one.empty3.feature20220726.ClassificationAvgColors Maven / Gradle / Ivy

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3D rendering engine. Plus modelling. Expected glsl textures 3d and 2d rendering3D primitives, and a lot of scenes' samples to test.+ Game Jogl reworked, Calculator (numbers and vectors). Java code parser implementation starts (<=1.2)

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/*
 *
 *  * Copyright (c) 2024. Manuel Daniel Dahmen
 *  *
 *  *
 *  *    Copyright 2024 Manuel Daniel Dahmen
 *  *
 *  *    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 one.empty3.feature20220726;

import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;
import java.util.HashMap;
import java.util.Map;
import java.util.Objects;
import java.util.function.BiConsumer;

import javaAnd.awt.image.imageio.ImageIO;
import one.empty3.io.ProcessFile;
import one.empty3.library.Point3D;

public class ClassificationAvgColors extends ProcessFile {
    public ClassificationAvgColors() {

    }

    @Override
    public boolean process(File in, File out) {
        KMeans classification = new KMeans();
        classification.process(in, out);
        // Processed by "classification
        // Non filtered image
        BufferedImage original = ImageIO.read(in);
        PixM pixMOriginal = new PixM(Objects.requireNonNull(original));
        PixM toProcess = new PixM(original);
        Map c = classification.kClusterer.centroids;
        Map sum = new HashMap<>();
        Map count = new HashMap<>();
        // Faire les moyennes des points de même groupe
        c.forEach(new BiConsumer() {
            @Override
            public void accept(Integer integer, double[] doubles) {
                sum.putIfAbsent(integer, Point3D.O0);
                count.putIfAbsent(integer, 0);
                sum.put(integer, sum.get(integer).plus(pixMOriginal.getP((int) doubles[0], (int) doubles[1])));
                count.put(integer, count.get(integer) + 1);
            }
        });
        Point3D[] ps = new Point3D[c.keySet().size()];
        c.forEach(new BiConsumer() {
            @Override
            public void accept(Integer integer, double[] doubles) {
                Integer countI = count.get(integer);
                Point3D sumI = sum.get(integer);
                sumI = sumI.mult(1. / countI);
                ps[integer] = sumI;
            }
        });
        c.forEach(new BiConsumer() {
            @Override
            public void accept(Integer integer, double[] doubles) {
                Integer countI = count.get(integer);
                Point3D sumI = sum.get(integer);
                sumI = sumI.mult(1. / countI);
                for (int c = 0; c < 3; c++)
                    doubles[c + 2] = ps[integer].get(c);

                toProcess.setP((int) (doubles[0]), (int) (doubles[1]),
                        sumI);
            }
        });


        return ImageIO.write(toProcess.getImage(), "jpg", out);
    }
}