KNIME Image Processing Course

KNIME Image Processing - Course Material

Make sure that you set up the KNIME Image Processing developer environment beforehand.

Wrap ImageJ2 Command as KNIME Image Processing Plugin

The folder knip-course-ij2-buddy contains a KNIME Image Processing plugin that wraps an ImageJ2 Command.

If you are using this plugin as skeleton for a new project, you have to change the EclipseHelper according to Point 4.

Exercise 0

1. Create a lib/ folder within the project and download the required artifacts to build the Coloc2 wrapper from maven.scijava.org into that folder.
2. Add the libraries to the Runtime classpath (open plugin.xml in project) to add the lib/*.jar jars
3. Check if your Command is picked up when you execute the knime-launch-configuration
4. Export the plugin to yor local KNIME installation (Right click knip-course-ij2-buddy > Export > Plug-in Development > Deployable plug-ins and fragments; select the plugins folder of your installation as destination)
5. Restart KNIME to see if it is picked up

Add ImageJ2 Command to KNIME Analytics Platform

The dirctory knip-course-ij2-vanilla contains an example ImageJ2 Command that can be installed as a KNIME Image Processing node via the ImageJ2 integration.

Exercise 0

1. Implement a Command that computes the mean intensity of an image
2. Open your KNIME installation with the installed Image Processing Extensions
3. Go to Preferences > KNIME > Image Processing Plugin > ImageJ2 Plugin Installation
4. Add and select the JAR file that contains your Command
5. Find the Command in the Node Repository

Exercise 1

1. Implement a Command that creates an empty image with dimensions read from a text file of the form: dim0,dim1,dim2,...,dimN
2. Open your KNIME installation with the installed Image Processing Extensions
3. Go to Preferences > KNIME > Image Processing Plugin > ImageJ2 Plugin Installation
4. Add and select the JAR file that contains your Command
5. Find the Command in the Node Repository - any issues?

Write an KNIME Image Processing Plugin

Import the directory org.knime.knip.course via "Existing Projects into Workspace".

The has multiple packages:

• example.copyimg: Example implementation that shows how to access an ImgPlusCell and create a new ImgPlusCell. This example node simply copies every pixel of the input image to an output image.
• skeleton: Empty node skeleton with no functionality and can be used as starting point to develop a new KNIME Image Processing Node.
• exercise: Three exercises that of variing difficulty. The method signatures are alredy there and the exercises are described in comments.
  • addconstant: Exercise for a node which adds a constant value to an image. This is a good exercise to understand which parts a KNIME node consists of and how to handle the different states of a node.
  • numpixels: Exercise for a node which counts the number of pixels for each segment of a labeling. This is a good exercise to learn how to access a LabelingCell and LabelRegions and how to create multiple output rows for one input row.
  • minmaxradius: Exercise for a node which computes the minumum and maximum radius of each segment of a labeling. This is a good exercise to learn how to use imagej-ops in KNIME Image Processing nodes.
• solution: Example solutions for all three exercises.

Adding a new Node-Category:

1. Open plugin.xml
2. Go to Extensions
3. Add org.knime.workbench.repository.categories extension point.
4. Right click on extension point -> New -> category

Add a new Node to a Category:

1. Open plugin.xml
2. Go to Extensions
3. Add org.knime.workbench.repository.nodes extension point.
4. Right click on extension point -> New -> node