/**
 * 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
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 * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 */
package org.openimaj.tools.globalfeature.type;

import org.kohsuke.args4j.Option;
import org.openimaj.feature.FeatureVector;
import org.openimaj.image.FImage;
import org.openimaj.image.MBFImage;
import org.openimaj.image.feature.global.ModifiedLuoSimplicity;
import org.openimaj.tools.globalfeature.GlobalFeatureExtractor;

/**
 * Modified version of Luo's simplicity feature
 * @see ModifiedLuoSimplicity
 */
public class ModifiedLuoSimplicityExtractor extends GlobalFeatureExtractor {
        @Option(name="--bins-per-band", aliases="-bpb", required=false, usage="Number of bins to split the R, G and B bands into when constructing the histogram (default 16)")
        int binsPerBand = 16;

        @Option(name="--gamma", required=false, usage="percentage threshold on the max value of the histogram for counting high-valued bins (default 0.01)")
        float gamma = 0.01f;

        @Option(name="--no-box", required=false, usage="use the actual predicted foreground/background pixels rather than their bounding box (default false)")
        boolean noBoxMode = false;

        @Option(name="--alpha", aliases="-a", required=false, usage="The proportion of the maximum saliency value at which we choose the ROI components (default 0.67)")
        float alpha = 0.67f;

        @Option(name="--saliency-sigma", aliases="-sals", required=false, usage="the amount of Gaussian blurring for the saliency estimation (default 1.0)")
        float saliencySigma = 1f;

        @Option(name="--segment-sigma", aliases="-segs", required=false, usage="the amount of Gaussian blurring applied prior to segmentation (default 0.5)")
        float segmenterSigma = 0.5f;

        @Option(name="--threshold", aliases="-k", required=false, usage="the segmentation threshold (default 500/255)")
        float k = 500f / 255f;

        @Option(name="--min-size", aliases="-m", required=false, usage="the minimum segment size (default 50)")
        int minSize = 50;

        @Override
        public FeatureVector extract(MBFImage image, FImage mask) {
                ModifiedLuoSimplicity cc = new ModifiedLuoSimplicity(binsPerBand, gamma, !noBoxMode, alpha, saliencySigma, segmenterSigma, k, minSize);
                image.analyseWith(cc);
                return cc.getFeatureVector();
        }
}