andynoodles/omnidoc-ocr-correction-bench

--- dataset_info: features: - name: prompt dtype: string - name: image dtype: image num_examples: 1355 license: cc-by-4.0 task_categories: - image-to-text tags: - ocr - document-understanding - markdown - paddleocr - omnidocbench size_categories: - 1K<n<10K --- # OmniDoc OCR Correction Bench A benchmark dataset for evaluating VLMs on OCR error correction and document-to-markdown formatting. ## Overview Each sample pairs a document image from [OmniDocBench v1.5](https://github.com/opendatalab/OmniDocBench) with a prompt containing PaddleOCR-extracted markdown text. The task is to correct OCR errors and restore proper formatting using the source image as reference. ## Dataset Structure | Field | Type | Description | |-------|------|-------------| | `prompt` | `string` | System prompt with OCR-extracted markdown text to correct | | `image` | `image` | Source document image | ## Sources - **Images**: [OmniDocBench v1.5](https://github.com/opendatalab/OmniDocBench) — covers books, papers, exams, newspapers, magazines, PPTs, notes, textbooks, and financial reports - **OCR extraction**: PaddleOCR with markdown output - **Prompts**: Custom correction prompts instructing the model to fix OCR errors while preserving document structure