updated retina interface for cleaner use, following OpenCV standards

modules/contrib/doc/retina/index.rst

@@ -22,9 +22,9 @@ The retina can be settled up with various parameters, by default, the retina can
     // parameters setup instance
     struct RetinaParameters; // this class is detailled later
 
-    // constructors
-    Retina (Size inputSize);
-    Retina (Size inputSize, const bool colorMode, RETINA_COLORSAMPLINGMETHOD colorSamplingMethod=RETINA_COLOR_BAYER, const bool useRetinaLogSampling=false, const double reductionFactor=1.0, const double samplingStrenght=10.0);
+    // constructors (interfaces)
+    cv::Ptr<Retina> createRetina (Size inputSize);
+    cv::Ptr<Retina> createRetina (Size inputSize, const bool colorMode, RETINA_COLORSAMPLINGMETHOD colorSamplingMethod=RETINA_COLOR_BAYER, const bool useRetinaLogSampling=false, const double reductionFactor=1.0, const double samplingStrenght=10.0);
 
     // main method for input frame processing
     void run (const Mat &inputImage);
@@ -32,19 +32,19 @@ The retina can be settled up with various parameters, by default, the retina can
     // output buffers retreival methods
     // -> foveal color vision details channel with luminance and noise correction
     void getParvo (Mat &retinaOutput_parvo);
-    void getParvo (std::valarray< float > &retinaOutput_parvo);
-    const std::valarray< float > & getParvo () const;
+    void getParvoRAW (Mat &retinaOutput_parvo);// retreive original output buffers without any normalisation
+    const Mat getParvo () const;// retreive original output buffers without any normalisation
     // -> peripheral monochrome motion and events (transient information) channel
     void getMagno (Mat &retinaOutput_magno);
-    void getMagno (std::valarray< float > &retinaOutput_magno);
-    const std::valarray< float > & getMagno () const;
+    void getMagnoRAW (Mat &retinaOutput_magno); // retreive original output buffers without any normalisation 
+    const Mat getMagno () const;// retreive original output buffers without any normalisation
 
     // reset retina buffers... equivalent to closing your eyes for some seconds
     void clearBuffers ();
 
     // retreive input and output buffers sizes
-    Size inputSize ();
-    Size outputSize ();
+    Size getInputSize ();
+    Size getOutputSize ();
 
     // setup methods with specific parameters specification of global xml config file loading/write
     void setup (std::string retinaParameterFile="", const bool applyDefaultSetupOnFailure=true);
@@ -127,13 +127,13 @@ Methods description
 
 Here are detailled the main methods to control the retina model
 
-Retina::Retina
+Ptr<Retina>::createRetina
 ++++++++++++++
 
-.. ocv:function:: Retina::Retina(Size inputSize)
-.. ocv:function:: Retina::Retina(Size inputSize, const bool colorMode, RETINA_COLORSAMPLINGMETHOD colorSamplingMethod = RETINA_COLOR_BAYER, const bool useRetinaLogSampling = false, const double reductionFactor = 1.0, const double samplingStrenght = 10.0 )
+.. ocv:function:: Ptr<Retina> createRetina(Size inputSize)
+.. ocv:function:: Ptr<Retina> createRetina(Size inputSize, const bool colorMode, RETINA_COLORSAMPLINGMETHOD colorSamplingMethod = RETINA_COLOR_BAYER, const bool useRetinaLogSampling = false, const double reductionFactor = 1.0, const double samplingStrenght = 10.0 )
 
-    Constructors
+    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
@@ -209,8 +209,21 @@ Retina::getParameters
 
     :return: the current parameters setup
 
-Retina::inputSize
-+++++++++++++++++
+Retina::getParvo/getMagno
++++++++++++++++++++++++++
+
+.. ocv:function:: void getParvo(Mat parvoOutput)
+.. ocv:function:: void getParvoRAW(Mat parvoOutput)
+.. ocv:function:: Mat getParvoRAW() 
+    Retrieve the Parvocellular channel (details with color) output normalized between range [0;255] if not 'RAW'.
+
+.. ocv:function:: void getParvo(Mat parvoOutput)
+.. ocv:function:: void getParvoRAW(Mat parvoOutput)
+.. ocv:function:: Mat getParvoRAW() 
+    Retrieve the Magnocellular channel (transient events, grayscale) output normalized between range [0;255] if not 'RAW'.
+
+Retina::getInputSize
+++++++++++++++++++++
 
