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Commit 8dc1920b authored by Vladislav Sovrasov's avatar Vladislav Sovrasov
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bioinspired: cleanup in samples

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modules/bioinspired/samples/basicRetina.cpp deleted 100644 → 0
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//============================================================================
// Name : retinademo.cpp
// Author : Alexandre Benoit, benoit.alexandre.vision@gmail.com
// Version : 0.1
// Copyright : LISTIC/GIPSA French Labs, May 2015
// Description : Gipsa/LISTIC Labs quick retina demo in C++, Ansi-style
//============================================================================
// include bioinspired module and OpenCV core utilities
#include "opencv2/bioinspired.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/videoio.hpp"
#include "opencv2/highgui.hpp"
#include <iostream>
#include <cstring>
// main function
int main(int argc, char* argv[]) {
// basic input arguments checking
if (argc>1)
{
std::cout<<"****************************************************"<<std::endl;
std::cout<<"* Retina demonstration : demonstrates the use of is a wrapper class of the Gipsa/Listic Labs retina model."<<std::endl;
std::cout<<"* This retina model allows spatio-temporal image processing (applied on a webcam sequences)."<<std::endl;
std::cout<<"* As a summary, these are the retina model properties:"<<std::endl;
std::cout<<"* => It applies a spectral whithening (mid-frequency details enhancement)"<<std::endl;
std::cout<<"* => high frequency spatio-temporal noise reduction"<<std::endl;
std::cout<<"* => low frequency luminance to be reduced (luminance range compression)"<<std::endl;
std::cout<<"* => local logarithmic luminance compression allows details to be enhanced in low light conditions\n"<<std::endl;
std::cout<<"* for more information, reer to the following papers :"<<std::endl;
std::cout<<"* 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;
std::cout<<"* 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;
std::cout<<"* => reports comments/remarks at benoit.alexandre.vision@gmail.com"<<std::endl;
std::cout<<"* => more informations and papers at : http://sites.google.com/site/benoitalexandrevision/"<<std::endl;
std::cout<<"****************************************************"<<std::endl;
std::cout<<" NOTE : this program generates the default retina parameters file 'RetinaDefaultParameters.xml'"<<std::endl;
std::cout<<" => you can use this to fine tune parameters and load them if you save to file 'RetinaSpecificParameters.xml'"<<std::endl;
if (strcmp(argv[1], "help")==0){
std::cout<<"No help provided for now, please test the retina Demo for a more complete program"<<std::endl;
}
}
std::string inputMediaType=argv[1];
// declare the retina input buffer.
cv::Mat inputFrame;
// setup webcam reader and grab a first frame to get its size
cv::VideoCapture videoCapture(0);
videoCapture>>inputFrame;
// allocate a retina instance with input size equal to the one of the loaded image
cv::Ptr<cv::bioinspired::Retina> myRetina = cv::bioinspired::createRetina(inputFrame.size());
/* retina parameters management methods use sample
-> save current (here default) retina parameters to a xml file (you may use it only one time to get the file and modify it)
*/
myRetina->write("RetinaDefaultParameters.xml");
// -> load parameters if file exists
myRetina->setup("RetinaSpecificParameters.xml");
// reset all retina buffers (open your eyes)
myRetina->clearBuffers();
// declare retina output buffers
cv::Mat retinaOutput_parvo;
cv::Mat retinaOutput_magno;
//main processing loop
bool stillProcess=true;
while(stillProcess){
// if using video stream, then, grabbing a new frame, else, input remains the same
if (videoCapture.isOpened())
videoCapture>>inputFrame;
else
stillProcess=false;
// run retina filter
myRetina->run(inputFrame);
// Retrieve and display retina output
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);
cv::waitKey(5);
}
}
modules/bioinspired/samples/retinaDemo.cpp
View file @ 8dc1920b
......@@ -13,96 +13,66 @@
#include "opencv2/imgcodecs.hpp"
#include "opencv2/videoio.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/core/ocl.hpp"
static void help(std::string errorMessage)
{
std::cout<<"Program init error : "<<errorMessage<<std::endl;
std::cout<<"\nProgram call procedure : retinaDemo [processing mode] [Optional : media target] [Optional LAST parameter: \"log\" to activate retina log sampling]"<<std::endl;
std::cout<<"\t[processing mode] :"<<std::endl;
std::cout<<"\t -image : for still image processing"<<std::endl;
