| | --- |
| | tags: |
| | - ocr |
| | - document-processing |
| | - dots-ocr |
| | - multilingual |
| | - markdown |
| | - uv-script |
| | - generated |
| | --- |
| | |
| | # Document OCR using dots.ocr |
| |
|
| | This dataset contains OCR results from images in [davanstrien/ufo-ColPali](https://huggingface.co/datasets/davanstrien/ufo-ColPali) using DoTS.ocr, a compact 1.7B multilingual model. |
| |
|
| | ## Processing Details |
| |
|
| | - **Source Dataset**: [davanstrien/ufo-ColPali](https://huggingface.co/datasets/davanstrien/ufo-ColPali) |
| | - **Model**: [rednote-hilab/dots.ocr](https://huggingface.co/rednote-hilab/dots.ocr) |
| | - **Number of Samples**: 20 |
| | - **Processing Time**: 2.8 min |
| | - **Processing Date**: 2026-02-25 13:36 UTC |
| |
|
| | ### Configuration |
| |
|
| | - **Image Column**: `image` |
| | - **Output Column**: `markdown` |
| | - **Dataset Split**: `train` |
| | - **Batch Size**: 16 |
| | - **Prompt Mode**: ocr |
| | - **Max Model Length**: 8,192 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 \ |
| | davanstrien/ufo-ColPali \ |
| | <output-dataset> \ |
| | --image-column image \ |
| | --batch-size 16 \ |
| | --prompt-mode ocr \ |
| | --max-model-len 8192 \ |
| | --max-tokens 8192 \ |
| | --gpu-memory-utilization 0.8 |
| | ``` |
| |
|
| | Generated with 🤖 [UV Scripts](https://huggingface.co/uv-scripts) |
| |
|