FishingROV/scallop_yolov5s_mosaic_640_4class

该数据集是为FishingROV边缘推理流水线生成的优化衍生格式，基于圣安德鲁斯大学国王扇贝数据集。它用于对象检测任务，特别关注水下环境、海洋生物学中的扇贝识别，并利用遥控潜水器（ROV）收集数据。数据集采用YOLOv5s模型，并经过mosaic增强和640x640分辨率处理，包含4个类别，规模在1,000到10,000个样本之间，适用于边缘计算场景。

This dataset is an optimized derivative format generated for the FishingROV edge inference pipeline, based on the University of St Andrews King Scallop dataset. It is designed for object detection tasks, specifically focusing on underwater environments, marine biology for scallop identification, and data collected using remotely operated vehicles (ROVs). The dataset utilizes the YOLOv5s model with mosaic augmentation and 640x640 resolution, containing 4 classes, with a size between 1K and 10K samples, suitable for edge computing applications.