Datasets:
Tasks:
Image-to-Text
Modalities:
Image
Formats:
imagefolder
Languages:
Hebrew
Size:
1K - 10K
License:
| license: cc0-1.0 | |
| task_categories: | |
| - image-to-text | |
| language: | |
| - he | |
| tags: | |
| - biblical-text | |
| - hebrew | |
| - new-testament | |
| - ocr | |
| - besorah | |
| - elias-hutter | |
| - text-recognition | |
| - religious-text | |
| size_categories: | |
| - 1K-10K | |
| # Dataset Card for Hebrew Biblical Text Images | |
| ## Dataset Description | |
| ### Dataset Summary | |
| This dataset contains rendered images of biblical texts in Hebrew, specifically covering books from the Elias Hutter's Besorah (New Testament). The dataset is organized into two main subsets: | |
| - **Hebrew** (`hebrew/`): Processed/rendered Hebrew text images (1,243 images) | |
| - **Raw** (`raw/`): Original raw text images (2,541 images) | |
| Each book is organized in its own directory, with images sequentially numbered (e.g., `000001.png`, `000002.png`). | |
| ### Supported Tasks and Leaderboards | |
| This dataset is designed for: | |
| - **Optical Character Recognition (OCR)**: Training and evaluating OCR models to recognize Hebrew text from rendered images | |
| - **Image-to-Text**: Converting rendered text images back to machine-readable Hebrew text | |
| - **Biblical Text Processing**: Research and analysis of biblical texts in Hebrew | |
| - **Document Understanding**: Understanding document structure and layout of religious texts | |
| - **Multilingual OCR**: Supporting Hebrew language OCR research | |
| ### Citation Information | |
| If you use this dataset in your research, please cite it as: | |
| ```bibtex | |
| @dataset{hutter, | |
| title={Elias Hutter's hebrew besorah (new testament) translation}, | |
| author={edyhvh}, | |
| year={2025}, | |
| url={https://huggingface.co/datasets/edyhvh/hutter}, | |
| license={CC0-1.0} | |
| } | |
| ``` | |
| ### Contributions | |
| Contributions, suggestions, and improvements are welcome. Please open an issue or submit a pull request if you have suggestions for improving the dataset or documentation. | |