GPU accelerated image processing for everyone
Determines the mean average of all pixels in a given image.
It will be stored in a new row of ImageJs Results table in the column ‘Mean’.### Parameters
source : Image The image of which the mean average of all pixels or voxels will be determined.
Category: Measurements
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_meanOfAllPixels(Image source);
// init CLIJ and GPU import net.haesleinhuepf.clij2.CLIJ2; import net.haesleinhuepf.clij.clearcl.ClearCLBuffer; CLIJ2 clij2 = CLIJ2.getInstance(); // get input parameters ClearCLBuffer source = clij2.push(sourceImagePlus);
// Execute operation on GPU double resultMeanOfAllPixels = clij2.meanOfAllPixels(source);
// show result System.out.println(resultMeanOfAllPixels); // cleanup memory on GPU clij2.release(source);
% init CLIJ and GPU clij2 = init_clatlab(); % get input parameters source = clij2.pushMat(source_matrix);
% Execute operation on GPU double resultMeanOfAllPixels = clij2.meanOfAllPixels(source);
% show result System.out.println(resultMeanOfAllPixels); % cleanup memory on GPU clij2.release(source);
// init CLIJ and GPU importClass(net.haesleinhuepf.clicy.CLICY); importClass(Packages.icy.main.Icy); clij2 = CLICY.getInstance(); // get input parameters source_sequence = getSequence(); source = clij2.pushSequence(source_sequence);
// Execute operation on GPU double resultMeanOfAllPixels = clij2.meanOfAllPixels(source);
// show result System.out.println(resultMeanOfAllPixels); // cleanup memory on GPU clij2.release(source);
import pyclesperanto_prototype as cle cle.mean_of_all_pixels(source)
shape_descriptors_based_on_neighborhood_graphs.ipynb
Segmentation_3D.ipynb