_OFF+r.start;
 
                 for (int IDpixel=r.start ; IDpixel!=r.end; ++IDpixel)
                 {

modules/bioinspired/src/parvoretinafilter.cpp

@@ -191,11 +191,11 @@ const std::valarray<float> &ParvoRetinaFilter::runFilter(const std::valarray<flo
         //
         //// loop that makes the difference between photoreceptor cells output and horizontal cells
         //// positive part goes on the ON way, negative pat goes on the OFF way
-        register float *parvocellularOutputONminusOFF_PTR=&(*_parvocellularOutputONminusOFF)[0];
-        register float *parvocellularOutputON_PTR=&_parvocellularOutputON[0];
-        register float *parvocellularOutputOFF_PTR=&_parvocellularOutputOFF[0];
+        float *parvocellularOutputONminusOFF_PTR=&(*_parvocellularOutputONminusOFF)[0];
+        float *parvocellularOutputON_PTR=&_parvocellularOutputON[0];
+        float *parvocellularOutputOFF_PTR=&_parvocellularOutputOFF[0];
 
-        for (register unsigned int IDpixel=0 ; IDpixel<_filterOutput.getNBpixels() ; ++IDpixel)
+        for (unsigned int IDpixel=0 ; IDpixel<_filterOutput.getNBpixels() ; ++IDpixel)
             *(parvocellularOutputONminusOFF_PTR++)= (*(parvocellularOutputON_PTR++)-*(parvocellularOutputOFF_PTR++));
     }
     return (*_parvocellularOutputONminusOFF);
@@ -217,7 +217,7 @@ void ParvoRetinaFilter::_OPL_OnOffWaysComputing() // WARNING : this method requi
     float *parvocellularOutputOFF_PTR= &_parvocellularOutputOFF[0];
     // compute bipolar cells response equal to photoreceptors minus horizontal cells response
     // and copy the result on parvo cellular outputs... keeping time before their local contrast adaptation for final result
-    for (register unsigned int IDpixel=0 ; IDpixel<_filterOutput.getNBpixels() ; ++IDpixel)
+    for (unsigned int IDpixel=0 ; IDpixel<_filterOutput.getNBpixels() ; ++IDpixel)
     {
         float pixelDifference = *(photoreceptorsOutput_PTR++) -*(horizontalCellsOutput_PTR++);
         // test condition to allow write pixelDifference in ON or OFF buffer and 0 in the over

modules/bioinspired/src/retina.cpp

@@ -293,6 +293,7 @@ private:
     bool _convertCvMat2ValarrayBuffer(InputArray inputMatToConvert, std::valarray<float> &outputValarrayMatrix);
 
 
+    bool _wasOCLRunCalled;
 #ifdef HAVE_OPENCL
     ocl::RetinaOCLImpl* _ocl_retina;
 
@@ -305,12 +306,12 @@ private:
 };
 
 // smart pointers allocation :
-Ptr<Retina> createRetina(Size inputSize)
+Ptr<Retina> Retina::create(Size inputSize)
 {
     return makePtr<RetinaImpl>(inputSize);
 }
 
-Ptr<Retina> createRetina(Size inputSize, const bool colorMode, int colorSamplingMethod, const bool useRetinaLogSampling, const float reductionFactor, const float samplingStrenght)
+Ptr<Retina> Retina::create(Size inputSize, const bool colorMode, int colorSamplingMethod, const bool useRetinaLogSampling, const float reductionFactor, const float samplingStrenght)
 {
     return makePtr<RetinaImpl>(inputSize, colorMode, colorSamplingMethod, useRetinaLogSampling, reductionFactor, samplingStrenght);
 }
@@ -334,7 +335,7 @@ RetinaImpl::RetinaImpl(const cv::Size inputSz, const bool colorMode, int colorSa
     _init(inputSz, colorMode, colorSamplingMethod, useRetinaLogSampling, reductionFactor, samplingStrenght);
 #ifdef HAVE_OPENCL
     _ocl_retina = 0;
-    if (inputSz.width % 4 == 0)
+    if (inputSz.width % 4 == 0 && !useRetinaLogSampling)
         _ocl_retina = new ocl::RetinaOCLImpl(inputSz, colorMode, colorSamplingMethod,
                                              useRetinaLogSampling, reductionFactor, samplingStrenght);
 #endif
@@ -564,6 +565,7 @@ void RetinaImpl::setupIPLMagnoChannel(const bool normaliseOutput, const float pa
 bool RetinaImpl::ocl_run(InputArray inputMatToConvert)
 {
     _ocl_retina->run(inputMatToConvert);
+    _wasOCLRunCalled = true;
     return true;
 }
 #endif
@@ -572,6 +574,7 @@ void RetinaImpl::run(InputArray inputMatToConvert)
 {
     CV_OCL_RUN((_ocl_retina != 0), ocl_run(inputMatToConvert));
 
