A Labeled Data Set Of Underwater Images Of Fish And Crab Species From Five Mesohabitats In Puget Sound Wa Usa

Farrell, Dara M.; Ferriss, Bridget; Sanderson, Beth; Veggerby, Karl; Robinson, Lauren; Trivedi, Anusua; Pathak, Shreyaan; Muppalla, Sreya; Wang, Jane; Morris, Dan; Dodhia, Rahul

doi:10.1038/s41597-023-02557-6

i

A Labeled Data Set Of Underwater Images Of Fish And Crab Species From Five Mesohabitats In Puget Sound Wa Usa

2023
By Farrell, Dara M. ; Ferriss, Bridget ; Sanderson, Beth ; ...

Details

Journal Title:

Scientific Data
Personal Author:

Farrell, Dara M. ; Ferriss, Bridget ; Sanderson, Beth ; Veggerby, Karl ; Robinson, Lauren ; Trivedi, Anusua ; Pathak, Shreyaan ; Muppalla, Sreya ; Wang, Jane ; Morris, Dan ; Dodhia, Rahul
NOAA Program & Office:

NMFS (National Marine Fisheries Service) ; AFSC (Alaska Fisheries Science Center) ; NWFSC (Northwest Fisheries Science Center) ; Sea Grant ; OAR (Oceanic and Atmospheric Research)
Sea Grant Program:

WASHU (Washington Sea Grant)
Description:

The sustainable management of fisheries and aquaculture requires an understanding of how these activities interact with natural fish populations. GoPro cameras were used to collect an underwater video data set on and around shellfish aquaculture farms in an estuary in the NE Pacific from June to August 2017 and June to August 2018 to better understand habitat use by the local fish and crab communities. Images extracted from these videos were labeled to produce a data set that is suitable for use in training computer vision models. The labeled data set contains 77,739 images sampled from the collected video; 67,990 objects (fishes and crustaceans) have been annotated in 30,384 images (the remainder have been annotated as “empty”). The metadata of the data set also indicates whether a physical magenta filter was used during video collection to counteract reduced visibility. These data have the potential to help researchers address system-level and in-depth regional shellfish aquaculture questions related to ecosystem services and shellfish aquaculture interactions.
Keywords:

Computer Science Applications Education Information Systems Library And Information Sciences Statistics, Probability And Uncertainty Statistics And Probability Library And Information Sciences Statistics, Probability And Uncertainty Statistics And Probability Library And Information Sciences Statistics, Probability And Uncertainty Statistics And Probability
Source:

Scientific Data, 10(1)
DOI:

https://doi.org/10.1038/s41597-023-02557-6
ISSN:

2052-4463
Format:

PDF
Publisher:

Springer Science and Business Media LLC
Document Type:

Journal Article
Funding:

Grant no. NA17OAR4170218
License:

https://creativecommons.org/licenses/by/4.0/
Rights Information:

CC BY
Compliance:

Submitted
Main Document Checksum:

urn:sha256:ee5eaa4dd24916a67c289c79097e7113a51ade8dd652850079eecf7d1d084de1
Download URL:

https://repository.library.noaa.gov/view/noaa/56686/noaa_56686_DS1.pdf
File Type:

[PDF - 1.74 MB ]

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