Boats Dataset

Dataset details

Last updated: 15 Dec 2022
Meta Album ID VCL.BTS
Domain ID VCL
Domain Name Vehicles
Set Number 2
Dataset ID BTS
Dataset Name Boats
Short Description Dataset with images of different boats
Long Description The original version of the Meta-Album boats dataset is called MARVEL dataset (https://github.com/avaapm/marveldataset2016). It has more than 138 000 images of 26 different maritime vessels in their natural background. Each class can have 1 802 to 8 930 images of variable resolutions. To preprocess this dataset, we either duplicate the top and bottom-most 3 rows or the left and right most 3 columns based on the orientation of the original image to create square images. No cropping was applied because the boats occupy most of the image, and applying this technique will lead to incomplete images. Finally, the square images were resized into 128x128 px using an anti-aliasing filter
# Classes 26
# Images 138367
Keywords vehicles, boats
Data Format images
Image size 128x128
License
(original data release)		 Cite paper to use dataset
License
(Meta-Album data release)		 CC BY-NC 4.0
License URL
(Meta-Album data release)		 https://creativecommons.org/licenses/by-nc/4.0/
Source MARVEL: A LARGE-SCALE IMAGE DATASET FOR MARITIME VESSELS
Source URL https://github.com/avaapm/marveldataset2016
Original Author Gundogdu E., Solmaz B, Yucesoy V., Koc A.
Original contact
Meta Album author Dustin Carrion
Created Date 01 March 2022
Contact Name Ihsan Ullah
Contact Email meta-album@chalearn.org
Contact URL https://meta-album.github.io/

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Dataset Info Datasheet

Download Dataset from OpenML

Dataset Version OpenML ID
Micro 44279 Download
Mini 44309 Download
Extended 44343 Download

Code to download dataset using OpenML API

      # import openml
      import openml
  
      # download dataset with DATASET_ID. DATASET_ID is OpenML ID
      dataset = openml.datasets.get_dataset(DATASET_ID)
  
      # display dataset info
      print(dataset.name)

Sample Images

Cite this dataset 

@InProceedings{MARVEL,
    author="Gundogdu, Erhan and Solmaz, Berkan and Yucesoy, Veysel and Koc, Aykut",
    editor="Lai, Shang-Hong and Lepetit, Vincent and Nishino, Ko and Sato, Yoichi",
    title="MARVEL: A Large-Scale Image Dataset for Maritime Vessels",
    booktitle="Computer Vision --  ACCV 2016",
    year="2017",
    publisher="Springer International Publishing",
    address="Cham",
    pages="165--180",
    isbn="978-3-319-54193-8"
}
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Cite Meta-Album

  @inproceedings{meta-album-2022,
    title={Meta-Album: Multi-domain Meta-Dataset for Few-Shot Image Classification},
    author={Ullah, Ihsan and Carrion, Dustin and Escalera, Sergio and Guyon, Isabelle M and Huisman, Mike and Mohr, Felix and van Rijn, Jan N and Sun, Haozhe and Vanschoren, Joaquin and Vu, Phan Anh},
    booktitle={Thirty-sixth Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
    url = {https://meta-album.github.io/},
    year = {2022}
  }
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