 .. ocv:function:: Size Retina::inputSize()
 
@@ -218,8 +231,8 @@ Retina::inputSize
 
     :return: the retina input buffer size
 
-Retina::outputSize
-++++++++++++++++++
+Retina::getOutputSize
++++++++++++++++++++++
 
 .. ocv:function:: Size Retina::outputSize()
 
@@ -329,7 +342,7 @@ Parameters structure for better clarity, check explenations on the comments of m
                   photoreceptorsTemporalConstant(0.5f),// the time constant of the first order low pass filter of the photoreceptors, use it to cut high temporal frequencies (noise or fast motion), unit is frames, typical value is 1 frame
                   photoreceptorsSpatialConstant(0.53f),// the spatial constant of the first order low pass filter of the photoreceptors, use it to cut high spatial frequencies (noise or thick contours), unit is pixels, typical value is 1 pixel
                   horizontalCellsGain(0.0f),//gain of the horizontal cells network, if 0, then the mean value of the output is zero, if the parameter is near 1, then, the luminance is not filtered and is still reachable at the output, typicall value is 0
-                  hcellsTemporalConstant(1.f),// the time constant of the first order low pass filter of the horizontal cells, use it to cut low temporal frequencies (local luminance variations), unit is frames, typical value is 1 frame, as the photoreceptors
+                  hcellsTemporalConstant(1.f),// the time constant of the first order low pass filter of the horizontal cells, use it to cut low temporal frequencies (local luminance variations), unit is frames, typical value is 1 frame, as the photoreceptors. Reduce to 0.5 to limit retina after effects.
                   hcellsSpatialConstant(7.f),//the spatial constant of the first order low pass filter of the horizontal cells, use it to cut low spatial frequencies (local luminance), unit is pixels, typical value is 5 pixel, this value is also used for local contrast computing when computing the local contrast adaptation at the ganglion cells level (Inner Plexiform Layer parvocellular channel model)
                   ganglionCellsSensitivity(0.7f)//the compression strengh of the ganglion cells local adaptation output, set a value between 0.6 and 1 for best results, a high value increases more the low value sensitivity... and the output saturates faster, recommended value: 0.7
                   {};// default setup

modules/contrib/include/opencv2/contrib/retina.hpp

@@ -110,7 +110,7 @@ class RetinaFilter;
  * _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.
  */
-class CV_EXPORTS Retina {
+class CV_EXPORTS Retina : public Algorithm {
 
 public:
 
@@ -147,33 +147,14 @@ public:
     };
 
     /**
-     * Main constructor with most commun use setup : create an instance of color ready retina model
-     * @param inputSize : the input frame size
-     */
-    Retina(Size inputSize);
-
-    /**
-     * Complete Retina filter constructor which allows all basic structural parameters definition
-         * @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
-     * @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
-     */
-    Retina(Size inputSize, const bool colorMode, RETINA_COLORSAMPLINGMETHOD colorSamplingMethod=RETINA_COLOR_BAYER, const bool useRetinaLogSampling=false, const double reductionFactor=1.0, const double samplingStrenght=10.0);
-
-    virtual ~Retina();
+    * retreive retina input buffer size
+    */
+    virtual Size getInputSize()=0;
 
     /**
-        * retreive retina input buffer size
-        */
-        Size inputSize();
-
-    /**
-        * retreive retina output buffer size
-        */
-        Size outputSize();
+    * retreive retina output buffer size
+    */
+    virtual Size getOutputSize()=0;
 
     /**
      * try to open an XML retina parameters file to adjust current retina instance setup
@@ -182,7 +163,7 @@ public:
      * @param retinaParameterFile : the parameters filename
          * @param applyDefaultSetupOnFailure : set to true if an error must be thrown on error
      */
-    void setup(std::string retinaParameterFile="", const bool applyDefaultSetupOnFailure=true);
+    virtual void setup(std::string retinaParameterFile="", const bool applyDefaultSetupOnFailure=true)=0;
 
