Example Image Classification - Revision history

Peter at 23:17, 17 January 2022

2022-01-17T23:17:05Z

← Older revision		Revision as of 23:17, 17 January 2022
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.38/examples/src/boofcv/examples/recognition/ExampleImageClassification.java ExampleImageClassification.java ]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.40/examples/src/boofcv/examples/recognition/ExampleImageClassification.java ExampleImageClassification.java ]

	Concepts:		Concepts:
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	Collections.sort(images);		Collections.sort(images);

	~~ImageClassificationPanel~~ gui = new ImageClassificationPanel();		var gui = new ImageClassificationPanel();
	ShowImages.showWindow(gui, "Image Classification", true);		ShowImages.showWindow(gui, "Image Classification", true);

	for (String path : images) {		for (String path : images) {
	File f = new File(path);		File f = new File(path);
	BufferedImage buffered = UtilImageIO.~~loadImage~~(path);		BufferedImage buffered = UtilImageIO.loadImageNotNull(path);
	~~if (buffered == null)~~
	~~throw new RuntimeException("Couldn't find input image"~~);

	Planar<GrayF32> image = new Planar<>(GrayF32.class, buffered.getWidth(), buffered.getHeight(), 3);		Planar<GrayF32> image = new Planar<>(GrayF32.class, buffered.getWidth(), buffered.getHeight(), 3);

Peter at 19:09, 12 July 2021

2021-07-12T19:09:39Z

← Older revision		Revision as of 19:09, 12 July 2021
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.37/examples/src/boofcv/examples/recognition/ExampleImageClassification.java ExampleImageClassification.java ]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.38/examples/src/boofcv/examples/recognition/ExampleImageClassification.java ExampleImageClassification.java ]

	Concepts:		Concepts:

Peter at 02:34, 22 December 2020

2020-12-22T02:34:41Z

← Older revision		Revision as of 02:34, 22 December 2020
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.32/examples/src/boofcv/examples/recognition/ExampleImageClassification.java ExampleImageClassification.java ]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.37/examples/src/boofcv/examples/recognition/ExampleImageClassification.java ExampleImageClassification.java ]

	Concepts:		Concepts:
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	*/		*/
	public class ExampleImageClassification {		public class ExampleImageClassification {
			public static void main( String[] args ) throws IOException {
	public static void main(String[] args) throws IOException {
	ClassifierAndSource cs = FactoryImageClassifier.vgg_cifar10(); // Test set 89.9% for 10 categories		ClassifierAndSource cs = FactoryImageClassifier.vgg_cifar10(); // Test set 89.9% for 10 categories
	// ClassifierAndSource cs = FactoryImageClassifier.nin_imagenet(); // Test set 62.6% for 1000 categories		// ClassifierAndSource cs = FactoryImageClassifier.nin_imagenet(); // Test set 62.6% for 1000 categories

	File modelPath = DeepBoofDataBaseOps.downloadModel(cs.getSource(),new File("download_data"));		File modelPath = DeepBoofDataBaseOps.downloadModel(cs.getSource(), new File("download_data"));

	ImageClassifier<Planar<GrayF32>> classifier = cs.getClassifier();		ImageClassifier<Planar<GrayF32>> classifier = cs.getClassifier();
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	String imagePath = UtilIO.pathExample("recognition/pixabay");		String imagePath = UtilIO.pathExample("recognition/pixabay");
	List<String> images = UtilIO.listByPrefix(imagePath,null,".jpg");		List<String> images = UtilIO.listByPrefix(imagePath, null, ".jpg");
	Collections.sort(images);		Collections.sort(images);

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	ShowImages.showWindow(gui, "Image Classification", true);		ShowImages.showWindow(gui, "Image Classification", true);

	for( String path : images ) {		for (String path : images) {
	File f = new File(path);		File f = new File(path);
	BufferedImage buffered = UtilImageIO.loadImage(path);		BufferedImage buffered = UtilImageIO.loadImage(path);
	if( buffered == null)		if (buffered == null)
	throw new RuntimeException("Couldn't find input image");		throw new RuntimeException("Couldn't find input image");

