From fe839689ce4e4ae6e61d7a42d12323db221704c7 Mon Sep 17 00:00:00 2001 From: haesleinhuepf Date: Mon, 13 Apr 2020 20:34:53 +0200 Subject: [PATCH] regenerated ops and docs --- .../clijx/jython/CLIJ2AutoComplete.java | 11 +- .../clijx/jython/CLIJxAutoComplete.java | 11 +- .../clijx/utilities/CLIJxOps.java | 148 +++++++++--------- 3 files changed, 89 insertions(+), 81 deletions(-) diff --git a/src/main/java/net/haesleinhuepf/clijx/jython/CLIJ2AutoComplete.java b/src/main/java/net/haesleinhuepf/clijx/jython/CLIJ2AutoComplete.java index 0b527ee..097333a 100644 --- a/src/main/java/net/haesleinhuepf/clijx/jython/CLIJ2AutoComplete.java +++ b/src/main/java/net/haesleinhuepf/clijx/jython/CLIJ2AutoComplete.java @@ -302,8 +302,11 @@ public static ArrayList getCompletions(final ScriptingAutoCompl headline = "clij2.pullAsROI(ClearCLBuffer binary_input)"; description = "pullAsROI

Pulls a binary image from the GPU memory and puts it on the currently active ImageJ window.

Parameters:
ClearCLBuffer binary_input"; list.add(new BasicCompletion(provider, headline, null, description)); - headline = "clij2.pullLabelsToROIManager(ClearCLBuffer binary_input)"; - description = "pullLabelsToROIManager

Pulls all labels in a label map as ROIs to the ROI manager.

Parameters:
ClearCLBuffer binary_input"; + headline = "clij2.pullLabelsToROIList(ClearCLBuffer labelmap_input)"; + description = "pullLabelsToROIList

Pulls all labels in a label map as ROIs to a list.

Parameters:
ClearCLBuffer labelmap_input"; + list.add(new BasicCompletion(provider, headline, null, description)); + headline = "clij2.pullLabelsToROIManager(ClearCLBuffer labelmap_input)"; + description = "pullLabelsToROIManager

Pulls all labels in a label map as ROIs to the ROI manager.

Parameters:
ClearCLBuffer labelmap_input"; list.add(new BasicCompletion(provider, headline, null, description)); headline = "clij2.resliceBottom(ClearCLImageInterface source, ClearCLImageInterface destination)"; description = "resliceBottom

Flippes Y and Z axis of an image stack. This operation is similar to ImageJs 'Reslice [/]' method but
offers less flexibility such as interpolation.

Parameters:
ClearCLImageInterface source, ClearCLImageInterface destination"; @@ -378,7 +381,7 @@ public static ArrayList getCompletions(final ScriptingAutoCompl description = "standardDeviationOfMaskedPixels

Determines the standard deviation of all pixels in an image which have non-zero value in a corresponding mask image. The value will be stored in a new row of ImageJs
Results table in the column 'Masked_standard_deviation'.

Parameters:
ClearCLBuffer source, ClearCLBuffer mask"; list.add(new BasicCompletion(provider, headline, null, description)); headline = "clij2.statisticsOfLabelledPixels(ClearCLBuffer input, ClearCLBuffer labelmap)"; - description = "statisticsOfLabelledPixels

Determines bounding box, area (in pixels/voxels), min, max and mean intensity of a labelled object in a label map and corresponding pixels in the original image.Instead of a label map, you can also use a binary image as a binary image is a label map with just one label.

Parameters:
ClearCLBuffer input, ClearCLBuffer labelmap"; + description = "statisticsOfLabelledPixels

Determines bounding box, area (in pixels/voxels), min, max and mean intensity of labelled objects in a label map and corresponding pixels in the original image.Instead of a label map, you can also use a binary image as a binary image is a label map with just one label.