+    _wasOCLRunCalled = false;
     // first convert input image to the compatible format : std::valarray<float>
     const bool colorMode = _convertCvMat2ValarrayBuffer(inputMatToConvert.getMat(), _inputBuffer);
     // process the retina
@@ -603,6 +606,7 @@ void RetinaImpl::applyFastToneMapping(InputArray inputImage, OutputArray outputT
 #ifdef HAVE_OPENCL
 bool RetinaImpl::ocl_getParvo(OutputArray retinaOutput_parvo)
 {
+    CV_Assert(_wasOCLRunCalled);
     _ocl_retina->getParvo(retinaOutput_parvo);
     return true;
 }
@@ -611,6 +615,7 @@ bool RetinaImpl::ocl_getParvo(OutputArray retinaOutput_parvo)
 void RetinaImpl::getParvo(OutputArray retinaOutput_parvo)
 {
     CV_OCL_RUN((_ocl_retina != 0) && retinaOutput_parvo.isUMat(), ocl_getParvo(retinaOutput_parvo));
+    CV_Assert(!_wasOCLRunCalled);
 
     if (_retinaFilter->getColorMode())
     {
@@ -627,6 +632,7 @@ void RetinaImpl::getParvo(OutputArray retinaOutput_parvo)
 #ifdef HAVE_OPENCL
 bool RetinaImpl::ocl_getMagno(OutputArray retinaOutput_magno)
 {
+    CV_Assert(_wasOCLRunCalled);
     _ocl_retina->getMagno(retinaOutput_magno);
     return true;
 }
@@ -635,6 +641,7 @@ bool RetinaImpl::ocl_getMagno(OutputArray retinaOutput_magno)
 void RetinaImpl::getMagno(OutputArray retinaOutput_magno)
 {
     CV_OCL_RUN((_ocl_retina != 0) && retinaOutput_magno.isUMat(), ocl_getMagno(retinaOutput_magno));
+    CV_Assert(!_wasOCLRunCalled);
 
     // reallocate output buffer (if necessary)
     _convertValarrayBuffer2cvMat(_retinaFilter->getMovingContours(), _retinaFilter->getOutputNBrows(), _retinaFilter->getOutputNBcolumns(), false, retinaOutput_magno);
@@ -644,6 +651,7 @@ void RetinaImpl::getMagno(OutputArray retinaOutput_magno)
 #ifdef HAVE_OPENCL
 bool RetinaImpl::ocl_getMagnoRAW(OutputArray magnoOutputBufferCopy)
 {
+    CV_Assert(_wasOCLRunCalled);
     _ocl_retina->getMagnoRAW(magnoOutputBufferCopy);
     return true;
 }
@@ -653,7 +661,7 @@ bool RetinaImpl::ocl_getMagnoRAW(OutputArray magnoOutputBufferCopy)
 void RetinaImpl::getMagnoRAW(OutputArray magnoOutputBufferCopy){
 