	Planar<GrayF32> image = new Planar<>(GrayF32.class,buffered.getWidth(), buffered.getHeight(), 3);		Planar<GrayF32> image = new Planar<>(GrayF32.class, buffered.getWidth(), buffered.getHeight(), 3);
	ConvertBufferedImage.convertFromPlanar(buffered,image,true,GrayF32.class);		ConvertBufferedImage.convertFromPlanar(buffered, image, true, GrayF32.class);

	classifier.classify(image);		classifier.classify(image);

	// add image and results to the GUI for display		// add image and results to the GUI for display
	gui.addImage(buffered,f.getName(),classifier.getAllResults(),categories);		gui.addImage(buffered, f.getName(), classifier.getAllResults(), categories);
	}		}
	}		}
	}		}
	</syntaxhighlight>		</syntaxhighlight>

Peter at 03:59, 27 December 2018

2018-12-27T03:59:35Z

← Older revision		Revision as of 03:59, 27 December 2018
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.27/examples/src/boofcv/examples/recognition/ExampleImageClassification.java ExampleImageClassification.java ]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.32/examples/src/boofcv/examples/recognition/ExampleImageClassification.java ExampleImageClassification.java ]

	Concepts:		Concepts:
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	// ClassifierAndSource cs = FactoryImageClassifier.nin_imagenet(); // Test set 62.6% for 1000 categories		// ClassifierAndSource cs = FactoryImageClassifier.nin_imagenet(); // Test set 62.6% for 1000 categories

	File ~~path~~ = DeepBoofDataBaseOps.downloadModel(cs.getSource(),new File("download_data"));		File modelPath = DeepBoofDataBaseOps.downloadModel(cs.getSource(),new File("download_data"));

	ImageClassifier<Planar<GrayF32>> classifier = cs.getClassifier();		ImageClassifier<Planar<GrayF32>> classifier = cs.getClassifier();
	classifier.loadModel(~~path~~);		classifier.loadModel(modelPath);
	List<String> categories = classifier.getCategories();		List<String> categories = classifier.getCategories();

	String imagePath = UtilIO.pathExample("recognition/pixabay");		String imagePath = UtilIO.pathExample("recognition/pixabay");
	List<~~File~~> images = ~~Arrays.asList(~~UtilIO.~~findMatches(new File~~(imagePath),"\\w*.jpg"));		List<String> images = UtilIO.listByPrefix(imagePath,null,".jpg");
	Collections.sort(images);		Collections.sort(images);

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	ShowImages.showWindow(gui, "Image Classification", true);		ShowImages.showWindow(gui, "Image Classification", true);

	for( ~~File f~~ : images ) {		for( String path : images ) {
	BufferedImage buffered = UtilImageIO.loadImage(~~f.getPath()~~);		File f = new File(path);
			BufferedImage buffered = UtilImageIO.loadImage(path);
	if( buffered == null)		if( buffered == null)
	throw new RuntimeException("Couldn't find input image");		throw new RuntimeException("Couldn't find input image");

Peter at 16:06, 17 August 2017

2017-08-17T16:06:09Z

← Older revision		Revision as of 16:06, 17 August 2017
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	Example Code:		Example Code:
	* [https://github.com/lessthanoptimal/BoofCV/blob/v0.25/examples/src/boofcv/examples/recognition/ExampleImageClassification.java ExampleImageClassification.java ]		* [https://github.com/lessthanoptimal/BoofCV/blob/v0.27/examples/src/boofcv/examples/recognition/ExampleImageClassification.java ExampleImageClassification.java ]

	Concepts:		Concepts:
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	Videos:		Videos:
	* [https://youtu.be/qMTtdiujAtQ?t=347 Example]		* [https://youtu.be/qMTtdiujAtQ?t=347 Example]


	= Example Code =		= Example Code =
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	List<String> categories = classifier.getCategories();		List<String> categories = classifier.getCategories();

