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updated demos and tutorial regarding the Retina class transfer to bioinspired module.

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pull/984/head
alexandre benoit 12 years ago
parent cdbbe0dfbe
commit 7bff79bbeb
10 changed files with 97 additions and 47 deletions
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  1. 4
      doc/CMakeLists.txt
  2. 12
      doc/tutorials/tutorials.rst
  3. 1
      include/opencv2/opencv.hpp
  4. 2
      modules/bioinspired/include/opencv2/bioinspired.hpp
  5. 28
      modules/contrib/doc/retina/index.rst
  6. 1
      modules/contrib/include/opencv2/contrib.hpp
  7. 2
      samples/cpp/CMakeLists.txt
  8. 72
      samples/cpp/OpenEXRimages_HighDynamicRange_Retina_toneMapping.cpp
  9. 11
      samples/cpp/OpenEXRimages_HighDynamicRange_Retina_toneMapping_video.cpp
  10. 11
      samples/cpp/retinaDemo.cpp

4
doc/CMakeLists.txt
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@ -17,7 +17,7 @@ if(BUILD_DOCS AND HAVE_SPHINX)
set(OPTIONAL_DOC_LIST "")
set(OPENCV2_BASE_MODULES core imgproc highgui video calib3d features2d objdetect ml flann gpu photo stitching nonfree contrib legacy)
set(OPENCV2_BASE_MODULES core imgproc highgui video calib3d features2d objdetect ml flann gpu photo stitching nonfree contrib legacy bioinspired)
# build lists of modules to be documented
set(OPENCV2_MODULES "")
@ -122,4 +122,4 @@ if(BUILD_DOCS AND HAVE_SPHINX)
install(FILES "${f}" DESTINATION "${OPENCV_DOC_INSTALL_PATH}" OPTIONAL)
endforeach()
endif()
endif()

12
doc/tutorials/tutorials.rst
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@ -156,17 +156,17 @@ As always, we would be happy to hear your comments and receive your contribution
:width: 80pt
:alt: gpu icon
* :ref:`Table-Of-Content-Contrib`
* :ref:`Table-Of-Content-Bioinspired`
.. tabularcolumns:: m{100pt} m{300pt}
.. cssclass:: toctableopencv
=========== =======================================================
|Contrib| Discover additional contribution to OpenCV.
============= =======================================================
|Bioinspired| Algorithms inspired from biological models.
=========== =======================================================
============= =======================================================
.. |Contrib| image:: images/retina.jpg
.. |Bioinspired| image:: images/retina.jpg
:height: 80pt
:width: 80pt
:alt: gpu icon
@ -219,6 +219,6 @@ As always, we would be happy to hear your comments and receive your contribution
objdetect/table_of_content_objdetect/table_of_content_objdetect
ml/table_of_content_ml/table_of_content_ml
gpu/table_of_content_gpu/table_of_content_gpu
contrib/table_of_content_contrib/table_of_content_contrib
bioinspired/table_of_content_bioinspired/table_of_content_bioinspired
ios/table_of_content_ios/table_of_content_ios
general/table_of_content_general/table_of_content_general

1
include/opencv2/opencv.hpp
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@ -52,6 +52,7 @@
#include "opencv2/calib3d.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/contrib.hpp"
#include "opencv2/bioinspired.hpp"
#include "opencv2/ml.hpp"
#endif

2
modules/bioinspired/include/opencv2/bioinspired.hpp
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@ -47,5 +47,5 @@
#include "opencv2/bioinspired/retina.hpp"
#include "opencv2/bioinspired/retinafasttonemapping.hpp"
using namespace cv::hvstools;
using namespace cv::hvstools; // used to avoid complex namespace inclusions cv::hvstools::Retina => cv::Retina preferred
#endif