     CV_OCL_RUN((_ocl_retina != 0) && magnoOutputBufferCopy.isUMat(), ocl_getMagnoRAW(magnoOutputBufferCopy));
-
+    CV_Assert(!_wasOCLRunCalled);
     // get magno channel header
     const cv::Mat magnoChannel=cv::Mat(getMagnoRAW());
     // copy data
@@ -663,6 +671,7 @@ void RetinaImpl::getMagnoRAW(OutputArray magnoOutputBufferCopy){
 #ifdef HAVE_OPENCL
 bool RetinaImpl::ocl_getParvoRAW(OutputArray parvoOutputBufferCopy)
 {
+    CV_Assert(_wasOCLRunCalled);
     _ocl_retina->getParvoRAW(parvoOutputBufferCopy);
     return true;
 }
@@ -671,7 +680,7 @@ bool RetinaImpl::ocl_getParvoRAW(OutputArray parvoOutputBufferCopy)
 void RetinaImpl::getParvoRAW(OutputArray parvoOutputBufferCopy){
 
     CV_OCL_RUN((_ocl_retina != 0) && parvoOutputBufferCopy.isUMat(), ocl_getParvoRAW(parvoOutputBufferCopy));
-
+    CV_Assert(!_wasOCLRunCalled);
     // get parvo channel header
     const cv::Mat parvoChannel=cv::Mat(getParvoRAW());
     // copy data
@@ -680,12 +689,14 @@ void RetinaImpl::getParvoRAW(OutputArray parvoOutputBufferCopy){
 
 // original API level data accessors : get buffers addresses...
 const Mat RetinaImpl::getMagnoRAW() const {
+    CV_Assert(!_wasOCLRunCalled);
     // create a cv::Mat header for the valarray
     return Mat((int)_retinaFilter->getMovingContours().size(),1, CV_32F, (void*)get_data(_retinaFilter->getMovingContours()));
 
 }
 
 const Mat RetinaImpl::getParvoRAW() const {
+    CV_Assert(!_wasOCLRunCalled);
     if (_retinaFilter->getColorMode()) // check if color mode is enabled
     {
         // create a cv::Mat table (for RGB planes as a single vector)
@@ -699,6 +710,7 @@ const Mat RetinaImpl::getParvoRAW() const {
 // private method called by constructors
 void RetinaImpl::_init(const cv::Size inputSz, const bool colorMode, int colorSamplingMethod, const bool useRetinaLogSampling, const float reductionFactor, const float samplingStrenght)
 {
+    _wasOCLRunCalled = false;
     // basic error check
     if (inputSz.height*inputSz.width <= 0)
         throw cv::Exception(-1, "Bad retina size setup : size height and with must be superior to zero", "RetinaImpl::setup", "Retina.cpp", 0);

modules/bioinspired/src/retinacolor.cpp

@@ -239,7 +239,7 @@ void RetinaColor::_initColorSampling()
     _spatiotemporalLPfilter(&_RGBmosaic[0]+_filterOutput.getNBpixels(), &_colorLocalDensity[0]+_filterOutput.getNBpixels());
     _spatiotemporalLPfilter(&_RGBmosaic[0]+_filterOutput.getDoubleNBpixels(), &_colorLocalDensity[0]+_filterOutput.getDoubleNBpixels());
     unsigned int maxNBpixels=3*_filterOutput.getNBpixels();
-    register float *colorLocalDensityPTR=&_colorLocalDensity[0];
+    float *colorLocalDensityPTR=&_colorLocalDensity[0];
     for (unsigned int i=0;i<maxNBpixels;++i, ++colorLocalDensityPTR)
         *colorLocalDensityPTR=1.f/ *colorLocalDensityPTR;
 
@@ -258,8 +258,8 @@ void RetinaColor::runColorDemultiplexing(const std::valarray<float> &multiplexed
     // -> first set demultiplexed frame to 0
     _demultiplexedTempBuffer=0;
     // -> demultiplex process
-    register unsigned int *colorSamplingPRT=&_colorSampling[0];
-    register const float *multiplexedColorFramePtr=get_data(multiplexedColorFrame);
+    unsigned int *colorSamplingPRT=&_colorSampling[0];
+    const float *multiplexedColorFramePtr=get_data(multiplexedColorFrame);
     for (unsigned int indexa=0; indexa<_filterOutput.getNBpixels() ; ++indexa)
         _demultiplexedTempBuffer[*(colorSamplingPRT++)]=*(multiplexedColorFramePtr++);
 
