README.md

Lifebuoy Underwater Dataset for Object Detection

Overview

This dataset contains images of virtual underwater lifebuoy for object detection tasks. It can be used to train and evaluate object detection models.

Demo Example:

Video is available on video/lifebuoy_underwater_detection.mp4 or by clicking the image youtube link.

Dataset Structure

Data Instances

A data point comprises an image and its object annotations.

{'image_id': 1,
 'image_path': 'images/Lifebuoy_Scene2_1.png',
 'width': 640,
 'height': 480,
 'objects': {'id': [1],
  'area': [7273.22705078125],
  'bbox': [[316.0, 254.0, 106.0, 46.0]],
  'category': [0]}}

Data Fields

• image_id: the image id
• width: the image width
• height: the image height
• objects: a dictionary containing bounding box metadata for the objects present on the image
  • id: the annotation id
  • area: the area of the bounding box
  • bbox: the object's bounding box (in the coco format)
  • category: the object's category, with possible values including
    • Lifebuoy (0)

Data Splits

• Training dataset (2396)

  • Virtual
    • Lifebuoy (2396)

• Val dataset (598)

  • Virtual
    • Lifebuoy (598)

Usage

from datasets import load_dataset

dataset = load_dataset("ARG-NCTU/Lifebuoy_underwater_dataset_2024")