 
     /**
@@ -192,7 +173,7 @@ public:
      * @param fs : the open Filestorage which contains retina parameters
          * @param applyDefaultSetupOnFailure : set to true if an error must be thrown on error
      */
-        void setup(cv::FileStorage &fs, const bool applyDefaultSetupOnFailure=true);
+    virtual void setup(cv::FileStorage &fs, const bool applyDefaultSetupOnFailure=true)=0;
 
     /**
      * try to open an XML retina parameters file to adjust current retina instance setup
@@ -201,31 +182,31 @@ public:
      * @param newParameters : a parameters structures updated with the new target configuration
          * @param applyDefaultSetupOnFailure : set to true if an error must be thrown on error
      */
-    void setup(RetinaParameters newParameters);
+    virtual void setup(RetinaParameters newParameters)=0;
 
-        /**
-         * @return the current parameters setup
-         */
-        struct Retina::RetinaParameters getParameters();
+    /**
+    * @return the current parameters setup
+    */
+    virtual struct Retina::RetinaParameters getParameters()=0;
 
     /**
      * parameters setup display method
      * @return a string which contains formatted parameters information
      */
-    const std::string printSetup();
+    virtual const std::string printSetup()=0;
 
     /**
      * write xml/yml formated parameters information
      * @rparam fs : the filename of the xml file that will be open and writen with formatted parameters information
      */
-    virtual void write( std::string fs ) const;
+    virtual void write( std::string fs ) const=0;
 
 
     /**
      * write xml/yml formated parameters information
      * @param fs : a cv::Filestorage object ready to be filled
          */
-    virtual void write( FileStorage& fs ) const;
+    virtual void write( FileStorage& fs ) const=0;
 
     /**
      * setup the OPL and IPL parvo channels (see biologocal model)
@@ -242,7 +223,7 @@ public:
      * @param HcellsSpatialConstant: the spatial constant of the first order low pass filter of the horizontal cells, use it to cut low spatial frequencies (local luminance), unit is pixels, typical value is 5 pixel, this value is also used for local contrast computing when computing the local contrast adaptation at the ganglion cells level (Inner Plexiform Layer parvocellular channel model)
      * @param ganglionCellsSensitivity: the compression strengh of the ganglion cells local adaptation output, set a value between 160 and 250 for best results, a high value increases more the low value sensitivity... and the output saturates faster, recommended value: 230
      */
-    void setupOPLandIPLParvoChannel(const bool colorMode=true, const bool normaliseOutput = true, const float photoreceptorsLocalAdaptationSensitivity=0.7, const float photoreceptorsTemporalConstant=0.5, const float photoreceptorsSpatialConstant=0.53, const float horizontalCellsGain=0, const float HcellsTemporalConstant=1, const float HcellsSpatialConstant=7, const float ganglionCellsSensitivity=0.7);
+    virtual void setupOPLandIPLParvoChannel(const bool colorMode=true, const bool normaliseOutput = true, const float photoreceptorsLocalAdaptationSensitivity=0.7, const float photoreceptorsTemporalConstant=0.5, const float photoreceptorsSpatialConstant=0.53, const float horizontalCellsGain=0, const float HcellsTemporalConstant=1, const float HcellsSpatialConstant=7, const float ganglionCellsSensitivity=0.7)=0;
 
     /**
      * set parameters values for the Inner Plexiform Layer (IPL) magnocellular channel
@@ -256,41 +237,41 @@ public:
      * @param localAdaptintegration_tau: specifies the temporal constant of the low pas filter involved in the computation of the local "motion mean" for the local adaptation computation
      * @param localAdaptintegration_k: specifies the spatial constant of the low pas filter involved in the computation of the local "motion mean" for the local adaptation computation
      */
-    void setupIPLMagnoChannel(const bool normaliseOutput = true, const float parasolCells_beta=0, const float parasolCells_tau=0, const float parasolCells_k=7, const float amacrinCellsTemporalCutFrequency=1.2, const float V0CompressionParameter=0.95, const float localAdaptintegration_tau=0, const float localAdaptintegration_k=7);
+    virtual void setupIPLMagnoChannel(const bool normaliseOutput = true, const float parasolCells_beta=0, const float parasolCells_tau=0, const float parasolCells_k=7, const float amacrinCellsTemporalCutFrequency=1.2, const float V0CompressionParameter=0.95, const float localAdaptintegration_tau=0, const float localAdaptintegration_k=7)=0;
 
