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--- |
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license: cc-by-4.0 |
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task_categories: |
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- image-classification |
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language: |
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- en |
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pretty_name: 'JAMBO, A Multi-Annotator Image Dataset for Benthic Habitat Classification ' |
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size_categories: |
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- 1K<n<10K |
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--- |
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The JAMBO dataset contains 3290 underwater images of the seabed captured by an ROV in temperate waters in the Jammer Bay area off the North West coast of Jutland, Denmark. |
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All the images have been annotated by six annotators to contain one of three classes: sand, stone, or bad. The three classes are defined as follows: |
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* **Sand** habitats are characterized as primarily sand or muddy sand with less than 5% clay and less than 30% cover of stones/boulders, vegetation, and mussel bed. |
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* **Stone** reef habitats are characterized by having more than 30% seabed cover of stones or boulders. |
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* **Bad** is a class used to label images that cannot be confidently annotated as containing one of the aforementioned habitat types by the annotator due to poor image quality, turbidity, or similar. |
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Each of the six annotators have labelled all the images (that is, six individual annotations are provided for each image), which allows for analyzing how inter-annotator disagreement can affect the performance of machine learning models. |
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The easiest way to fetch the dataset is to simply clone this repository using git: |
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```bash |
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sudo apt-get install git-lfs # in case it's not installed |
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git lfs install |
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git clone https://huggingface.co/datasets/vapaau/jambo |
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``` |
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Cross-validation splits and date-based splits are provided in the [jambo_splits_public.csv](jambo_splits_public.csv) file. Check out the starter notebook [howto_jambo.ipynb](howto_jambo.ipynb) to get started. |
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For more information about the dataset and baseline models, please see the paper presented at the ECCV 2024 Computer Vision for Ecology (CV4E) Workshop: |
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[Underwater Uncertainty: A Multi-Annotator Image Dataset for Benthic Habitat |
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Classification](https://vbn.aau.dk/da/publications/underwater-uncertainty) (Springer link [here](https://doi.org/10.1007/978-3-031-92387-6_6)) |
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Citation: |
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``` |
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@InProceedings{jambo_dataset, |
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author="Humblot-Renaux, Galadrielle and Johansen, Anders Skaarup and Schmidt, Jonathan Eichild and Irlind, Amanda Frederikke and Madsen, Niels and Moeslund, Thomas B. and Pedersen, Malte", |
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title="Underwater Uncertainty: A Multi-annotator Image Dataset for Benthic Habitat Classification", |
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booktitle="Computer Vision -- ECCV 2024 Workshops", |
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year="2025", |
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publisher="Springer Nature Switzerland", |
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address="Cham", |
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pages="87--104", |
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isbn="978-3-031-92387-6" |
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doi="10.1007/978-3-031-92387-6_6" |
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} |
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``` |
