| --- |
| 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-1 |
| --- |
| |
| # RASAM 1 — Line-Level HTR Ground-Truth for Arabic historical manuscripts (Maghrebi) |
|
|
| <p align="center"> |
| <a href="https://doi.org/10.1007/978-3-030-86198-8_19"><img src="https://img.shields.io/badge/Paper-ICDAR 2021-blue" alt="Paper ICDAR 2021"></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 1 is a specialized dataset for Handwritten Text Recognition (HTR) focusing on Arabic historical manuscripts in **Maghrebi script**. |
|
|
| This HuggingFace dataset provides **cropped line-level images** paired with their transcriptions and rich metadata for 3 Arabic Maghrebi manuscripts from the BULAC Library. It is designed as a ready-to-use resource for benchmarking and training HTR models on under-resourced historical scripts. |
|
|
| | | | |
| |---|---| |
| | Manuscripts | 3 | |
| | Pages | 299 | |
| | Lines | 7,331 | |
| | Words | 97,311 | |
| | Characters | 492,221 | |
|
|
| > The full page-level dataset (PageXML + full-page images) is available on [GitHub](https://github.com/calfa-co/rasam-dataset). |
|
|
| ## Source Documents |
|
|
| The corpus consists of three manuscripts from the BULAC Library (Paris), dating from the 17th to the 19th centuries: |
| - `BULAC_MS_ARA_417` (Historical) |
| - `BULAC_MS_ARA_609` (Inheritance law) |
| - `BULAC_MS_ARA_1977` (Historical) |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| # Load the full dataset |
| ds = load_dataset("calfa-ai/rasam-1") |
| |
| # Access a sample |
| sample = ds["train"][0] |
| sample["image"].show() |
| print(sample["transcription"]) |
| |
| # Filter by manuscript |
| bulac_609 = ds["train"].filter(lambda x: x["manuscript_name"].startswith("BULAC_MS_ARA_609")) |
| ``` |
|
|
| ## Transcription Guidelines (Summary) |
| The RASAM transcription protocol prioritizes fidelity to the scribe's practice over modern standard orthography to ensure robust HTR training. Key principles include: |
|
|
| - Orthographic Preservation: Scribes' specific spellings (including archaisms and variant usages of characters like *dād*/*ẓāʾ* or *ṣād*/*ṭāʾ*) are maintained exactly as they appear in the manuscript. |
| - Normalization Exceptions: To facilitate computational consistency, specific glyphic forms for relative pronouns (e.g., *allaḏī*/*allatī*) and the preposition *fī* are standardized. |
| - Diacritics & Hamza: Vocalization and diacritics are generally excluded unless semantically essential. Hamzas are only transcribed if explicitly present in the source. |
| - Handling Uncertainty: Illegible or damaged characters are marked with #. Gaps in the source text are not reconstructed. |
| - Formatting: Spaces are restored in the transcription regardless of their visual presence in the manuscript layout. |
|
|
| *Source*: For a detailed breakdown of specifications and paleographical considerations, please refer to the full paper (see below) |
|
|
| ## Citation |
|
|
| ```bibtex |
| @InProceedings{2021rasam-dataset, |
| author = {Vidal-Gorène, Chahan and Lucas, Noëmie and Salah, Clément and Decours-Perez, Aliénor and Dupin, Boris}, |
| editor = {Barney Smith, Elisa H. and Pal, Umapada}, |
| title = {RASAM -- A Dataset for the Recognition and Analysis of Scripts in Arabic Maghrebi}, |
| booktitle = {Document Analysis and Recognition -- ICDAR 2021 Workshops}, |
| year = {2021}, |
| publisher = {Springer International Publishing}, |
| address = {Cham}, |
| pages = {265--281}, |
| isbn = {978-3-030-86198-8} |
| } |
| ``` |
|
|
| ## 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> |
