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Boat Dataset for Object Detection

Overview

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

Dataset Structure

Data Instances

A data point comprises an image and its object annotations.

{'image_id': 0,
 'image_path': 'images/0720_0937_2023-07-20-09-37-30_0_middle_color000220.jpg',
 'width': 640,
 'height': 480,
 'objects': {'id': [1],
  'area': [328.0],
  'bbox': [[153.69000244140625,
    101.76499938964844,
    21.924999237060547,
    14.972999572753906]],
  'category': [8]}}

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
  - BallonBoat (0)
  - BigBoat (1)
  - Boat (2)
  - JetSki (3)
  - Katamaran (4)
  - SailBoat (5)
  - SmallBoat (6)
  - SpeedBoat (7)
  - WAM_V (8)

Data Splits

Training dataset (42833)
- Real
  - WAM_V (2333)
- Virtual
  - BallonBoat (4500)
  - BigBoat (4500)
  - Boat (4500)
  - JetSki (4500)
  - Katamaran (4500)
  - SailBoat (4500)
  - SmallBoat (4500)
  - SpeedBoat (4500)
  - WAM_V (4500)
Val dataset (5400)
- Real
  - WAM_V (900)
- Virtual
  - BallonBoat (500)
  - BigBoat (500)
  - Boat (500)
  - JetSki (500)
  - Katamaran (500)
  - SailBoat (500)
  - SmallBoat (500)
  - SpeedBoat (500)
  - WAM_V (500)

Usage

from datasets import load_dataset
dataset = load_dataset("zhuchi76/Boat_dataset")

Citation

If you use this dataset in your research, please cite the following paper: