org.openimaj.demos.FisherTesting 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: 1.3.8
/**
 * 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.ArrayList;
import java.util.Collections;
import java.util.List;

import org.openimaj.feature.local.list.MemoryLocalFeatureList;
import org.openimaj.image.feature.local.aggregate.FisherVector;
import org.openimaj.image.feature.local.keypoints.FloatKeypoint;
import org.openimaj.image.feature.local.keypoints.Keypoint;
import org.openimaj.math.matrix.algorithm.pca.ThinSvdPrincipalComponentAnalysis;
import org.openimaj.math.statistics.distribution.MixtureOfGaussians;
import org.openimaj.ml.gmm.GaussianMixtureModelEM;
import org.openimaj.ml.gmm.GaussianMixtureModelEM.CovarianceType;
import org.openimaj.util.array.ArrayUtils;

import Jama.Matrix;

public class FisherTesting {
	public static void main(String[] args) throws IOException {
		final List> data = new ArrayList>();
		final List allKeys = new ArrayList();

		for (int i = 0; i < 100; i++) {
			final MemoryLocalFeatureList tmp = FloatKeypoint.convert(MemoryLocalFeatureList.read(
					new File(String.format("/Users/jsh2/Data/ukbench/sift/ukbench%05d.jpg", i)), Keypoint.class));
			data.add(tmp);
			allKeys.addAll(tmp);
		}

		Collections.shuffle(allKeys);

		final double[][] sample128 = new double[1000][];
		for (int i = 0; i < sample128.length; i++) {
			sample128[i] = ArrayUtils.convertToDouble(allKeys.get(i).vector);
		}

		System.out.println("Performing PCA " + sample128.length);
		final ThinSvdPrincipalComponentAnalysis pca = new ThinSvdPrincipalComponentAnalysis(64);
		pca.learnBasis(sample128);
		final double[][] sample64 = pca.project(new Matrix(sample128)).getArray();

		System.out.println("Projecting features");
		for (final MemoryLocalFeatureList kpl : data) {
			for (final FloatKeypoint kp : kpl) {
				kp.vector = ArrayUtils.convertToFloat(pca.project(ArrayUtils.convertToDouble(kp.vector)));
			}
		}

		System.out.println("Learning GMM " + sample64.length);
		final GaussianMixtureModelEM gmmem = new GaussianMixtureModelEM(512, CovarianceType.Diagonal);
		final MixtureOfGaussians gmm = gmmem.estimate(sample64);

		final double[][] v1 = gmm.logProbability(new double[][] { sample64[0] });
		final double[][] v2 = MixtureOfGaussians.logProbability(new double[][] { sample64[0] }, gmm.gaussians);

		System.out.println("Done");

		// for (int i = 0; i < 512; i++) {
		// System.out.println(gmm.gaussians[i].getMean().get(0, 0) + "," +
		// gmm.gaussians[i].getMean().get(0, 1));
		// }

		final FisherVector fisher = new FisherVector(gmm, true, true);

		final List kpl = allKeys.subList(0, 26000);
		final long t1 = System.currentTimeMillis();
		fisher.aggregate(kpl).asDoubleVector();
		final long t2 = System.currentTimeMillis();
		System.out.println(t2 - t1);

		// int i = 0;
		// final double[][] fvs = new double[5][];
		// for (final MemoryLocalFeatureList kpl : data) {
		// final long t1 = System.currentTimeMillis();
		// fvs[i++] = fisher.aggregate(kpl).asDoubleVector();
		// final long t2 = System.currentTimeMillis();
		// System.out.println(t2 - t1);
		//
		// if (i == 5)
		// break;
		// }
		//
		// final ThinSvdPrincipalComponentAnalysis pca2 = new
		// ThinSvdPrincipalComponentAnalysis(128);
		// pca2.learnBasis(fvs);
	}
}