Example Superpixels - Revision history

Peter at 23:26, 17 January 2022

2022-01-17T23:26:55Z

Peter at 19:44, 12 July 2021

2021-07-12T19:44:19Z

← Older revision		Revision as of 19:44, 12 July 2021
Line 10:		Line 10:

	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.37/examples/src/main/java/boofcv/examples/segmentation/ExampleSegmentSuperpixels.java ExampleSegmentSuperpixels.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.38/examples/src/main/java/boofcv/examples/segmentation/ExampleSegmentSuperpixels.java ExampleSegmentSuperpixels.java]

	Concepts:		Concepts:
Line 26:		Line 26:
	<syntaxhighlight lang="java">		<syntaxhighlight lang="java">
	/**		/**
	* Example demonstrating high level image segmentation interface. An image segmented using this		* Example demonstrating high level image segmentation interface. An image segmented using this
	* interface will have each pixel assigned a unique label from 0 to N-1, where N is the number of regions.		* interface will have each pixel assigned a unique label from 0 to N-1, where N is the number of regions.
	* All pixels which belong to the same region are connected. These regions are also known as superpixels.		* All pixels which belong to the same region are connected. These regions are also known as superpixels.
	*		*
	* @author Peter Abeles		* @author Peter Abeles
Line 38:		Line 38:
	public static <T extends ImageBase<T>>		public static <T extends ImageBase<T>>
	void performSegmentation( ImageSuperpixels<T> alg, T color ) {		void performSegmentation( ImageSuperpixels<T> alg, T color ) {
	// Segmentation often works better after blurring the image. Reduces high frequency image components which		// Segmentation often works better after blurring the image. Reduces high frequency image components which
	// can cause over segmentation		// can cause over segmentation
	GBlurImageOps.gaussian(color, color, 0.5, -1, null);		GBlurImageOps.gaussian(color, color, 0.5, -1, null);

	// Storage for segmented image. Each pixel will be assigned a label from 0 to N-1, where N is the number		// Storage for segmented image. Each pixel will be assigned a label from 0 to N-1, where N is the number
	// of segments in the image		// of segments in the image
	GrayS32 pixelToSegment = new GrayS32(color.width, color.height);		GrayS32 pixelToSegment = new GrayS32(color.width, color.height);
Line 54:		Line 54:

	/**		/**
	* Visualizes results three ways. 1) Colorized segmented image where each region is given a random color.		* Visualizes results three ways. 1) Colorized segmented image where each region is given a random color.
	* 2) Each pixel is assigned the mean color through out the region. 3) Black pixels represent the border		* 2) Each pixel is assigned the mean color through out the region. 3) Black pixels represent the border
	* between regions.		* between regions.
Line 101:		Line 101:
	image = ConvertBufferedImage.stripAlphaChannel(image);		image = ConvertBufferedImage.stripAlphaChannel(image);

	// Select input image type. Some algorithms behave different depending on image type		// Select input image type. Some algorithms behave different depending on image type
	ImageType<Planar<GrayF32>> imageType = ImageType.pl(3, GrayF32.class);		ImageType<Planar<GrayF32>> imageType = ImageType.pl(3, GrayF32.class);
	// ImageType<Planar<GrayU8>> imageType = ImageType.pl(3, GrayU8.class);		// ImageType<Planar<GrayU8>> imageType = ImageType.pl(3, GrayU8.class);

Peter at 02:38, 22 December 2020

2020-12-22T02:38:52Z

Peter at 02:43, 8 December 2016

2016-12-08T02:43:23Z

← Older revision		Revision as of 02:43, 8 December 2016
Line 21:		Line 21:
	* [[Example_Thresholding\| Thresholding]]		* [[Example_Thresholding\| Thresholding]]
	* [[Tutorial_Image_Segmentation\| Tutorial Image Segmentation]]		* [[Tutorial_Image_Segmentation\| Tutorial Image Segmentation]]

	~~Relevant Applets:~~
	* [[Applet Image Segmentation\| Image Segmentation]]

