173 lines
6.6 KiB
C++
173 lines
6.6 KiB
C++
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/*
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By downloading, copying, installing or using the software you agree to this license.
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If you do not agree to this license, do not download, install,
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copy or use the software.
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License Agreement
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For Open Source Computer Vision Library
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(3-clause BSD License)
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Copyright (C) 2000-2016, Intel Corporation, all rights reserved.
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Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
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Copyright (C) 2009-2016, NVIDIA Corporation, all rights reserved.
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Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved.
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Copyright (C) 2015-2016, OpenCV Foundation, all rights reserved.
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Copyright (C) 2015-2016, Itseez Inc., all rights reserved.
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Third party copyrights are property of their respective owners.
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Redistribution and use in source and binary forms, with or without modification,
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are permitted provided that the following conditions are met:
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* Redistributions of source code must retain the above copyright notice,
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this list of conditions and the following disclaimer.
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* Redistributions in binary form must reproduce the above copyright notice,
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this list of conditions and the following disclaimer in the documentation
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and/or other materials provided with the distribution.
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* Neither the names of the copyright holders nor the names of the contributors
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may be used to endorse or promote products derived from this software
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without specific prior written permission.
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This software is provided by the copyright holders and contributors "as is" and
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any express or implied warranties, including, but not limited to, the implied
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warranties of merchantability and fitness for a particular purpose are disclaimed.
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In no event shall copyright holders or contributors be liable for any direct,
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indirect, incidental, special, exemplary, or consequential damages
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(including, but not limited to, procurement of substitute goods or services;
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loss of use, data, or profits; or business interruption) however caused
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and on any theory of liability, whether in contract, strict liability,
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or tort (including negligence or otherwise) arising in any way out of
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the use of this software, even if advised of the possibility of such damage.
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*/
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/*
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Contributed by Gregor Kovalcik <gregor dot kovalcik at gmail dot com>
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based on code provided by Martin Krulis, Jakub Lokoc and Tomas Skopal.
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References:
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Martin Krulis, Jakub Lokoc, Tomas Skopal.
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Efficient Extraction of Clustering-Based Feature Signatures Using GPU Architectures.
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Multimedia tools and applications, 75(13), pp.: 8071<EFBFBD>8103, Springer, ISSN: 1380-7501, 2016
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Christian Beecks, Merih Seran Uysal, Thomas Seidl.
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Signature quadratic form distance.
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In Proceedings of the ACM International Conference on Image and Video Retrieval, pages 438-445.
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ACM, 2010.
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*/
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#include <opencv2/core.hpp>
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#include <opencv2/highgui.hpp>
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#include <opencv2/xfeatures2d.hpp>
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#include <iostream>
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#include <string>
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using namespace std;
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using namespace cv;
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using namespace xfeatures2d;
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void printHelpMessage(void);
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void printHelpMessage(void)
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{
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cout << "Example of the PCTSignatures algorithm computing and visualizing\n"
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"image signature for one image, or comparing multiple images with the first\n"
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"image using the signature quadratic form distance.\n\n"
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"Usage: pct_signatures ImageToProcessAndDisplay\n"
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"or: pct_signatures ReferenceImage [ImagesToCompareWithTheReferenceImage]\n\n"
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"The program has 2 modes:\n"
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"- single argument: program computes and visualizes the image signature\n"
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"- multiple arguments: program compares the first image to the others\n"
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" using pct signatures and signature quadratic form distance (SQFD)";
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}
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/** @brief
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Example of the PCTSignatures algorithm.
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The program has 2 modes:
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- single argument mode, where the program computes and visualizes the image signature
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- multiple argument mode, where the program compares the first image to the others
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using signatures and signature quadratic form distance (SQFD)
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*/
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int main(int argc, char** argv)
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{
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if (argc < 2) // Check arguments
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{
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printHelpMessage();
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return 1;
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}
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Mat source;
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source = imread(argv[1]); // Read the file
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if (!source.data) // Check for invalid input
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{
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cerr << "Could not open or find the image: " << argv[1];
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return -1;
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}
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Mat signature, result; // define variables
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int initSampleCount = 2000;
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int initSeedCount = 400;
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int grayscaleBitsPerPixel = 4;
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vector<Point2f> initPoints;
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namedWindow("Source", WINDOW_AUTOSIZE); // Create windows for display.
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namedWindow("Result", WINDOW_AUTOSIZE);
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// create the algorithm
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PCTSignatures::generateInitPoints(initPoints, initSampleCount, PCTSignatures::UNIFORM);
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Ptr<PCTSignatures> pctSignatures = PCTSignatures::create(initPoints, initSeedCount);
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pctSignatures->setGrayscaleBits(grayscaleBitsPerPixel);
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// compute and visualize the first image
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double start = (double)getTickCount();
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pctSignatures->computeSignature(source, signature);
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double end = (double)getTickCount();
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cout << "Signature of the reference image computed in " << (end - start) / (getTickFrequency() * 1.0f) << " seconds." << endl;
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PCTSignatures::drawSignature(source, signature, result);
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imshow("Source", source); // show the result
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imshow("Result", result);
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if (argc == 2) // single image -> finish right after the visualization
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{
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waitKey(0); // Wait for user input
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return 0;
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}
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// multiple images -> compare to the first one
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else
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{
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vector<Mat> images;
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vector<Mat> signatures;
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vector<float> distances;
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for (int i = 2; i < argc; i++)
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{
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Mat image = imread(argv[i]);
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if (!source.data) // Check for invalid input
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{
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cerr << "Could not open or find the image: " << argv[i] << std::endl;
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return 1;
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}
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images.push_back(image);
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}
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pctSignatures->computeSignatures(images, signatures);
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Ptr<PCTSignaturesSQFD> pctSQFD = PCTSignaturesSQFD::create();
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pctSQFD->computeQuadraticFormDistances(signature, signatures, distances);
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for (int i = 0; i < (int)(distances.size()); i++)
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{
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cout << "Image: " << argv[i + 2] << ", similarity: " << distances[i] << endl;
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}
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waitKey(0); // Wait for user input
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}
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return 0;
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}
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