GPU accelerated image processing for everyone
This operation removes labels from a labelmap and renumbers the remaining labels.
Hand over a vector of values and a range specifying which labels with which values are eliminated.
Categories: Filter, Measurements, Labels
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_excludeLabelsWithValuesOutOfRange(Image values_vector, Image label_map_input, Image label_map_destination, Number minimum_value_range, Number maximum_value_range);
// init CLIJ and GPU import net.haesleinhuepf.clij2.CLIJ2; import net.haesleinhuepf.clij.clearcl.ClearCLBuffer; CLIJ2 clij2 = CLIJ2.getInstance(); // get input parameters ClearCLBuffer values_vector = clij2.push(values_vectorImagePlus); ClearCLBuffer label_map_input = clij2.push(label_map_inputImagePlus); label_map_destination = clij2.create(values_vector); float minimum_value_range = 1.0; float maximum_value_range = 2.0;
// Execute operation on GPU clij2.excludeLabelsWithValuesOutOfRange(values_vector, label_map_input, label_map_destination, minimum_value_range, maximum_value_range);
// show result label_map_destinationImagePlus = clij2.pull(label_map_destination); label_map_destinationImagePlus.show(); // cleanup memory on GPU clij2.release(values_vector); clij2.release(label_map_input); clij2.release(label_map_destination);
% init CLIJ and GPU clij2 = init_clatlab(); % get input parameters values_vector = clij2.pushMat(values_vector_matrix); label_map_input = clij2.pushMat(label_map_input_matrix); label_map_destination = clij2.create(values_vector); minimum_value_range = 1.0; maximum_value_range = 2.0;
% Execute operation on GPU clij2.excludeLabelsWithValuesOutOfRange(values_vector, label_map_input, label_map_destination, minimum_value_range, maximum_value_range);
% show result label_map_destination = clij2.pullMat(label_map_destination) % cleanup memory on GPU clij2.release(values_vector); 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 values_vector_sequence = getSequence(); values_vector = clij2.pushSequence(values_vector_sequence); label_map_input_sequence = getSequence(); label_map_input = clij2.pushSequence(label_map_input_sequence); label_map_destination = clij2.create(values_vector); minimum_value_range = 1.0; maximum_value_range = 2.0;
// Execute operation on GPU clij2.excludeLabelsWithValuesOutOfRange(values_vector, label_map_input, label_map_destination, minimum_value_range, maximum_value_range);
// show result label_map_destination_sequence = clij2.pullSequence(label_map_destination) Icy.addSequence(label_map_destination_sequence); // cleanup memory on GPU clij2.release(values_vector); clij2.release(label_map_input); clij2.release(label_map_destination);
import pyclesperanto_prototype as cle cle.exclude_labels_with_values_out_of_range(values_vector, label_map_input, label_map_destination, minimum_value_range, maximum_value_range)
excludeLabelsWithinRange.ijm
parametric_images.ijm