| --- |
| license: apache-2.0 |
| language: |
| - ar |
| task_categories: |
| - image-to-text |
| tags: |
| - htr |
| - ocr |
| - arabic |
| - manuscripts |
| - historical |
| size_categories: |
| - 1K<n<10K |
| pretty_name: RASAM-2 |
| --- |
| |
| # RASAM 2 — Line-Level HTR Ground-Truth for Arabic historical manuscripts (Maghrebi) |
|
|
| <p align="center"> |
| <a href="https://ceur-ws.org/Vol-3834/paper35.pdf"><img src="https://img.shields.io/badge/Paper-CHR 2024-blue" alt="Paper CHR 2024"></a> |
| <a href="https://github.com/calfa-co/rasam-dataset"><img src="https://img.shields.io/badge/GitHub-PageXML dataset-green" alt="GitHub"></a> |
| <a href="https://calfa.fr"><img src="https://img.shields.io/badge/Platform-Calfa Vision-purple" alt="Calfa"></a> |
| </p> |
|
|
| ## Dataset Description |
|
|
| RASAM 2 extends the initial initiative [RASAM 1](https://huggingface.co/datasets/calfa-ai/RASAM-1) by integrating the outcomes of the second manuscript transcription hackathon organized by the Research Consortium Middle-East and Muslim Worlds (GIS MOMM) and Calfa at BULAC (Paris) between December 2021 and March 2022. |
|
|
| This HuggingFace dataset provides cropped line-level images paired with their transcriptions and rich metadata for 15 Arabic Maghrebi manuscripts sourced from the BULAC Library. Building upon the original RASAM 1 collection, this expanded resource features a deliberately heterogeneous corpus that includes Berber texts written in Arabic script, covering diverse genres such as history (chronicles), law, literature, poetry, Muslim piety, and grammar. |
|
|
| The collection is composed primarily of texts copied during the modern period (17th–19th centuries) and is specifically designed as a ready-to-use, robust resource for Arabic Maghrebi Handwritten Text Recognition (HTR) benchmarking and model training. |
|
|
| | | | |
| |---|---| |
| | Manuscripts | 15 | |
| | Pages | 162 | |
| | Lines | 3,720 | |
| | Words | 45,645 | |
| | Characters | 223,426 | |
|
|
| > The full page-level dataset (PageXML + full-page images) is available on [GitHub](https://github.com/calfa-co/rasam-dataset). |
|
|
| ## Source Documents |
|
|
| 15 manuscripts from the BULAC Library (Paris), spanning history, law, literature, poetry, and religious studies, 17th–19th centuries: |
| - `BULAC_MS_ARA_6`, `BULAC_MS_ARA_9`, `BULAC_MS_ARA_23`, `BULAC_MS_ARA_24`, `BULAC_MS_ARA_45b`, `BULAC_MS_ARA_65`, `BULAC_ARA_MS_1982`, `BULAC_MS_ARA_1926`, `BULAC_MS_ARA_1936`, `BULAC_MS_ARA_1943`, `BULAC_MS_ARA_1944`, `BULAC_MS_ARA_1946`, `BULAC_MS_ARA_1947`, `BULAC_MS_ARA_1960`, `BULAC_MS_ARA_1983` |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| # Load the full dataset |
| ds = load_dataset("calfa-ai/rasam-2") |
| |
| # Access a sample |
| sample = ds["train"][0] |
| sample["image"].show() |
| print(sample["transcription"]) |
| |
| # Filter by manuscript |
| bulac_9 = ds["train"].filter(lambda x: x["manuscript_name"].startswith("BULAC_MS_ARA_9")) |
| ``` |
|
|
| ## Transcription Guidelines (Summary) |
|
|
| The transcription guidelines follow the RASAM specification: transcriptions preserve the text as found in the image, including variant spellings, while excluding vocalization marks unless structurally significant. See [RASAM 1](https://huggingface.co/datasets/calfa-ai/RASAM-1) and [original paper](https://link.springer.com/chapter/10.1007/978-3-030-86198-8_19) for details. |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{2024rasam-dataset, |
| title = {{Enhancing Arabic Maghribi Handwritten Text Recognition with RASAM 2: A Comprehensive Dataset and Benchmarking}}, |
| author = {Vidal-Gorène, Chahan and Salah, Clément and Lucas, Noëmie and Decours-Perez, Aliénor and Perrier, Antoine}, |
| url = {https://enc.hal.science/hal-04722622}, |
| booktitle = {{Computational Humanities Research (CHR)}}, |
| address = {Aarhus, Denmark}, |
| volume = {3834}, |
| pages = {200--216}, |
| year = {2024}, |
| month = dec, |
| } |
| ``` |
|
|
| ## License |
|
|
| This dataset is released under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0). |
|
|
| ## Acknowledgements |
|
|
| The RASAM dataset was developed collaboratively between 2021–2023 by the Research Consortium Middle-East and Muslim Worlds (GIS MOMM), DISTAM, Calfa, and the BULAC Library. The project was funded by the French Ministry of Higher Education, Research and Innovation. |
|
|
| <div style="display: flex; align-items: center; gap: 15px;"> |
| <img src="./assets/bulac.png" style="height: 50px;" alt="bulac-logo"> |
| <img src="./assets/calfa.png" style="height: 50px;" alt="calfa-logo"> |
| <img src="./assets/distam.png" style="height: 50px;" alt="distam-logo"> |
| <img src="./assets/gis-momm.png" style="height: 50px;" alt="gis-logo"> |
| <img src="./assets/cnrs.png" style="height: 50px;" alt="cnrs-logo"> |
| <img src="./assets/mesri.png" style="height: 50px;" alt="mesri-logo"> |
| </div> |