eridgd/honmono-ocr-test

honmono-ocr test set

A held-out benchmark of 14,256 real Japanese text lines, each a cropped line image paired with its transcription. It is the evaluation set for the honmono-ocr recognition models, intended both for reproducing their reported accuracy and for benchmarking other Japanese line-recognition models on the same data.

The lines are drawn from printed books, scanned print, and scene text, spanning the conditions a camera-based Japanese OCR system typically meets.

Dataset structure

A single test split of 14,256 examples. Each example has three fields:

field	type	description
image	image	one cropped text line
text	string	transcription, NFKC-normalized
source	string	origin: ndl_pdm, ndl_ndlocr, icdar_mlt, or ndl_oneline

Reported scores for the honmono-ocr models are computed against the NFKC-normalized text.

Composition by source:

source	lines	description
ndl_pdm	8,768	scanned pre-war printed books (National Diet Library)
icdar_mlt	4,114	Japanese scene text (signs, storefronts, displays)
ndl_ndlocr	1,353	National Diet Library print, more modern
ndl_oneline	21	a small NDL one-line set, reported for completeness

Both horizontal and vertical (縦書き) lines are included. Vertical crops are stored rotated 90°, the form the models consume at inference.

Usage

from datasets import load_dataset

ds = load_dataset("eridgd/honmono-ocr-test", split="test")
print(ds[0]["text"], ds[0]["source"])
ds[0]["image"]

To reproduce the published honmono-ocr scores, use the evaluation runner in the code repository. This dataset bundles test_real.manifest.txt, which lists the same 14,256 lines:

python eval/run_eval.py \
  --model models/v6-small/honmono-v6-small-fp16.onnx \
  --manifest path/to/honmono-ocr-test/test_real.manifest.txt \
  --crops_dir path/to/honmono-ocr-test

Reference results, whole-line accuracy (a line counts as correct only when every character matches):

model	overall	NDL PDM	NDL NDLOCR	ICDAR MLT
honmono v6-small	83.5	87.5	83.2	75.2
honmono v6-tiny	73.6	80.7	77.8	57.3
PP-OCRv6-small (off-the-shelf)	50.2	50.8	48.9	49.6
PP-OCRv6-tiny (off-the-shelf)	26.2	29.8	22.3	19.8

Source data and licensing

This dataset is redistributed under CC-BY-4.0, the license of both source datasets, and contains material modified from the originals as noted below.

National Diet Library (NDL) OCR datasets (ndl_pdm, ndl_ndlocr, ndl_oneline). © National Diet Library, Japan. Licensed CC-BY-4.0. Source: https://lab.ndl.go.jp/

ICDAR Robust Reading Challenge on Multi-Lingual Scene Text — RRC-MLT, 2017 and 2019 (icdar_mlt). Licensed CC-BY-4.0. Source: https://rrc.cvc.uab.es/?ch=8 (2017) and https://rrc.cvc.uab.es/?ch=15 (2019). Dataset described in N. Nayef et al., ICDAR2019 Robust Reading Challenge on Multi-Lingual Scene Text Detection and Recognition (RRC-MLT-2019), ICDAR 2019.

Modifications applied to both sources: restricted to Japanese text; images cropped to individual text-line regions; annotations converted to a single text field and NFKC-normalized; unusable samples removed. RRC-MLT-2019's test-set ground truth was not publicly released and is not included; the ICDAR lines are taken from the publicly released train/validation portions. No endorsement by the original creators is implied.

The NDL portion (approximately 10,000 lines) requires no registration. The ICDAR portion originates from the RRC site, which requires a free account to download the source data.

The ICDAR MLT portion consists of photographs of real-world scenes. CC-BY-4.0 grants the copyright and database rights held by the licensors; it does not address privacy, publicity, or trademark rights that may attach to people, signage, or logos visible in individual images. This is standard for scene-text datasets and does not restrict ordinary research or benchmarking use. Anyone reusing specific images in other contexts should evaluate those rights independently.

Citation

For the honmono-ocr models and this dataset packaging:

@software{honmono_ocr,
  title  = {honmono-ocr: on-device Japanese book OCR},
  author = {Evan Davis},
  year   = {2026},
  url    = {https://github.com/eridgd/honmono-ocr}
}

Users must also credit the source datasets (NDL Lab; ICDAR RRC-MLT) under their CC-BY-4.0 terms.

Links

• Models: https://huggingface.co/eridgd/honmono-ocr-v6-small (also -v6-tiny, -v5)
• Code, training recipe, and evaluation runner: https://github.com/eridgd/honmono-ocr