     /**
      * method which allows retina to be applied on an input image, after run, encapsulated retina module is ready to deliver its outputs using dedicated acccessors, see getParvo and getMagno methods
      * @param inputImage : the input cv::Mat image to be processed, can be gray level or BGR coded in any format (from 8bit to 16bits)
      */
-    void run(const Mat &inputImage);
+    virtual void run(const Mat &inputImage)=0;
 
     /**
      * accessor of the details channel of the retina (models foveal vision)
      * @param retinaOutput_parvo : the output buffer (reallocated if necessary), this output is rescaled for standard 8bits image processing use in OpenCV
      */
-    void getParvo(Mat &retinaOutput_parvo);
+    virtual void getParvo(Mat &retinaOutput_parvo)=0;
 
     /**
      * accessor of the details channel of the retina (models foveal vision)
-     * @param retinaOutput_parvo : the output buffer (reallocated if necessary), this output is the original retina filter model output, without any quantification or rescaling
+     * @param retinaOutput_parvo : a cv::Mat header filled with the internal parvo buffer of the retina module. This output is the original retina filter model output, without any quantification or rescaling
      */
-    void getParvo(std::valarray<float> &retinaOutput_parvo);
+    virtual void getParvoRAW(Mat &retinaOutput_parvo)=0;
 
     /**
      * accessor of the motion channel of the retina (models peripheral vision)
      * @param retinaOutput_magno : the output buffer (reallocated if necessary), this output is rescaled for standard 8bits image processing use in OpenCV
      */
-    void getMagno(Mat &retinaOutput_magno);
+    virtual void getMagno(Mat &retinaOutput_magno)=0;
 
     /**
      * accessor of the motion channel of the retina (models peripheral vision)
-     * @param retinaOutput_magno : the output buffer (reallocated if necessary), this output is the original retina filter model output, without any quantification or rescaling
+     * @param retinaOutput_magno : a cv::Mat header filled with the internal retina magno buffer of the retina module. This output is the original retina filter model output, without any quantification or rescaling
      */
-    void getMagno(std::valarray<float> &retinaOutput_magno);
+    virtual void getMagnoRAW(Mat &retinaOutput_magno)=0;
 
-    // original API level data accessors : get buffers addresses...
-    const std::valarray<float> & getMagno() const;
-    const std::valarray<float> & getParvo() const;
+    // original API level data accessors : get buffers addresses from a Mat header, similar to getParvoRAW and getMagnoRAW...
+    virtual const Mat getMagnoRAW() const=0;
+    virtual const Mat getParvoRAW() const=0;
 
     /**
      * activate color saturation as the final step of the color demultiplexing process
@@ -298,58 +279,27 @@ public:
      * @param saturateColors: boolean that activates color saturation (if true) or desactivate (if false)
      * @param colorSaturationValue: the saturation factor
      */
-    void setColorSaturation(const bool saturateColors=true, const float colorSaturationValue=4.0);
+    virtual void setColorSaturation(const bool saturateColors=true, const float colorSaturationValue=4.0)=0;
 
     /**
      * clear all retina buffers (equivalent to opening the eyes after a long period of eye close ;o)
      */
-    void clearBuffers();
-
-        /**
-        * Activate/desactivate the Magnocellular pathway processing (motion information extraction), by default, it is activated
-        * @param activate: true if Magnocellular output should be activated, false if not
-        */
-        void activateMovingContoursProcessing(const bool activate);
-
-        /**
-        * Activate/desactivate the Parvocellular pathway processing (contours information extraction), by default, it is activated
-        * @param activate: true if Parvocellular (contours information extraction) output should be activated, false if not
-        */
-        void activateContoursProcessing(const bool activate);
-
-protected:
-    // Parameteres setup members
-    RetinaParameters _retinaParameters; // structure of parameters
-
-        // Retina model related modules
-    std::valarray<float> _inputBuffer; //!< buffer used to convert input cv::Mat to internal retina buffers format (valarrays)
-
-    // pointer to retina model
-    RetinaFilter* _retinaFilter; //!< the pointer to the retina module, allocated with instance construction
+    virtual void clearBuffers()=0;
 
