The easiest way to get started with the ImageJ and SciJava APIs is via the
ImageJ Jupyter notebooks,
located in the
notebooks subfolder of this repository.
Use the "launch binder" badge above to try the Jupyter notebooks on the cloud using Binder, with no local installation necessary.
The introductory notebooks use the Groovy kernel from BeakerX. Several other JVM-based kernels are usable as well, including Clojure, Java, Kotlin and Scala.
There are also notebooks using the standard Python kernel plus the pyimagej package, enabling use of ImageJ from Python programs.
There is more than one way to install Jupyter, but here is the procedure we recommend to get started quickly:
- Install Miniconda.
- Clone this
- Open a console and
cdto your cloned working copy.
conda env create -f environment.ymlto create a conda environment with the dependencies these notebooks need.
conda activate scijavato activate the environment.
jupyter notebookto launch Jupyter Notebook in a web browser window.
- In the browser, click into
notebooks, then click on the
ImageJ-Tutorials-and-Demo.ipynbnotebook to open it.
Learn more about Jupyter Notebook on its web site.
this repository also contains Maven projects written in Java, located in the
maven-projects subfolder of this repository.
Use the "Open in Gitpod" button above to run the (non-GUI) Java projects on the cloud using Gitpod, with no local installation necessary.
You can import these projects into your favorite IDE:
- Eclipse: File > Import > Existing Maven Projects
- NetBeans: File > Open Project
- IDEA: File > Open Project... (select pom.xml)
Or build and run from the command line:
mvn cd maven-projects/simple-commands mvn -Pexec -Dmain-class=GradientImage
To the extent possible under law, the ImageJ developers have waived all copyright and related or neighboring rights to this tutorial code.
See unlicense.org for details.