deepdoctection/deepdoctection

Health v2 · maintenance only

Adoption not part of the score

3248 stars · 196 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

deepdoctection is a Python library for Document AI that orchestrates document layout analysis, table recognition, OCR, and document/token classification into configurable pipelines. It supports fine-tuning and inference with models like LayoutLM, LiLT, and Detectron2-based detectors, and integrates OCR backends such as Tesseract, DocTr, and AWS Textract.

Use cases

• extract text and tables from scanned PDFs
• run OCR on document images
• detect document layout and tables
• classify documents with LayoutLM
• fine-tune document understanding models
• parse native PDF text

When to choose

• building document extraction pipelines with layout analysis and OCR
• need table detection and recognition in documents
• want to fine-tune or use LayoutLM-family models
• processing scanned or PDF documents at scale in Python

When to avoid

• need a simple one-line PDF text extractor without ML models
• working outside Python or without GPU/deep learning dependencies
• need a ready-made end-user application rather than a library

Facets

library · maturity active

ocr pdf machine-learning computer-vision nlp image-processing parser artificial-intelligence computer-vision pdf deep-learning python cross-platform document-ai document-layout-analysis table-recognition document-understanding layoutlm detectron2 pdf-parsing natural-language-processing

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