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//============================================================================
// Name : retinademo.cpp
// Author : Alexandre Benoit, benoit.alexandre.vision@gmail.com
// Version : 0.1
// Copyright : LISTIC/GIPSA French Labs, july 2011
// Description : Gipsa/LISTIC Labs retina demo in C++, Ansi-style
//============================================================================
#include <iostream>
#include <cstring>
#include "opencv2/bioinspired.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/videoio.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/core/ocl.hpp"
const std::string keys =
"{image | | Input from image file }"
"{video | | Input from video file }"
"{camera | 0 | Index of input camera. If image or video is not specified, camera 0 will be used }"
"{log | | Activate retina log sampling }"
"{ocl | | Use OpenCL acceleration if possible }"
"{help | | Print help}";
int main(int argc, char* argv[])
{
// welcome message
std::cout<<"****************************************************"<<std::endl
<<"* Retina demonstration : demonstrates the use of is a wrapper class of the Gipsa/Listic Labs retina model."<<std::endl
<<"* This retina model allows spatio-temporal image processing (applied on still images, video sequences)."<<std::endl
<<"* As a summary, these are the retina model properties:"<<std::endl
<<"* => It applies a spectral whithening (mid-frequency details enhancement)"<<std::endl
<<"* => high frequency spatio-temporal noise reduction"<<std::endl
<<"* => low frequency luminance to be reduced (luminance range compression)"<<std::endl
<<"* => local logarithmic luminance compression allows details to be enhanced in low light conditions\n"<<std::endl
<<"* for more information, reer to the following papers :"<<std::endl
<<"* 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
<<"* 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
<<"* => reports comments/remarks at benoit.alexandre.vision@gmail.com"<<std::endl
<<"* => more informations and papers at : http://sites.google.com/site/benoitalexandrevision/"<<std::endl
<<"****************************************************"<<std::endl
<<" NOTE : this program generates the default retina parameters file 'RetinaDefaultParameters.xml'"<<std::endl
<<" => you can use this to fine tune parameters and load them if you save to file 'RetinaSpecificParameters.xml'"<<std::endl;
cv::CommandLineParser parser(argc, argv, keys);
if(!parser.check() || parser.has("help")) {
parser.printMessage();
return 0;
}
bool useLogSampling = parser.has("log"); // check if user wants retina log sampling processing
bool useOCL = parser.has("ocl");
cv::ocl::setUseOpenCL(useOCL);
if(useOCL && !cv::ocl::useOpenCL())
{
std::cout << "Failed to enable OpenCL\n";
}
// declare the retina input buffer... that will be fed differently in regard of the input media
cv::Mat inputFrame;
cv::VideoCapture videoCapture; // in case a video media is used, its manager is declared here
if(parser.has("video"))
videoCapture.open(parser.get<cv::String>("video"));
else if(parser.has("image"))
inputFrame = cv::imread(parser.get<cv::String>("image"));
else
videoCapture.open(parser.get<int>("camera"));
if (videoCapture.isOpened())
{
videoCapture >> inputFrame;
}
if(inputFrame.empty())
{
std::cout << "Failed to open media source\n";
return 0;
}
//////////////////////////////////////////////////////////////////////////////
// Program start in a try/catch safety context (Retina may throw errors)
try
{
// create a retina instance with default parameters setup, uncomment the initialisation you wanna test
cv::Ptr<cv::bioinspired::Retina> myRetina;
// if the last parameter is 'log', then activate log sampling (favour foveal vision and subsamples peripheral vision)
if (useLogSampling)
{
myRetina = cv::bioinspired::Retina::create(inputFrame.size(),
true, cv::bioinspired::RETINA_COLOR_BAYER, true, 2.0, 10.0);
}
else// -> else allocate "classical" retina :
myRetina = cv::bioinspired::Retina::create(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");
// load parameters if file exists
myRetina->setup("RetinaSpecificParameters.xml");
myRetina->clearBuffers();
// declare retina output buffers
cv::UMat retinaOutput_parvo;
cv::UMat retinaOutput_magno;
// processing loop with stop condition
int64 totalTime = 0;
int64 totalFrames = 0;
while(true)
{
// if using video stream, then, grabbing a new frame, else, input remains the same
if (videoCapture.isOpened())
videoCapture>>inputFrame;
if(inputFrame.empty())
break;
// run retina filter
int64 frameTime = cv::getTickCount();
myRetina->run(inputFrame);
// Retrieve and display retina output
frameTime = cv::getTickCount() - frameTime;
totalTime += frameTime;
totalFrames++;
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);
int key = cv::waitKey(5);
if(key == 'q')
break;
}
std::cout << "\nMean frame processing time: " << (totalTime / cv::getTickFrequency()) / totalFrames << " s" << std::endl;
std::cout << "Retina demo end" << std::endl;
}
catch(const cv::Exception& e)
{
std::cerr<<"Error using Retina : "<<e.what()<<std::endl;
}
return 0;
}
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