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dotsocr_markdown_dataset
Dataset Description
This dataset contains training data for DotsOCR to convert document images directly to markdown format.
Training Objective
The model learns to:
- Convert document images to clean markdown format
- Preserve document structure and hierarchy
- Extract all text content accurately
- Use appropriate markdown formatting for different content types
Dataset Structure
- Training samples: 798
- Validation samples: 200
- Total samples: 998
Files
data/dotsocr_markdown_dataset_train.json: Training data in conversation formatdata/dotsocr_markdown_dataset_val.json: Validation data in conversation formatimages/: Directory containing all referenced images
Data Format
Each sample follows this conversation format:
{
"conversations": [
{
"from": "user",
"value": "<|imgpad|>images/example.jpg<|/imgpad|>\nPlease convert this document image to markdown format..."
},
{
"from": "assistant",
"value": "# Document Title\n\n## Section Header\n\nContent text here..."
}
]
}
Training Prompt
The training uses this prompt to teach the model markdown conversion:
Convert this document image to markdown format. Extract and structure the text content as follows:
- Headers and titles as plain text on separate lines
- Body text as plain text paragraphs
- Lists using * for bullet points
- Tables using HTML table format: <table><thead><tr><th>...</th></tr></thead><tbody><tr><td>...</td></tr></tbody></table>
- Preserve the original reading order and document structure
- Extract all visible text exactly as it appears
Output the content in markdown format with HTML tables for tabular data.
Usage
This dataset is designed to train DotsOCR models for direct image-to-markdown conversion tasks. The model learns to:
- Analyze document images
- Extract text content in reading order
- Apply appropriate markdown formatting
- Output clean, structured markdown
Citation
Based on the DotsOCR model by rednote-hilab: https://github.com/rednote-hilab/dots.ocr
Generated on: 2025-09-26 17:35:35
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