GPU accelerated image processing for everyone
Combines an intensity image and a label (or binary) image so that you can see segmentation outlines on the intensity image.
Category: Labels
Ext.CLIJx_visualizeOutlinesOnOriginal(Image intensity, Image labels, Image destination);
// init CLIJ and GPU import net.haesleinhuepf.clijx.CLIJx; import net.haesleinhuepf.clij.clearcl.ClearCLBuffer; CLIJx clijx = CLIJx.getInstance(); // get input parameters ClearCLBuffer intensity = clijx.push(intensityImagePlus); ClearCLBuffer labels = clijx.push(labelsImagePlus); destination = clijx.create(intensity);
// Execute operation on GPU clijx.visualizeOutlinesOnOriginal(intensity, labels, destination);
// show result destinationImagePlus = clijx.pull(destination); destinationImagePlus.show(); // cleanup memory on GPU clijx.release(intensity); clijx.release(labels); clijx.release(destination);
% init CLIJ and GPU clijx = init_clatlabx(); % get input parameters intensity = clijx.pushMat(intensity_matrix); labels = clijx.pushMat(labels_matrix); destination = clijx.create(intensity);
% Execute operation on GPU clijx.visualizeOutlinesOnOriginal(intensity, labels, destination);
% show result destination = clijx.pullMat(destination) % cleanup memory on GPU clijx.release(intensity); clijx.release(labels); clijx.release(destination);