	= Example Code =		= Example Code =

Peter at 05:34, 28 March 2016

2016-03-28T05:34:43Z

← Older revision		Revision as of 05:34, 28 March 2016
Line 10:		Line 10:

	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.20/examples/src/boofcv/examples/segmentation/ExampleSegmentSuperpixels.java ExampleSegmentSuperpixels.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.23/examples/src/boofcv/examples/segmentation/ExampleSegmentSuperpixels.java ExampleSegmentSuperpixels.java]

	Concepts:		Concepts:
Line 49:		Line 49:
	// Storage for segmented image. Each pixel will be assigned a label from 0 to N-1, where N is the number		// Storage for segmented image. Each pixel will be assigned a label from 0 to N-1, where N is the number
	// of segments in the image		// of segments in the image
	~~ImageSInt32~~ pixelToSegment = new ~~ImageSInt32~~(color.width,color.height);		GrayS32 pixelToSegment = new GrayS32(color.width,color.height);

	// Segmentation magic happens here		// Segmentation magic happens here
Line 64:		Line 64:
	*/		*/
	public static <T extends ImageBase>		public static <T extends ImageBase>
	void visualize( ~~ImageSInt32~~ pixelToRegion , T color , int numSegments )		void visualize(GrayS32 pixelToRegion , T color , int numSegments )
	{		{
	// Computes the mean color inside each region		// Computes the mean color inside each region
Line 108:		Line 108:

	// Select input image type. Some algorithms behave different depending on image type		// Select input image type. Some algorithms behave different depending on image type
	ImageType<~~MultiSpectral~~<~~ImageFloat32~~>> imageType = ImageType.ms(3, ~~ImageFloat32~~.class);		ImageType<Planar<GrayF32>> imageType = ImageType.pl(3, GrayF32.class);
	// ImageType<~~MultiSpectral~~<~~ImageUInt8~~>> imageType = ImageType.ms(3,~~ImageUInt8~~.class);		// ImageType<Planar<GrayU8>> imageType = ImageType.pl(3,GrayU8.class);
	// ImageType<~~ImageFloat32~~> imageType = ImageType.single(~~ImageFloat32~~.class);		// ImageType<GrayF32> imageType = ImageType.single(GrayF32.class);
	// ImageType<~~ImageUInt8~~> imageType = ImageType.single(~~ImageUInt8~~.class);		// ImageType<GrayU8> imageType = ImageType.single(GrayU8.class);

	// ImageSuperpixels alg = FactoryImageSegmentation.meanShift(null, imageType);		// ImageSuperpixels alg = FactoryImageSegmentation.meanShift(null, imageType);

Peter at 16:55, 9 November 2015

2015-11-09T16:55:58Z

Peter at 01:05, 20 September 2015

2015-09-20T01:05:11Z

← Older revision		Revision as of 01:05, 20 September 2015
Line 10:		Line 10:

	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.18/examples/src/boofcv/examples/segmentation/ExampleSegmentSuperpixels.java ExampleSegmentSuperpixels.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.19/examples/src/boofcv/examples/segmentation/ExampleSegmentSuperpixels.java ExampleSegmentSuperpixels.java]

	Concepts:		Concepts:
Line 86:		Line 86:
	// Make region edges appear red		// Make region edges appear red
	BufferedImage outBorder = new BufferedImage(color.width,color.height,BufferedImage.TYPE_INT_RGB);		BufferedImage outBorder = new BufferedImage(color.width,color.height,BufferedImage.TYPE_INT_RGB);
	ConvertBufferedImage.convertTo(color,outBorder,true);		ConvertBufferedImage.convertTo(color, outBorder, true);
	VisualizeRegions.regionBorders(pixelToRegion,0xFF0000,outBorder);		VisualizeRegions.regionBorders(pixelToRegion,0xFF0000,outBorder);

