wekaLabelClassifier

Applies a pre-trained CLIJx-Weka model to an image and a corresponding label map to classify labeled objects.

Make sure that the handed over feature list is the same used while training the model.

Availability: Available in Fiji by activating the update sites clij and clij2. This function is part of clijx-weka_-0.32.0.1.jar.

Usage in ImageJ macro

Ext.CLIJx_wekaLabelClassifier(Image input, Image label_map, Image destination, String features, String modelfilename);

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 input = clijx.push(inputImagePlus);
ClearCLBuffer label_map = clijx.push(label_mapImagePlus);
destination = clijx.create(input);

// Execute operation on GPU
clijx.wekaLabelClassifier(input, label_map, destination, features, modelfilename);

// show result
destinationImagePlus = clijx.pull(destination);
destinationImagePlus.show();

// cleanup memory on GPU
clijx.release(input);
clijx.release(label_map);
clijx.release(destination);

Matlab

% init CLIJ and GPU
clijx = init_clatlabx();

% get input parameters
input = clijx.pushMat(input_matrix);
label_map = clijx.pushMat(label_map_matrix);
destination = clijx.create(input);

% Execute operation on GPU
clijx.wekaLabelClassifier(input, label_map, destination, features, modelfilename);

% show result
destination = clijx.pullMat(destination)

% cleanup memory on GPU
clijx.release(input);
clijx.release(label_map);
clijx.release(destination);

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