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dots-ocr-playbills

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204486095
205328545
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204486095
205328558
SOME BRITISH FASHIONS Gir.H.
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204486095
205328571
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204486095
205328584
c 1 *
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204486095
205328597
BRITAIN AN OFFICIAL HANDBOOK
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204486095
205328610
I
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204486095
205328623
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204486095
205328636
‘Piping aboard’ ceremony on H.M.S. Lion
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204486095
205328649
BRITAIN AN OFFICIAL HANDBOOK PREPARED BY THE CENTRAL OFFICE OF INFORMATION, LONDON 1 967 EDITION London: Her Majesty’s Stationery Office: 1967
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204486095
205328662
© Crown copyright 19^7 Printed and published by HER MAJESTY’S STATIONERY OFFICE To be purchased from 49 High Holborn, London w.c.i 423 Oxford Street, London w.i 13A Castle Street, Edinburgh 2 109 St. Mary Street, Cardiff Brazennose Street, Manchester 2 50 Fairfax Street, Bristol 1 35 Smallbrook, Ringway, Birmingham 5 80 Chichester Street, Belfast 1 or through any bookseller Obtainable in the United States of America from British Information Services, 845 Third Avenue, New York, N.Y. 10022 v, C w X % 1967 '.V QV Printed in England
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[{"bbox": [105, 64, 226, 79], "category": "Page-header", "text": "© Crown copyright 1967"}, {"bbox": [105, 141, 332, 169], "category": "Text", "text": "Printed and published by\nHER MAJESTY'S STATIONERY OFFICE"}, {"bbox": [105, 182, 217, 196], "category": "Text", "text": "To be purchased from"}, {"bbox": [105, 195, 268, 209], "category": "Text", "text": "49 High Holborn, London W.C.1"}, {"bbox": [105, 208, 264, 223], "category": "Text", "text": "423 Oxford Street, London W.1"}, {"bbox": [106, 222, 261, 237], "category": "Text", "text": "13A Castle Street, Edinburgh 2"}, {"bbox": [106, 236, 248, 250], "category": "Text", "text": "109 St. Mary Street, Cardiff"}, {"bbox": [106, 248, 270, 262], "category": "Text", "text": "Brazennose Street, Manchester 2"}, {"bbox": [106, 261, 239, 276], "category": "Text", "text": "50 Fairfax Street, Bristol 1"}, {"bbox": [106, 274, 306, 289], "category": "Text", "text": "35 Smallbrook, Ringway, Birmingham 5"}, {"bbox": [106, 288, 258, 302], "category": "Text", "text": "80 Chichester Street, Belfast 1"}, {"bbox": [106, 301, 235, 315], "category": "Text", "text": "or through any bookseller"}, {"bbox": [106, 334, 324, 378], "category": "Text", "text": "Obtainable in the United States of America\nfrom British Information Services,\n845 Third Avenue, New York, N.Y. 10022"}, {"bbox": [235, 490, 312, 568], "category": "Picture"}, {"bbox": [114, 859, 207, 872], "category": "Page-footer", "text": "Printed in England"}]
[{"model_id": "rednote-hilab/dots.ocr", "column_name": "markdown", "timestamp": "2025-10-08T16:53:58.014483", "prompt_mode": "layout-all"}]

Document OCR using dots.ocr

This dataset contains OCR results from images in NationalLibraryOfScotland/Britain-and-UK-Handbooks-Dataset using DoTS.ocr, a compact 1.7B multilingual model.

Processing Details

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 

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 DoTS OCR script:

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

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