	// Show the visualization results		// Show the visualization results
	~~ShowImages~~.~~showWindow~~(~~outSegments~~, "~~Regions~~");		ListDisplayPanel gui = new ListDisplayPanel();
	~~ShowImages~~.~~showWindow~~(outBorder,"Region Borders");		gui.addImage(outColor,"Color of Segments");
	ShowImages.showWindow(~~outColor~~,"~~Color of Segments~~");		gui.addImage(outBorder, "Region Borders");
			gui.addImage(outSegments, "Regions");
			ShowImages.showWindow(gui,"Superpixels", true);
	}		}

Peter at 21:38, 22 September 2014

2014-09-22T21:38:52Z

← Older revision		Revision as of 21:38, 22 September 2014
Line 19:		Line 19:
	* [[Example_Color_Segmentation\| Color Segmentation]]		* [[Example_Color_Segmentation\| Color Segmentation]]
	* [[Example_Watershed_with_Seeds\| Watershed with Seeds]]		* [[Example_Watershed_with_Seeds\| Watershed with Seeds]]
			* [[Example_Thresholding\| Thresholding]]
			* [[Tutorial_Image_Segmentation\| Tutorial Image Segmentation]]

	Relevant Applets:		Relevant Applets:

Peter at 21:36, 22 September 2014

2014-09-22T21:36:46Z

← Older revision		Revision as of 21:36, 22 September 2014
Line 10:		Line 10:

	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.17/examples/src/boofcv/examples/segmentation/~~ExampleImageSegmentation~~.java ~~ExampleImageSegmentation~~.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.18/examples/src/boofcv/examples/segmentation/ExampleSegmentSuperpixels.java ExampleSegmentSuperpixels.java]

	Concepts:		Concepts:
Line 28:		Line 28:
	/**		/**
	* Example demonstrating high level image segmentation interface. An image segmented using this		* Example demonstrating high level image segmentation interface. An image segmented using this
	* interface will have each pixel assigned a unique label from 0 to N-1, where N is the number of regions.		* interface will have each pixel assigned a unique label from 0 to N-1, where N is the number of regions.
	* All pixels which belong to the same region are connected. These regions are also known as superpixels.		* All pixels which belong to the same region are connected. These regions are also known as superpixels.
	*		*
	* @author Peter Abeles		* @author Peter Abeles
	*/		*/
	public class ~~ExampleImageSegmentation~~ {		public class ExampleSegmentSuperpixels {

	/**		/**
Line 39:		Line 39:
	*/		*/
	public static <T extends ImageBase>		public static <T extends ImageBase>
	void performSegmentation( ~~ImageSegmentation~~<T> alg , T color )		void performSegmentation( ImageSuperpixels<T> alg , T color )
	{		{
	// Segmentation often works better after blurring the image. Reduces high frequency image components which		// Segmentation often works better after blurring the image. Reduces high frequency image components which
Line 53:		Line 53:

	// Displays the results		// Displays the results
	visualize(pixelToSegment,color,alg.~~getTotalSegments~~());		visualize(pixelToSegment,color,alg.getTotalSuperpixels());
	}		}

Line 106:		Line 106:
	// ImageType<ImageUInt8> imageType = ImageType.single(ImageUInt8.class);		// ImageType<ImageUInt8> imageType = ImageType.single(ImageUInt8.class);

	// ~~ImageSegmentation~~ alg = FactoryImageSegmentation.meanShift(null, imageType);		// ImageSuperpixels alg = FactoryImageSegmentation.meanShift(null, imageType);
	// ~~ImageSegmentation~~ alg = FactoryImageSegmentation.slic(new ConfigSlic(~~800~~), imageType);		// ImageSuperpixels alg = FactoryImageSegmentation.slic(new ConfigSlic(400), imageType);
	~~ImageSegmentation~~ alg = FactoryImageSegmentation.fh04(new ConfigFh04(100,30), imageType);		ImageSuperpixels alg = FactoryImageSegmentation.fh04(new ConfigFh04(100,30), imageType);
	// ~~ImageSegmentation~~ alg = FactoryImageSegmentation.watershed(~~ConnectRule.EIGHT~~);		// ImageSuperpixels alg = FactoryImageSegmentation.watershed(null,imageType);

