CLIJ2

Logo

GPU accelerated image processing for everyone

CLIJ2 home

visualizeOutlinesOnOriginal

Combines an intensity image and a label (or binary) image so that you can see segmentation outlines on the intensity image.

Category: Labels

Usage in ImageJ macro

Ext.CLIJx_visualizeOutlinesOnOriginal(Image intensity, Image labels, Image destination);

Usage in object oriented programming languages

Java
// 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);
Matlab
% 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);

Back to CLIJ2 reference Back to CLIJ2 documentation

Imprint