Example Data#
The Paidiverpy package includes a selection of example datasets designed for testing and demonstration purposes. These datasets encompass both plankton and benthic data types, each accompanied by their respective metadata files. The metadata files are formatted according to the IFDO standard as well as in CSV format.
Automatic Download#
When you execute the example notebooks in the gallery examples, the required example data will be automatically downloaded. This facilitates an easy setup for users to quickly start testing and experimenting with the package.
Manual Download#
If you prefer to manually download the example data for testing, you can do so using the following command:
from paidiverpy.utils.data import PaidiverpyData
PaidiverpyData().load(DATASET_NAME)
Available Datasets#
Plankton: Dataset name “plankton_csv”#
Pelagic Plankton Images (2023) - DY157 RSS Discovery Cruise
Equipment: Red camera frame deployed vertically via winches
Metadata: CSV File
Benthic 1: Dataset name “benthic_csv”#
Benthic Images (2018) – Clarion Clipperton Zone (~5000m depth),
Equipment: Camera mounted on the front of an ROV
Metadata: CSV File
Benthic 2: Dataset name “benthic_ifdo”#
Benthic Images (2012) – Haig Fras, UK.
Equipment: Camera mounted on the front of an ROV
Metadata: IFDO File
Citation: Benoist, N.; Bett, B.J.; Morris, K.; Ruhl, H. (2023): Greater Haig Fras autonomous underwater vehicle seafloor survey - mosaicked image tiles used to assess benthic assemblages and seabed types (2012).. NERC EDS British Oceanographic Data Centre NOC, 27 November 2023. doi:10.5285/093edbc7-3552-3d35-e063-6c86abc099d5. https://dx.doi.org/10.5285/093edbc7-3552-3d35-e063-6c86abc099d5
Nikon Raw Sample images: Dataset name “nef_raw”#
Sample .NEF images available in this link: MannyPhoto’s Nikon samples.
Metadata: CSV File
Benthic 3: Dataset name “benthic_raw”#
Benthic Images (2014) – Clarion Clipperton Zone (~4000m depth), JS257 RSS James Cook Cruise.
Equipment: Camera mounted on the front of an ROV
Metadata: CSV File
These example datasets provide a foundation for users to explore the functionalities of the Paidiverpy package and conduct their analyses effectively.