Layout-Parser/layout-parser
A Unified Toolkit for Deep Learning Based Document Image Analysis
Provides pre-trained deep learning models (EfficientDet, Detectron2-based) for layout detection via unified APIs, with specialized data structures for spatial filtering and region-based operations on document elements. Integrates OCR backends like Tesseract and supports loading/serializing layouts from JSON, CSV, and PDF formats. Designed as an open platform for community contribution of detection models and document analysis pipelines.
5,678 stars. No commits in the last 6 months.
Stars
5,678
Forks
525
Language
Python
License
Apache-2.0
Category
Last pushed
Aug 15, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Layout-Parser/layout-parser"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related frameworks
Psarpei/Multi-Type-TD-TSR
Extracting Tables from Document Images using a Multi-stage Pipeline for Table Detection and...
ses4255/Versatile-OCR-Program
Multi-modal OCR pipeline optimized for ML training (text, figure, math, tables, diagrams)
Sudhanshu1304/table-transformer
🔍 Table Extraction Tool: A powerful open-source solution combining OCR and computer vision for...
asagar60/TableNet-pytorch
Pytorch Implementation of TableNet
JG1VPP/MuTabNet
ICDAR 2024 Table OCR Model