28
modules/contrib/doc/retina/index.rst
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@ -61,9 +61,12 @@ Here is an overview of the abstract Retina interface, allocate one instance with
// parameters setup instance
struct RetinaParameters; // this class is detailled later
// main method for input frame processing
// main method for input frame processing (all use method, can also perform High Dynamic Range tone mapping)
void run (InputArray inputImage);
// specific method aiming at correcting luminance only (faster High Dynamic Range tone mapping)
void applyFastToneMapping(InputArray inputImage, OutputArray outputToneMappedImage)
// output buffers retreival methods
// -> foveal color vision details channel with luminance and noise correction
void getParvo (OutputArray retinaOutput_parvo);
@ -138,6 +141,10 @@ This retina filter code includes the research contributions of phd/research coll
* 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.
* Meylan&al work on HDR tone mapping that is implemented as a specific method within the model :
.. [Meylan2007] L. Meylan , D. Alleysson, S. Susstrunk, "A Model of Retinal Local Adaptation for the Tone Mapping of Color Filter Array Images", Journal of Optical Society of America, A, Vol. 24, N 9, September, 1st, 2007, pp. 2807-2816
Demos and experiments !
=======================
@ -161,11 +168,13 @@ Take a look at the provided C++ examples provided with OpenCV :
Then, take a HDR image using bracketing with your camera and generate an OpenEXR image and then process it using the demo.
Typical use, supposing that you have the OpenEXR image *memorial.exr* (present in the samples/cpp/ folder)
Typical use, supposing that you have the OpenEXR image such as *memorial.exr* (present in the samples/cpp/ folder)
**OpenCVReleaseFolder/bin/OpenEXRimages_HighDynamicRange_Retina_toneMapping memorial.exr**
**OpenCVReleaseFolder/bin/OpenEXRimages_HighDynamicRange_Retina_toneMapping memorial.exr [optionnal: 'fast']**
Note that some sliders are made available to allow you to play with luminance compression.
If not using the 'fast' option, then, tone mapping is performed using the full retina model [Benoit2010]_. It includes spectral whitening that allows luminance energy to be reduced. When using the 'fast' option, then, a simpler method is used, it is an adaptation of the algorithm presented in [Meylan2007]_. This method gives also good results and is faster to process but it sometimes requires some more parameters adjustement.
Methods description
@ -275,7 +284,7 @@ Retina::printSetup
Outputs a string showing the used parameters setup
:return: a string which contains formatted parameters information
:return: a string which contains formated parameters information
Retina::run
+++++++++++
@ -286,6 +295,17 @@ Retina::run
:param inputImage: the input Mat image to be processed, can be gray level or BGR coded in any format (from 8bit to 16bits)
Retina::applyFastToneMapping
++++++++++++++++++++++++++++
.. ocv:function:: void Retina::applyFastToneMapping(InputArray inputImage, OutputArray outputToneMappedImage)
Method which processes an image in the aim to correct its luminance : correct backlight problems, enhance details in shadows. This method is designed to perform High Dynamic Range image tone mapping (compress >8bit/pixel images to 8bit/pixel). This is a simplified version of the Retina Parvocellular model (simplified version of the run/getParvo methods call) since it does not include the spatio-temporal filter modelling the Outer Plexiform Layer of the retina that performs spectral whitening and many other stuff. However, it works great for tone mapping and in a faster way.
Check the demos and experiments section to see examples and the way to perform tone mapping using the original retina model and the method.
:param inputImage: the input image to process (should be coded in float format : CV_32F, CV_32FC1, CV832F_C3, CV832F_C4, the 4th channel won't be considered).
:param outputToneMappedImage: the output 8bit/channel tone mapped image (CV_8U or CV_8UC3 format).
Retina::setColorSaturation
++++++++++++++++++++++++++

1
modules/contrib/include/opencv2/contrib.hpp
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@ -633,7 +633,6 @@ CV_EXPORTS_W void applyColorMap(InputArray src, OutputArray dst, int colormap);
CV_EXPORTS bool initModule_contrib();
}
#include "opencv2/contrib/retina.hpp"
#include "opencv2/contrib/openfabmap.hpp"
#endif

2
samples/cpp/CMakeLists.txt
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@ -5,7 +5,7 @@
SET(OPENCV_CPP_SAMPLES_REQUIRED_DEPS opencv_core opencv_flann opencv_imgproc
opencv_highgui opencv_ml opencv_video opencv_objdetect opencv_photo opencv_nonfree opencv_softcascade
opencv_features2d opencv_calib3d opencv_legacy opencv_contrib opencv_stitching opencv_videostab)
opencv_features2d opencv_calib3d opencv_legacy opencv_contrib opencv_stitching opencv_videostab opencv_bioinspired)
ocv_check_dependencies(${OPENCV_CPP_SAMPLES_REQUIRED_DEPS})

