SEACrowd/sleukrith_ocr

SleukRith Set is the first dataset specifically created for Khmer palm leaf manuscripts. The dataset consists of annotated data from 657 pages of digitized palm leaf manuscripts which are selected arbitrarily from a large collection of existing and also recently digitized images. The dataset contains three types of data: isolated characters, words, and lines. Each type of data is annotated with the ground truth information which is very useful for evaluating and serving as a training set for common document analysis tasks such as character/text recognition, word/line segmentation, and word spotting.

The character mapping (per label) is not explained anywhere in the dataset homepage, thus the labels are simply numbered from 0 to 110, each corresponds to a distinct character.

Languages

khm

Supported Tasks

Optical Character Recognition

Dataset Usage

Using datasets library

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

Using seacrowd library

# Load the dataset using the default config
dset = sc.load_dataset("sleukrith_ocr", schema="seacrowd")
# Check all available subsets (config names) of the dataset
print(sc.available_config_names("sleukrith_ocr"))
# 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://github.com/donavaly/SleukRith-Set

Dataset Version

Source: 1.0.0. SEACrowd: 2024.06.20.

Dataset License

Unknown (unknown)

Citation

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

@inproceedings{10.1145/3151509.3151510,
    author = {Valy, Dona and Verleysen, Michel and Chhun, Sophea and Burie, Jean-Christophe},
    title = {A New Khmer Palm Leaf Manuscript Dataset for Document Analysis and Recognition: SleukRith Set},
    year = {2017},
    isbn = {9781450353908},
    publisher = {Association for Computing Machinery},
    address = {New York, NY, USA},
    url = {https://doi.org/10.1145/3151509.3151510},
    doi = {10.1145/3151509.3151510},
    booktitle = {Proceedings of the 4th International Workshop on Historical Document Imaging and Processing},
    pages = {1-6},
    numpages = {6},
    location = {Kyoto, Japan},
    series = {HIP '17}
}


@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}
}