GPU accelerated image processing for everyone
Takes a label image and a parametric intensity image and will replace each labels value in the parametric image by the most popular value of neighboring labels.
The distance range of the centroids of the neighborhood can be configured. Note: Values of all pixels in a label each must be identical.
parametric_map : Image label_map : Image parametric_map_destination : Image min_distance : float, optional default : 0 max_distance : float, optional default: maximum float value
Categories: Measurements, Filter, Graphs
Availability: Available in Fiji by activating the update sites clij and clij2. This function is part of clijx_-0.30.1.21.jar.
Ext.CLIJx_modeOfProximalNeighborsMap(Image parametric_map, Image label_map, Image parametric_map_destination, Number min_distance, Number max_distance);
// init CLIJ and GPU import net.haesleinhuepf.clijx.CLIJx; import net.haesleinhuepf.clij.clearcl.ClearCLBuffer; CLIJx clijx = CLIJx.getInstance(); // get input parameters ClearCLBuffer parametric_map = clijx.push(parametric_mapImagePlus); ClearCLBuffer label_map = clijx.push(label_mapImagePlus); parametric_map_destination = clijx.create(parametric_map); float min_distance = 1.0; float max_distance = 2.0;
// Execute operation on GPU clijx.modeOfProximalNeighborsMap(parametric_map, label_map, parametric_map_destination, min_distance, max_distance);
// show result parametric_map_destinationImagePlus = clijx.pull(parametric_map_destination); parametric_map_destinationImagePlus.show(); // cleanup memory on GPU clijx.release(parametric_map); clijx.release(label_map); clijx.release(parametric_map_destination);
% init CLIJ and GPU clijx = init_clatlabx(); % get input parameters parametric_map = clijx.pushMat(parametric_map_matrix); label_map = clijx.pushMat(label_map_matrix); parametric_map_destination = clijx.create(parametric_map); min_distance = 1.0; max_distance = 2.0;
% Execute operation on GPU clijx.modeOfProximalNeighborsMap(parametric_map, label_map, parametric_map_destination, min_distance, max_distance);
% show result parametric_map_destination = clijx.pullMat(parametric_map_destination) % cleanup memory on GPU clijx.release(parametric_map); clijx.release(label_map); clijx.release(parametric_map_destination);
import pyclesperanto_prototype as cle cle.mode_of_proximal_neighbors_map(parametric_map, label_map, parametric_map_destination, min_distance, max_distance)