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Layout-Parser avatar

Layout-Parser/layout-parser

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Layout Parser

Layout-parser ist ein Deep-Learning-Dokument-Layout-Parser und ein Framework zur Bildanalyse. Es bietet ein Toolkit zum Extrahieren struktureller Informationen und Layout-Muster aus gescannten Dokumenten und digitalen Bildern und transformiert diese in programmatische Datenstrukturen für die automatisierte Analyse.

Das Framework integriert Layout-Erkennung mit optischer Zeichenerkennung (OCR), um tabellarische Regionen in maschinenlesbare Daten umzuwandeln. Es nutzt neuronale Netzwerke, um strukturelle Elemente innerhalb von Dokumentbildern zu identifizieren und zu klassifizieren, ohne sich auf manuelle regelbasierte Systeme zu verlassen.

Das System deckt ein breites Spektrum an Dokumentanalysefunktionen ab, einschließlich Dokumentstruktur-Parsing, automatisierter Tabellenextraktion und hierarchischer Layout-Repräsentation. Es enthält zudem Visualisierungstools, um erkannte Elemente und Hierarchien über Originalbildern zur Ergebnisverifizierung darzustellen.

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Features

  • Document Layout Analysis - Provides deep learning tools to identify complex structures and layout elements from document images.
  • Layout Parsing Toolkits - Provides a deep learning toolkit to detect and analyze structural elements within document images.
  • Document Analysis Models - Applies neural networks to detect and classify document components without relying on manual rules.
  • Document Structure Analysis - Extracts layout and text from images into specialized programmatic data structures for analysis.
  • Hierarchical Representations - Organizes detected document elements into a parent-child tree structure to preserve logical information flow.
  • Tabular Grid Mapping - Combines visual region detection with OCR to map textual content into structured tabular grids.
  • Document Region Detectors - Uses deep learning neural networks to identify and classify structural regions within document images.
  • Table Structure Reconstructions - Transforms tabular regions into machine-readable formats by reconstructing logical grids from visual elements.
  • Visual Structural Elements - Locates and identifies specific structural elements within document images using deep learning models.
  • Document Extraction Tools - Offers a library for parsing document images into programmatic data structures for downstream analysis.
  • Tabular Data Extraction - Converts tabular data from document images into machine-readable formats using layout detection and OCR.
  • Pixel Coordinate Mappings - Maps neural network bounding box outputs to normalized pixel coordinates for consistent document analysis.
  • Bounding Box Visualizers - Renders detection masks and bounding boxes over original images for manual verification of parsing accuracy.
  • OCR Layout Integration Pipelines - Combines layout detection with OCR in a pipeline to convert tabular regions into machine-readable data.
  • Parsing Verification Overlays - Renders detected layout elements and hierarchies visually to verify automated document parsing accuracy.
  • Layout Visualization Tools - Renders detected document elements and hierarchies visually to verify automated parsing accuracy.
  • Unified Model Wrappers - Standardizes different deep learning backends under a single API to allow swapping detection models seamlessly.
  • PDF Processing Tools - Deep learning-based tool for document layout analysis.
5,749 Stars·536 Forks·Python·Apache-2.0·5 Aufrufe

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Frequently asked questions

What does layout-parser/layout-parser do?

Layout-parser ist ein Deep-Learning-Dokument-Layout-Parser und ein Framework zur Bildanalyse. Es bietet ein Toolkit zum Extrahieren struktureller Informationen und Layout-Muster aus gescannten Dokumenten und digitalen Bildern und transformiert diese in programmatische Datenstrukturen für die automatisierte Analyse.

What are the main features of layout-parser/layout-parser?

The main features of layout-parser/layout-parser are: Document Layout Analysis, Layout Parsing Toolkits, Document Analysis Models, Document Structure Analysis, Hierarchical Representations, Tabular Grid Mapping, Document Region Detectors, Table Structure Reconstructions.

What are some open-source alternatives to layout-parser/layout-parser?

Open-source alternatives to layout-parser/layout-parser include: kreuzberg-dev/kreuzberg — Kreuzberg is a document extraction engine that converts PDFs, Office files, images, and over 90 other formats into… pymupdf/pymupdf — PyMuPDF is a comprehensive PDF manipulation library and document analysis tool. It serves as a text extraction tool,… grobidorg/grobid — Grobid is a machine learning system designed to transform academic and scientific PDF publications into structured… oomol-lab/pdf-craft — pdf-craft is an OCR-based document parser and structure extractor designed to convert PDF files into structured data,… funstory-ai/babeldoc — BabelDOC is a technical document translation system designed to translate PDF files while preserving their original… bytedance/dolphin — Dolphin is a multimodal layout analyzer and image-to-structure converter that transforms photographed or digital…