	// Convert image into BoofCV format		// Convert image into BoofCV format

Peter: Peter moved page Example Image Segmentation to Example Superpixels

2014-09-12T17:14:03Z

Peter moved page Example Image Segmentation to Example Superpixels

← Older revision	Revision as of 17:14, 12 September 2014
(No difference)

← Older revision		Revision as of 23:26, 17 January 2022
Line 7:		Line 7:
	</center>		</center>

	Image segmentation is an important (and very much unsolved) problem in computer vision. In this example, different techniques are used to break the image up into regions (or superpixels). The goal of this segmentation is to simplify the image's description, which can then be used for object detection/recognition.		Image segmentation is an important (and very much unsolved) problem in computer vision. In this example, different techniques are used to break the image up into regions (or superpixels). The goal of this segmentation is to simplify the image's description, which can then be used for object detection/recognition.

	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.38/examples/src/main/java/boofcv/examples/segmentation/ExampleSegmentSuperpixels.java ExampleSegmentSuperpixels.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.40/examples/src/main/java/boofcv/examples/segmentation/ExampleSegmentSuperpixels.java ExampleSegmentSuperpixels.java]

	Concepts:		Concepts:
Line 44:		Line 44:
	// Storage for segmented image. Each pixel will be assigned a label from 0 to N-1, where N is the number		// Storage for segmented image. Each pixel will be assigned a label from 0 to N-1, where N is the number
	// of segments in the image		// of segments in the image
	~~GrayS32~~ pixelToSegment = new GrayS32(color.width, color.height);		var pixelToSegment = new GrayS32(color.width, color.height);

	// Segmentation magic happens here		// Segmentation magic happens here
Line 64:		Line 64:
	ComputeRegionMeanColor<T> colorize = FactorySegmentationAlg.regionMeanColor(type);		ComputeRegionMeanColor<T> colorize = FactorySegmentationAlg.regionMeanColor(type);

	~~DogArray<float[]>~~ segmentColor = new ColorQueue_F32(type.getNumBands());		var segmentColor = new ColorQueue_F32(type.getNumBands());
	segmentColor.resize(numSegments);		segmentColor.resize(numSegments);

	~~DogArray_I32~~ regionMemberCount = new DogArray_I32();		var regionMemberCount = new DogArray_I32();
	regionMemberCount.resize(numSegments);		regionMemberCount.resize(numSegments);

Line 79:		Line 79:

	// Make region edges appear red		// Make region edges appear red
	~~BufferedImage~~ outBorder = new BufferedImage(color.width, color.height, BufferedImage.TYPE_INT_RGB);		var outBorder = new BufferedImage(color.width, color.height, BufferedImage.TYPE_INT_RGB);
	ConvertBufferedImage.convertTo(color, outBorder, true);		ConvertBufferedImage.convertTo(color, outBorder, true);
	VisualizeRegions.regionBorders(pixelToRegion, 0xFF0000, outBorder);		VisualizeRegions.regionBorders(pixelToRegion, 0xFF0000, outBorder);

	// Show the visualization results		// Show the visualization results
	~~ListDisplayPanel~~ gui = new ListDisplayPanel();		var gui = new ListDisplayPanel();
	gui.addImage(outColor, "Color of Segments");		gui.addImage(outColor, "Color of Segments");
	gui.addImage(outBorder, "Region Borders");		gui.addImage(outBorder, "Region Borders");
Line 92:		Line 92:

