What is the project about?

OCRmyPDF is a command-line tool that adds an Optical Character Recognition (OCR) text layer to scanned PDF files, making them searchable and copy-pasteable.

What problem does it solve?

It solves the problem of scanned PDFs being images only, and therefore not searchable or allowing text selection. It converts image-only PDFs into text-searchable PDFs, preserving the original image quality and layout as much as possible. It addresses limitations of other OCR tools, such as misplaced text, poor handling of non-English characters, resolution changes, large file sizes, and lack of PDF/A support.

What are the features of the project?

• Generates searchable PDF/A files from scanned PDFs.
• Accurately places OCR text below the image.
• Preserves the original image resolution.
• Inserts OCR information losslessly when possible.
• Optimizes PDF images, often reducing file size.
• Optionally deskews and cleans images before OCR.
• Validates input and output files.
• Uses multi-core processing for speed.
• Supports over 100 languages via the Tesseract OCR engine.
• Privacy-focused: processes files locally.
• Scales to handle large files with thousands of pages.

What are the technologies used in the project?

• Python: The core programming language.
• Tesseract OCR: The OCR engine used for text recognition.
• Ghostscript: Used for PDF processing and manipulation.
• jbig2enc (optional): For JBIG2 image encoding.
• unpaper (optional): For image cleaning and deskewing.
• pikepdf, qpdf: For PDF manipulation.

What are the benefits of the project?

• Makes scanned documents searchable.
• Enables text selection and copying from scanned documents.
• Creates archival-quality PDF/A files.
• Improves accessibility of scanned documents.
• Often reduces file size compared to the original scanned PDF.
• Automates the OCR process through a command-line interface.
• Open source and free to use.

What are the use cases of the project?

• Digitizing paper documents for archiving and searching.
• Making scanned lecture notes or books searchable.
• Converting scanned forms into editable documents.
• Creating accessible PDFs from scanned materials.
• Batch processing of scanned documents.
• Integrating OCR into document management workflows.