Layout-Parser/layout-parser

Health v2 · maintenance only

Adoption not part of the score

5774 stars · 532 forks observed · 2026-08-28

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

LayoutParser is a Python toolkit for deep learning based document image analysis, offering unified APIs for layout detection models, layout data structures, OCR integration, and visualization. It includes a model zoo of pre-trained layout detection models loadable in a few lines of code.

Use cases

• detect text blocks and layout regions in scanned documents
• extract document structure from pdf page images
• run ocr on detected layout regions
• train custom document layout detection models
• visualize bounding boxes of document elements
• parse tables and figures from research paper images

When to choose

• you need deep-learning-based document layout analysis in Python
• you want a unified API over multiple pre-trained layout detection models
• you need to combine layout detection with OCR pipelines

When to avoid

• you only need simple text extraction from digital PDFs without layout models
• you need a maintained project with frequent updates
• you work outside Python or need GPU-free lightweight inference

Facets

library · maturity maintenance

computer-vision ocr image-processing machine-learning deep-learning pdf computer-vision machine-learning python cross-platform layout-detection document-image-analysis detectron2 object-detection pretrained-models document-parsing document-layout-analysis natural-language-processing

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