Build OCR and layout-analysis preprocessing pipelines with deepd

Build OCR and layout-analysis preprocessing pipelines with deepdoctection

Use deepdoctection when an agent workflow needs a local Python pipeline for document layout analysis, OCR, table recognition, and page-level extraction before LLM ingestion.

Prerequisites

Python environment; deepdoctection package; selected OCR/layout/model dependencies; local PDFs or scanned document images

Installation

Use the upstream install or setup path that matches your environment:

• uv pip install timm # needed for the default setup
• uv pip install transformers
• uv pip install python-doctr
• uv pip install deepdoctection

Requirements and caveats from upstream:

• deepdoctection is a Python library that orchestrates Scan and PDF document layout analysis, OCR and document
• python
• Python >= 3.10

Basic usage or getting-started notes:

• and token classification. Build and run a pipeline for your document extraction tasks, develop your own document

• The following example shows how to use the built-in analyzer to decompose a PDF document into its layout structures.

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• Source: https://github.com/deepdoctection/deepdoctection

• Extracted from upstream docs: https://raw.githubusercontent.com/deepdoctection/deepdoctection/HEAD/README.md

Documentation

• https://deepdoctection.readthedocs.io/

Source

• Agent Skill Exchange