Fish-gres YOLOv8 Object Detection Annotations (Derived Release) v1.0

This record provides a detection-ready derivative release of the Fish-gres image dataset, containing manual bounding-box annotations in YOLOv8 format.

Source images:Fish-gres Dataset for Fish Species Classification (Mendeley Data), DOI: 10.17632/76cr3wfhff.1, licensed under CC BY 4.0.

What was added/changed:• Manual bounding-box annotation for single-fish object detection (one fish per image), created using Roboflow and exported in YOLOv8 label format.• Train/validation/test split files and a YOLO dataset configuration file (e.g., data.yaml).

Dataset size and split:Total 2,000 images:• Train: 1,400 (70%)• Validation: 400 (20%)• Test: 200 (10%)

Filename note:Because the dataset was exported via Roboflow, image filenames may differ from the original Fish-gres filenames. Labels match images by basename within each split folder (e.g., xxx.jpg ↔ xxx.txt).

Attribution:Required citation: Fish-gres (images) and this Zenodo record (YOLOv8 annotations/splits).Recommended citation: our paper (IOP EES, 10.1088/1755-1315/1359/1/012023) if you rely on the experimental setup or wish to reference the study that used these annotations.

This dataset release was uploaded after the article’s publication to support replication and reuse of the object-detection experiments reported in the paper.

本记录发布了可直接用于目标检测任务的Fish-gres图像数据集衍生版本，其中包含YOLOv8格式的人工标注边界框。

源图像来源：用于鱼类物种分类的Fish-gres数据集（Mendeley Data），DOI编号为10.17632/76cr3wfhff.1，采用CC BY 4.0许可协议。

新增/修改内容：• 针对单目标鱼类检测任务的人工边界框标注（单张图像仅包含一条鱼类），通过Roboflow平台完成标注并以YOLOv8标签格式导出。• 训练集/验证集/测试集划分文件，以及YOLO数据集配置文件（例如data.yaml）。

数据集规模与划分：总计2000张图像：• 训练集：1400张（占比70%）• 验证集：400张（占比20%）• 测试集：200张（占比10%）

文件名说明：由于本数据集通过Roboflow平台导出，图像文件名可能与原始Fish-gres数据集的文件名不一致。各划分文件夹内的标签文件与图像文件通过基础文件名进行匹配（例如xxx.jpg ↔ xxx.txt）。

引用要求：需标注的引用来源：Fish-gres图像数据集（原始图像）以及本Zenodo记录（YOLOv8标注与划分文件）。推荐引用：若您使用本数据集的实验设置或希望引用采用本标注的相关研究，请引用本文（IOP EES，DOI: 10.1088/1755-1315/1359/1/012023）。

本数据集发布于论文正式发表之后，旨在支持论文中报道的目标检测实验的复现与复用。