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> **Preamble:** We strive to make marine image data [FAIR](https://gitlab.hzdr.de/datahub/marehub/ag-videosimages/metadata-profiles-fdos/-/blob/master/FAIR-marine-images.md). We maintain [data profiles](https://gitlab.hzdr.de/datahub/marehub/ag-videosimages/metadata-profiles-fdos) to establish a common language for marine imagery, we develop best-practice [operating procedures](https://gitlab.hzdr.de/datahub/marehub/ag-videosimages/standard-operating-procedures) for handling marine images and - here in this repository - we develop [software tools](https://gitlab.hzdr.de/datahub/marehub/ag-videosimages/software/mar-iqt) to apply the vocabulary and procedures to marine imagery.
> **Preamble:** We strive to make marine image data [FAIR](https://gitlab.hzdr.de/datahub/marehub/ag-videosimages/fair-marine-images/-/blob/master/docs/FAIR-marine-images.md). We develop [FDOs](https://gitlab.hzdr.de/datahub/marehub/ag-videosimages/fair-marine-images/-/blob/master/docs/ifdos/iFDO-overview.md) for images to establish a common language for marine imagery, we develop best-practice [operating procedures](https://gitlab.hzdr.de/datahub/marehub/ag-videosimages/fair-marine-images/-/blob/master/docs/sops/sop-overview.md) for handling marine images and - here in this repository - we develop [software tools](https://gitlab.hzdr.de/datahub/marehub/ag-videosimages/mariqt) to apply the vocabulary and procedures to marine imagery.
# MarIQT
Image Quality control / quality assurance and curation Tools (IQT) conceptualised and developed by the MareHub working group on Videos/Images (part of the DataHub, a research data manangement initiative by the Helmholtz association). The MarIQT core is a [python package](https://gitlab.hzdr.de/datahub/marehub/ag-videosimages/software/mar-iqt/-/tree/master/mariqt) which is helpful on its own but is key to the more user-friendly [jupyter notebooks](https://gitlab.hzdr.de/datahub/marehub/ag-videosimages/software/mar-iqt/-/tree/master/jupyter) that make extensive use of the python package.
# Get started
1. Check-out this repository
2. Run the notebook 0_Initialize and populate it with your project's details to create a curation folder and curation settings file
3. Switch to your new project curation folder (its also a Git repo by now)
4. Run the notebook 1_CurationOverview now (and whenever you need an update) to see which steps still lie ahead of you
5. Run other notebooks to conduct the data curation steps. An overview of their functionality is given in the notebook folder's README.me
Image Quality control / quality assurance and curation Tools (IQT) conceptualised and developed by the MareHub working group on Videos/Images (part of the DataHub, a research data manangement initiative by the Helmholtz association). The MarIQT core is a [python package](https://gitlab.hzdr.de/datahub/marehub/ag-videosimages/mariqt) which is helpful on its own but is key to the more user-friendly [jupyter notebooks](https://gitlab.hzdr.de/datahub/marehub/ag-videosimages/mariqt-notebooks) that make extensive use of the python package.
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