GPU accelerated image processing for everyone
This operation removes labels from a labelmap and renumbers the remaining labels.
Hand over a binary flag list vector starting with a flag for the background, continuing with label1, label2, …
For example if you pass 0,1,0,0,1: Labels 1 and 4 will be removed (those with a 1 in the vector will be excluded). Labels 2 and 3 will be kept and renumbered to 1 and 2.
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_excludeLabels(Image binary_flaglist, Image label_map_input, Image label_map_destination);
// init CLIJ and GPU import net.haesleinhuepf.clij2.CLIJ2; import net.haesleinhuepf.clij.clearcl.ClearCLBuffer; CLIJ2 clij2 = CLIJ2.getInstance(); // get input parameters ClearCLBuffer binary_flaglist = clij2.push(binary_flaglistImagePlus); ClearCLBuffer label_map_input = clij2.push(label_map_inputImagePlus); label_map_destination = clij2.create(binary_flaglist);
// Execute operation on GPU clij2.excludeLabels(binary_flaglist, label_map_input, label_map_destination);
// show result label_map_destinationImagePlus = clij2.pull(label_map_destination); label_map_destinationImagePlus.show(); // cleanup memory on GPU clij2.release(binary_flaglist); clij2.release(label_map_input); clij2.release(label_map_destination);
% init CLIJ and GPU clij2 = init_clatlab(); % get input parameters binary_flaglist = clij2.pushMat(binary_flaglist_matrix); label_map_input = clij2.pushMat(label_map_input_matrix); label_map_destination = clij2.create(binary_flaglist);
% Execute operation on GPU clij2.excludeLabels(binary_flaglist, label_map_input, label_map_destination);
% show result label_map_destination = clij2.pullMat(label_map_destination) % cleanup memory on GPU clij2.release(binary_flaglist); clij2.release(label_map_input); clij2.release(label_map_destination);
// init CLIJ and GPU importClass(net.haesleinhuepf.clicy.CLICY); importClass(Packages.icy.main.Icy); clij2 = CLICY.getInstance(); // get input parameters binary_flaglist_sequence = getSequence(); binary_flaglist = clij2.pushSequence(binary_flaglist_sequence); label_map_input_sequence = getSequence(); label_map_input = clij2.pushSequence(label_map_input_sequence); label_map_destination = clij2.create(binary_flaglist);
// Execute operation on GPU clij2.excludeLabels(binary_flaglist, label_map_input, label_map_destination);
// show result label_map_destination_sequence = clij2.pullSequence(label_map_destination) Icy.addSequence(label_map_destination_sequence); // cleanup memory on GPU clij2.release(binary_flaglist); clij2.release(label_map_input); clij2.release(label_map_destination);
import pyclesperanto_prototype as cle cle.exclude_labels(binary_flaglist, label_map_input, label_map_destination)
labeling
outlines_numbers_overlay
parametric_images
superpixel_segmentation
count_blobs.ipynb
excludeLabelsOnEdges.ijm
excludeLabelsWithinRange.ijm
filter_label_maps.ijm
labeling.ijm
outlines_numbers_overlay.ijm
parametric_images.ijm
superpixel_segmentation.ijm
segmentation.py