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