PaddleOCR Document Parsing
Skill Verified ActiveUse this skill to extract structured Markdown/JSON from PDFs and document images—tables with cell-level precision, formulas as LaTeX, figures, seals, charts, headers/footers, multi-column layout and correct reading order. Trigger terms: 文档解析, 版面分析, 版面还原, 表格提取, 公式识别, 多栏排版, 扫描件结构化, 发票, 财报, 复杂 PDF, PDF转Markdown, 图表, 阅读顺序; reading order, formula, LaTeX, layout parsing, structure extraction, PP-StructureV3, PaddleOCR-VL.
To accurately extract structured information from complex documents and images, making the content easily usable for LLMs and downstream processing.
Features
- Extract tables with cell-level precision
- Recognize formulas as LaTeX
- Parse multi-column layouts and reading order
- Output structured Markdown or JSON
- Support for PDFs and document images
Use Cases
- Processing invoices and financial reports
- Extracting content from academic papers
- Structuring data from scanned documents
- Analyzing complex document layouts
Non-Goals
- Simple text-only OCR tasks
- Speed-critical OCR on basic images
- Processing screenshots or basic images with clear text
Workflow
- Identify input source (URL or local file)
- Execute document parsing script with appropriate parameters
- Parse the JSON response (checking `ok` status and `error` fields)
- Extract relevant data (text, tables, formulas) from the structured output
- Present results to the user or use for further processing
Prerequisites
- Python 3.9+
- uv package manager
- Internet access for API calls
- PADDLEOCR_DOC_PARSING_API_URL environment variable
- PADDLEOCR_ACCESS_TOKEN environment variable
Installation
npx skills add PaddlePaddle/PaddleOCRRuns the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.
Quality Score
VerifiedTrust Signals
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