I also saw it used in an example workflow of his presented during the KNIME summit 2017 wherer i found a collapsed node “Transform Tracking Data” mentioned, and would be interested to see whats behind it. Thanks so much!
Yes, currently the ImageJ2 plugin (that auto-generates this KNIME node) is hard-coded to use TrackMate’s LogDetectorFactory, see the source code in the fmi-ij2-plugins repository:
(as you can see from the TODO comment, I wanted to extend this to allow the choice of more TrackMate detectors, but never got around to do it… let me know if it would be useful for you)
The output of the ImageJ2 plugin is double (which is presented as a “Collection Cell” in KNIME), since currently the ImageJ integration in KNIME only allows one-to-one row processing (and not one-to-many, which would be needed for mapping one input image to many output spots). I hope this technical limitation will be gone with a newer version of Knime Image Processing (KNIP) in the future, @christian.dietz or @gabriel.einsdorf can certainly provide information on this.
You’ll have to use a Split Collection Column node to split the values. As you have multiple output columns of double (and int), and each row can contain a different number of spots, this requires using a Transpose or an Unpivoting node to transform the data to a “tidy” format. The mentioned metanode does all this processing, I attached a small workflow file that contains the node: