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2017-09-25 - KNIME Image Processing hackathon

    From Wednesday, September 20, 2017 through Friday, September 28, 2017, Christian Dietz of KNIME hosted ~20 developers at the KNIME Konstanz Regional Office for a hackathon to develop the KNIME Image Processing extensions along with the underlying ImageJ Ops library, as well as other related and/or supporting technologies such as Ilastik, ImgLib2 and BigDataViewer.

    There was a big focus this time on machine learning, particularly deep learning networks applied to biological data.

    Participants

    Hackathon progress

    Curtis Rueden

    • Worked with Stefan Helfrich on automating releases of SciJava components via Travis CI ([https://github.com/scijava/scijava-scripts/compare/0235621…f5965c3 1], 2 , 3 ).
    • Assisted Stefan Helfrich in improvements to the imagej-maven-plugin (1 )
    • Reviewed and merged maarzt ‘s initial revamp of the SciJava log framework (1 , 2 ).
    • Reviewed and merged Jan Eglinger ‘s work adding a SciJava widget for File[] inputs (1 , 2 , 3 ).
    • With Jan Eglinger , began work on several related SciJava scripting enhancements (1).
    • Helped Benjamin Wilhelm and Deborah Schmidt with ImageJ/TensorFlow integration and API improvements (PR(s) to imagej/imagej-tensorflow forthcoming).
    • With Christian Dietz , continued work on the next-generation SciJava Struct API, including an overhauled widget framework and Swing widget implementations (as of this writing, on an unstable branch of scijava/scijava-ops repository; see here for a written update with illustration of progress).
    • Helped chaubold set up his shiny new Ilastik-ImageJ integration with Travis CI and deploy it to the ImageJ Maven repository.

    Florian Jug

    • Worked on a KNIME workflow that starts IsoNet-type deep nets on a image column. Works well now, but we want to move tiled executions out from python and move it into KNIME (and also Fiji). This follow-up work will be performed by Deborah Schmidt and Benjamin Wilhelm .
    • Received TGMM groin truth data an started working on Tr3d demo dataset.
    • Started working on min cell-cycle constraints for Tr2d. This will make the ILP explode…
    • Discussions with ctrueden , Stefan Helfrich and tpietzsch about ImageJ Conference details for 2018.

    Tim-Oliver Buchholz

    Benjamin Wilhelm

    • Worked on CSBDeep Fiji Plugin.
    • Added Overlap to TiledView PR in imglib2.
    • Worked on API improvements in imagej/imagej-tensorflow with the help of ctrueden .
    • Programmed KNIME Image Processing nodes which provied a loop over tiles of an image. See branch on GitHub.

    Stefan Helfrich

    • Worked on improvements to the imagej-maven-plugin (1 , 2 , 3 )
    • Got chaubold , maarzt , and Vladimír Ulman started on integrating their SciJava Commands as KNIME nodes
    • Reviewed PRs of imagej-ops (1 , 2 , 3 , 4)
    • Looked into migration of algorithms from MorphoLibJ to Ops/ImgLib2
    • Worked with milkyklim on migrating an ImageJ1 plugin to a SciJava Command (and possibly Ops for computations)
    • Fixed some bugs with respect to @Parameters (1 , 2 )
    • Paired with Curtis Rueden to push the cloud-based build and deploy infrastructure

    Tobias Pietzsch

    • Worked on imglib2 discrete regions framework (imglib2-roi branch “cleaned-up”, imglib-tests branch “roi”).
    • Reviewed imglib2-roi Masks PR , and worked on revision/re-implementation of core interfaces and operators (imglib2-roi branch “troi”).
    • Worked on reviewing and integrating “dynamic bookmarks” feature by Max Kleinhenz into BigDataViewer.
    • Minor BigDataViewer features to help tibuch with Big Data Viewer GUI.

    Matthias Arzt

    • Worked on revamp of the scijava logging framework.
    • Worked on LoopBuilder, as tool for writing loops on images with imglib2.
    • Got an introduction on KNIME Node development by Tim Oliver and Stefan Hilfrich
    • Created a KNIME image processing plugin for image segmentation based on Labkit / Trainable Segmentation.

    Technical discussions

    • Fiji component and application releases: today and in the future (ctrueden , fjug , tpietzsch )
      • Next stable release (December 2017) will still follow the ‘old’ way of doing things.
      • In case the DFG grant comes in and we hired the 2 people they will start implementing the new way of cutting stable releases. This will be great!
    • How to integrate ImageJ, KNIME and machine learning frameworks (particularly Keras and TensorFlow)