ocr-and-documents

To extract text from scanned PDFs, this Skill uses marker-pdf for OCR-based extraction, converting non-searchable content into editable, searchable text. It handles layout-aware results for research and archival workflows.

The best way to convert non-searchable PDFs into editable text is using pymupdf for text-based PDFs or marker-pdf for OCR-heavy documents, ensuring layout-aware results for reliable data collection.

Yes, remote URL extraction for PDF documents is supported via the web_extract function, allowing you to pull and process non-searchable content directly from online sources into editable text.

Yes, you can use this to process large archives of PDFs for research. It converts content into searchable formats for quick analysis, making it ideal for archival and data-collection workflows.

Yes, you need the pymupdf and marker-pdf Python libraries to extract text from local PDFs. PyMuPDF handles text-based PDFs while marker-pdf manages OCR-heavy and scanned document extraction.

Use marker-pdf instead of pymupdf when dealing with OCR-heavy or scanned documents that lack embedded text. PyMuPDF is suitable for text-based PDFs, while marker-pdf recovers text from images using layout-aware parsing.