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PaddleOCR Document Parsing

Free

Extract structured content from PDFs and images with precision.

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Free · Opens the source repo

What PaddleOCR Document Parsing does

PaddleOCR Document Parsing is a powerful tool designed for extracting structured data from various document formats, including PDFs and images. This skill excels in handling complex layouts, making it ideal for documents that contain tables, mathematical formulas, charts, and multi-column formats. By leveraging advanced layout analysis techniques, it ensures that the extracted content maintains the original structure and reading order, which is crucial for accurate data representation.

The skill supports a variety of document types, such as invoices, financial reports, academic papers, and brochures. It can extract not just text but also images and LaTeX-formatted equations, allowing for comprehensive document analysis. Users can specify different processing options to optimize performance based on the characteristics of their documents. For instance, disabling preprocessing can speed up extraction for well-oriented images, while keeping it enabled is beneficial for documents with significant distortion or complex layouts.

The output is provided in a structured format, allowing users to easily access the extracted content in Markdown or JSON. This makes it suitable for integration into various workflows, whether for data analysis, reporting, or further processing in other applications. The skill is particularly useful for developers and data analysts who need to automate the extraction of information from diverse document types, streamlining their workflows and improving efficiency.

Overall, PaddleOCR Document Parsing is a versatile solution for anyone needing to extract structured information from documents accurately and efficiently. Its ability to handle complex layouts and deliver precise outputs makes it a valuable addition to any developer's toolkit.

When to use it

Use this skill when you need to extract structured information from documents with tables, formulas, or complex layouts.

When not to use it

This skill may not be suitable for simple text extraction tasks or documents that do not require layout analysis.

What you can build with it

Extracting Financial Reports

Use the skill to extract tables and charts from financial PDFs, converting them into structured Markdown for analysis.

Processing Academic Papers

Leverage the skill to extract LaTeX formulas and structured content from academic PDFs, facilitating easier citation and reference.

Automating Invoice Processing

Implement the skill to automate the extraction of data from invoices, reducing manual entry and improving accuracy.

How to install PaddleOCR Document Parsing

View source

1. Install with the skills CLI

npx skills add paddlepaddle/paddleocr/paddleocr-doc-parsing --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by paddlepaddle

PaddleOCR Document Parsing

When to Use This Skill

Use this skill for:

  • Documents with tables (invoices, financial reports, spreadsheets)
  • Documents with mathematical formulas (academic papers, scientific documents)
  • Documents with charts and diagrams
  • Multi-column layouts (newspapers, magazines, brochures)
  • Complex document structures requiring layout analysis

Usage

Basic Document Parsing

From URL:

paddleocr api \
  --model_type doc_parsing \
  --file_url "https://example.com/report.pdf"

From local file:

paddleocr api \
  --model_type doc_parsing \
  --file_path "./document.pdf"

Common Options

# With specific model
paddleocr api \
  --model_type doc_parsing \
  --model PP-StructureV3 \
  --file_path "./report.pdf"

# Disable preprocessing (faster, for flat/well-oriented images)
paddleocr api \
  --model_type doc_parsing \
  --file_path "./document.pdf" \
  --use_doc_unwarping False \
  --use_doc_orientation_classify False

# With page ranges
paddleocr api \
  --model_type doc_parsing \
  --file_path "./large.pdf" \
  --page_ranges "1-5,10,15-20"

# Save result and resources
paddleocr api \
  --model_type doc_parsing \
  --file_url "https://..." \
  --output result.json \
  --save_resources ./resources

# Prettify markdown output
paddleocr api \
  --model_type doc_parsing \
  --file_path "./document.pdf" \
  --prettify_markdown True

Output Format

{
  "jobId": "job-xxx",
  "pages": [
    {
      "markdownText": "# Title\n\nContent...",
      "markdownImages": {
        "img1": "https://...",
        "img2": "https://..."
      },
      "outputImages": {
        "layout1": "https://..."
      }
    }
  ]
}

Important Notes

Preprocessing options: For flat, well-oriented images (screenshots, properly scanned documents), you can disable preprocessing for faster results:

paddleocr api --model_type doc_parsing --file_path "./document.pdf" --use_doc_unwarping False --use_doc_orientation_classify False

Keep preprocessing enabled when:

  • The input is a photo of a curved or folded document
  • The document has significant perspective distortion
  • Orientation is uncertain (rotated 90/180/270 degrees)

Display complete results: Always show the full extracted content to users. Do not truncate with "..." unless content exceeds 10,000 characters. When multiple pages are processed, summarize if needed but provide complete results when explicitly requested.

Handle errors gracefully: When the CLI returns an error, inform the user of the specific issue rather than silently failing. Common errors:

  • Authentication: PADDLEOCR_ACCESS_TOKEN invalid or missing
  • Quota: API rate limit exceeded
  • No content detected: Document may be blank or contain no extractable text

CLI Reference

Run paddleocr api --help for all options.

For full documentation, see: PaddleOCR Official Documentation

Frequently asked questions about PaddleOCR Document Parsing

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