	public static void main( String[] args ) {		public static void main( String[] args ) {
	BufferedImage image = UtilImageIO.~~loadImage~~(UtilIO.pathExample("segment/berkeley_horses.jpg"));		BufferedImage image = UtilImageIO.loadImageNotNull(UtilIO.pathExample("segment/berkeley_horses.jpg"));
	// BufferedImage image = UtilImageIO.~~loadImage~~(UtilIO.pathExample("segment/berkeley_kangaroo.jpg"));		// BufferedImage image = UtilImageIO.loadImageNotNull(UtilIO.pathExample("segment/berkeley_kangaroo.jpg"));
	// BufferedImage image = UtilImageIO.~~loadImage~~(UtilIO.pathExample("segment/berkeley_man.jpg"));		// BufferedImage image = UtilImageIO.loadImageNotNull(UtilIO.pathExample("segment/berkeley_man.jpg"));
	// BufferedImage image = UtilImageIO.~~loadImage~~(UtilIO.pathExample("segment/mountain_pines_people.jpg"));		// BufferedImage image = UtilImageIO.loadImageNotNull(UtilIO.pathExample("segment/mountain_pines_people.jpg"));
	// BufferedImage image = UtilImageIO.~~loadImage~~(UtilIO.pathExample("particles01.jpg"));		// BufferedImage image = UtilImageIO.loadImageNotNull(UtilIO.pathExample("particles01.jpg"));

	// you probably don't want to segment along the image's alpha channel and the code below assumes 3 channels		// you probably don't want to segment along the image's alpha channel and the code below assumes 3 channels

← Older revision		Revision as of 02:38, 22 December 2020
Line 10:		Line 10:

	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.23/examples/src/boofcv/examples/segmentation/ExampleSegmentSuperpixels.java ExampleSegmentSuperpixels.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.37/examples/src/main/java/boofcv/examples/segmentation/ExampleSegmentSuperpixels.java ExampleSegmentSuperpixels.java]

	Concepts:		Concepts:
Line 33:		Line 33:
	*/		*/
	public class ExampleSegmentSuperpixels {		public class ExampleSegmentSuperpixels {

	/**		/**
	* Segments and visualizes the image		* Segments and visualizes the image
	*/		*/
	public static <T extends ImageBase>		public static <T extends ImageBase<T>>
	void performSegmentation( ImageSuperpixels<T> alg , T color )		void performSegmentation( ImageSuperpixels<T> alg, T color ) {
	{
	// Segmentation often works better after blurring the image. Reduces high frequency image components which		// Segmentation often works better after blurring the image. Reduces high frequency image components which
	// can cause over segmentation		// can cause over segmentation
Line 46:		Line 44:
	// Storage for segmented image. Each pixel will be assigned a label from 0 to N-1, where N is the number		// Storage for segmented image. Each pixel will be assigned a label from 0 to N-1, where N is the number
	// of segments in the image		// of segments in the image
	GrayS32 pixelToSegment = new GrayS32(color.width,color.height);		GrayS32 pixelToSegment = new GrayS32(color.width, color.height);

	// Segmentation magic happens here		// Segmentation magic happens here
	alg.segment(color,pixelToSegment);		alg.segment(color, pixelToSegment);

	// Displays the results		// Displays the results
	visualize(pixelToSegment,color,alg.getTotalSuperpixels());		visualize(pixelToSegment, color, alg.getTotalSuperpixels());
	}		}

Line 60:		Line 58:
	* between regions.		* between regions.
	*/		*/
	public static <T extends ImageBase>		public static <T extends ImageBase<T>>
	void visualize(GrayS32 pixelToRegion , T color , int numSegments )		void visualize( GrayS32 pixelToRegion, T color, int numSegments ) {
	{
	// Computes the mean color inside each region		// Computes the mean color inside each region
	ImageType<T> type = color.getImageType();		ImageType<T> type = color.getImageType();
	ComputeRegionMeanColor<T> colorize = FactorySegmentationAlg.regionMeanColor(type);		ComputeRegionMeanColor<T> colorize = FactorySegmentationAlg.regionMeanColor(type);

	~~FastQueue~~<float[]> segmentColor = new ColorQueue_F32(type.getNumBands());		DogArray<float[]> segmentColor = new ColorQueue_F32(type.getNumBands());
	segmentColor.resize(numSegments);		segmentColor.resize(numSegments);

