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Orbit, a versatile image analysis software for biological image-based quantification
/*
* Orbit, a versatile image analysis software for biological image-based quantification.
* Copyright (C) 2009 - 2018 Idorsia Pharmaceuticals Ltd., Hegenheimermattweg 91, CH-4123 Allschwil, Switzerland.
*
* This program 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 3 of the License, or
* (at your option) any later version.
*
* This program 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 this program. If not, see .
*
*/
package com.actelion.research.orbit.imageAnalysis.features;
import com.actelion.research.orbit.exceptions.OrbitImageServletException;
import com.actelion.research.orbit.imageAnalysis.models.FeatureDescription;
import com.actelion.research.orbit.imageAnalysis.utils.TiledImagePainter;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.awt.*;
import java.awt.image.Raster;
/**
* Attention: This class is not thread-safe!!!
* Channel usage (useRed,useGreen,useBlue) is treated in feats[] assignment loop - all samples are calculated!
*
* @author stritma1
*/
public class TissueFeaturesPlain extends TissueFeatures {
private final static Logger logger = LoggerFactory.getLogger(TissueFeaturesPlain.class);
private int samples = 3;
private int windowSize = 4;
private int[] buf = null;
private TiledImagePainter bimg = null;
//private int[] p = new int[4]; // buffer of one pixel up to 4 samples
private FeatureDescription featureDescription = null;
/**
* bimg can be null (then raster r in buildFeatures cannot be null)
*/
public TissueFeaturesPlain(final FeatureDescription featureDescription, final TiledImagePainter bimg) {
this.samples = featureDescription.getSampleSize();
this.windowSize = featureDescription.getWindowSize();
this.bimg = bimg;
buf = new int[(windowSize * 2 + 1) * (windowSize * 2 + 1) * samples];
}
/**
* Initializes a double array of a sufficient size given the feature description.
*
* @return
*/
public double[] prepareDoubleArray() {
return new double[(windowSize * 2 + 1) * (windowSize * 2 + 1) * samples + 1]; // +1 for contextclassification???
}
public double[] buildFeatures(final Raster r, final int x, final int y, final double classVal) throws OrbitImageServletException {
if (r != null) // faster if raster is pre-assigned (e.g. the shape fits into memory)
{
buf = r.getPixels(x - windowSize, y - windowSize, (windowSize * 2) + 1, (windowSize * 2) + 1, buf);
//p = r.getPixel(x, y, p); // mid-pixel
} else { // slower, but works for very large shapes
Raster r2 = bimg.getData(new Rectangle(x - windowSize, y - windowSize, (windowSize * 2) + 1, (windowSize * 2) + 1), featureDescription);
if (r2 == null) System.out.println("r2 is null!!");
buf = r2.getPixels(x - windowSize, y - windowSize, (windowSize * 2) + 1, (windowSize * 2) + 1, buf);
//p = r2.getPixel(x, y, p);
}
double[] feats = prepareDoubleArray();
for (int i = 0; i < buf.length; i++) {
feats[i] = buf[i];
}
feats[feats.length - 1] = classVal;
//logger.trace(Arrays.toString(feats));
return feats;
}
}