I noticed that a K-means clustering command was added to CLIJx recently. I’m very curious in this, as I am doing some of this using the Cluster Image function of the Beat plugin in Fiji. However, I’m unsure of how to use the CLIJx version, as some of the options are not clear to me. Perhaps you, or someone else, could provide some help? I’ve uploaded a sample image that I have performed the Beat>Cluster Image function on, its result, and I’ve included the code from the macro recorder and a screenshot of the original image and result.
Here is the command for the K-means clustering in CLIJx:
Ext.CLIJx_kMeansLabelClusterer(Image_input, Image_label_map, Image_destination, String_features, String_modelfilename, Number_number_of_classes, Number_neighbor_radius, Boolean_train);
I have bolded the options that I’m not sure about.
Here is the readout from the macro recorder from running Beat>Cluster Image:
run("Cluster Image", "clustering=K-means provide=none additional= mask= factor elki=[-algorithm clustering.kmeans.KMeansLloyd -kmeans.k 7 -projhistogram.curves -parallel.clusteroutline.straight] path= captures= plot= sort=s weights= number=5 maximum=100 random=0 fuzziness=2 kernel=50.0000 normalization=1.00000000 error=0.000000001 initialize=50 total=0.0000 single=0.0000 minimal=0 maximally=100.0000 digits=-1 text1=");
Any help would be greatly appreciated!