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/*
 * Copyright (c) 2021, Peter Abeles. All Rights Reserved.
 *
 * This file is part of BoofCV (http://boofcv.org).
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *   http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package boofcv.alg.tracker.meanshift;

import boofcv.struct.image.GrayU8;
import georegression.struct.shapes.RectangleLength2D_I32;

/**
 * 

* Creates a histogram in a gray scale image which is then used to compute the likelihood of a color being a * member of the original distribution based on its frequency. *

* *

* Design Note:
* The reason operations in {@link boofcv.alg.feature.color.GHistogramFeatureOps} is not used internally is because * those are for histograms stored in double arrays, while this has to use floats/ *

* * @author Peter Abeles */ @SuppressWarnings({"NullAway.Init"}) public class LikelihoodHistCoupled_SB_U8 implements PixelLikelihood { GrayU8 image; // maximum value a pixel can have. int maxPixelValue; // Number of bins for each channel in the histogram int numBins; float[] hist = new float[0]; public LikelihoodHistCoupled_SB_U8( int maxPixelValue, int numBins ) { this.maxPixelValue = maxPixelValue + 1; this.numBins = numBins; } @Override public void setImage( GrayU8 image ) { this.image = image; if (hist.length != numBins) { hist = new float[numBins]; } } @Override public boolean isInBounds( int x, int y ) { return image.isInBounds(x, y); } @Override public void createModel( RectangleLength2D_I32 target ) { for (int y = 0; y < target.height; y++) { int index = image.startIndex + (y + target.y0)*image.stride + target.x0; for (int x = 0; x < target.width; x++, index++) { int value = image.data[index] & 0xFF; int bin = numBins*value/maxPixelValue; hist[bin]++; } } float total = target.width*target.height; for (int i = 0; i < hist.length; i++) { hist[i] /= total; } } @Override public float compute( int x, int y ) { int index = image.startIndex + y*image.stride + x; int value = image.data[index] & 0xFF; int bin = numBins*value/maxPixelValue; return hist[bin]; } }




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