Parameters:
ClearCLBuffer input, ClearCLBuffer labelmap"; list.add(new BasicCompletion(provider, headline, null, description)); headline = "clij2.subtractImages(ClearCLImageInterface subtrahend, ClearCLImageInterface minuend, ClearCLImageInterface destination)"; description = "subtractImages

Subtracts one image X from another image Y pixel wise.

f(x, y) = x - y


Parameters:
ClearCLImageInterface subtrahend, ClearCLImageInterface minuend, ClearCLImageInterface destination"; @@ -413,4 +416,4 @@ public static ArrayList getCompletions(final ScriptingAutoCompl return list; } } -// 134 methods generated. +// 135 methods generated. diff --git a/src/main/java/net/haesleinhuepf/clijx/jython/CLIJxAutoComplete.java b/src/main/java/net/haesleinhuepf/clijx/jython/CLIJxAutoComplete.java index 96a9dc4..d1ff62a 100644 --- a/src/main/java/net/haesleinhuepf/clijx/jython/CLIJxAutoComplete.java +++ b/src/main/java/net/haesleinhuepf/clijx/jython/CLIJxAutoComplete.java @@ -335,8 +335,11 @@ public static ArrayList getCompletions(final ScriptingAutoCompl headline = "clijx.pullAsROI(ClearCLBuffer binary_input)"; description = "pullAsROI

Pulls a binary image from the GPU memory and puts it on the currently active ImageJ window.

Parameters:
ClearCLBuffer binary_input"; list.add(new BasicCompletion(provider, headline, null, description)); - headline = "clijx.pullLabelsToROIManager(ClearCLBuffer binary_input)"; - description = "pullLabelsToROIManager

Pulls all labels in a label map as ROIs to the ROI manager.

Parameters:
ClearCLBuffer binary_input"; + headline = "clijx.pullLabelsToROIList(ClearCLBuffer labelmap_input)"; + description = "pullLabelsToROIList

Pulls all labels in a label map as ROIs to a list.

Parameters:
ClearCLBuffer labelmap_input"; + list.add(new BasicCompletion(provider, headline, null, description)); + headline = "clijx.pullLabelsToROIManager(ClearCLBuffer labelmap_input)"; + description = "pullLabelsToROIManager

Pulls all labels in a label map as ROIs to the ROI manager.

Parameters:
ClearCLBuffer labelmap_input"; list.add(new BasicCompletion(provider, headline, null, description)); headline = "clijx.resliceBottom(ClearCLImageInterface source, ClearCLImageInterface destination)"; description = "resliceBottom

Flippes Y and Z axis of an image stack. This operation is similar to ImageJs 'Reslice [/]' method but
offers less flexibility such as interpolation.

Parameters:
ClearCLImageInterface source, ClearCLImageInterface destination"; @@ -426,7 +429,7 @@ public static ArrayList getCompletions(final ScriptingAutoCompl description = "startContinuousWebcamAcquisition

Acquires an image (in fact an RGB image stack with three slices) of given size using a webcam. It uses the webcam-capture library by Bartosz Firyn.https://github.com/sarxos/webcam-capture

Parameters:
Integer cameraDeviceIndex, Integer imageWidth, Integer imageHeight"; list.add(new BasicCompletion(provider, headline, null, description)); headline = "clijx.statisticsOfLabelledPixels(ClearCLBuffer input, ClearCLBuffer labelmap)"; - description = "statisticsOfLabelledPixels

Determines bounding box, area (in pixels/voxels), min, max and mean intensity of a labelled object in a label map and corresponding pixels in the original image.Instead of a label map, you can also use a binary image as a binary image is a label map with just one label.

Parameters:
ClearCLBuffer input, ClearCLBuffer labelmap"; + description = "statisticsOfLabelledPixels

Determines bounding box, area (in pixels/voxels), min, max and mean intensity of labelled objects in a label map and corresponding pixels in the original image.Instead of a label map, you can also use a binary image as a binary image is a label map with just one label.

Parameters:
ClearCLBuffer input, ClearCLBuffer labelmap"; list.add(new BasicCompletion(provider, headline, null, description)); headline = "clijx.stopContinuousWebcamAcquisition(Integer cameraDeviceIndex)"; description = "stopContinuousWebcamAcquisition

Acquires an image (in fact an RGB image stack with three slices) of given size using a webcam. It uses the webcam-capture library by Bartosz Firyn.https://github.com/sarxos/webcam-capture

