An Object Recognition Dataset for Marine Fish Based on a Fixed Subtidal Real-time Underwater Video Streaming System in Ulleungdo

Continuous ecological monitoring of coastal fish communities is essential for understanding the impacts of climate change and environmental variability on marine ecosystems. However, in remote island areas such as Ulleungdo in the East Sea of Korea, conventional dive-based surveys are constrained by weather conditions, geographical isolation, and limited observation time, making long-term continuous data acquisition challenging. This study presents a labeled underwater image dataset for marine fish object detection, constructed from continuous footage acquired via a fixed subtidal real-time video streaming system installed at a depth of 6 m at the Cheonbu Underwater Observatory, Ulleungdo, South Korea. The system employs a 4K ultra-high-resolution camera operating 24 hours a day, enabling uninterrupted day/night and seasonal recording. The system continues to collect footage on an ongoing basis; the present dataset was constructed from two periods, April to August 2024 and February to September 2025, selected to capture seasonal variation including the high water temperature period and ensure representation of thermophilic species. The final dataset consists of 6,190 high-resolution underwater images (.jpg) and 88,157 corresponding bounding box annotation files (.txt), labeled using the Roboflow platform and verified through expert review. At least 17 marine fish species identified in the coastal waters of Ulleungdo were classified into 13 object detection classes, with Chromis spp. accounting for approximately 49.1% of total annotations. For five low-frequency classes (Hyporthodus septemfasciatus, Hexagrammos spp., Semicossyphus reticulatus, Seriola spp., and Thamnaconus modestus), supplementary images acquired via SCUBA diving were incorporated to improve class-level representation. Taxonomic classification followed FishBase and the National Species List of Korea. This dataset provides a foundation for developing underwater fish recognition models and is expected to contribute to long-term monitoring of fish community changes associated with ongoing sea surface temperature rise in the East Sea.