//============================================================================ // 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")); 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; }