# 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 format - `data/dotsocr_markdown_dataset_val.json`: Validation data in conversation format - `images/`: Directory containing all referenced images ## Data Format Each sample follows this conversation format: ```json { "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:
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- 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: 1. Analyze document images 2. Extract text content in reading order 3. Apply appropriate markdown formatting 4. 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