D_six: Dataset for Floating Debris Detection in Aquatic Environments

D_six is a curated dataset for the detection of floating debris in aquatic environments, designed to support the development of real-time object detection models such as YOLOv5. The dataset is organized in standard YOLO format and includes:- Training and validation images in `images/train` and `images/validation`- Corresponding YOLO labels in `labels/train` and `labels/validation`- A separate set of test images in the `test` folder Classes include: plastic bottles, drink cans, food wrappers, styrofoam, plastic bags, and others. Each label follows YOLO format: `[class x_center y_center width height]` with normalized coordinates. This dataset was used in the paper: **"A Hybrid Machine Learning Framework for Detecting Floating Objects in Water Bodies"** (submitted to *Ocean Engineering*). Recommended citation provided after DOI is generated.