Datasets:
Attribute source text to DiEm (Rigsarkivet, CC-BY-4.0); correct splits (all-train by design) and diacritic note; link generation code
e985037 verified | license: cc-by-4.0 | |
| task_categories: | |
| - image-to-text | |
| language: | |
| - da | |
| tags: | |
| - htr | |
| - handwritten-text-recognition | |
| - historical | |
| - danish | |
| - synthetic | |
| - ocr | |
| - document-ai | |
| size_categories: | |
| - 100K<n<1M | |
| pretty_name: Danish HTR Synthetic (18th-Century) | |
| # Danish HTR Synthetic — 18th-Century Handwriting | |
| > 📝 **Blog:** [Segmentation is the hidden tax in historical HTR](https://dev.to/abhipandit1/segmentation-is-the-hidden-tax-in-historical-htr-1i67) | |
| > 🛠️ **Generation code:** [github.com/AbhiPandit1/danish-htr-synthetic → `generator/`](https://github.com/AbhiPandit1/danish-htr-synthetic/tree/master/generator) | |
| <p align="center"> | |
| <img src="https://huggingface.co/datasets/abhishekjha1008/danish-htr-synthetic/resolve/main/assets/dataset_demo.gif" alt="Synthetic Danish line images with exact ground truth" width="600" /> | |
| </p> | |
| <p align="center"><em>Each synthetic line image is paired with its exact ground-truth transcription.</em></p> | |
| **160,000 synthetic handwritten-text-line images with perfect ground truth, for training and pretraining historical Danish handwriting recognition (HTR) models.** | |
| Historical HTR is data-starved: for most languages and eras there is too little *corrected* handwriting to train a recogniser directly. This dataset is a synthetic bootstrap — clean, perfectly-labelled lines that let a model learn Danish 18th-century letterforms and vocabulary *before* it ever sees scarce, expensive real transcriptions. | |
| --- | |
| ## What's inside | |
| | | | | |
| |---|---| | |
| | **Lines** | 160,000 | | |
| | **Era** | 18th-century Danish (`1700s`) | | |
| | **Split** | all `train` (by design — see [Splits](#splits)) | | |
| | **Label quality** | Exact — the text is known by construction (no transcription noise) | | |
| | **Format** | Parquet (auto-converted); source images are JPEG | | |
| | **License** | CC-BY 4.0 | | |
| ### Features | |
| | Column | Type | Description | | |
| |---|---|---| | |
| | `image` | image (JPEG) | A single rendered handwriting line | | |
| | `text` | string | Ground-truth transcription (3–102 characters) | | |
| | `era_bucket` | string | Period label (`1700s`) | | |
| | `split` | string | `train` for every line in the released set (see Splits) | | |
| --- | |
| ## How it was generated | |
| Each line pairs authentic-looking period handwriting with realistic capture degradation, so a model trained on it transfers to real scans: | |
| - **Scripts** — historical Danish hands: gothic cursive (*Kurrent*), the everyday administrative hand of the era, and *copperplate* for formal writing. The released generator ships a documented, openly-licensed font set (Kurrent + a Schwabacher face; the OFL faces *Herr Von Muellerhoff* and *Petit Formal Script*). | |
| - **Text** — real 18th-century Danish transcriptions (see [Source & attribution](#source--attribution)), so the model learns the right vocabulary, spelling and letter-combinations of the era. | |
| - **Degradation** — paper texture and tone, ink/stroke-weight variation, blur, noise and simulated bleed-through. In the released code **every line records the font and the exact degradation parameters** used, so individual factors can be isolated for diagnostic study. | |
| The full, deterministic pipeline (rendering, degradation, splitting, manifest) is released under MIT at [`generator/`](https://github.com/AbhiPandit1/danish-htr-synthetic/tree/master/generator). The result is training data with the one thing real historical corpora almost never have: **exact labels at scale.** | |
| --- | |
| ## Source & attribution | |