@@ -280,9 +280,9 @@ void RetinaColor::runColorDemultiplexing(const std::valarray<float> &multiplexed
     }*/
 
     // normalize by the photoreceptors local density and retrieve the local luminance
-    register float *chrominancePTR= &_chrominance[0];
-    register float *colorLocalDensityPTR= &_colorLocalDensity[0];
-    register float *luminance= &(*_luminance)[0];
+    float *chrominancePTR= &_chrominance[0];
+    float *colorLocalDensityPTR= &_colorLocalDensity[0];
+    float *luminance= &(*_luminance)[0];
     if (!adaptiveFiltering)// compute the gradient on the luminance
     {
         if (_samplingMethod==RETINA_COLOR_RANDOM)
@@ -326,7 +326,7 @@ void RetinaColor::runColorDemultiplexing(const std::valarray<float> &multiplexed
 
     }else
     {
-        register const float *multiplexedColorFramePTR= get_data(multiplexedColorFrame);
+        const float *multiplexedColorFramePTR= get_data(multiplexedColorFrame);
         for (unsigned int indexc=0; indexc<_filterOutput.getNBpixels() ; ++indexc, ++chrominancePTR, ++colorLocalDensityPTR, ++luminance, ++multiplexedColorFramePTR)
         {
             // normalize by photoreceptors density
@@ -412,8 +412,8 @@ void RetinaColor::runColorDemultiplexing(const std::valarray<float> &multiplexed
 void RetinaColor::runColorMultiplexing(const std::valarray<float> &demultiplexedInputFrame, std::valarray<float> &multiplexedFrame)
 {
     // multiply each color layer by its bayer mask
-    register unsigned int *colorSamplingPTR= &_colorSampling[0];
-    register float *multiplexedFramePTR= &multiplexedFrame[0];
+    unsigned int *colorSamplingPTR= &_colorSampling[0];
+    float *multiplexedFramePTR= &multiplexedFrame[0];
     for (unsigned int indexp=0; indexp<_filterOutput.getNBpixels(); ++indexp)
         *(multiplexedFramePTR++)=demultiplexedInputFrame[*(colorSamplingPTR++)];
 }
@@ -440,8 +440,8 @@ void RetinaColor::clipRGBOutput_0_maxInputValue(float *inputOutputBuffer, const
 #ifdef MAKE_PARALLEL // call the TemplateBuffer TBB clipping method
         cv::parallel_for_(cv::Range(0,_filterOutput.getNBpixels()*3), Parallel_clipBufferValues<float>(inputOutputBuffer, 0,  maxInputValue));
 #else
-    register float *inputOutputBufferPTR=inputOutputBuffer;
-    for (register unsigned int jf = 0; jf < _filterOutput.getNBpixels()*3; ++jf, ++inputOutputBufferPTR)
+    float *inputOutputBufferPTR=inputOutputBuffer;
+    for (unsigned int jf = 0; jf < _filterOutput.getNBpixels()*3; ++jf, ++inputOutputBufferPTR)
     {
         if (*inputOutputBufferPTR>maxInputValue)
             *inputOutputBufferPTR=maxInputValue;
@@ -587,12 +587,12 @@ void RetinaColor::_adaptiveHorizontalCausalFilter_addInput(const float *inputFra
 #ifdef MAKE_PARALLEL
         cv::parallel_for_(cv::Range(IDrowStart,IDrowEnd), Parallel_adaptiveHorizontalCausalFilter_addInput(inputFrame, outputFrame, &_imageGradient[0], _filterOutput.getNBcolumns()));
 #else
-    register float* outputPTR=outputFrame+IDrowStart*_filterOutput.getNBcolumns();
-    register const float* inputPTR=inputFrame+IDrowStart*_filterOutput.getNBcolumns();
-    register const float *imageGradientPTR= &_imageGradient[0]+IDrowStart*_filterOutput.getNBcolumns();
+    float* outputPTR=outputFrame+IDrowStart*_filterOutput.getNBcolumns();
+    const float* inputPTR=inputFrame+IDrowStart*_filterOutput.getNBcolumns();
+    const float *imageGradientPTR= &_imageGradient[0]+IDrowStart*_filterOutput.getNBcolumns();
     for (unsigned int IDrow=IDrowStart; IDrow<IDrowEnd; ++IDrow)
     {
-        register float result=0;
+        float result=0;
         for (unsigned int index=0; index<_filterOutput.getNBcolumns(); ++index)
         {
             //std::cout<<(*imageGradientPTR)<<" ";
@@ -616,9 +616,9 @@ void RetinaColor::_adaptiveVerticalAnticausalFilter_multGain(float *outputFrame,
 
