| --- |
| tags: |
| - ocr |
| - document-processing |
| - dots-ocr |
| - multilingual |
| - markdown |
| - uv-script |
| - generated |
| --- |
| |
| # Document OCR using dots.ocr |
|
|
| This dataset contains OCR results from images in [NationalLibraryOfScotland/Britain-and-UK-Handbooks-Dataset](https://huggingface.co/datasets/NationalLibraryOfScotland/Britain-and-UK-Handbooks-Dataset) using DoTS.ocr, a compact 1.7B multilingual model. |
|
|
| ## Processing Details |
|
|
| - **Source Dataset**: [NationalLibraryOfScotland/Britain-and-UK-Handbooks-Dataset](https://huggingface.co/datasets/NationalLibraryOfScotland/Britain-and-UK-Handbooks-Dataset) |
| - **Model**: [rednote-hilab/dots.ocr](https://huggingface.co/rednote-hilab/dots.ocr) |
| - **Number of Samples**: 10 |
| - **Processing Time**: 2.2 min |
| - **Processing Date**: 2025-10-08 16:53 UTC |
|
|
| ### Configuration |
|
|
| - **Image Column**: `image` |
| - **Output Column**: `markdown` |
| - **Dataset Split**: `train` |
| - **Batch Size**: 32 |
| - **Prompt Mode**: layout-all |
| - **Max Model Length**: 32,768 tokens |
| - **Max Output Tokens**: 8,192 |
| - **GPU Memory Utilization**: 80.0% |
|
|
| ## Model Information |
|
|
| DoTS.ocr is a compact multilingual document parsing model that excels at: |
| - 🌍 **100+ Languages** - Multilingual document support |
| - 📊 **Table extraction** - Structured data recognition |
| - 📐 **Formulas** - Mathematical notation preservation |
| - 📝 **Layout-aware** - Reading order and structure preservation |
| - 🎯 **Compact** - Only 1.7B parameters |
|
|
| ## Dataset Structure |
|
|
| The dataset contains all original columns plus: |
| - `markdown`: The extracted text in markdown format |
| - `inference_info`: JSON list tracking all OCR models applied to this dataset |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| import json |
| |
| # Load the dataset |
| dataset = load_dataset("{output_dataset_id}", split="train") |
| |
| # Access the markdown text |
| for example in dataset: |
| print(example["markdown"]) |
| break |
| |
| # View all OCR models applied to this dataset |
| inference_info = json.loads(dataset[0]["inference_info"]) |
| for info in inference_info: |
| print(f"Column: {info['column_name']} - Model: {info['model_id']}") |
| ``` |
|
|
| ## Reproduction |
|
|
| This dataset was generated using the [uv-scripts/ocr](https://huggingface.co/datasets/uv-scripts/ocr) DoTS OCR script: |
|
|
| ```bash |
| uv run https://huggingface.co/datasets/uv-scripts/ocr/raw/main/dots-ocr.py \ |
| NationalLibraryOfScotland/Britain-and-UK-Handbooks-Dataset \ |
| <output-dataset> \ |
| --image-column image \ |
| --batch-size 32 \ |
| --prompt-mode layout-all \ |
| --max-model-len 32768 \ |
| --max-tokens 8192 \ |
| --gpu-memory-utilization 0.8 |
| ``` |
|
|
| Generated with 🤖 [UV Scripts](https://huggingface.co/uv-scripts) |
|
|