Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
No file changes detected in this version. - Version and metadata remain unchanged. - No updates or modifications to functionality or documentation.
What This Skill Does
OpenOCR extracts text from images, scanned documents, and PDFs using a lightweight OCR engine. It supports text detection, recognition, formula and table recognition via a 0.1B parameter VLM, and full document parsing with layout analysis. Runs on CPU by default with optional GPU acceleration.
Runs entirely locally with a 0.1B parameter model on CPU, avoiding API costs and data privacy concerns of cloud OCR services.
When to use it
- Extracting text from scanned invoices or receipts
- Converting scanned academic papers to searchable Markdown
- Recognizing mathematical formulas from textbook photos
- Pulling structured data out of table screenshots
- Batch processing a folder of document images to plain text
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Parse this scanned PDF and convert it to Markdown
- 1Initialize OpenOCR with the doc task and layout detection enabled
- 2Load the PDF and convert pages to images internally
- 3Run layout analysis to identify text blocks, formulas, and tables
- 4Recognize content in each block using the UniRec VLM
- 5Save the structured output as a Markdown file per page
Markdown files with preserved document structure including headings, paragraphs, recognized formulas, and tables