     /**
-     * exports a valarray buffer outing from HVStools objects to a cv::Mat in CV_8UC1 (gray level picture) or CV_8UC3 (color) format
-     * @param grayMatrixToConvert the valarray to export to OpenCV
-     * @param nbRows : the number of rows of the valarray flatten matrix
-     * @param nbColumns : the number of rows of the valarray flatten matrix
-     * @param colorMode : a flag which mentions if matrix is color (true) or graylevel (false)
-     * @param outBuffer : the output matrix which is reallocated to satisfy Retina output buffer dimensions
-     */
-    void _convertValarrayBuffer2cvMat(const std::valarray<float> &grayMatrixToConvert, const unsigned int nbRows, const unsigned int nbColumns, const bool colorMode, Mat &outBuffer);
+    * Activate/desactivate the Magnocellular pathway processing (motion information extraction), by default, it is activated
+    * @param activate: true if Magnocellular output should be activated, false if not
+    */
+    virtual void activateMovingContoursProcessing(const bool activate)=0;
 
     /**
-     *
-     * @param inputMatToConvert : the OpenCV cv::Mat that has to be converted to gray or RGB valarray buffer that will be processed by the retina model
-     * @param outputValarrayMatrix : the output valarray
-     * @return the input image color mode (color=true, gray levels=false)
-     */
-        bool _convertCvMat2ValarrayBuffer(const cv::Mat inputMatToConvert, std::valarray<float> &outputValarrayMatrix);
-
-    //! private method called by constructors, gathers their parameters and use them in a unified way
-    void _init(const Size inputSize, const bool colorMode, RETINA_COLORSAMPLINGMETHOD colorSamplingMethod=RETINA_COLOR_BAYER, const bool useRetinaLogSampling=false, const double reductionFactor=1.0, const double samplingStrenght=10.0);
-
-
+    * Activate/desactivate the Parvocellular pathway processing (contours information extraction), by default, it is activated
+    * @param activate: true if Parvocellular (contours information extraction) output should be activated, false if not
+    */
+    virtual void activateContoursProcessing(const bool activate)=0;
 };
+Ptr<Retina> createRetina(Size inputSize);
+Ptr<Retina> createRetina(Size inputSize, const bool colorMode, RETINA_COLORSAMPLINGMETHOD colorSamplingMethod=RETINA_COLOR_BAYER, const bool useRetinaLogSampling=false, const double reductionFactor=1.0, const double samplingStrenght=10.0);
 
 }
 #endif /* __OPENCV_CONTRIB_RETINA_HPP__ */

modules/contrib/src/retinacolor.cpp

@@ -338,8 +338,11 @@ void RetinaColor::runColorDemultiplexing(const std::valarray<float> &multiplexed
         }
 
         // compute the gradient of the luminance
+#ifndef MAKE_PARALLEL // call the TemplateBuffer TBB clipping method
+        cv::parallel_for_(cv::Range(2,_filterOutput.getNBrows()-2), Parallel_computeGradient(_filterOutput.getNBcolumns(), _filterOutput.getNBrows(), &(*_luminance)[0], &_imageGradient[0]));
+#else
         _computeGradient(&(*_luminance)[0]);
-
+#endif
         // adaptively filter the submosaics to get the adaptive densities, here the buffer _chrominance is used as a temp buffer
         _adaptiveSpatialLPfilter(&_RGBmosaic[0], &_chrominance[0]);
         _adaptiveSpatialLPfilter(&_RGBmosaic[0]+_filterOutput.getNBpixels(), &_chrominance[0]+_filterOutput.getNBpixels());