	String ~~regex~~ = UtilIO.pathExample("recognition/pixabay")~~+"/^\\w*.jpg"~~;		String imagePath = UtilIO.pathExample("recognition/pixabay");
	List<File> images = Arrays.asList(~~BoofMiscOps~~.findMatches(~~regex~~));		List<File> images = Arrays.asList(UtilIO.findMatches(new File(imagePath),"\\w*.jpg"));
	Collections.sort(images);		Collections.sort(images);

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	Planar<GrayF32> image = new Planar<>(GrayF32.class,buffered.getWidth(), buffered.getHeight(), 3);		Planar<GrayF32> image = new Planar<>(GrayF32.class,buffered.getWidth(), buffered.getHeight(), 3);
	ConvertBufferedImage.~~convertFromMulti~~(buffered,image,true,GrayF32.class);		ConvertBufferedImage.convertFromPlanar(buffered,image,true,GrayF32.class);

	classifier.classify(image);		classifier.classify(image);

Peter at 17:55, 5 January 2017

2017-01-05T17:55:47Z

← Older revision		Revision as of 17:55, 5 January 2017
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	* [[Example_Scene_Classification\|KNN Scene Classification]]		* [[Example_Scene_Classification\|KNN Scene Classification]]
	* [[Example_Color_Histogram_Lookup\|Color Histogram Lookup]]		* [[Example_Color_Histogram_Lookup\|Color Histogram Lookup]]

			Videos:
			* [https://youtu.be/qMTtdiujAtQ?t=347 Example]

Peter at 23:22, 12 December 2016

2016-12-12T23:22:39Z

← Older revision		Revision as of 23:22, 12 December 2016
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	public static void main(String[] args) throws IOException {		public static void main(String[] args) throws IOException {
	ClassifierAndSource cs = FactoryImageClassifier.vgg_cifar10();		ClassifierAndSource cs = FactoryImageClassifier.vgg_cifar10(); // Test set 89.9% for 10 categories
	// ClassifierAndSource cs = FactoryImageClassifier.nin_imagenet();		// ClassifierAndSource cs = FactoryImageClassifier.nin_imagenet(); // Test set 62.6% for 1000 categories

	File path = DeepBoofDataBaseOps.downloadModel(cs.getSource(),new File("download_data"));		File path = DeepBoofDataBaseOps.downloadModel(cs.getSource(),new File("download_data"));

Peter at 22:36, 12 December 2016

2016-12-12T22:36:36Z

← Older revision		Revision as of 22:36, 12 December 2016
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	Related Examples:		Related Examples:
	* [[Example_Scene_Classification\|KNN Scene Classification]]		* [[Example_Scene_Classification\|KNN Scene Classification]]
			* [[Example_Color_Histogram_Lookup\|Color Histogram Lookup]]

Peter at 05:30, 2 December 2016

2016-12-02T05:30:10Z

← Older revision		Revision as of 05:30, 2 December 2016
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	* Deep Neural Networks		* Deep Neural Networks
	* Torch		* Torch

			Related Examples:
			* [[Example_Scene_Classification\|KNN Scene Classification]]


	= Example Code =		= Example Code =

Peter at 00:24, 2 December 2016

2016-12-02T00:24:29Z

← Older revision		Revision as of 00:24, 2 December 2016
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	</center>		</center>

	Example of how to use a previously trained neural network (trained using [http://torch.ch/ Torch] loaded using [https://github.com/lessthanoptimal/DeepBoof DeepBoof]) and apply it the problem of image classification. Model data is often quite large and so you will need to download it from an external source. Locations for where you can download the model from are included with the high level interface.		Example of how to use a previously trained neural network (trained using [http://torch.ch/ Torch] loaded and run in Java using [https://github.com/lessthanoptimal/DeepBoof DeepBoof]) and apply it the problem of image classification. Model data is often quite large and so you will need to download it from an external source. Locations for where you can download the model from are included with the high level interface.

	Example Code:		Example Code: