GPU accelerated image processing for everyone
Apply a minimum filter (diamond shape) to the input image.
The radius is fixed to 1 and pixels with value 0 are ignored.Note: Pixels with 0 value in the input image will not be overwritten in the output image. Thus, the result image should be initialized by copying the original image in advance.
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_nonzeroMinimumDiamond(Image input, 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 input = clij2.push(inputImagePlus); destination = clij2.create(input);
// Execute operation on GPU clij2.nonzeroMinimumDiamond(input, destination);
// show result destinationImagePlus = clij2.pull(destination); destinationImagePlus.show(); // cleanup memory on GPU clij2.release(input); clij2.release(destination);
% init CLIJ and GPU clij2 = init_clatlab(); % get input parameters input = clij2.pushMat(input_matrix); destination = clij2.create(input);
% Execute operation on GPU clij2.nonzeroMinimumDiamond(input, destination);
% show result destination = clij2.pullMat(destination) % cleanup memory on GPU clij2.release(input); clij2.release(destination);
// init CLIJ and GPU importClass(net.haesleinhuepf.clicy.CLICY); importClass(Packages.icy.main.Icy); clij2 = CLICY.getInstance(); // get input parameters input_sequence = getSequence(); input = clij2.pushSequence(input_sequence); destination = clij2.create(input);
// Execute operation on GPU clij2.nonzeroMinimumDiamond(input, destination);
// show result destination_sequence = clij2.pullSequence(destination) Icy.addSequence(destination_sequence); // cleanup memory on GPU clij2.release(input); clij2.release(destination);
import pyclesperanto_prototype as cle cle.nonzero_minimum_diamond(input, destination)