	~~GrowQueue_I32~~ regionMemberCount = new ~~GrowQueue_I32~~();		DogArray_I32 regionMemberCount = new DogArray_I32();
	regionMemberCount.resize(numSegments);		regionMemberCount.resize(numSegments);

	ImageSegmentationOps.countRegionPixels(pixelToRegion, numSegments, regionMemberCount.data);		ImageSegmentationOps.countRegionPixels(pixelToRegion, numSegments, regionMemberCount.data);
	colorize.process(color,pixelToRegion,regionMemberCount,segmentColor);		colorize.process(color, pixelToRegion, regionMemberCount, segmentColor);

	// Draw each region using their average color		// Draw each region using their average color
	BufferedImage outColor = VisualizeRegions.regionsColor(pixelToRegion,segmentColor,null);		BufferedImage outColor = VisualizeRegions.regionsColor(pixelToRegion, segmentColor, null);
	// Draw each region by assigning it a random color		// Draw each region by assigning it a random color
	BufferedImage outSegments = VisualizeRegions.regions(pixelToRegion, numSegments, null);		BufferedImage outSegments = VisualizeRegions.regions(pixelToRegion, numSegments, null);

	// Make region edges appear red		// Make region edges appear red
	BufferedImage outBorder = new BufferedImage(color.width,color.height,BufferedImage.TYPE_INT_RGB);		BufferedImage outBorder = new BufferedImage(color.width, color.height, BufferedImage.TYPE_INT_RGB);
	ConvertBufferedImage.convertTo(color, outBorder, true);		ConvertBufferedImage.convertTo(color, outBorder, true);
	VisualizeRegions.regionBorders(pixelToRegion,0xFF0000,outBorder);		VisualizeRegions.regionBorders(pixelToRegion, 0xFF0000, outBorder);

	// Show the visualization results		// Show the visualization results
	ListDisplayPanel gui = new ListDisplayPanel();		ListDisplayPanel gui = new ListDisplayPanel();
	gui.addImage(outColor,"Color of Segments");		gui.addImage(outColor, "Color of Segments");
	gui.addImage(outBorder, "Region Borders");		gui.addImage(outBorder, "Region Borders");
	gui.addImage(outSegments, "Regions");		gui.addImage(outSegments, "Regions");
	ShowImages.showWindow(gui,"Superpixels", true);		ShowImages.showWindow(gui, "Superpixels", true);
	}		}

	public static void main(String[] args) {		public static void main( String[] args ) {
	BufferedImage image = UtilImageIO.loadImage(UtilIO.pathExample("segment/berkeley_horses.jpg"));		BufferedImage image = UtilImageIO.loadImage(UtilIO.pathExample("segment/berkeley_horses.jpg"));
	// BufferedImage image = UtilImageIO.loadImage(UtilIO.pathExample("segment/berkeley_kangaroo.jpg"));		// BufferedImage image = UtilImageIO.loadImage(UtilIO.pathExample("segment/berkeley_kangaroo.jpg"));
Line 106:		Line 103:
	// Select input image type. Some algorithms behave different depending on image type		// Select input image type. Some algorithms behave different depending on image type
	ImageType<Planar<GrayF32>> imageType = ImageType.pl(3, GrayF32.class);		ImageType<Planar<GrayF32>> imageType = ImageType.pl(3, GrayF32.class);
	// ImageType<Planar<GrayU8>> imageType = ImageType.pl(3,GrayU8.class);		// ImageType<Planar<GrayU8>> imageType = ImageType.pl(3, GrayU8.class);
	// ImageType<GrayF32> imageType = ImageType.single(GrayF32.class);		// ImageType<GrayF32> imageType = ImageType.single(GrayF32.class);
	// ImageType<GrayU8> imageType = ImageType.single(GrayU8.class);		// ImageType<GrayU8> imageType = ImageType.single(GrayU8.class);
Line 112:		Line 109:
	// ImageSuperpixels alg = FactoryImageSegmentation.meanShift(null, imageType);		// ImageSuperpixels alg = FactoryImageSegmentation.meanShift(null, imageType);
	// ImageSuperpixels alg = FactoryImageSegmentation.slic(new ConfigSlic(400), imageType);		// ImageSuperpixels alg = FactoryImageSegmentation.slic(new ConfigSlic(400), imageType);
	ImageSuperpixels alg = FactoryImageSegmentation.fh04(new ConfigFh04(100,30), imageType);		ImageSuperpixels alg = FactoryImageSegmentation.fh04(new ConfigFh04(100, 30), imageType);
	// ImageSuperpixels alg = FactoryImageSegmentation.watershed(null,imageType);		// ImageSuperpixels alg = FactoryImageSegmentation.watershed(null, imageType);