modules/contrib/src/retinacolor.hpp

@@ -333,6 +333,53 @@ namespace cv
                 }
             }
         };
+
+        class Parallel_computeGradient: public cv::ParallelLoopBody
+        {
+        private:
+            float *imageGradient;
+            const float *luminance;
+            unsigned int nbColumns, doubleNbColumns, nbRows, nbPixels;
+        public:
+            Parallel_computeGradient(const unsigned int nbCols, const unsigned int nbRws, const float *lum, float *imageGrad)
+            :imageGradient(imageGrad), luminance(lum), nbColumns(nbCols), doubleNbColumns(2*nbCols), nbRows(nbRws), nbPixels(nbRws*nbCols){};
+
+            virtual void operator()( const Range& r ) const {
+                for (int idLine=r.start;idLine!=r.end;++idLine)
+                {
+                    for (unsigned int idColumn=2;idColumn<nbColumns-2;++idColumn)
+                    {
+                        const unsigned int pixelIndex=idColumn+nbColumns*idLine;
+        
+                        // horizontal and vertical local gradients
+                        const float verticalGrad=fabs(luminance[pixelIndex+nbColumns]-luminance[pixelIndex-nbColumns]);
+                        const float horizontalGrad=fabs(luminance[pixelIndex+1]-luminance[pixelIndex-1]);
+
+                        // neighborhood horizontal and vertical gradients
+                        const float verticalGrad_p=fabs(luminance[pixelIndex]-luminance[pixelIndex-doubleNbColumns]);
+                        const float horizontalGrad_p=fabs(luminance[pixelIndex]-luminance[pixelIndex-2]);
+                        const float verticalGrad_n=fabs(luminance[pixelIndex+doubleNbColumns]-luminance[pixelIndex]);
+                        const float horizontalGrad_n=fabs(luminance[pixelIndex+2]-luminance[pixelIndex]);
+
+                        const float horizontalGradient=0.5f*horizontalGrad+0.25f*(horizontalGrad_p+horizontalGrad_n);
+                        const float verticalGradient=0.5f*verticalGrad+0.25f*(verticalGrad_p+verticalGrad_n);
+
+                        // compare local gradient means and fill the appropriate filtering coefficient value that will be used in adaptative filters
+                        if (horizontalGradient<verticalGradient)
+                        {
+                            imageGradient[pixelIndex+nbPixels]=0.06f;
+                            imageGradient[pixelIndex]=0.57f;
+                        }
+                        else
+                        {
+                            imageGradient[pixelIndex+nbPixels]=0.57f;
+                            imageGradient[pixelIndex]=0.06f;
+                        }
+                    }
+                }
+            }
+        };
+
 #endif
     };
 }

samples/cpp/OpenEXRimages_HighDynamicRange_Retina_toneMapping.cpp

@@ -211,10 +211,10 @@ static void drawPlot(const cv::Mat curve, const std::string figureTitle, const i
           */
          if (useLogSampling)
                 {
-                     retina = new cv::Retina(inputImage.size(),true, cv::RETINA_COLOR_BAYER, true, 2.0, 10.0);
+                     retina = cv::createRetina(inputImage.size(),true, cv::RETINA_COLOR_BAYER, true, 2.0, 10.0);
                  }
          else// -> else allocate "classical" retina :
-             retina = new cv::Retina(inputImage.size());
+             retina = cv::createRetina(inputImage.size());
 
         // save default retina parameters file in order to let you see this and maybe modify it and reload using method "setup"
         retina->write("RetinaDefaultParameters.xml");

samples/cpp/OpenEXRimages_HighDynamicRange_Retina_toneMapping_video.cpp

@@ -279,10 +279,10 @@ static void loadNewFrame(const std::string filenamePrototype, const int currentF
           */
          if (useLogSampling)
                 {
-                     retina = new cv::Retina(inputImage.size(),true, cv::RETINA_COLOR_BAYER, true, 2.0, 10.0);
+                     retina = cv::createRetina(inputImage.size(),true, cv::RETINA_COLOR_BAYER, true, 2.0, 10.0);
                  }
          else// -> else allocate "classical" retina :
-             retina = new cv::Retina(inputImage.size());
+             retina = cv::createRetina(inputImage.size());
 
         // save default retina parameters file in order to let you see this and maybe modify it and reload using method "setup"
         retina->write("RetinaDefaultParameters.xml");

samples/cpp/retinaDemo.cpp

@@ -110,10 +110,10 @@ int main(int argc, char* argv[]) {
         // if the last parameter is 'log', then activate log sampling (favour foveal vision and subsamples peripheral vision)
         if (useLogSampling)
                 {
-                        myRetina = new cv::Retina(inputFrame.size(), true, cv::RETINA_COLOR_BAYER, true, 2.0, 10.0);
+                        myRetina = cv::createRetina(inputFrame.size(), true, cv::RETINA_COLOR_BAYER, true, 2.0, 10.0);
                 }
         else// -> else allocate "classical" retina :
-            myRetina = new cv::Retina(inputFrame.size());
+            myRetina = cv::createRetina(inputFrame.size());
 
         // save default retina parameters file in order to let you see this and maybe modify it and reload using method "setup"
         myRetina->write("RetinaDefaultParameters.xml");