README.md

Lifebuoy Dataset for Object Detection

Overview

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

Demo Example:

Video available on video/lifebuoy_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': <PIL.PngImagePlugin.PngImageFile image mode=RGB size=640x480>,
 'image_path': 'images/Lifebuoy_Scene3_blur1_2.png',
 'width': 640,
 'height': 480,
 'objects': {'id': [1],
  'area': [7140.0],
  'bbox': [[303.0, 248.0, 119.0, 60.0]],
  'category': [0]}}

Data Fields

• image_id: the image id
• image: the PIL image
• image_path: the image path
• 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 (3992)

  • Virtual
    • Lifebuoy (3992)

• Val dataset (998)

  • Virtual
    • Lifebuoy (998)

Usage

from datasets import load_dataset

dataset = load_dataset("ARG-NCTU/Lifebuoy_dataset_2024")