OpenCV_4.2.0/opencv_contrib-4.2.0/modules/xfeatures2d/samples/pct_signatures.cpp

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/*
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/*
Contributed by Gregor Kovalcik <gregor dot kovalcik at gmail dot com>
based on code provided by Martin Krulis, Jakub Lokoc and Tomas Skopal.
References:
Martin Krulis, Jakub Lokoc, Tomas Skopal.
Efficient Extraction of Clustering-Based Feature Signatures Using GPU Architectures.
Multimedia tools and applications, 75(13), pp.: 8071<37>8103, Springer, ISSN: 1380-7501, 2016
Christian Beecks, Merih Seran Uysal, Thomas Seidl.
Signature quadratic form distance.
In Proceedings of the ACM International Conference on Image and Video Retrieval, pages 438-445.
ACM, 2010.
*/
#include <opencv2/core.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/xfeatures2d.hpp>
#include <iostream>
#include <string>
using namespace std;
using namespace cv;
using namespace xfeatures2d;
void printHelpMessage(void);
void printHelpMessage(void)
{
cout << "Example of the PCTSignatures algorithm computing and visualizing\n"
"image signature for one image, or comparing multiple images with the first\n"
"image using the signature quadratic form distance.\n\n"
"Usage: pct_signatures ImageToProcessAndDisplay\n"
"or: pct_signatures ReferenceImage [ImagesToCompareWithTheReferenceImage]\n\n"
"The program has 2 modes:\n"
"- single argument: program computes and visualizes the image signature\n"
"- multiple arguments: program compares the first image to the others\n"
" using pct signatures and signature quadratic form distance (SQFD)";
}
/** @brief
Example of the PCTSignatures algorithm.
The program has 2 modes:
- single argument mode, where the program computes and visualizes the image signature
- multiple argument mode, where the program compares the first image to the others
using signatures and signature quadratic form distance (SQFD)
*/
int main(int argc, char** argv)
{
if (argc < 2) // Check arguments
{
printHelpMessage();
return 1;
}
Mat source;
source = imread(argv[1]); // Read the file
if (!source.data) // Check for invalid input
{
cerr << "Could not open or find the image: " << argv[1];
return -1;
}
Mat signature, result; // define variables
int initSampleCount = 2000;
int initSeedCount = 400;
int grayscaleBitsPerPixel = 4;
vector<Point2f> initPoints;
namedWindow("Source", WINDOW_AUTOSIZE); // Create windows for display.
namedWindow("Result", WINDOW_AUTOSIZE);
// create the algorithm
PCTSignatures::generateInitPoints(initPoints, initSampleCount, PCTSignatures::UNIFORM);
Ptr<PCTSignatures> pctSignatures = PCTSignatures::create(initPoints, initSeedCount);
pctSignatures->setGrayscaleBits(grayscaleBitsPerPixel);
// compute and visualize the first image
double start = (double)getTickCount();
pctSignatures->computeSignature(source, signature);
double end = (double)getTickCount();
cout << "Signature of the reference image computed in " << (end - start) / (getTickFrequency() * 1.0f) << " seconds." << endl;
PCTSignatures::drawSignature(source, signature, result);
imshow("Source", source); // show the result
imshow("Result", result);
if (argc == 2) // single image -> finish right after the visualization
{
waitKey(0); // Wait for user input
return 0;
}
// multiple images -> compare to the first one
else
{
vector<Mat> images;
vector<Mat> signatures;
vector<float> distances;
for (int i = 2; i < argc; i++)
{
Mat image = imread(argv[i]);
if (!source.data) // Check for invalid input
{
cerr << "Could not open or find the image: " << argv[i] << std::endl;
return 1;
}
images.push_back(image);
}
pctSignatures->computeSignatures(images, signatures);
Ptr<PCTSignaturesSQFD> pctSQFD = PCTSignaturesSQFD::create();
pctSQFD->computeQuadraticFormDistances(signature, signatures, distances);
for (int i = 0; i < (int)(distances.size()); i++)
{
cout << "Image: " << argv[i + 2] << ", similarity: " << distances[i] << endl;
}
waitKey(0); // Wait for user input
}
return 0;
}