Question

我是Java新手，正在尝试学习高级并发的概念。我在Java Tutorial Oracle中看到了这段代码。但是，当我运行代码时，IDE会输出一个全黑的图像。为什么会这样？而且，compute（）方法如何调用？

import java.awt.image.BufferedImage;
import java.io.File;
import java.util.concurrent.ForkJoinPool;
import java.util.concurrent.RecursiveAction;
import javax.imageio.ImageIO;

/**
 * ForkBlur implements a simple horizontal image blur. It averages pixels in the
 * source array and writes them to a destination array. The sThreshold value
 * determines whether the blurring will be performed directly or split into two
 * tasks.
 *
 * This is not the recommended way to blur images; it is only intended to
 * illustrate the use of the Fork/Join framework.
 */
public class ForkBlur extends RecursiveAction {

    private int[] mSource;
    private int mStart;
    private int mLength;
    private int[] mDestination;
    private int mBlurWidth = 15; // Processing window size, should be odd.

    public ForkBlur(int[] src, int start, int length, int[] dst) {
        mSource = src;
        mStart = start;
        mLength = length;
        mDestination = dst;
    }

    // Average pixels from source, write results into destination.
    protected void computeDirectly() {
        int sidePixels = (mBlurWidth - 1) / 2;
        for (int index = mStart; index < mStart + mLength; index++) {
            // Calculate average.
            float rt = 0, gt = 0, bt = 0;
            for (int mi = -sidePixels; mi <= sidePixels; mi++) {
                int mindex = Math.min(Math.max(mi + index, 0), mSource.length - 1);
                int pixel = mSource[mindex];
                rt += (float) ((pixel & 0x00ff0000) >> 16) / mBlurWidth;
                gt += (float) ((pixel & 0x0000ff00) >> 8) / mBlurWidth;
                bt += (float) ((pixel & 0x000000ff) >> 0) / mBlurWidth;
            }

            // Re-assemble destination pixel.
            int dpixel = (0xff000000)
                    | (((int) rt) << 16)
                    | (((int) gt) << 8)
                    | (((int) bt) << 0);
            mDestination[index] = dpixel;
        }
    }
    protected static int sThreshold = 10000;

    @Override
    protected void compute() {
        if (mLength < sThreshold) {
            computeDirectly();
            return;
        }

        int split = mLength / 2;

        invokeAll(new ForkBlur(mSource, mStart, split, mDestination),
                new ForkBlur(mSource, mStart + split, mLength - split, 
                mDestination));
    }

    // Plumbing follows.
    public static void main(String[] args) throws Exception {
        String srcName = "/Users/justin/NetBeansProjects/JavaTutorialOracle/src/JTOConcurrency/Screen Shot 2016-02-19 at 10.30.51 AM.jpg";
        File srcFile = new File(srcName);
        BufferedImage image = ImageIO.read(srcFile);

        System.out.println("Source image: " + srcName);

        BufferedImage blurredImage = blur(image);

        String dstName = "blurred-tulips.jpg";
        File dstFile = new File(dstName);
        ImageIO.write(blurredImage, "jpg", dstFile);

        System.out.println("Output image: " + dstName);

    }

    public static BufferedImage blur(BufferedImage srcImage) {
        int w = srcImage.getWidth();
        System.out.println("w: " + w);
        int h = srcImage.getHeight();
        System.out.println("h: " + h);

        int[] src = srcImage.getRGB(0, 0, w, h, null, 0, w);
        System.out.println("src[0]" + src[0]);
        System.out.println("src[src.length - 1]: " + src[src.length - 1]);
        int[] dst = new int[src.length];
        System.out.println("src.length: " + src.length);

        System.out.println("Array size is " + src.length);
        System.out.println("Threshold is " + sThreshold);

        int processors = Runtime.getRuntime().availableProcessors();
        System.out.println(Integer.toString(processors) + " processor"
                + (processors != 1 ? "s are " : " is ")
                + "available");

        ForkBlur fb = new ForkBlur(src, 0, src.length, dst);

        ForkJoinPool pool = new ForkJoinPool();

        long startTime = System.currentTimeMillis();
        pool.invoke(fb);

        long endTime = System.currentTimeMillis();

        System.out.println("Image blur took " + (endTime - startTime) + 
                " milliseconds.");

        BufferedImage dstImage =
                new BufferedImage(w, h, BufferedImage.TYPE_INT_ARGB);
        dstImage.setRGB(0, 0, w, h, dst, 0, w);

        return dstImage;
    }
}

输出：

Source image: /Users/justin/NetBeansProjects/JavaTutorialOracle/src/JTOConcurrency/Screen Shot 2016-02-19 at 10.30.51 AM.jpg
w: 454
h: 679
src[0]-5945082
src[src.length - 1]: -9673172
src.length: 308266
Array size is 308266
Threshold is 10000
4 processors are available
Image blur took 53 milliseconds.
Output image: blurred-tulips.jpg

我附上了一些有关我正在使用的照片的信息。

Answer 1

在OS X 10.11上使用Oracle JRE 1.7.0_71，我可以使用完全黑色的输出图像重现该问题。

但是，您的代码中没有错误，因为我可以看到dst数组包含fork / join模糊操作后的预期值。

相反，问题是我们的老朋友，ImageIO JPEGImageWriter。它不会按照JPEG惯例写入ARGB数据，因此其他软件会误解颜色*。

只需更改行：

BufferedImage dstImage = new BufferedImage(w, h, BufferedImage.TYPE_INT_ARGB);

为：

BufferedImage dstImage = new BufferedImage(w, h, BufferedImage.TYPE_INT_RGB); // No alpha here

这将创建一个没有alpha的图像。 JPEGImageWriter将做正确的事情，最终的输出图像看起来像预期的那样。

另一种选择，使用不同的文件格式，如PNG，也解决了这个问题。即：

ImageIO.write(blurredImage, "PNG", dstFile);

*）如果您在0x00方法中使用0xff代替computeDirectly(...) alpha，则可以更好地看到这一点。你会看到一个奇怪的，可能是粉红色/蓝色的图像。

使用java.util.concurrent模糊图像，但是，生成的图像完全是黑色的

1 个答案: