deepdoctection

Why we included this project

Building a document extraction system usually means glueing together a layout detector, an OCR engine, and a text model by hand. deepdoctection handles that assembly: it's a Python framework that chains layout analysis, table recognition, OCR, and document or token classification into one reusable pipeline, with traceability back to the original page. Teams working with scanned PDFs, invoices, forms, or research papers can run pretrained Detectron2 and LayoutLM-family models out of the box, swap in Tesseract, DocTR, or AWS Textract for text recognition, and fine-tune the detection models on their own document sets. The v1.0 refactor is PyTorch-only and splits the code into small sub-packages, which makes the library easier to understand and extend. If your job is turning messy document images into clean, structured data, this saves you from building that stack from scratch.