OpenViSTAI · Agents · Blockchain · Crypto
Submit a project
Menu
AI Developer Tools & SDKs

LayoutParser

LayoutParser is an Apache-2.0-licensed Python toolkit for document image analysis, combining APIs and deep-learning models for detecting page layouts with data structures for selecting, cropping and visualizing layout regions. Its documented workflows also support OCR processing and loading layout data from JSON, CSV and PDF.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

LayoutParser — OpenViST project profile in AI Developer Tools & SDKs.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use LayoutParser when a Python document-processing workflow needs page-layout detection alongside region manipulation, visualization or OCR-assisted extraction.

Who it is for

  • Python developers building document-image analysis workflows.
  • Teams extracting text or structure from scanned pages and complex documents.
  • Researchers or developers working with layout-detection models.

Documented uses

  • Detect regions and elements in document-page images.
  • Filter and crop selected layout regions, such as a page column.
  • Run OCR on detected regions and structure table-extraction results.
  • Visualize detected layouts and load layout data from JSON, CSV or PDF.
Before you choose

Requirements & limits

The project documents pip installation options and is licensed under Apache-2.0.

  • The base library, layout-model toolkit and OCR toolkit are available as separate documented installation choices.
  • Detectron2-based models require additional installation steps.
  • The documented examples include table OCR and parsing, as well as hierarchical layout analysis for complex documents.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Install the library and select task-specific extras

Set up LayoutParser with the documented optional toolkits for layout models or OCR.

Before you start

  • Python package installation with pip

Steps

  1. Install the base library with the command below.

    Documented command
    pip install layoutparser

  2. For the deep-learning layout model toolkit, install the command below.

    Documented command
    pip install "layoutparser[layoutmodels]"

  3. For the OCR toolkit, install the command below.

    Documented command
    pip install "layoutparser[ocr]"

  4. If using Detectron2-based models, follow the additional steps in the project's installation instructions.

Expected outcome

The base library or selected model/OCR toolkit is installed according to the project's documented package options.

Guide limitations

  • The guide covers installation options only; Detectron2-based models require additional steps.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
15 October 2026
Original website title
Layout-Parser/layout-parser · Official homepage title · retained in its source language
How we review sourcesSuggest a correction