GPU accelerated image processing for everyone
Apply a binary watershed to a binary image and introduces black pixels between objects.
Note: This parallel GPU-accelerated approach delivers results of limited quality.See the web for alternatives: https://github.com/clij/clij2/issues/18
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_watershed(Image binary_source, Image destination);
// init CLIJ and GPU import net.haesleinhuepf.clij2.CLIJ2; import net.haesleinhuepf.clij.clearcl.ClearCLBuffer; CLIJ2 clij2 = CLIJ2.getInstance(); // get input parameters ClearCLBuffer binary_source = clij2.push(binary_sourceImagePlus); destination = clij2.create(binary_source);
// Execute operation on GPU clij2.watershed(binary_source, destination);
// show result destinationImagePlus = clij2.pull(destination); destinationImagePlus.show(); // cleanup memory on GPU clij2.release(binary_source); clij2.release(destination);
% init CLIJ and GPU clij2 = init_clatlab(); % get input parameters binary_source = clij2.pushMat(binary_source_matrix); destination = clij2.create(binary_source);
% Execute operation on GPU clij2.watershed(binary_source, destination);
% show result destination = clij2.pullMat(destination) % cleanup memory on GPU clij2.release(binary_source); clij2.release(destination);
// init CLIJ and GPU importClass(net.haesleinhuepf.clicy.CLICY); importClass(Packages.icy.main.Icy); clij2 = CLICY.getInstance(); // get input parameters binary_source_sequence = getSequence(); binary_source = clij2.pushSequence(binary_source_sequence); destination = clij2.create(binary_source);
// Execute operation on GPU clij2.watershed(binary_source, destination);
// show result destination_sequence = clij2.pullSequence(destination) Icy.addSequence(destination_sequence); // cleanup memory on GPU clij2.release(binary_source); clij2.release(destination);