72
samples/cpp/OpenEXRimages_HighDynamicRange_Retina_toneMapping.cpp
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@ -10,8 +10,9 @@
#include <iostream>
#include <cstring>
#include "opencv2/contrib.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/bioinspired.hpp" // retina based algorithms
#include "opencv2/imgproc.hpp" // cvCvtcolor function
#include "opencv2/highgui.hpp" // display
static void help(std::string errorMessage)
{
@ -127,7 +128,7 @@ static void drawPlot(const cv::Mat curve, const std::string figureTitle, const i
normalize(imageInputRescaled, imageInputRescaled, 0.0, 255.0, cv::NORM_MINMAX);
}
cv::Ptr<cv::Retina> retina;
cv::Ptr<Retina> retina;
int retinaHcellsGain;
int localAdaptation_photoreceptors, localAdaptation_Gcells;
static void callBack_updateRetinaParams(int, void*)
@ -175,6 +176,12 @@ static void drawPlot(const cv::Mat curve, const std::string figureTitle, const i
}
bool useLogSampling = !strcmp(argv[argc-1], "log"); // check if user wants retina log sampling processing
int chosenMethod=0;
if (!strcmp(argv[argc-1], "fast"))
{
chosenMethod=1;
std::cout<<"Using fast method (no spectral whithning), adaptation of Meylan&al 2008 method"<<std::endl;
}
std::string inputImageName=argv[1];
@ -210,17 +217,22 @@ static void drawPlot(const cv::Mat curve, const std::string figureTitle, const i
* -> if the last parameter is 'log', then activate log sampling (favour foveal vision and subsamples peripheral vision)
*/
if (useLogSampling)
{
retina = cv::createRetina(inputImage.size(),true, cv::RETINA_COLOR_BAYER, true, 2.0, 10.0);
{
retina = createRetina(inputImage.size(),true, RETINA_COLOR_BAYER, true, 2.0, 10.0);
}
else// -> else allocate "classical" retina :
retina = cv::createRetina(inputImage.size());
retina = 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");
// create a fast retina tone mapper (Meyla&al algorithm)
std::cout<<"Allocating fast tone mapper..."<<std::endl;
//cv::Ptr<cv::RetinaFastToneMapping> fastToneMapper=createRetinaFastToneMapping(inputImage.size());
std::cout<<"Fast tone mapper allocated"<<std::endl;
// 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");
// desactivate Magnocellular pathway processing (motion information extraction) since it is not usefull here
retina->activateMovingContoursProcessing(false);
// desactivate Magnocellular pathway processing (motion information extraction) since it is not usefull here
retina->activateMovingContoursProcessing(false);
// declare retina output buffers
cv::Mat retinaOutput_parvo;
@ -230,20 +242,19 @@ static void drawPlot(const cv::Mat curve, const std::string figureTitle, const i
histogramClippingValue=0; // default value... updated with interface slider
//inputRescaleMat = inputImage;
//outputRescaleMat = imageInputRescaled;
cv::namedWindow("Retina input image (with cut edges histogram for basic pixels error avoidance)",1);
cv::createTrackbar("histogram edges clipping limit", "Retina input image (with cut edges histogram for basic pixels error avoidance)",&histogramClippingValue,50,callBack_rescaleGrayLevelMat);
cv::namedWindow("Processing configuration",1);
cv::createTrackbar("histogram edges clipping limit", "Processing configuration",&histogramClippingValue,50,callBack_rescaleGrayLevelMat);
cv::namedWindow("Retina Parvocellular pathway output : 16bit=>8bit image retina tonemapping", 1);
colorSaturationFactor=3;
cv::createTrackbar("Color saturation", "Retina Parvocellular pathway output : 16bit=>8bit image retina tonemapping", &colorSaturationFactor,5,callback_saturateColors);
cv::createTrackbar("Color saturation", "Processing configuration", &colorSaturationFactor,5,callback_saturateColors);
retinaHcellsGain=40;
cv::createTrackbar("Hcells gain", "Retina Parvocellular pathway output : 16bit=>8bit image retina tonemapping",&retinaHcellsGain,100,callBack_updateRetinaParams);
cv::createTrackbar("Hcells gain", "Processing configuration",&retinaHcellsGain,100,callBack_updateRetinaParams);
localAdaptation_photoreceptors=197;
localAdaptation_Gcells=190;
cv::createTrackbar("Ph sensitivity", "Retina Parvocellular pathway output : 16bit=>8bit image retina tonemapping", &localAdaptation_photoreceptors,199,callBack_updateRetinaParams);
cv::createTrackbar("Gcells sensitivity", "Retina Parvocellular pathway output : 16bit=>8bit image retina tonemapping", &localAdaptation_Gcells,199,callBack_updateRetinaParams);
cv::createTrackbar("Ph sensitivity", "Processing configuration", &localAdaptation_photoreceptors,199,callBack_updateRetinaParams);
cv::createTrackbar("Gcells sensitivity", "Processing configuration", &localAdaptation_Gcells,199,callBack_updateRetinaParams);
/////////////////////////////////////////////
@ -257,11 +268,28 @@ static void drawPlot(const cv::Mat curve, const std::string figureTitle, const i
while(continueProcessing)
{
// run retina filter
retina->run(imageInputRescaled);
// Retrieve and display retina output
retina->getParvo(retinaOutput_parvo);
cv::imshow("Retina input image (with cut edges histogram for basic pixels error avoidance)", imageInputRescaled/255.0);
cv::imshow("Retina Parvocellular pathway output : 16bit=>8bit image retina tonemapping", retinaOutput_parvo);
if (!chosenMethod)
{
retina->run(imageInputRescaled);
// Retrieve and display retina output
retina->getParvo(retinaOutput_parvo);
cv::imshow("Retina input image (with cut edges histogram for basic pixels error avoidance)", imageInputRescaled/255.0);
cv::imshow("Retina Parvocellular pathway output : 16bit=>8bit image retina tonemapping", retinaOutput_parvo);
cv::imwrite("HDRinput.jpg",imageInputRescaled/255.0);
cv::imwrite("RetinaToneMapping.jpg",retinaOutput_parvo);
}
else
{
// apply the simplified hdr tone mapping method
cv::Mat fastToneMappingOutput;
retina->applyFastToneMapping(imageInputRescaled, fastToneMappingOutput);
cv::imshow("Retina fast tone mapping output : 16bit=>8bit image retina tonemapping", fastToneMappingOutput);
}
/*cv::Mat fastToneMappingOutput_specificObject;
fastToneMapper->setup(3.f, 1.5f, 1.f);
fastToneMapper->applyFastToneMapping(imageInputRescaled, fastToneMappingOutput_specificObject);
cv::imshow("### Retina fast tone mapping output : 16bit=>8bit image retina tonemapping", fastToneMappingOutput_specificObject);
*/
cv::waitKey(10);
}
}catch(cv::Exception e)

