Java でのカーネル画像処理プロジェクト [終了]

I have a project made by ChatGPT and I wanted to ask , can someone explain me the parallelization, threads division between processors , synchronization mechanisms and also the methods that have been used in the code?

The project is about Kernel Image Processing

It also have distributed and sequential part too.

Thanks a lot.

package org.example;

import javax.imageio.ImageIO;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;
import java.util.Scanner;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.TimeUnit;

public class ParallelKernelImageProcessing {

    private static final int NUM_THREADS = Runtime.getRuntime().availableProcessors();

    public static void main(String[] args) {
        Scanner scanner = new Scanner(System.in);

        System.out.println("Enter the path to the image:");
        String imagePath = scanner.nextLine();

        File imageFile = new File(imagePath);

        try {
            BufferedImage originalImage = ImageIO.read(imageFile);

            long startTime = System.currentTimeMillis();
            BufferedImage resultImage = applyParallelKernel(originalImage, getDefaultKernel());
            long endTime = System.currentTimeMillis();

            // Save the result image with a filename including "Paralleled"
            String outputFileName = getOutputFileName(imageFile.getName());
            File outputImageFile = new File(outputFileName);
            ImageIO.write(resultImage, "jpg", outputImageFile);

            long runtime = endTime - startTime;
            System.out.println("Runtime: " + runtime + " milliseconds");
        } catch (IOException e) {
            e.printStackTrace();
        } finally {
            scanner.close();
        }
    }

    private static float[][] getDefaultKernel() {
        // Replace this with your desired kernel
        return new float[][]{
                {-1, -1, -1},
                {-1,  8, -1},
                {-1, -1, -1}
        };
    }

    private static BufferedImage applyParallelKernel(BufferedImage inputImage, float[][] kernel) {
        int width = inputImage.getWidth();
        int height = inputImage.getHeight();

        BufferedImage outputImage = new BufferedImage(width, height, BufferedImage.TYPE_INT_RGB);

        ExecutorService executorService = Executors.newFixedThreadPool(NUM_THREADS);

        try {
            for (int i = 0; i < NUM_THREADS; i++) {
                final int startRow = i * height / NUM_THREADS;
                final int endRow = (i + 1) * height / NUM_THREADS;
                executorService.submit(() -> processImageChunk(inputImage, outputImage, kernel, startRow, endRow));
            }

            executorService.shutdown();
            executorService.awaitTermination(Long.MAX_VALUE, TimeUnit.NANOSECONDS);
        } catch (InterruptedException e) {
            e.printStackTrace();
        }

        return outputImage;
    }

    private static void processImageChunk(BufferedImage inputImage, BufferedImage outputImage,
                                          float[][] kernel, int startRow, int endRow) {
        int width = inputImage.getWidth();

        for (int y = startRow + 1; y < endRow - 1; y++) {
            for (int x = 1; x < width - 1; x++) {
                float sum = 0;
                for (int i = -1; i <= 1; i++) {
                    for (int j = -1; j <= 1; j++) {
                        int rgb = inputImage.getRGB(x + j, y + i);
                        float pixelValue = (rgb & 0xFF) * kernel[i + 1][j + 1];
                        sum += pixelValue;
                    }
                }
                int resultPixel = Math.min(255, Math.max(0, Math.round(sum)));
                outputImage.setRGB(x, y, (resultPixel << 16) | (resultPixel << 8) | resultPixel);
            }
        }
    }

    private static String getOutputFileName(String originalFileName) {
        int dotIndex = originalFileName.lastIndexOf('.');
        if (dotIndex != -1) {
            return originalFileName.substring(0, dotIndex) + "ParalleledKerneled.jpg";
        } else {
            return originalFileName + "ParalleledKerneled.jpg";
        }
    }
}