Repository for OpenCV's extra modules
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2013, OpenCV Foundation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
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// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
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//M*/
#include <opencv2/core/utility.hpp>
#include <opencv2/saliency.hpp>
#include <opencv2/highgui.hpp>
#include <iostream>
using namespace std;
using namespace cv;
static const char* keys =
{ "{@saliency_algorithm | | Saliency algorithm <saliencyAlgorithmType.[saliencyAlgorithmTypeSubType]> }"
"{@video_name | | video name }"
"{@start_frame |1| Start frame }"
"{@training_path |1| Path of the folder containing the trained files}" };
static void help()
{
cout << "\nThis example shows the functionality of \"Saliency \""
"Call:\n"
"./example_saliency_computeSaliency <saliencyAlgorithmSubType> <video_name> <start_frame> \n"
<< endl;
}
int main( int argc, char** argv )
{
CommandLineParser parser( argc, argv, keys );
String saliency_algorithm = parser.get<String>( 0 );
String video_name = parser.get<String>( 1 );
int start_frame = parser.get<int>( 2 );
String training_path = parser.get<String>( 3 );
if( saliency_algorithm.empty() || video_name.empty() )
{
help();
return -1;
}
//open the capture
VideoCapture cap;
cap.open( video_name );
cap.set( CAP_PROP_POS_FRAMES, start_frame );
if( !cap.isOpened() )
{
help();
cout << "***Could not initialize capturing...***\n";
cout << "Current parameter's value: \n";
parser.printMessage();
return -1;
}
Mat frame;
//instantiates the specific Saliency
Ptr<Saliency> saliencyAlgorithm = Saliency::create( saliency_algorithm );
if( saliencyAlgorithm == NULL )
{
cout << "***Error in the instantiation of the saliency algorithm...***\n";
return -1;
}
Mat binaryMap;
Mat image;
cap >> frame;
if( frame.empty() )
{
return 0;
}
frame.copyTo( image );
if( saliency_algorithm.find( "SPECTRAL_RESIDUAL" ) == 0 )
{
Mat saliencyMap;
if( saliencyAlgorithm->computeSaliency( image, saliencyMap ) )
{
StaticSaliencySpectralResidual spec;
spec.computeBinaryMap( saliencyMap, binaryMap );
imshow( "Saliency Map", saliencyMap );
imshow( "Original Image", image );
imshow( "Binary Map", binaryMap );
waitKey( 0 );
}
}
else if( saliency_algorithm.find( "BING" ) == 0 )
{
if( training_path.empty() )
{
cout << "Path of trained files missing! " << endl;
return -1;
}
else
{
vector<Vec4i> saliencyMap;
saliencyAlgorithm.dynamicCast<ObjectnessBING>()->setTrainingPath( training_path );
saliencyAlgorithm.dynamicCast<ObjectnessBING>()->setBBResDir( training_path + "/Results" );
if( saliencyAlgorithm->computeSaliency( image, saliencyMap ) )
{
std::cout << "-----------------OBJECTNESS-----------" << std::endl;
std::cout << "OBJECTNESS BOUNDING BOX VECTOR SIZE" << saliencyMap.size() << std::endl;
std::cout << " " << saliencyMap[0] << std::endl;
std::cout << " " << saliencyMap[1] << std::endl;
std::cout << " " << saliencyMap[2] << std::endl;
}
}
}
else if( saliency_algorithm.find( "BinWangApr2014" ) == 0 )
{
Ptr<Size> size= Ptr<Size>( new Size( 64, 64 ) ) ;
saliencyAlgorithm.dynamicCast<MotionSaliencyBinWangApr2014>()->setWsize(size);
saliencyAlgorithm.dynamicCast<MotionSaliencyBinWangApr2014>()->init();
// Create an fake image test
Mat test( 64, 64, CV_8U );
RNG rand;
for(int i=0; i<test.rows; i++)
for(int j=0; j<test.cols; j++)
{
if(i<12 && i>=6 && j<12 && j>=6)
test.at<uchar>(i,j)=255;
else
test.at<uchar>(i,j)=rand.uniform(40,60);
}
//imshow("Test", test);
//waitKey(0);
Mat saliencyMap;
if( saliencyAlgorithm->computeSaliency( test, saliencyMap ) )
{
std::cout<<"motion saliency done"<<std::endl;
}
}
return 0;
}