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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];
	}
}