org.openimaj.demos.FVFWDSift Maven / Gradle / Ivy

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A project for various tests that don't quite constitute demos but might be useful to look at.
There is a newer version: 1.3.10
/**
 * Copyright (c) 2011, The University of Southampton and the individual contributors.
 * All rights reserved.
 *
 * 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 name of the University of Southampton nor the names of its
 * 	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 THE COPYRIGHT OWNER 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.
 */
package org.openimaj.demos;

import java.io.File;
import java.io.IOException;
import java.util.Arrays;

import org.openimaj.feature.local.list.LocalFeatureList;
import org.openimaj.feature.local.list.MemoryLocalFeatureList;
import org.openimaj.image.FImage;
import org.openimaj.image.ImageUtilities;
import org.openimaj.image.analysis.pyramid.SimplePyramid;
import org.openimaj.image.feature.dense.gradient.dsift.ApproximateDenseSIFT;
import org.openimaj.image.feature.dense.gradient.dsift.ByteDSIFTKeypoint;
import org.openimaj.image.feature.dense.gradient.dsift.DenseSIFT;
import org.openimaj.image.feature.dense.gradient.dsift.FloatDSIFTKeypoint;
import org.openimaj.io.IOUtils;
import org.openimaj.util.function.Operation;
import org.openimaj.util.parallel.Parallel;

public class FVFWDSift {
	static interface DSFactory {
		DenseSIFT create();
	}

	private static void extractPDSift(final File indir, final File outDir, final DSFactory factory) throws IOException
	{
		Parallel.forEach(Arrays.asList(indir.listFiles()), new Operation() {

			@Override
			public void perform(File dir) {
				try {
					if (!dir.isDirectory())
						return;

					final DenseSIFT sift = factory.create();

					for (final File imgfile : dir.listFiles()) {
						if (!imgfile.getName().endsWith(".jpg"))
							continue;

						final File outfile = new File(outDir, imgfile.getAbsolutePath().replace(indir.getAbsolutePath(),
								"").replace(".jpg", ".bin"));
						outfile.getParentFile().mkdirs();

						final FImage image = ImageUtilities.readF(imgfile);

						final SimplePyramid pyr = new SimplePyramid((float) Math.sqrt(2), 5);
						pyr.processImage(image);

						final LocalFeatureList allKeys = new MemoryLocalFeatureList();
						for (final FImage img : pyr) {
							sift.analyseImage(img);

							final double scale = 160.0 / img.height;
							final LocalFeatureList kps = sift.getByteKeypoints();
							for (final ByteDSIFTKeypoint kp : kps) {
								kp.x *= scale;
								kp.y *= scale;

								final float[] descriptor = new float[128];
								float sumsq = 0;

								// reorder to make comparision with matlab
								// easier; add offset
								for (int i = 0; i < 16; i++) {
									descriptor[i * 8] = kp.descriptor[i * 8] + 128;
									descriptor[i * 8 + 1] = kp.descriptor[i * 8 + 7] + 128;
									descriptor[i * 8 + 2] = kp.descriptor[i * 8 + 6] + 128;
									descriptor[i * 8 + 3] = kp.descriptor[i * 8 + 5] + 128;
									descriptor[i * 8 + 4] = kp.descriptor[i * 8 + 4] + 128;
									descriptor[i * 8 + 5] = kp.descriptor[i * 8 + 3] + 128;
									descriptor[i * 8 + 6] = kp.descriptor[i * 8 + 2] + 128;
									descriptor[i * 8 + 7] = kp.descriptor[i * 8 + 1] + 128;
								}
								// rootsift
								for (int i = 0; i < 128; i++) {
									descriptor[i] = (float) Math.sqrt(descriptor[i]);
									sumsq += descriptor[i] * descriptor[i];
								}
								sumsq = (float) Math.sqrt(sumsq);
								final float norm = 1f / Math.max(Float.MIN_NORMAL, sumsq);
								for (int i = 0; i < 128; i++) {
									descriptor[i] *= norm;
								}

								allKeys.add(new FloatDSIFTKeypoint(kp.x, kp.y, descriptor, kp.energy));
							}
						}

						IOUtils.writeBinary(outfile, allKeys);

						System.out.println(imgfile + " " + allKeys.size());
					}
				} catch (final Exception e) {
					e.printStackTrace();
					System.err.println(e);
				}
			}
		});
	}

	/**
	 * @param args
	 * @throws IOException
	 */
	public static void main(String[] args) throws IOException {
		final DSFactory factory = new DSFactory() {
			@Override
			public DenseSIFT create() {
				return new ApproximateDenseSIFT(1, 6);
			}
		};

		extractPDSift(
				new File("/Volumes/Raid/face_databases/lfw-centre-affine-matlab/"),
				new File("/Volumes/Raid/face_databases/lfw-centre-affine-pdsift/"),
				factory);
	}

}