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Welcome to the MultipleTemplateMatching-KNIME wiki!
If you use this implementation for your research, please cite:
Multi-Template Matching: a versatile tool for object-localization in microscopy images;
Laurent SV Thomas, Jochen Gehrig
bioRxiv 619338; doi: https://doi.org/10.1101/619338
The content of this wiki (including illustrations and videos) is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
This work has been part of the PhD project of Laurent Thomas under supervision of Dr. Jochen Gehrig at:
ACQUIFER a division of DITABIS AG
Digital Biomedical Imaging Systems AG
Freiburger Str. 3
75179 Pforzheim
This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 721537 ImageInLife.
Install the following extensions in KNIME:
KNIME image processingKNIME image processing - Python extensionKNIME python integration
Set up a new pre-configured python environment in Anaconda using the dependency file (see the code tab).
To do so, once anaconda installed, open the anaconda prompt in the folder containing the environment file and type
conda env create -f environment.yml
Then set the python environment in KNIME
File>Preferences>KNIME>Python
and paste the path to the python.exe usually in C:\SomePath\Anaconda\envs\KNIME-TemplateMatching
Finally download and open the workflow file Multi-Template matching
Alternatively a pre-configured KNIME installation and Anaconda environment are archived on Zenodo.
Just unzip the KNIME.zip to have a functional KNIME installation. It is still needed to set the python environment in KNIME.
Similarly unzip the archived environment in a new subfolder of C:\SomePath\Anaconda\envs\.
Click on the images to open the video in Youtube.
The video are also hosted on Zenodo and can be cited using the following DOI
