# 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:

[![Lifebuoy Underwater Detection Video](https://img.youtube.com/vi/azpLvmDEy3A/0.jpg)](https://www.youtube.com/watch?v=azpLvmDEy3A)

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](https://albumentations.ai/docs/getting_started/bounding_boxes_augmentation/#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")
```