std::cout<<"\t -video : for video stream processing"<<std::endl;
std::cout<<"\t[Optional : media target] :"<<std::endl;
std::cout<<"\t if processing an image or video file, then, specify the path and filename of the target to process"<<std::endl;
std::cout<<"\t leave empty if processing video stream coming from a connected video device"<<std::endl;
std::cout<<"\t[Optional : activate retina log sampling] : an optional last parameter can be specified for retina spatial log sampling"<<std::endl;
std::cout<<"\t set \"log\" without quotes to activate this sampling, output frame size will be divided by 4"<<std::endl;
std::cout<<"\nExamples:"<<std::endl;
std::cout<<"\t-Image processing : ./retinaDemo -image lena.jpg"<<std::endl;
std::cout<<"\t-Image processing with log sampling : ./retinaDemo -image lena.jpg log"<<std::endl;
std::cout<<"\t-Video processing : ./retinaDemo -video myMovie.mp4"<<std::endl;
std::cout<<"\t-Live video processing : ./retinaDemo -video"<<std::endl;
std::cout<<"\nPlease start again with new parameters"<<std::endl;
}
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;
std::cout<<"* Retina demonstration : demonstrates the use of is a wrapper class of the Gipsa/Listic Labs retina model."<<std::endl;
std::cout<<"* This retina model allows spatio-temporal image processing (applied on still images, video sequences)."<<std::endl;
std::cout<<"* As a summary, these are the retina model properties:"<<std::endl;
std::cout<<"* => It applies a spectral whithening (mid-frequency details enhancement)"<<std::endl;
std::cout<<"* => high frequency spatio-temporal noise reduction"<<std::endl;
std::cout<<"* => low frequency luminance to be reduced (luminance range compression)"<<std::endl;
std::cout<<"* => local logarithmic luminance compression allows details to be enhanced in low light conditions\n"<<std::endl;
std::cout<<"* for more information, reer to the following papers :"<<std::endl;
std::cout<<"* 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;
std::cout<<"* 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;
std::cout<<"* => reports comments/remarks at benoit.alexandre.vision@gmail.com"<<std::endl;
std::cout<<"* => more informations and papers at : http://sites.google.com/site/benoitalexandrevision/"<<std::endl;
std::cout<<"****************************************************"<<std::endl;
std::cout<<" NOTE : this program generates the default retina parameters file 'RetinaDefaultParameters.xml'"<<std::endl;
std::cout<<" => you can use this to fine tune parameters and load them if you save to file 'RetinaSpecificParameters.xml'"<<std::endl;
// basic input arguments checking
if (argc<2)
{
help("bad number of parameter");
return -1;
}
bool useLogSampling = !strcmp(argv[argc-1], "log"); // check if user wants retina log sampling processing
std::string inputMediaType=argv[1];
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
//////////////////////////////////////////////////////////////////////////////
// checking input media type (still image, video file, live video acquisition)
if (!strcmp(inputMediaType.c_str(), "-image") && argc >= 3)
{
std::cout<<"RetinaDemo: processing image "<<argv[2]<<std::endl;
// image processing case
inputFrame = cv::imread(std::string(argv[2]), 1); // load image in RGB mode
}else
if (!strcmp(inputMediaType.c_str(), "-video"))
{
if (argc == 2 || (argc == 3 && useLogSampling)) // attempt to grab images from a video capture device
{
videoCapture.open(0);
}else// attempt to grab images from a video filestream
{
std::cout<<"RetinaDemo: processing video stream "<<argv[2]<<std::endl;
videoCapture.open(argv[2]);
}
// grab a first frame to check if everything is ok
videoCapture>>inputFrame;
}else
{
// bad command parameter
help("bad command parameter");
return -1;
}
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 (inputFrame.empty())
{
help("Input media could not be loaded, aborting");
return -1;
}
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)
......@@ -127,8 +97,8 @@ int main(int argc, char* argv[])
myRetina->clearBuffers();
// declare retina output buffers
cv::Mat retinaOutput_parvo;
cv::Mat retinaOutput_magno;
cv::UMat retinaOutput_parvo;
cv::UMat retinaOutput_magno;
// processing loop with stop condition
bool continueProcessing=true; // FIXME : not yet managed during process...
......@@ -147,7 +117,9 @@ int main(int argc, char* argv[])
cv::imshow("Retina Parvo", retinaOutput_parvo);
cv::imshow("Retina Magno", retinaOutput_magno);
cv::waitKey(5);
int key = cv::waitKey(5);
if(key == 'q')
break;
}
}catch(cv::Exception e)
{
......
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