Real Lifebuoy Dataset for Object Detection

Overview

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

Demo Example 1:

The video is available on video/detr_finetuned_2.mp4 or by clicking the image youtube link.

Demo Example 2:

Left hand side: 1th finetuned with virtual dataset Right hand side: 2nd further finetuned with real dataset

The video is available on video/detr_finetuned_1vs2.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 at 0x7781535B67C0>
  'image_path': 'images/2024-10-23-20-57-55_mid_305.png', 
  'width': 640, 
  'height': 480, 
  'objects': 
    {
      'id': [1], 
      'area': [4110.0], 
      'bbox': [[262.0, 312.0, 137.0, 30.0]], 
      '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 (540)
- Virtual
  - Lifebuoy (540)
Val dataset (135)
- Virtual
  - Lifebuoy (135)

Usage

from datasets import load_dataset

dataset = load_dataset("ARG-NCTU/Real_Lifebuoy_dataset_2024")