Layout-Parser

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LayoutParser is an AI Agents & Automation tool that provides a unified toolkit for deep learning-based document image analysis. It offers a rich repository of deep learning models and APIs to streamline DIA tasks.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is layout-parser?

LayoutParser is a comprehensive toolkit designed to streamline Deep Learning Based Document Image Analysis (DIA) tasks. It offers a rich repository of deep learning models for layout detection, along with unified APIs for easy integration and use. The toolkit includes carefully designed layout data structures optimized for DIA, enabling tasks like selecting specific layout elements or performing OCR on detected regions. LayoutParser also provides flexible APIs for visualizing detected layouts and supports loading layout data from various formats including JSON, CSV, and PDFs. It functions as an open platform, encouraging the sharing of layout detection models and DIA pipelines within the community, making it a versatile resource for researchers and developers in the field.

Best used for

Ideal for developers and data scientists who need to perform deep learning-based document image analysis, detect layouts, and extract information from complex documents. Especially valuable for researchers and practitioners working with large volumes of scanned or digital documents requiring automated processing and data extraction.

Common actions

analyze document images

detect document layouts

perform OCR

extract structured data

process document hierarchies

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Capabilities

Key features

Deep learning layout detection
Unified APIs
Layout data structures
OCR integration
Layout visualization
Load JSON/CSV/PDF layouts

Target Audience

developerdata scientist

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What kind of deep learning models does LayoutParser support?

LayoutParser provides a rich repository of deep learning models for layout detection, including those based on architectures like EfficientDet and Detectron2. It offers unified APIs to easily integrate and utilize these models for various document image analysis tasks.

Can LayoutParser perform OCR on detected regions?

Yes, LayoutParser integrates with OCR agents like Tesseract. You can detect layout regions, crop the image segments corresponding to those regions, and then use the OCR agent to extract text from each segment, streamlining the data extraction process.

How can I install LayoutParser and its dependencies?

LayoutParser can be installed via pip. You can install the base library with `pip install layoutparser`, and then add optional dependencies for layout models (`layoutparser[layoutmodels]`) or OCR (`layoutparser[ocr]`) as needed for your specific project requirements.

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Also listed in

This tool also appears in

Productivity & Business › Document Management Data & Analytics › Web Scraping & Extraction

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