GPU accelerated image processing for everyone
Computes a masked image by applying a binary mask to an image.
All pixel values x of image X will be copied to the destination image in case pixel value m at the same position in the mask image is not equal to zero.
f(x,m) = (x if (m != 0); (0 otherwise))
Availability: Available in Fiji by activating the update sites clij and clij2. This function is part of clij2_-2.5.0.1.jar.
Ext.CLIJ2_mask(Image source, Image mask, Image destination);
// init CLIJ and GPU import net.haesleinhuepf.clij2.CLIJ2; import net.haesleinhuepf.clij.clearcl.ClearCLBuffer; CLIJ2 clij2 = CLIJ2.getInstance(); // get input parameters ClearCLBuffer source = clij2.push(sourceImagePlus); ClearCLBuffer mask = clij2.push(maskImagePlus); destination = clij2.create(source);
// Execute operation on GPU clij2.mask(source, mask, destination);
// show result destinationImagePlus = clij2.pull(destination); destinationImagePlus.show(); // cleanup memory on GPU clij2.release(source); clij2.release(mask); clij2.release(destination);
% init CLIJ and GPU clij2 = init_clatlab(); % get input parameters source = clij2.pushMat(source_matrix); mask = clij2.pushMat(mask_matrix); destination = clij2.create(source);
% Execute operation on GPU clij2.mask(source, mask, destination);
% show result destination = clij2.pullMat(destination) % cleanup memory on GPU clij2.release(source); clij2.release(mask); clij2.release(destination);
// init CLIJ and GPU importClass(net.haesleinhuepf.clicy.CLICY); importClass(Packages.icy.main.Icy); clij2 = CLICY.getInstance(); // get input parameters source_sequence = getSequence(); source = clij2.pushSequence(source_sequence); mask_sequence = getSequence(); mask = clij2.pushSequence(mask_sequence); destination = clij2.create(source);
// Execute operation on GPU clij2.mask(source, mask, destination);
// show result destination_sequence = clij2.pullSequence(destination) Icy.addSequence(destination_sequence); // cleanup memory on GPU clij2.release(source); clij2.release(mask); clij2.release(destination);
import pyclesperanto_prototype as cle cle.mask(source, mask, destination)
outlines_numbers_overlay
tribolium_morphometry
voronoi_otsu_labeling
napari_dask.ipynb
voronoi_otsu_labeling.ipynb
tribolium_morphometry.ipynb
division_visualisation.ijm
intensity_per_label.ijm
outlines_numbers_overlay.ijm
tribolium_morphometry.ijm
voronoi_otsu_labeling.ijm
statistics.py
tribolium.py