	// Convert image into BoofCV format		// Convert image into BoofCV format
	ImageBase color = imageType.createImage(image.getWidth(),image.getHeight());		ImageBase color = imageType.createImage(image.getWidth(), image.getHeight());
	ConvertBufferedImage.convertFrom(image, color, true);		ConvertBufferedImage.convertFrom(image, color, true);

	// Segment and display results		// Segment and display results
	performSegmentation(alg,color);		performSegmentation(alg, color);
	}		}
	}		}
	</syntaxhighlight>		</syntaxhighlight>

← Older revision		Revision as of 16:55, 9 November 2015
Line 10:		Line 10:

	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.19/examples/src/boofcv/examples/segmentation/ExampleSegmentSuperpixels.java ExampleSegmentSuperpixels.java]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.20/examples/src/boofcv/examples/segmentation/ExampleSegmentSuperpixels.java ExampleSegmentSuperpixels.java]

	Concepts:		Concepts:
Line 98:		Line 98:

	public static void main(String[] args) {		public static void main(String[] args) {
	BufferedImage image = UtilImageIO.loadImage("~~../data/applet/~~segment/berkeley_horses.jpg");		BufferedImage image = UtilImageIO.loadImage(UtilIO.pathExample("segment/berkeley_horses.jpg"));
	// BufferedImage image = UtilImageIO.loadImage("~~../data/applet/~~segment/berkeley_kangaroo.jpg");		// BufferedImage image = UtilImageIO.loadImage(UtilIO.pathExample("segment/berkeley_kangaroo.jpg"));
	// BufferedImage image = UtilImageIO.loadImage("~~../data/applet/~~segment/berkeley_man.jpg");		// BufferedImage image = UtilImageIO.loadImage(UtilIO.pathExample("segment/berkeley_man.jpg"));
	// BufferedImage image = UtilImageIO.loadImage("~~../data/applet/~~segment/mountain_pines_people.jpg");		// BufferedImage image = UtilImageIO.loadImage(UtilIO.pathExample("segment/mountain_pines_people.jpg"));
	// BufferedImage image = UtilImageIO.loadImage("../~~data~~/~~applet/particles01~~.~~jpg"~~);		// BufferedImage image = UtilImageIO.loadImage(UtilIO.pathExample("particles01.jpg"));

			// you probably don't want to segment along the image's alpha channel and the code below assumes 3 channels
			image = ConvertBufferedImage.stripAlphaChannel(image);

	// Select input image type. Some algorithms behave different depending on image type		// Select input image type. Some algorithms behave different depending on image type
	ImageType<MultiSpectral<ImageFloat32>> imageType = ImageType.ms(3,ImageFloat32.class);		ImageType<MultiSpectral<ImageFloat32>> imageType = ImageType.ms(3, ImageFloat32.class);
	// ImageType<MultiSpectral<ImageUInt8>> imageType = ImageType.ms(3,ImageUInt8.class);		// ImageType<MultiSpectral<ImageUInt8>> imageType = ImageType.ms(3,ImageUInt8.class);
	// ImageType<ImageFloat32> imageType = ImageType.single(ImageFloat32.class);		// ImageType<ImageFloat32> imageType = ImageType.single(ImageFloat32.class);