README.md

metadata

pretty_name: Chinese OCR Line Dataset (EvaHan Competition @ LREC2026)
task_categories:
  - image-to-text
language:
  - zh
license: cc-by-4.0
tags:
  - ocr
  - historical-documents
  - chinese
  - lrec-2026
links:
  paper: https://hal.science/hal-05622586
  repository: https://github.com/<org>/<repo>
  competition: https://<competition-url>

Chinese OCR Line Dataset

This repository contains the synthetic dataset used by the ENCHANTeam team for the EvaHan 2026 competition on OCR/HTR of Chinese documents.

Final ranking of the team: 3rd.

UltraGlyph data consist in a automatic mix of real data provided by the organizers, for the closed modality of the competition (no external dataset authorized).

Resource	Link
Preprint	HAL
Code	GitHub
Competition	EvaHan @ LREC 2026

Dataset description

Pairs of line images and Chinese transcriptions drawn from two sources:

Source label	Origin	Train	Val
fonts	Synthetic printed lines using chinese fonts	72 323	12 676
ultraglyph	Synthetic lines using real data and ultraglyph generator (mix handwritten and printed)	57 063	10 201
Total		129 386	22 877

Transcription lengths range from 2 to 30 characters (median 16).

Usage

from datasets import load_dataset

ds = load_dataset("<org>/<dataset-name>")
example = ds["train"][0]
example["image"].show()
print(example["transcription"], example["source"])

Citation

If you use this dataset, please cite this work:

@misc{<bibtex-key>,
  title  = {},
  author = {},
  year   = {2026},
  url    = {https://hal.science/<HAL-ID>}
}

Acknowledgement

This study was conducted as part of the DH master’s program at École nationale des chartes–PSL and with the support of the PSL Research University’s Major Research Program CultureLab, implemented by the ANR (reference ANR-10-IDEX-0001).