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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:

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