ForkLoop Images Assignment

Motivation

We gain experience using a parallel fork loop. Image processing often presents the opportunity for a lot of parallelism. Here we will operate on a single image, making a parallel task for each row.

Background

Revisit the Image Batch Race Condition Exercise's Background section for information on pixels and images.

Code To Investigate

Image Batch Race Condition Exercise

Image Batch Race Condition Code To Investigate

PixelFilters

public class PixelFilters {
	private static class HueSettingPixelFilter implements PixelFilter {
		private final double hue;

		public HueSettingPixelFilter(double hue) {
			this.hue = hue;
		}

		@Override
		public HsvColor apply(HsvColor src) {
			double saturation = src.saturation();
			double value = src.value();
			return new HsvColor(hue, saturation, value);
		}
	}

	public static PixelFilter hueSettingPixelFilterOf(double hue) {
		// return new instance of named class HueSettingPixelFilter
		return new HueSettingPixelFilter(hue);
	}

	public static PixelFilter hueAdjustingPixelFilterOf(double deltaHue) {
		// return new instance of anonymous class
		return new PixelFilter() {
			@Override
			public HsvColor apply(HsvColor src) {
				double hue = src.hue();
				double saturation = src.saturation();
				double value = src.value();
				return new HsvColor(hue + deltaHue, saturation, value);
			}
		};
	}

	public static PixelFilter saturationAdjustingPixelFilterOf(double deltaSaturation) {
		// return anonymous function (also known as a lambda) with parameter type
		return (HsvColor src) -> {
			double hue = src.hue();
			double saturation = src.saturation();
			double value = src.value();
			return new HsvColor(hue, saturation + deltaSaturation, value);
		};
	}

	public static PixelFilter valueAdjustingPixelFilterOf(double deltaValue) {
		// return anonymous function (also known as a lambda) without parameter type
		return src -> {
			double hue = src.hue();
			double saturation = src.saturation();
			double value = src.value();
			return new HsvColor(hue, saturation, value + deltaValue);
		};
	}
}

Code To Implement

ParallelTaskPerRowImageFilter

class:	ParallelTaskPerRowImageFilter.java
methods:	apply
package:	imagefilter.exercise
source folder:	student/src/main/java

apply

method: public HsvImage apply(HsvImage src, PixelFilter pixelFilter) (parallel implementation required)

Warning: When applying pixelFilter(), always put the result in a new array. Don't overwrite values of the source array.

This code need only include one: join_fork_loop(array, (arrayValue) -> // etc... ) and an inner for loop using pixelFilter.apply(). Each join_fork_loop iteration should return an HsvColor[].

However, if you do this, join_fork_loop() will default to returning a List<HsvColor[]> which we don't want. To avoid this, hand join_fork_loop() the class you'll return: e.g. HsvColor[][] destination = join_fork_loop(HsvColor[].class, array, (arrayValue) -> // code returning HsvColor[]'s).

Finish out the method by returning a new DefaultHsvImage() which accepts a HsvColor[][] in its constructor.

Visualization

class:	ImageFilterApp.java	VIZ
package:	imagefilter.viz
source folder:	student/src/main/java

Testing Your Solution

class:	__ParallelTaskPerRowImageFilterTestSuite.java
package:	imagefilter.exercise
source folder:	testing/src/test/java

Pledge, Acknowledgments, Citations

file:

exercise-fork-loop-images-pledge-acknowledgments-citations.txt

More info about the Honor Pledge