Parameters:
Integer cameraDeviceIndex"; @@ -482,4 +485,4 @@ public static ArrayList getCompletions(final ScriptingAutoCompl return list; } } -// 157 methods generated. +// 158 methods generated. diff --git a/src/main/java/net/haesleinhuepf/clijx/utilities/CLIJxOps.java b/src/main/java/net/haesleinhuepf/clijx/utilities/CLIJxOps.java index bcd4307..a0f5ba7 100644 --- a/src/main/java/net/haesleinhuepf/clijx/utilities/CLIJxOps.java +++ b/src/main/java/net/haesleinhuepf/clijx/utilities/CLIJxOps.java @@ -12,6 +12,8 @@ import ij.plugin.frame.RoiManager; import java.util.HashMap; import ij.ImagePlus; +import java.util.List; +import java.util.ArrayList; import net.haesleinhuepf.clij.kernels.Kernels; import net.haesleinhuepf.clijx.plugins.CrossCorrelation; import net.haesleinhuepf.clijx.plugins.Extrema; @@ -76,10 +78,17 @@ public abstract interface CLIJxOps { // net.haesleinhuepf.clij.kernels.Kernels //---------------------------------------------------- /** - * Deforms an image according to distances provided in the given vector images. It is recommended to use 32-bit images for input, output and vector images. + * */ - default boolean applyVectorfield(ClearCLBuffer source, ClearCLBuffer vectorX, ClearCLBuffer vectorY, ClearCLBuffer destination) { - return Kernels.applyVectorfield(getCLIJ(), source, vectorX, vectorY, destination); + default boolean detectOptima(ClearCLBuffer arg1, ClearCLBuffer arg2, double arg3, boolean arg4) { + return Kernels.detectOptima(getCLIJ(), arg1, arg2, new Double (arg3).intValue(), arg4); + } + + /** + * + */ + default boolean detectOptima(ClearCLImage arg1, ClearCLImage arg2, double arg3, boolean arg4) { + return Kernels.detectOptima(getCLIJ(), arg1, arg2, new Double (arg3).intValue(), arg4); } /** @@ -104,78 +113,71 @@ default boolean applyVectorfield(ClearCLImage source, ClearCLImage vectorX, Clea } /** - * - */ - default boolean detectOptima(ClearCLImage arg1, ClearCLImage arg2, double arg3, boolean arg4) { - return Kernels.detectOptima(getCLIJ(), arg1, arg2, new Double (arg3).intValue(), arg4); - } - - /** - * + * Deforms an image according to distances provided in the given vector images. It is recommended to use 32-bit images for input, output and vector images. */ - default boolean detectOptima(ClearCLBuffer arg1, ClearCLBuffer arg2, double arg3, boolean arg4) { - return Kernels.detectOptima(getCLIJ(), arg1, arg2, new Double (arg3).intValue(), arg4); + default boolean applyVectorfield(ClearCLBuffer source, ClearCLBuffer vectorX, ClearCLBuffer vectorY, ClearCLBuffer destination) { + return Kernels.applyVectorfield(getCLIJ(), source, vectorX, vectorY, destination); } /** + * Determines the maximum projection of an image along a given dimension. Furthermore, the X and Y + * dimesions of the resulting image must be specified by the user according to its definition: + * X = 0 + * Y = 1 + * Z = 2 * */ - default double[] sumPixelsSliceBySlice(ClearCLImage arg1) { - return Kernels.sumPixelsSliceBySlice(getCLIJ(), arg1); + default boolean maximumXYZProjection(ClearCLImage arg1, ClearCLImage arg2, double arg3, double arg4, double arg5) { + return Kernels.maximumXYZProjection(getCLIJ(), arg1, arg2, new Double (arg3).intValue(), new Double (arg4).intValue(), new Double (arg5).intValue()); } /** + * Determines the maximum projection of an image along a given dimension. Furthermore, the X and Y + * dimesions of the resulting image must be specified by the user according to its definition: + * X = 0 + * Y = 1 + * Z = 2 * */ - default double[] sumPixelsSliceBySlice(ClearCLBuffer arg1) { - return Kernels.sumPixelsSliceBySlice(getCLIJ(), arg1); + default boolean maximumXYZProjection(ClearCLBuffer arg1, ClearCLBuffer arg2, double arg3, double arg4, double