GPU accelerated image processing for everyone
Takes a touch matrix and a vector of values to determine the most popular integer value among touching neighbors for every object. TODO: This only works for values between 0 and 255 for now.
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_modeOfTouchingNeighbors(Image values, Image touch_matrix, Image mode_values_destination);
// init CLIJ and GPU import net.haesleinhuepf.clij2.CLIJ2; import net.haesleinhuepf.clij.clearcl.ClearCLBuffer; CLIJ2 clij2 = CLIJ2.getInstance(); // get input parameters ClearCLBuffer values = clij2.push(valuesImagePlus); ClearCLBuffer touch_matrix = clij2.push(touch_matrixImagePlus); mode_values_destination = clij2.create(values);
// Execute operation on GPU clij2.modeOfTouchingNeighbors(values, touch_matrix, mode_values_destination);
// show result mode_values_destinationImagePlus = clij2.pull(mode_values_destination); mode_values_destinationImagePlus.show(); // cleanup memory on GPU clij2.release(values); clij2.release(touch_matrix); clij2.release(mode_values_destination);
% init CLIJ and GPU clij2 = init_clatlab(); % get input parameters values = clij2.pushMat(values_matrix); touch_matrix = clij2.pushMat(touch_matrix_matrix); mode_values_destination = clij2.create(values);
% Execute operation on GPU clij2.modeOfTouchingNeighbors(values, touch_matrix, mode_values_destination);
% show result mode_values_destination = clij2.pullMat(mode_values_destination) % cleanup memory on GPU clij2.release(values); clij2.release(touch_matrix); clij2.release(mode_values_destination);
// init CLIJ and GPU importClass(net.haesleinhuepf.clicy.CLICY); importClass(Packages.icy.main.Icy); clij2 = CLICY.getInstance(); // get input parameters values_sequence = getSequence(); values = clij2.pushSequence(values_sequence); touch_matrix_sequence = getSequence(); touch_matrix = clij2.pushSequence(touch_matrix_sequence); mode_values_destination = clij2.create(values);
// Execute operation on GPU clij2.modeOfTouchingNeighbors(values, touch_matrix, mode_values_destination);
// show result mode_values_destination_sequence = clij2.pullSequence(mode_values_destination) Icy.addSequence(mode_values_destination_sequence); // cleanup memory on GPU clij2.release(values); clij2.release(touch_matrix); clij2.release(mode_values_destination);
import pyclesperanto_prototype as cle cle.mode_of_touching_neighbors(values, touch_matrix, mode_values_destination)
tissue_neighborhood_quantification.ipynb