11
samples/cpp/OpenEXRimages_HighDynamicRange_Retina_toneMapping_video.cpp
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@ -14,8 +14,9 @@
#include <stdio.h>
#include <cstring>
#include "opencv2/contrib.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/bioinspired.hpp" // retina based algorithms
#include "opencv2/imgproc.hpp" // cvCvtcolor function
#include "opencv2/highgui.hpp" // display
static void help(std::string errorMessage)
{
@ -160,7 +161,7 @@ static void rescaleGrayLevelMat(const cv::Mat &inputMat, cv::Mat &outputMat, con
}
cv::Ptr<cv::Retina> retina;
cv::Ptr<Retina> retina;
int retinaHcellsGain;
int localAdaptation_photoreceptors, localAdaptation_Gcells;
static void callBack_updateRetinaParams(int, void*)
@ -280,10 +281,10 @@ static void loadNewFrame(const std::string filenamePrototype, const int currentF
*/
if (useLogSampling)
{
retina = cv::createRetina(inputImage.size(),true, cv::RETINA_COLOR_BAYER, true, 2.0, 10.0);
retina = createRetina(inputImage.size(),true, RETINA_COLOR_BAYER, true, 2.0, 10.0);
}
else// -> else allocate "classical" retina :
retina = cv::createRetina(inputImage.size());
retina = 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");

11
samples/cpp/retinaDemo.cpp
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@ -9,7 +9,7 @@
#include <iostream>
#include <cstring>
#include "opencv2/contrib.hpp"
#include "opencv2/bioinspired.hpp"
#include "opencv2/highgui.hpp"
static void help(std::string errorMessage)
@ -106,15 +106,15 @@ int main(int argc, char* argv[]) {
try
{
// create a retina instance with default parameters setup, uncomment the initialisation you wanna test
cv::Ptr<cv::Retina> myRetina;
cv::Ptr<Retina> myRetina;
// if the last parameter is 'log', then activate log sampling (favour foveal vision and subsamples peripheral vision)
if (useLogSampling)
{
myRetina = cv::createRetina(inputFrame.size(), true, cv::RETINA_COLOR_BAYER, true, 2.0, 10.0);
myRetina = createRetina(inputFrame.size(), true, RETINA_COLOR_BAYER, true, 2.0, 10.0);
}
else// -> else allocate "classical" retina :
myRetina = cv::createRetina(inputFrame.size());
myRetina = 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");
@ -143,7 +143,8 @@ int main(int argc, char* argv[]) {
cv::imshow("retina input", inputFrame);
cv::imshow("Retina Parvo", retinaOutput_parvo);
cv::imshow("Retina Magno", retinaOutput_magno);
cv::waitKey(10);
cv::waitKey(5);
}
}catch(cv::Exception e)
{

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