GPU accelerated image processing for everyone
Takes a label map, determines which labels touch and replaces every label with the average distance to their neighboring labels.
To determine the distances, the centroid of the labels is determined internally.
Categories: Graphs, Labels, Measurements
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_averageNeighborDistanceMap(Image input, 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 input = clij2.push(inputImagePlus); destination = clij2.create(input);
// Execute operation on GPU clij2.averageNeighborDistanceMap(input, destination);
// show result destinationImagePlus = clij2.pull(destination); destinationImagePlus.show(); // cleanup memory on GPU clij2.release(input); clij2.release(destination);
% init CLIJ and GPU clij2 = init_clatlab(); % get input parameters input = clij2.pushMat(input_matrix); destination = clij2.create(input);
% Execute operation on GPU clij2.averageNeighborDistanceMap(input, destination);
% show result destination = clij2.pullMat(destination) % cleanup memory on GPU clij2.release(input); clij2.release(destination);
// init CLIJ and GPU importClass(net.haesleinhuepf.clicy.CLICY); importClass(Packages.icy.main.Icy); clij2 = CLICY.getInstance(); // get input parameters input_sequence = getSequence(); input = clij2.pushSequence(input_sequence); destination = clij2.create(input);
// Execute operation on GPU clij2.averageNeighborDistanceMap(input, destination);
// show result destination_sequence = clij2.pullSequence(destination) Icy.addSequence(destination_sequence); // cleanup memory on GPU clij2.release(input); clij2.release(destination);
import pyclesperanto_prototype as cle cle.average_neighbor_distance_map(input, destination)
quantitative_neighbor_maps.ipynb