GPU accelerated image processing for everyone
Determines the mean squared error (MSE) between two images.
The MSE will be stored in a new row of ImageJs Results table in the column ‘MSE’.
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_meanSquaredError(Image source1, Image source2);
// init CLIJ and GPU import net.haesleinhuepf.clij2.CLIJ2; import net.haesleinhuepf.clij.clearcl.ClearCLBuffer; CLIJ2 clij2 = CLIJ2.getInstance(); // get input parameters ClearCLBuffer source1 = clij2.push(source1ImagePlus); ClearCLBuffer source2 = clij2.push(source2ImagePlus);
// Execute operation on GPU double resultMeanSquaredError = clij2.meanSquaredError(source1, source2);
// show result System.out.println(resultMeanSquaredError); // cleanup memory on GPU clij2.release(source1); clij2.release(source2);
% init CLIJ and GPU clij2 = init_clatlab(); % get input parameters source1 = clij2.pushMat(source1_matrix); source2 = clij2.pushMat(source2_matrix);
% Execute operation on GPU double resultMeanSquaredError = clij2.meanSquaredError(source1, source2);
% show result System.out.println(resultMeanSquaredError); % cleanup memory on GPU clij2.release(source1); clij2.release(source2);
// init CLIJ and GPU importClass(net.haesleinhuepf.clicy.CLICY); importClass(Packages.icy.main.Icy); clij2 = CLICY.getInstance(); // get input parameters source1_sequence = getSequence(); source1 = clij2.pushSequence(source1_sequence); source2_sequence = getSequence(); source2 = clij2.pushSequence(source2_sequence);
// Execute operation on GPU double resultMeanSquaredError = clij2.meanSquaredError(source1, source2);
// show result System.out.println(resultMeanSquaredError); // cleanup memory on GPU clij2.release(source1); clij2.release(source2);
import pyclesperanto_prototype as cle cle.mean_squared_error(source1, source2)