This page was created by the AI4Life project using data provided by Nils Jacobsen at Royal Belgian Institute of Natural Sciences. All the images demonstrated in this tutorial are provided under CC-BY licence.
If any of the instructions are not working, please open an issue or contact us at [email protected]!
Project challenges: instance segmentation
Monitoring of ecologically important marine habitats (gravel beds) and benthic communities by analysis of videos recorded by a towed underwater video system.
You can clone the repository and create an environment from the environment file included as follows.
git clone [email protected]:BIIFSweden/AI4Life_OC2_2024_11.git
cd AI4Life_OC2_2024_11
conda env create -f environment.yml
Once the environment is created, you can open the prompt, activate the environment and start jupyter lab.
conda activate ai4life_11
jupyter lab
Inside the notebooks folder you will find notebooks for:
In this tutorial, we showed how to perform semantic segmentation of objects in images with SAM.
AI4Life is a Horizon Europe-funded project that brings together the computational and life science communities.
AI4Life has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement number 101057970. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.
If you wish to contribute, it would be nice to chekc the style and other things through pre-commit. You can do this by installing pre-commit before making new commits.
pip install pre-commit
pre-commit install
Author list (2024). Title. Zenodo. https://doi.org/... .
SciLifeLab BioImage Informatics Facility (BIIF)
Developed by Mehdi Seifi, Agustin Corbat and Kristina Lidayova