     for (unsigned int IDcolumn=IDcolumnStart; IDcolumn<IDcolumnEnd; ++IDcolumn)
     {
-        register float result=0;
-        register float *outputPTR=outputOffset+IDcolumn;
-        register float *imageGradientPTR=gradOffset+IDcolumn;
+        float result=0;
+        float *outputPTR=outputOffset+IDcolumn;
+        float *imageGradientPTR=gradOffset+IDcolumn;
         for (unsigned int index=0; index<_filterOutput.getNBrows(); ++index)
         {
             result = *(outputPTR) + (*(imageGradientPTR)) * result;

modules/bioinspired/src/retinacolor.hpp

@@ -291,12 +291,12 @@ namespace bioinspired
 
             virtual void operator()( const Range& r ) const
             {
-                register float* outputPTR=outputFrame+r.start*nbColumns;
-                register const float* inputPTR=inputFrame+r.start*nbColumns;
-                register const float *imageGradientPTR= imageGradient+r.start*nbColumns;
+                float* outputPTR=outputFrame+r.start*nbColumns;
+                const float* inputPTR=inputFrame+r.start*nbColumns;
+                const float *imageGradientPTR= imageGradient+r.start*nbColumns;
                 for (int IDrow=r.start; IDrow!=r.end; ++IDrow)
                 {
-                    register float result=0;
+                    float result=0;
                     for (unsigned int index=0; index<nbColumns; ++index)
                     {
                         result = *(inputPTR++) + (*imageGradientPTR++)* result;
@@ -322,9 +322,9 @@ namespace bioinspired
                 const float* gradOffset= imageGradient+nbColumns*nbRows-nbColumns;
                 for (int IDcolumn=r.start; IDcolumn!=r.end; ++IDcolumn)
                 {
-                    register float result=0;
-                    register float *outputPTR=offset+IDcolumn;
-                    register const float *imageGradientPTR=gradOffset+IDcolumn;
+                    float result=0;
+                    float *outputPTR=offset+IDcolumn;
+                    const float *imageGradientPTR=gradOffset+IDcolumn;
                     for (unsigned int index=0; index<nbRows; ++index)
                     {
                         result = *(outputPTR) + *(imageGradientPTR) * result;

modules/bioinspired/src/retinafasttonemapping.cpp

@@ -309,7 +309,7 @@ void _runRGBToneMapping(const std::valarray<float> &RGBimageInput, std::valarray
 
 };
 
-CV_EXPORTS Ptr<RetinaFastToneMapping> createRetinaFastToneMapping(Size inputSize)
+Ptr<RetinaFastToneMapping> RetinaFastToneMapping::create(Size inputSize)
 {
     return makePtr<RetinaFastToneMappingImpl>(inputSize);
 }

modules/bioinspired/src/retinafilter.cpp

@@ -469,10 +469,10 @@ namespace bioinspired
     // return image with center Parvo and peripheral Magno channels
     void RetinaFilter::_processRetinaParvoMagnoMapping()
     {
-        register float *hybridParvoMagnoPTR= &_retinaParvoMagnoMappedFrame[0];
-        register const float *parvoOutputPTR= get_data(_ParvoRetinaFilter.getOutput());
-        register const float *magnoXOutputPTR= get_data(_MagnoRetinaFilter.getOutput());
-        register float *hybridParvoMagnoCoefTablePTR= &_retinaParvoMagnoMapCoefTable[0];
+        float *hybridParvoMagnoPTR= &_retinaParvoMagnoMappedFrame[0];
+        const float *parvoOutputPTR= get_data(_ParvoRetinaFilter.getOutput());
+        const float *magnoXOutputPTR= get_data(_MagnoRetinaFilter.getOutput());
+        float *hybridParvoMagnoCoefTablePTR= &_retinaParvoMagnoMapCoefTable[0];
 
