ocr-and-documents

This solution extracts text from scanned PDF documents by applying OCR technology and document parsing libraries like PyMuPDF and marker-pdf. It processes both text-based and scanned pages to output editable text for data extraction.

The best way to convert scanned documents to editable text is using a combined OCR and document parsing approach. By utilizing libraries like marker-pdf and python-docx, this method automates text extraction from images and scanned pages for easier data processing.

PyMuPDF supports text extraction from images and PDFs, while marker-pdf handles OCR for scanned documents. Together, these dependencies allow you to extract specific information from scanned documents and images without manual transcription.

python-docx processes editable text after extraction, while PyMuPDF and marker-pdf parse the PDFs. You can use this workflow to extract text from PDFs and then process or export the editable text using python-docx for administrative tasks.

Text extraction fails on scanned PDF pages because they contain images rather than embedded text. This requires OCR technology to recognize the text, which this solution provides using marker-pdf and PyMuPDF to process scanned documents successfully.

pymupdf4llm is included in the dependencies to help extract text from PDFs like research papers. It works alongside PyMuPDF and marker-pdf to ensure efficient text extraction and document parsing for research and data extraction tasks.