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• Version 2 • Released on: 2015-07-21 06:07:20
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  Description:

  Added documentation

  /* import the different Classes needed - FileDialog is used to select file and Loader to load the image - Package filtering is used to create the kernel and perform the convolution - Package thresholder is needed to do the threshold with Thresholder and KMeans classes. */ importClass(Packages.plugins.tprovoost.scripteditor.uitools.filedialogs.FileDialog) importClass(Packages.icy.file.Loader) importClass(Packages.plugins.adufour.filtering.Convolution1D) importClass(Packages.plugins.adufour.filtering.Kernels1D) importClass(Packages.plugins.adufour.thresholder.Thresholder) importClass(Packages.plugins.adufour.thresholder.KMeans) importClass(Packages.icy.file.Saver) /* * Request image file and verify if path is not empty */ f = FileDialog.open() if (!f.toString().equals("")) { /* * Load sequence from f and check if seq is valid */ seq = Loader.loadSequence(f, 0, true) if (seq != null) { /* * Set the kernel of 3x3 */ sigma = 3 kernelX = Kernels1D.CUSTOM_GAUSSIAN.createGaussianKernel1D(sigma).getData() kernelY = Kernels1D.CUSTOM_GAUSSIAN.createGaussianKernel1D(sigma).getData() /* * Create a copy of the original sequence and perform convolution */ seqf = seq.getCopy() Convolution1D.convolve(seqf, kernelX, kernelY, null) /* * Show gaussian result */ gui.addSequence(seqf) /* * Find threshold using KMeans method and perform binary threshold */ kmeans = KMeans.computeKMeansThresholds(seq, 2, 2, 255) result = Thresholder.threshold(seqf, 2, kmeans, false) result.setName(seq.getName() + " - thresholded") /* * Show result of binary Threshold */ gui.addSequence(result) /* * Save result to file */ //f = FileDialog.save() //Saver.save(result, f, true, true) } }

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  /* import the different Classes needed - FileDialog is used to select file and Loader to load the image - Package filtering is used to create the kernel and perform the convolution - Package thresholder is needed to do the threshold with   Thresholder and KMeans classes. */ importClass(Packages.plugins.tprovoost.scripteditor.uitools.filedialogs.FileDialog) importClass(Packages.icy.file.Loader) importClass(Packages.plugins.adufour.filtering.Convolution1D) importClass(Packages.plugins.adufour.filtering.Kernels1D) importClass(Packages.plugins.adufour.thresholder.Thresholder) importClass(Packages.plugins.adufour.thresholder.KMeans) importClass(Packages.icy.file.Saver)   /* * Request image file and verify if path is not empty */ f = FileDialog.open() if (!f.toString().equals("")) { /* * Load sequence from f and check if seq is valid */ seq = Loader.loadSequence(f, 0, true) if (seq != null) { /* * Set the kernel of 3x3 */ sigma = 3 kernelX = Kernels1D.CUSTOM_GAUSSIAN.createGaussianKernel1D(sigma).getData() kernelY = Kernels1D.CUSTOM_GAUSSIAN.createGaussianKernel1D(sigma).getData() /* * Create a copy of the original sequence and perform convolution */ seqf = seq.getCopy() Convolution1D.convolve(seqf, kernelX, kernelY, null) /* * Show gaussian result */ gui.addSequence(seqf) /* * Find threshold using KMeans method and perform binary threshold */ kmeans = KMeans.computeKMeansThresholds(seq, 2, 2, 255) result = Thresholder.threshold(seqf, 2, kmeans, false) result.setName(seq.getName() + " - thresholded") /* * Show result of binary Threshold */ gui.addSequence(result)   /* * Save result to file */ //f = FileDialog.save() //Saver.save(result, f, true, true) } }

• Version 1 • Released on: 2015-07-21 05:48:57
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  Description:

  initial version

  importClass(Packages.plugins.adufour.filtering.Convolution1D) importClass(Packages.plugins.adufour.filtering.Kernels1D) importClass(Packages.icy.file.Saver) importClass(Packages.icy.file.Loader) importClass(Packages.plugins.tprovoost.scripteditor.uitools.filedialogs.FileDialog) importClass(Packages.plugins.adufour.thresholder.Thresholder) importClass(Packages.plugins.adufour.thresholder.KMeans) importClass(Packages.icy.sequence.SequenceUtil) f = FileDialog.open() seq = Loader.loadSequence(f, 0, true) sigma = 3 kernelX = Kernels1D.CUSTOM_GAUSSIAN.createGaussianKernel1D(sigma).getData() kernelY = Kernels1D.CUSTOM_GAUSSIAN.createGaussianKernel1D(sigma).getData() seqf = seq.getCopy() Convolution1D.convolve(seqf, kernelX, kernelY, null) gui.addSequence(seqf) kmeans = KMeans.computeKMeansThresholds(seq, 2, 2, 255) result = Thresholder.threshold(seqf, 2, kmeans, false) result.setName(seq.getName() + " - thresholded") gui.addSequence(result) //f = FileDialog.save() //Saver.save(result, f, true, true)

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  importClass(Packages.plugins.adufour.filtering.Convolution1D) importClass(Packages.plugins.adufour.filtering.Kernels1D) importClass(Packages.icy.file.Saver) importClass(Packages.icy.file.Loader) importClass(Packages.plugins.tprovoost.scripteditor.uitools.filedialogs.FileDialog) importClass(Packages.plugins.adufour.thresholder.Thresholder) importClass(Packages.plugins.adufour.thresholder.KMeans) importClass(Packages.icy.sequence.SequenceUtil) f = FileDialog.open() seq = Loader.loadSequence(f, 0, true)   sigma = 3 kernelX = Kernels1D.CUSTOM_GAUSSIAN.createGaussianKernel1D(sigma).getData() kernelY = Kernels1D.CUSTOM_GAUSSIAN.createGaussianKernel1D(sigma).getData() seqf = seq.getCopy() Convolution1D.convolve(seqf, kernelX, kernelY, null)   gui.addSequence(seqf)   kmeans = KMeans.computeKMeansThresholds(seq, 2, 2, 255) result = Thresholder.threshold(seqf, 2, kmeans, false) result.setName(seq.getName() + " - thresholded")   gui.addSequence(result)   //f = FileDialog.save() //Saver.save(result, f, true, true)