         for (unsigned int i=0 ; i<_photoreceptorsPrefilter.getNBpixels() ; ++i, hybridParvoMagnoCoefTablePTR+=2)
         {
@@ -491,9 +491,9 @@ namespace bioinspired
         if (parvoFovealResponse.size() != _ParvoRetinaFilter.getNBpixels())
             return false;
 
-        register const float *parvoOutputPTR= get_data(_ParvoRetinaFilter.getOutput());
-        register float *fovealParvoResponsePTR= &parvoFovealResponse[0];
-        register float *hybridParvoMagnoCoefTablePTR= &_retinaParvoMagnoMapCoefTable[0];
+        const float *parvoOutputPTR= get_data(_ParvoRetinaFilter.getOutput());
+        float *fovealParvoResponsePTR= &parvoFovealResponse[0];
+        float *hybridParvoMagnoCoefTablePTR= &_retinaParvoMagnoMapCoefTable[0];
 
         for (unsigned int i=0 ; i<_photoreceptorsPrefilter.getNBpixels() ; ++i, hybridParvoMagnoCoefTablePTR+=2)
         {
@@ -511,9 +511,9 @@ namespace bioinspired
         if (magnoParafovealResponse.size() != _MagnoRetinaFilter.getNBpixels())
             return false;
 
-        register const float *magnoXOutputPTR= get_data(_MagnoRetinaFilter.getOutput());
-        register float *parafovealMagnoResponsePTR=&magnoParafovealResponse[0];
-        register float *hybridParvoMagnoCoefTablePTR=&_retinaParvoMagnoMapCoefTable[0]+1;
+        const float *magnoXOutputPTR= get_data(_MagnoRetinaFilter.getOutput());
+        float *parafovealMagnoResponsePTR=&magnoParafovealResponse[0];
+        float *hybridParvoMagnoCoefTablePTR=&_retinaParvoMagnoMapCoefTable[0]+1;
 
         for (unsigned int i=0 ; i<_photoreceptorsPrefilter.getNBpixels() ; ++i, hybridParvoMagnoCoefTablePTR+=2)
         {

modules/bioinspired/src/templatebuffer.hpp

@@ -95,8 +95,8 @@ public:
         : bufferToClip(bufferToProcess), minValue(min), maxValue(max) { }
 
     virtual void operator()( const cv::Range &r ) const {
-        register type *inputOutputBufferPTR=bufferToClip+r.start;
-        for (register int jf = r.start; jf != r.end; ++jf, ++inputOutputBufferPTR)
+        type *inputOutputBufferPTR=bufferToClip+r.start;
+        for (int jf = r.start; jf != r.end; ++jf, ++inputOutputBufferPTR)
         {
             if (*inputOutputBufferPTR>maxValue)
                 *inputOutputBufferPTR=maxValue;
@@ -430,8 +430,8 @@ public:
         type maxValue=inputOutputBuffer[0], minValue=inputOutputBuffer[0];
 
         // get the min and max value
-        register type *inputOutputBufferPTR=inputOutputBuffer;
-        for (register size_t j = 0; j<processedPixels; ++j)
+        type *inputOutputBufferPTR=inputOutputBuffer;
+        for (size_t j = 0; j<processedPixels; ++j)
         {
             type pixValue = *(inputOutputBufferPTR++);
             if (maxValue < pixValue)
@@ -445,7 +445,7 @@ public:
         type offset = (type)(-minValue*factor);
 
         inputOutputBufferPTR=inputOutputBuffer;
-        for (register size_t j = 0; j < processedPixels; ++j, ++inputOutputBufferPTR)
+        for (size_t j = 0; j < processedPixels; ++j, ++inputOutputBufferPTR)
             *inputOutputBufferPTR=*(inputOutputBufferPTR)*factor+offset;
 
     }
@@ -460,10 +460,10 @@ public:
 
         type X0cube=sensitivity*sensitivity*sensitivity;
 
-        register type *inputBufferPTR=inputBuffer;
-        register type *outputBufferPTR=outputBuffer;
+        type *inputBufferPTR=inputBuffer;
+        type *outputBufferPTR=outputBuffer;
 
-        for (register size_t j = 0; j < _NBpixels; ++j, ++inputBufferPTR)
+        for (size_t j = 0; j < _NBpixels; ++j, ++inputBufferPTR)
         {
 
             type currentCubeLuminance=*inputBufferPTR**inputBufferPTR**inputBufferPTR;
@@ -485,10 +485,10 @@ public:
 
         type X0=maxOutputValue/(sensitivity-(type)1.0);
 
-        register type *inputBufferPTR=inputBuffer;
-        register type *outputBufferPTR=outputBuffer;
+        type *inputBufferPTR=inputBuffer;
+        type *outputBufferPTR=outputBuffer;
 
-        for (register size_t j = 0; j < nbPixels; ++j, ++inputBufferPTR)
+        for (size_t j = 0; j < nbPixels; ++j, ++inputBufferPTR)
             *(outputBufferPTR++)=(meanValue+(meanValue+X0)*(*(inputBufferPTR)-meanValue)/(_abs(*(inputBufferPTR)-meanValue)+X0));
 
     }
@@ -503,12 +503,12 @@ public:
         type meanValue=0, stdValue=0;
 
         // compute mean value
-        for (register size_t j = 0; j < _NBpixels; ++j)
+        for (size_t j = 0; j < _NBpixels; ++j)
             meanValue+=inputOutputBuffer[j];
         meanValue/=((type)_NBpixels);
 
         // compute std value
-        register type *inputOutputBufferPTR=inputOutputBuffer;
+        type *inputOutputBufferPTR=inputOutputBuffer;
         for (size_t index=0;index<_NBpixels;++index)
         {
             type inputMinusMean=*(inputOutputBufferPTR++)-meanValue;

modules/bioinspired/src/transientareassegmentationmodule.cpp

@@ -247,7 +247,7 @@ private:
 * allocator
 * @param Size : size of the images input to segment (output will be the same size)
 */
-Ptr<TransientAreasSegmentationModule> createTransientAreasSegmentationModule(Size inputSize){
+Ptr<TransientAreasSegmentationModule> TransientAreasSegmentationModule::create(Size inputSize){
     return makePtr<TransientAreasSegmentationModuleImpl_>(inputSize);
 }
 
@@ -462,7 +462,7 @@ void TransientAreasSegmentationModuleImpl::_run(const std::valarray<float> &inpu
     float*localMotionPTR=&_localMotion[0], *neighborhoodMotionPTR=&_neighborhoodMotion[0], *contextMotionPTR=&_contextMotionEnergy[0];
 
     // float meanEnergy=LPfilter2.sum()/(float)_LPfilter2.size();
-    register bool *segmentationPicturePTR= &_segmentedAreas[0];
+    bool *segmentationPicturePTR= &_segmentedAreas[0];
     for (unsigned int index=0; index<_filterOutput.getNBpixels() ; ++index, ++segmentationPicturePTR, ++localMotionPTR, ++neighborhoodMotionPTR, contextMotionPTR++)
     {
         float generalMotionContextDecision=*neighborhoodMotionPTR-*contextMotionPTR;

modules/bioinspired/test/test_retina_ocl.cpp

@@ -76,7 +76,7 @@ OCL_TEST_P(Retina_OCL, Accuracy)
     Mat input = imread(cvtest::TS::ptr()->get_data_path() + "shared/lena.png", colorMode);
     CV_Assert(!input.empty());
 
-    Ptr<bioinspired::Retina> retina = bioinspired::createRetina(
+    Ptr<bioinspired::Retina> retina = bioinspired::Retina::create(
         input.size(),
         colorMode,
         colorSamplingMethod,