arg5) { + return Kernels.maximumXYZProjection(getCLIJ(), arg1, arg2, new Double (arg3).intValue(), new Double (arg4).intValue(), new Double (arg5).intValue()); } /** + * Applies Gaussian blur to the input image twice with different sigma values resulting in two images which are then subtracted from each other. * + * It is recommended to apply this operation to images of type Float (32 bit) as results might be negative. */ - default boolean multiplySliceBySliceWithScalars(ClearCLImage arg1, ClearCLImage arg2, float[] arg3) { - return Kernels.multiplySliceBySliceWithScalars(getCLIJ(), arg1, arg2, arg3); + default boolean differenceOfGaussian(ClearCLImage arg1, ClearCLImage arg2, double arg3, double arg4, double arg5) { + return Kernels.differenceOfGaussian(getCLIJ(), arg1, arg2, new Double (arg3).intValue(), new Double (arg4).floatValue(), new Double (arg5).floatValue()); } /** * */ - default boolean multiplySliceBySliceWithScalars(ClearCLBuffer arg1, ClearCLBuffer arg2, float[] arg3) { - return Kernels.multiplySliceBySliceWithScalars(getCLIJ(), arg1, arg2, arg3); + default boolean convertToImageJBinary(ClearCLImage arg1, ClearCLImage arg2) { + return Kernels.convertToImageJBinary(getCLIJ(), arg1, arg2); } /** - * Determines the maximum projection of an image along a given dimension. Furthermore, the X and Y - * dimesions of the resulting image must be specified by the user according to its definition: - * X = 0 - * Y = 1 - * Z = 2 * */ - default boolean maximumXYZProjection(ClearCLImage arg1, ClearCLImage arg2, double arg3, double arg4, double arg5) { - return Kernels.maximumXYZProjection(getCLIJ(), arg1, arg2, new Double (arg3).intValue(), new Double (arg4).intValue(), new Double (arg5).intValue()); + default boolean convertToImageJBinary(ClearCLBuffer arg1, ClearCLBuffer arg2) { + return Kernels.convertToImageJBinary(getCLIJ(), arg1, arg2); } /** - * Determines the maximum projection of an image along a given dimension. Furthermore, the X and Y - * dimesions of the resulting image must be specified by the user according to its definition: - * X = 0 - * Y = 1 - * Z = 2 * */ - default boolean maximumXYZProjection(ClearCLBuffer arg1, ClearCLBuffer arg2, double arg3, double arg4, double arg5) { - return Kernels.maximumXYZProjection(getCLIJ(), arg1, arg2, new Double (arg3).intValue(), new Double (arg4).intValue(), new Double (arg5).intValue()); + default boolean detectOptimaSliceBySlice(ClearCLBuffer arg1, ClearCLBuffer arg2, double arg3, boolean arg4) { + return Kernels.detectOptimaSliceBySlice(getCLIJ(), arg1, arg2, new Double (arg3).intValue(), arg4); } /** - * Applies Gaussian blur to the input image twice with different sigma values resulting in two images which are then subtracted from each other. * - * It is recommended to apply this operation to images of type Float (32 bit) as results might be negative. */ - default boolean differenceOfGaussian(ClearCLImage arg1, ClearCLImage arg2, double arg3, double arg4, double arg5) { - return Kernels.differenceOfGaussian(getCLIJ(), arg1, arg2, new Double (arg3).intValue(), new Double (arg4).floatValue(), new Double (arg5).floatValue()); + default boolean detectOptimaSliceBySlice(ClearCLImage arg1, ClearCLImage arg2, double arg3, boolean arg4) { + return Kernels.detectOptimaSliceBySlice(getCLIJ(), arg1, arg2, new Double (arg3).intValue(), arg4); } /** @@ -188,29 +190,29 @@ default boolean differenceOfGaussianSliceBySlice(ClearCLImage arg1, ClearCLImage /** * */ - default boolean convertToImageJBinary(ClearCLImage arg1, ClearCLImage arg2) { - return Kernels.convertToImageJBinary(getCLIJ(), arg1, arg2); + default double[] sumPixelsSliceBySlice(ClearCLBuffer arg1) { + return Kernels.sumPixelsSliceBySlice(getCLIJ(), arg1); } /** * */ - default boolean convertToImageJBinary(ClearCLBuffer arg1, ClearCLBuffer arg2) { - return Kernels.convertToImageJBinary(getCLIJ(), arg1, arg2); + default double[] sumPixelsSliceBySlice(ClearCLImage arg1) { + return Kernels.sumPixelsSliceBySlice(getCLIJ(), arg1); } /** * */ - default boolean detectOptimaSliceBySlice(ClearCLBuffer arg1, ClearCLBuffer arg2, double arg3, boolean arg4) { - return Kernels.detectOptimaSliceBySlice(getCLIJ(), arg1, arg2, new Double (arg3).intValue(), arg4); + default boolean multiplySliceBySliceWithScalars(ClearCLImage arg1, ClearCLImage arg2, float[] arg3) { + return Kernels.multiplySliceBySliceWithScalars(getCLIJ(), arg1, arg2, arg3); } /** * */ - default boolean detectOptimaSliceBySlice(ClearCLImage arg1, ClearCLImage arg2, double arg3, boolean arg4) { - return Kernels.detectOptimaSliceBySlice(getCLIJ(), arg1, arg2, new Double (arg3).intValue(), arg4); + default boolean multiplySliceBySliceWithScalars(ClearCLBuffer arg1, ClearCLBuffer arg2, float[] arg3) { + return Kernels.multiplySliceBySliceWithScalars(getCLIJ(), arg1, arg2, arg3); } @@ -286,15 +288,15 @@ default boolean stackToTiles(ClearCLImageInterface arg1, ClearCLImageInterface a /** * Applies Gaussian blur to the input image and subtracts the result from the original image. */ - default boolean subtractBackground2D(ClearCLImageInterface arg1, ClearCLImageInterface arg2, double arg3, double arg4) { - return SubtractBackground2D.subtractBackground2D(getCLIJx(), arg1, arg2, new Double (arg3).floatValue(), new Double (arg4).floatValue()); + default boolean subtractBackground(ClearCLImageInterface arg1, ClearCLImageInterface arg2, double arg3, double arg4) { + return SubtractBackground2D.subtractBackground(getCLIJx(), arg1, arg2, new Double (arg3).floatValue(), new Double (arg4).floatValue()); } /** * Applies Gaussian blur to the input image and subtracts the result from the original image. */ - default boolean subtractBackground(ClearCLImageInterface arg1, ClearCLImageInterface arg2, double arg3, double arg4) { - return SubtractBackground2D.subtractBackground(getCLIJx(), arg1, arg2, new Double (arg3).floatValue(), new Double (arg4).floatValue()); + default boolean subtractBackground2D(ClearCLImageInterface arg1, ClearCLImageInterface arg2, double arg3, double arg4) { + return SubtractBackground2D.subtractBackground2D(getCLIJx(), arg1, arg2, new Double (arg3).floatValue(), new Double (arg4).floatValue()); } @@ -303,15 +305,15 @@ default boolean subtractBackground(ClearCLImageInterface arg1, ClearCLImageInter /** * Applies Gaussian blur to the input image and subtracts the result from the original image. */ - default boolean subtractBackground(ClearCLImageInterface arg1, ClearCLImageInterface arg2, double arg3, double arg4, double arg5) { - return SubtractBackground3D.subtractBackground(getCLIJx(), arg1, arg2, new Double (arg3).floatValue(), new Double (arg4).floatValue(), new Double (arg5).floatValue()); + default boolean subtractBackground3D(ClearCLImageInterface arg1, ClearCLImageInterface arg2, double arg3, double arg4, double arg5) { + return SubtractBackground3D.subtractBackground3D(getCLIJx(), arg1, arg2, new Double (arg3).floatValue(), new Double (arg4).floatValue(), new Double (arg5).floatValue()); } /** * Applies Gaussian blur to the input image and subtracts the result from the original image. */ - default boolean subtractBackground3D(ClearCLImageInterface arg1, ClearCLImageInterface arg2, double arg3, double arg4, double arg5) { - return SubtractBackground3D.subtractBackground3D(getCLIJx(), arg1, arg2, new Double (arg3).floatValue(), new Double (arg4).floatValue(), new Double (arg5).floatValue()); + default boolean subtractBackground(ClearCLImageInterface arg1, ClearCLImageInterface arg2, double arg3, double arg4, double arg5) { + return SubtractBackground3D.subtractBackground(getCLIJx(), arg1, arg2, new Double (arg3).floatValue(), new Double (arg4).floatValue(), new Double (arg5).floatValue()); } @@ -320,14 +322,14 @@ default boolean subtractBackground3D(ClearCLImageInterface arg1, ClearCLImageInt /** * */ - default boolean particleImageVelocimetry2D(ClearCLImage arg1, ClearCLImage arg2, ClearCLImage arg3, ClearCLImage arg4, double arg5) { + default boolean particleImageVelocimetry2D(ClearCLBuffer arg1, ClearCLBuffer arg2, ClearCLBuffer arg3, ClearCLBuffer arg4, double arg5) { return FastParticleImageVelocimetry.particleImageVelocimetry2D(getCLIJ(), arg1, arg2, arg3, arg4, new Double (arg5).intValue()); } /** * */ - default boolean particleImageVelocimetry2D(ClearCLBuffer arg1, ClearCLBuffer arg2, ClearCLBuffer arg3, ClearCLBuffer arg4, double arg5) { + default boolean particleImageVelocimetry2D(ClearCLImage arg1, ClearCLImage arg2, ClearCLImage arg3, ClearCLImage arg4, double arg5) { return FastParticleImageVelocimetry.particleImageVelocimetry2D(getCLIJ(), arg1, arg2, arg3, arg4, new Double (arg5).intValue()); } @@ -406,15 +408,15 @@ default ClearCLBuffer readImageFromDisc(String arg1) { /** * Reads a raw file from disc and pushes it immediately to the GPU. */ - default boolean readRawImageFromDisc(ClearCLBuffer arg1, String arg2) { - return ReadRawImageFromDisc.readRawImageFromDisc(getCLIJ(), arg1, arg2); + default ClearCLBuffer readRawImageFromDisc(String arg1, double arg2, double arg3, double arg4, double arg5) { + return ReadRawImageFromDisc.readRawImageFromDisc(getCLIJ(), arg1, new Double (arg2).intValue(), new Double (arg3).intValue(), new Double (arg4).intValue(), new Double (arg5).intValue()); } /** * Reads a raw file from disc and pushes it immediately to the GPU. */ - default ClearCLBuffer readRawImageFromDisc(String arg1, double arg2, double arg3, double arg4, double arg5) { - return ReadRawImageFromDisc.readRawImageFromDisc(getCLIJ(), arg1, new Double (arg2).intValue(), new Double (arg3).intValue(), new Double (arg4).intValue(), new Double (arg5).intValue()); + default boolean readRawImageFromDisc(ClearCLBuffer arg1, String arg2) { + return ReadRawImageFromDisc.readRawImageFromDisc(getCLIJ(), arg1, arg2); } @@ -686,22 +688,22 @@ default boolean skeletonize(ClearCLBuffer arg1, ClearCLBuffer arg2) { /** * Copies a tile in an image specified by its name, position and size to GPU memory in order to process it there later. */ - default ClearCLBuffer pushTile(ClearCLBuffer arg1, int arg2, int arg3, int arg4, int arg5, int arg6, int arg7, int arg8, int arg9, int arg10) { + default ClearCLBuffer pushTile(ImagePlus arg1, int arg2, int arg3, int arg4, int arg5, int arg6, int arg7, int arg8, int arg9, int arg10) { return PushTile.pushTile(getCLIJ2(), arg1, arg2, arg3, arg4, arg5, arg6, arg7, arg8, arg9, arg10); } /** * Copies a tile in an image specified by its name, position and size to GPU memory in order to process it there later. */ - default ClearCLBuffer pushTile(ImagePlus arg1, int arg2, int arg3, int arg4, int arg5, int arg6, int arg7, int arg8, int arg9, int arg10) { - return PushTile.pushTile(getCLIJ2(), arg1, arg2, arg3, arg4, arg5, arg6, arg7, arg8, arg9, arg10); + default void pushTile(ImagePlus arg1, String arg2, int arg3, int arg4, int arg5, int arg6, int arg7, int arg8, int arg9, int arg10, int arg11) { + PushTile.pushTile(getCLIJ2(), arg1, arg2, arg3, arg4, arg5, arg6, arg7, arg8, arg9, arg10, arg11); } /** * Copies a tile in an image specified by its name, position and size to GPU memory in order to process it there later. */ - default void pushTile(ImagePlus arg1, String arg2, int arg3, int