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Languages:
Tagalog
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metadata
license: cc-by-4.0
language:
  - tgl
pretty_name: Baybayin
task_categories:
  - optical-character-recognition
tags:
  - optical-character-recognition

The Baybayin dataset contains binary images of Baybayin characters, Latin characters, and 4 character symbols of Baybayin diacritics in MATLAB format. It consisted of 17000 images for Baybayin (1000 per character), 18200 images for Latin (700 per character), and 2000 images for Baybayin diacritics (500 per symbol). Each character image is strictly center-fitted with a size 56x56 pixels. This dataset was initially used to discriminate Latin script from Baybayin script in character recognition.

This is local dataset, please download the dataset from the _HOMEPAGE URL.

This is a local dataset. You have to obtain this dataset separately from {homepage} to use this dataloader.

Languages

tgl

Supported Tasks

Optical Character Recognition

Dataset Usage

Using datasets library

from datasets import load_dataset
dset = datasets.load_dataset("SEACrowd/baybayin", trust_remote_code=True)

Using seacrowd library

# Load the dataset using the default config
dset = sc.load_dataset("baybayin", schema="seacrowd")
# Check all available subsets (config names) of the dataset
print(sc.available_config_names("baybayin"))
# Load the dataset using a specific config
dset = sc.load_dataset_by_config_name(config_name="<config_name>")

More details on how to load the seacrowd library can be found here.

Dataset Homepage

https://www.kaggle.com/datasets/rodneypino/baybayin-and-latin-binary-images-in-mat-format

Dataset Version

Source: 4.0.0. SEACrowd: 2024.06.20.

Dataset License

Creative Commons Attribution 4.0 (cc-by-4.0)

Citation

If you are using the Baybayin dataloader in your work, please cite the following:

@article{Pino2021,
    title = {Optical character recognition system for Baybayin scripts using support vector machine},
    volume = {7},
    ISSN = {2376-5992},
    url = {http://dx.doi.org/10.7717/peerj-cs.360},
    DOI = {10.7717/peerj-cs.360},
    journal = {PeerJ Computer Science},
    publisher = {PeerJ},
    author = {Pino,  Rodney and Mendoza,  Renier and Sambayan,  Rachelle},
    year = {2021},
    month = feb,
    pages = {e360}
}


@article{lovenia2024seacrowd,
    title={SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages}, 
    author={Holy Lovenia and Rahmad Mahendra and Salsabil Maulana Akbar and Lester James V. Miranda and Jennifer Santoso and Elyanah Aco and Akhdan Fadhilah and Jonibek Mansurov and Joseph Marvin Imperial and Onno P. Kampman and Joel Ruben Antony Moniz and Muhammad Ravi Shulthan Habibi and Frederikus Hudi and Railey Montalan and Ryan Ignatius and Joanito Agili Lopo and William Nixon and Börje F. Karlsson and James Jaya and Ryandito Diandaru and Yuze Gao and Patrick Amadeus and Bin Wang and Jan Christian Blaise Cruz and Chenxi Whitehouse and Ivan Halim Parmonangan and Maria Khelli and Wenyu Zhang and Lucky Susanto and Reynard Adha Ryanda and Sonny Lazuardi Hermawan and Dan John Velasco and Muhammad Dehan Al Kautsar and Willy Fitra Hendria and Yasmin Moslem and Noah Flynn and Muhammad Farid Adilazuarda and Haochen Li and Johanes Lee and R. Damanhuri and Shuo Sun and Muhammad Reza Qorib and Amirbek Djanibekov and Wei Qi Leong and Quyet V. Do and Niklas Muennighoff and Tanrada Pansuwan and Ilham Firdausi Putra and Yan Xu and Ngee Chia Tai and Ayu Purwarianti and Sebastian Ruder and William Tjhi and Peerat Limkonchotiwat and Alham Fikri Aji and Sedrick Keh and Genta Indra Winata and Ruochen Zhang and Fajri Koto and Zheng-Xin Yong and Samuel Cahyawijaya},
    year={2024},
    eprint={2406.10118},
    journal={arXiv preprint arXiv: 2406.10118}
}