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Project #11: Automated species annotation in turbid waters


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This repo 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 ai4life@fht.org!

Installation

You can clone the repository and create an environment from the environment file included as follows:

git clone git@github.com:ai4life-opencalls/oc_2_project_11.git
cd oc_2_project_11

If you have a GPU:

conda env create -f env_gpu.yml

Otherwise:

conda env create -f env_cpu.yml

Note:

GPU installation might get a bit tricky depend on your nvidia driver and cuda version. sam-2 on GPU needs cuda >= 12, otherwise it might replace the pytorch with the CPU version.
You can check the pytorch instructions for the manual installation here.

Usage

Once the environment is created, you can open the prompt, activate the environment and start jupyter lab.

conda activate ai4life
jupyter lab

Inside the notebooks folder you will find notebooks for:



Acknowledgements

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.

Contact

SciLifeLab BioImage Informatics Facility (BIIF)

Developed by Mehdi Seifi, Agustin Corbat and Kristina Lidayova