LayoutParser

LayoutParser is an open-source document AI and document understanding framework designed for analyzing, extracting, and processing information from PDFs, scanned documents, forms, invoices, reports, books, and images. Built on modern deep learning frameworks such as PyTorch and Detectron2, LayoutParser combines document layout analysis, optical character recognition (OCR), and computer vision technologies to transform unstructured documents into structured, searchable, and machine-readable data.

Features of LayoutParser:

• Detects document elements such as text blocks, tables, titles, figures, lists, and forms using deep learning models.
• Integrates with OCR engines including Tesseract for automated text extraction and document digitization.
• Provides pretrained document layout models for research, enterprise, and production workloads.
• Supports PDF, image, scanned document, invoice, receipt, and form processing workflows.
• Enables intelligent document processing (IDP), information extraction, and document automation.
• Integrates seamlessly with Python, PyTorch, Detectron2, machine learning pipelines, and AI applications.
• Supports custom model development and training for specialized document understanding tasks.

LayoutParser usage:

$ sudo su
$ cd /opt/layoutparser

# Activate virtual environment:
$ source venv/bin/activate

# Verify installation:
$ pip show layoutparser
$ python3 -c "import layoutparser as lp; print(lp.__version__)"

# Verify OCR support:
$ tesseract --version

# Verify PyTorch:
$ python3 -c "import torch; print(torch.__version__)"

# Test LayoutParser:
$ python3 -c "import layoutparser as lp; print('LayoutParser Ready')"

# Verify Detectron2 (if installed):
$ python3 -c "import detectron2; print('Detectron2 OK')"

Disclaimer: LayoutParser is provided under the applicable open-source licensing terms of its respective contributors and dependencies. Users are responsible for managing OCR engines, document datasets, AI models, storage, security configurations, and ensuring compliance with organizational, legal, privacy, and regulatory requirements when processing, analyzing, or extracting information from documents and images.