Data from: Towards a fully automated underwater census for fish assemblages in the Mediterranean Sea

Assessing underwater biodiversity is labour-intensive and costly, but is
crucial for measuring the extent of the decline in local fish stock. In
most cases, Underwater Visual Census (UVC) is the preferred method,
however this can be costly in terms of human effort and is limited by
meteorological and logistical factors. Advances in technology allows the
utilisation of more autonomous video recording methods (i.e. Remote
Operated Vehicles (ROV)) which addresses these limitations. This study
used a transect-wise UVC coupled with diver operated videos (DOV). For the
video analysis, a comprehensive fully automated pipeline was developed to
extract frames from DOV and perform colour correction. This pipeline
integrates a YOLO-based model to detect 20 Mediterranean fish species and
validate the presence or absence of each species within individual
transects. This study was conducted to evaluate the feasibility of using
video-based methods for UVC with minimal human-input. The result of
automated video analysis were in agreement with manual video counting,
validating the autonomous and bias-free procedure for video assessment. In
conclusion, utilising a minimal-human-input video method liberates the
data acquisition from limiting factors (i.e. meteorological and
logistical) and automation of this video analysis significantly reduces
the labour and time required. For future fieldwork campaigns, the video
data collection protocol needs to be modified to better resemble
traditional UVC and enhance this acquisition method.