/* 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 (3-clause BSD License) Copyright (C) 2000-2016, Intel Corporation, all rights reserved. Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved. Copyright (C) 2009-2016, NVIDIA Corporation, all rights reserved. Copyright (C) 2010-2013, Advanced Micro Devices, Inc., all rights reserved. Copyright (C) 2015-2016, OpenCV Foundation, all rights reserved. Copyright (C) 2015-2016, Itseez Inc., 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: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither the names of the copyright holders nor the names of the contributors may be used to endorse or promote products derived from this software without specific prior written permission. This software is provided by the copyright holders and contributors "as is" and any express or implied warranties, including, but not limited to, the implied warranties of merchantability and fitness for a particular purpose are disclaimed. In no event shall copyright holders or contributors be liable for any direct, indirect, incidental, special, exemplary, or consequential damages (including, but not limited to, procurement of substitute goods or services; loss of use, data, or profits; or business interruption) however caused and on any theory of liability, whether in contract, strict liability, or tort (including negligence or otherwise) arising in any way out of the use of this software, even if advised of the possibility of such damage. */ /* Contributed by Gregor Kovalcik 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.: 8071–8103, 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 #include #include #include #include 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 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::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 images; vector signatures; vector 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 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; }