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davanstrien
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dots-ocr-1.5-nls-layout-test

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ocr
document-processing
dots-ocr-1.5
multilingual
markdown
uv-script
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1922-01-01 00:00:00
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https://view.nls.uk/manifest/2437/3296/243732962/manifest.json
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Highland News issue: 599
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Saturday 30/03/1895
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https://view.nls.uk/manifest/2486/4757/248647577/manifest.json
[{"bbox": [68, 189, 421, 258], "category": "Text"}, {"bbox": [122, 267, 366, 301], "category": "Title"}, {"bbox": [68, 307, 421, 406], "category": "Text"}, {"bbox": [175, 401, 317, 416], "category": "Text"}, {"bbox": [125, 416, 366, 431], "category": "Text"}, {"bbox": [71, 444, 415, 478], "category": "Title"}, {"bbox":...
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Document OCR using dots.ocr-1.5

This dataset contains OCR results from images in davanstrien/nls-highland-news-sample using DoTS.ocr-1.5, a 3B multilingual model with SOTA document parsing.

Processing Details

Configuration

  • Image Column: image
  • Output Column: markdown
  • Dataset Split: train
  • Batch Size: 16
  • Prompt Mode: layout-only
  • Max Model Length: 24,000 tokens
  • Max Output Tokens: 24,000
  • GPU Memory Utilization: 90.0%

Model Information

DoTS.ocr-1.5 is a 3B 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
  • Web screen parsing — Webpage layout analysis
  • Scene text spotting — Text detection in natural scenes

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 1.5 script:

uv run https://huggingface.co/datasets/uv-scripts/ocr/raw/main/dots-ocr-1.5.py \
    davanstrien/nls-highland-news-sample \
    <output-dataset> \
    --image-column image \
    --batch-size 16 \
    --prompt-mode layout-only \
    --max-model-len 24000 \
    --max-tokens 24000 \
    --gpu-memory-utilization 0.9

Generated with UV Scripts
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