arg4, int arg5, int arg6, int arg7, int arg8, int arg9, int arg10, int arg11) { - PushTile.pushTile(getCLIJ2(), arg1, arg2, arg3, arg4, arg5, arg6, arg7, arg8, arg9, arg10, arg11); + default ClearCLBuffer pushTile(ClearCLBuffer arg1, int arg2, int arg3, int arg4, int arg5, int arg6, int arg7, int arg8, int arg9, int arg10) { + return PushTile.pushTile(getCLIJ2(), arg1, arg2, arg3, arg4, arg5, arg6, arg7, arg8, arg9, arg10); } @@ -710,21 +712,21 @@ default void pushTile(ImagePlus arg1, String arg2, int arg3, int arg4, int arg5, /** * Copies a tile in an image specified by its name, position and size to GPU memory in order to process it there later. */ - default void pullTile(ClearCLBuffer arg1, ClearCLBuffer arg2, int arg3, int arg4, int arg5, int arg6, int arg7, int arg8, int arg9, int arg10, int arg11) { + default void pullTile(ImagePlus arg1, String arg2, int arg3, int arg4, int arg5, int arg6, int arg7, int arg8, int arg9, int arg10, int arg11) { PullTile.pullTile(getCLIJ2(), arg1, arg2, arg3, arg4, arg5, arg6, arg7, arg8, arg9, arg10, arg11); } /** * Copies a tile in an image specified by its name, position and size to GPU memory in order to process it there later. */ - default void pullTile(ImagePlus arg1, String arg2, int arg3, int arg4, int arg5, int arg6, int arg7, int arg8, int arg9, int arg10, int arg11) { + default void pullTile(ImagePlus arg1, ClearCLBuffer arg2, int arg3, int arg4, int arg5, int arg6, int arg7, int arg8, int arg9, int arg10, int arg11) { PullTile.pullTile(getCLIJ2(), arg1, arg2, arg3, arg4, arg5, arg6, arg7, arg8, arg9, arg10, arg11); } /** * Copies a tile in an image specified by its name, position and size to GPU memory in order to process it there later. */ - default void pullTile(ImagePlus arg1, ClearCLBuffer arg2, int arg3, int arg4, int arg5, int arg6, int arg7, int arg8, int arg9, int arg10, int arg11) { + default void pullTile(ClearCLBuffer arg1, ClearCLBuffer arg2, int arg3, int arg4, int arg5, int arg6, int arg7, int arg8, int arg9, int arg10, int arg11) { PullTile.pullTile(getCLIJ2(), arg1, arg2, arg3, arg4, arg5, arg6, arg7, arg8, arg9, arg10, arg11); } @@ -755,16 +757,16 @@ default boolean trainAutoContextWekaModelWithOptions(ClearCLBuffer arg1, ClearCL * Applies a Weka model using functionality of Fijis Trainable Weka Segmentation plugin. * It takes a 3D feature stack (e.g. first plane original image, second plane blurred, third plane edge image)and applies a pre-trained a Weka model. Take care that the feature stack has been generated in the sameway as for training the model! */ - default CLIJxWeka2 applyWekaModel(ClearCLBuffer featureStack3D, ClearCLBuffer prediction2D_destination, String loadModelFilename) { - return ApplyWekaModel.applyWekaModel(getCLIJ2(), featureStack3D, prediction2D_destination, loadModelFilename); + default boolean applyWekaModel(ClearCLBuffer arg1, ClearCLBuffer arg2, CLIJxWeka2 arg3) { + return ApplyWekaModel.applyWekaModel(getCLIJ2(), arg1, arg2, arg3); } /** * Applies a Weka model using functionality of Fijis Trainable Weka Segmentation plugin. * It takes a 3D feature stack (e.g. first plane original image, second plane blurred, third plane edge image)and applies a pre-trained a Weka model. Take care that the feature stack has been generated in the sameway as for training the model! */ - default boolean applyWekaModel(ClearCLBuffer arg1, ClearCLBuffer arg2, CLIJxWeka2 arg3) { - return ApplyWekaModel.applyWekaModel(getCLIJ2(), arg1, arg2, arg3); + default CLIJxWeka2 applyWekaModel(ClearCLBuffer featureStack3D, ClearCLBuffer prediction2D_destination, String loadModelFilename) { + return ApplyWekaModel.applyWekaModel(getCLIJ2(), featureStack3D, prediction2D_destination, loadModelFilename); }