| The text is **not invented**. It is drawn from the **DiEm HTR dataset** (*Digitalisering af Enesteministerialbøger*) — the volunteer-verified transcriptions of Danish parish registers released by the **Danish National Archives (Rigsarkivet)** under CC-BY 4.0: [RA-Data-Science/DiEm_HTR](https://huggingface.co/datasets/RA-Data-Science/DiEm_HTR). This dataset re-uses only the text strings, with attribution, under that licence. | |
| Provenance is verifiable: of the 36,056 unique strings here, **39% are verbatim DiEm transcription lines and 71% appear verbatim within a DiEm page**, with **99% of word tokens** present in the DiEm vocabulary (the remainder is the same text re-segmented at different line boundaries). | |
| **Orthography:** the period form *aa* dominates (22% of lines); the modern letter *å* (official only from 1948) appears in only 8 of 160,000 lines (0.005%), where the source transcription itself uses a modernised spelling. Text is rendered as transcribed; the generator has an optional normalisation hook (e.g. `å → aa`), off by default. | |
| --- | |
| ## Intended use | |
| - **Pretraining / warm-start** a CTC or sequence recogniser (e.g. PyLaia, TrOCR) before fine-tuning on a small set of *real* corrected lines. | |
| - **Data augmentation** to stabilise training on tiny real-world historical corpora. | |
| - **Ablations** on how synthetic volume, degradation and script style affect downstream accuracy. | |
| > **Honest note:** synthetic data is a *bootstrap*, not a substitute for real ground truth. Always report final accuracy on a **held-out set of real documents**, not on synthetic data. Because the text here is drawn from DiEm, your real test set should be held out from the DiEm transcriptions to avoid text leakage. | |
| --- | |
| ## Splits | |
| The released set labels **every line `train`**: it was built purely as a pre-training / augmentation source, with final accuracy always measured on **held-out real documents** (a synthetic test split is not a meaningful target). If you want explicit, reproducible `train`/`val`/`test` splits, the [generator](https://github.com/AbhiPandit1/danish-htr-synthetic/tree/master/generator) produces them (assigned by hashing the text, so there is no leakage). | |
| ## Quick start | |
| ```python | |
| from datasets import load_dataset | |
| ds = load_dataset("abhishekjha1008/danish-htr-synthetic") | |
| sample = ds["train"][0] | |
| sample["image"] # PIL.Image — the handwriting line | |
| sample["text"] # str — the ground-truth transcription | |
| ``` | |
| --- | |
| ## Why this exists | |
| This dataset is part of ongoing independent research on recognising historical and handwritten text across languages and scripts — building specialist recognisers that stay faithful to the page where general vision-language models tend to hallucinate. Synthetic data like this is how you cold-start a recogniser for a language and era that does not yet have enough labelled real data. | |
| If you use it, I'd genuinely like to hear what you built — feel free to open a discussion on the dataset. | |
| --- | |
| ## Citation | |
| ```bibtex | |
| @misc{jha2026danishhtrsynthetic, | |
| title = {Danish HTR Synthetic: 160k Synthetic 18th-Century Danish Handwriting Lines}, | |
| author = {Jha, Abhishek}, | |
| year = {2026}, | |
| howpublished = {Hugging Face Datasets}, | |
| url = {https://huggingface.co/datasets/abhishekjha1008/danish-htr-synthetic} | |
| } | |
| ``` | |
| Please also credit the source text: the DiEm HTR dataset (Rigsarkivet), CC-BY 4.0. | |
| --- | |
| ## License & contact | |
| Released under **CC-BY 4.0** — free to use with attribution. Source text © the Danish National Archives (Rigsarkivet) / DiEm contributors, CC-BY 4.0. | |
| **Author:** Abhishek Jha · [GitHub](https://github.com/AbhiPandit1) · [Hugging Face](https://huggingface.co/abhishekjha1008) | |