Java tutorial
/* * This file is part of the LIRE project: http://lire-project.net * LIRE is free software; you can redistribute it and/or modify * it under the terms of the GNU General Public License as published by * the Free Software Foundation; either version 2 of the License, or * (at your option) any later version. * * LIRE is distributed in the hope that it will be useful, * but WITHOUT ANY WARRANTY; without even the implied warranty of * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the * GNU General Public License for more details. * * You should have received a copy of the GNU General Public License * along with LIRE; if not, write to the Free Software * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA * * We kindly ask you to refer the any or one of the following publications in * any publication mentioning or employing Lire: * * Lux Mathias, Savvas A. Chatzichristofis. Lire: Lucene Image Retrieval - * An Extensible Java CBIR Library. In proceedings of the 16th ACM International * Conference on Multimedia, pp. 1085-1088, Vancouver, Canada, 2008 * URL: http://doi.acm.org/10.1145/1459359.1459577 * * Lux Mathias. Content Based Image Retrieval with LIRE. In proceedings of the * 19th ACM International Conference on Multimedia, pp. 735-738, Scottsdale, * Arizona, USA, 2011 * URL: http://dl.acm.org/citation.cfm?id=2072432 * * Mathias Lux, Oge Marques. Visual Information Retrieval using Java and LIRE * Morgan & Claypool, 2013 * URL: http://www.morganclaypool.com/doi/abs/10.2200/S00468ED1V01Y201301ICR025 */ package net.semanticmetadata.lire.imageanalysis.features.local.opencvfeatures; import net.semanticmetadata.lire.imageanalysis.features.LocalFeature; import net.semanticmetadata.lire.imageanalysis.features.LocalFeatureExtractor; import org.opencv.core.Core; import org.opencv.core.CvType; import org.opencv.core.Mat; import org.opencv.core.MatOfKeyPoint; import org.opencv.features2d.DescriptorExtractor; import org.opencv.features2d.FeatureDetector; import org.opencv.features2d.KeyPoint; import org.opencv.imgproc.Imgproc; import java.awt.image.BufferedImage; import java.awt.image.DataBufferByte; import java.io.File; import java.io.FileWriter; import java.io.IOException; import java.util.Iterator; import java.util.LinkedList; import java.util.List; /** * Created by Nektarios on 1/10/2014. * * @author Nektarios Anagnostopoulos, nek.anag@gmail.com */ public class CvSiftExtractor implements LocalFeatureExtractor { //Default: int nfeatures=0, int nOctaveLayers=3, double contrastThreshold=0.04, double edgeThreshold=10, double sigma=1.6 private int nfeatures = 0; private int nOctaveLayers = 3; private double contrastThreshold = 0.04; private double edgeThreshold = 10; private double sigma = 1.6; LinkedList<CvSiftFeature> features = null; FeatureDetector detector; DescriptorExtractor extractor; // private boolean passingParams = false; public CvSiftExtractor() { init(); } public CvSiftExtractor(int features, int OctaveLayers, double contrastThres, double edgeThres, double sgm) { this.nfeatures = features; this.nOctaveLayers = OctaveLayers; this.contrastThreshold = contrastThres; this.edgeThreshold = edgeThres; this.sigma = sgm; // this.passingParams = true; init(); } private void init() { System.loadLibrary(Core.NATIVE_LIBRARY_NAME); detector = FeatureDetector.create(FeatureDetector.SIFT); extractor = DescriptorExtractor.create(DescriptorExtractor.SIFT); // if (passingParams) { try { File temp = File.createTempFile("tempFile", ".tmp"); //int nfeatures=0, int nOctaveLayers=3, double contrastThreshold=0.04, double edgeThreshold=10, double sigma=1.6 //String settings = "%YAML:1.0\nnfeatures: 0\nnOctaveLayers: 3\ncontrastThreshold: 0.04\nedgeThreshold: 10\nsigma: 1.6"; String settings = "%YAML:1.0\nnfeatures: " + nfeatures + "\nnOctaveLayers: " + nOctaveLayers + "\ncontrastThreshold: " + contrastThreshold + "\nedgeThreshold: " + edgeThreshold + "\nsigma: " + sigma; FileWriter writer = new FileWriter(temp, false); writer.write(settings); writer.close(); extractor.read(temp.getPath()); detector.read(temp.getPath()); temp.deleteOnExit(); } catch (IOException e) { e.printStackTrace(); } // } } @Override public LinkedList<CvSiftFeature> getFeatures() { return features; } @Override public Class<? extends LocalFeature> getClassOfFeatures() { return CvSiftFeature.class; } @Override public void extract(BufferedImage img) { MatOfKeyPoint keypoints = new MatOfKeyPoint(); Mat descriptors = new Mat(); List<KeyPoint> myKeys; // Mat img_object = Highgui.imread(image, 0); //0 = CV_LOAD_IMAGE_GRAYSCALE // detector.detect(img_object, keypoints); byte[] data = ((DataBufferByte) img.getRaster().getDataBuffer()).getData(); Mat matRGB = new Mat(img.getHeight(), img.getWidth(), CvType.CV_8UC3); matRGB.put(0, 0, data); Mat matGray = new Mat(img.getHeight(), img.getWidth(), CvType.CV_8UC1); Imgproc.cvtColor(matRGB, matGray, Imgproc.COLOR_BGR2GRAY); //TODO: RGB or BGR? byte[] dataGray = new byte[matGray.rows() * matGray.cols() * (int) (matGray.elemSize())]; matGray.get(0, 0, dataGray); detector.detect(matGray, keypoints); extractor.compute(matGray, keypoints, descriptors); myKeys = keypoints.toList(); features = new LinkedList<CvSiftFeature>(); KeyPoint key; CvSiftFeature feat; double[] desc; int cols, rows = myKeys.size(); for (int i = 0; i < rows; i++) { cols = (descriptors.row(i)).cols(); desc = new double[cols]; key = myKeys.get(i); for (int j = 0; j < cols; j++) { desc[j] = descriptors.get(i, j)[0]; } feat = new CvSiftFeature(key.pt.x, key.pt.y, key.size, desc); features.add(feat); } } public LinkedList<CvSiftFeature> computeSiftKeypoints(BufferedImage img) { MatOfKeyPoint keypoints = new MatOfKeyPoint(); List<KeyPoint> myKeys; // Mat img_object = Highgui.imread(image, 0); //0 = CV_LOAD_IMAGE_GRAYSCALE // detector.detect(img_object, keypoints); byte[] data = ((DataBufferByte) img.getRaster().getDataBuffer()).getData(); Mat matRGB = new Mat(img.getHeight(), img.getWidth(), CvType.CV_8UC3); matRGB.put(0, 0, data); Mat matGray = new Mat(img.getHeight(), img.getWidth(), CvType.CV_8UC1); Imgproc.cvtColor(matRGB, matGray, Imgproc.COLOR_BGR2GRAY); //TODO: RGB or BGR? byte[] dataGray = new byte[matGray.rows() * matGray.cols() * (int) (matGray.elemSize())]; matGray.get(0, 0, dataGray); detector.detect(matGray, keypoints); myKeys = keypoints.toList(); LinkedList<CvSiftFeature> myKeypoints = new LinkedList<CvSiftFeature>(); KeyPoint key; CvSiftFeature feat; for (Iterator<KeyPoint> iterator = myKeys.iterator(); iterator.hasNext();) { key = iterator.next(); feat = new CvSiftFeature(key.pt.x, key.pt.y, key.size, null); myKeypoints.add(feat); } return myKeypoints; } public String getParameters() { return "nfeatures: " + nfeatures + " nOctaveLayers: " + nOctaveLayers + " contrastThreshold: " + contrastThreshold + " edgeThreshold: " + edgeThreshold + " sigma: " + sigma; } }