| --- |
| license: cc-by-4.0 |
| task_categories: |
| - image-to-text |
| language: |
| - ja |
| tags: |
| - ocr |
| - japanese |
| - text-recognition |
| - book-ocr |
| - scene-text |
| pretty_name: honmono-ocr test set |
| size_categories: |
| - 10K<n<100K |
| --- |
| |
| # 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](https://github.com/eridgd/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 |
|
|
| ```python |
| 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](https://github.com/eridgd/honmono-ocr). This dataset bundles `test_real.manifest.txt`, which lists the same 14,256 lines: |
|
|
| ```bash |
| 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: |
|
|
| ```bibtex |
| @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> |
|
|
