rednote-hilab/dots.ocr

Features

• Document Analysis Tools - Provides a comprehensive tool for detecting bounding boxes and layout categories to structure documents as JSON.
• Bounding Box Detection - Provides bounding box detection to locate page elements and distinguish body text from headers and footers.
• Multilingual OCR Systems - Extracts digital text and structured layout data from images and PDFs across various human scripts.
• Document Layout Analysis - Identifies bounding boxes and categories for layout elements within images and PDF files.
• Multilingual Text Recognition - Implements a unified recognition engine to process diverse character sets and writing systems from images into digital text.
• Scene Text Recognition - Locates and extracts digital text from natural images and complex environmental backgrounds.
• OCR-Based Extraction - Extracts digital text and structured layout data from images and PDFs across various human scripts.
• Scene Text Detection Systems - Finds and digitizes text embedded within natural scene images and web screenshots.
• Document Digitization Tools - Converts images and PDFs containing various human scripts into digital text while preserving document structure.
• Automated Generation - Transforms extracted text and structural layout from documents and web screenshots into formatted Markdown files.
• Document Layout Analyzers - Identifies bounding boxes and categories of layout elements to produce structured JSON representations of documents.
• Markdown Converters - Transforms extracted text and structural layout from images and documents into formatted Markdown files.
• Visual-to-Markdown Pipelines - Transforms scanned documents and web screenshots into formatted Markdown files for editing and archival.
• Layout-Aware Extraction - Maps spatial relationships between text elements and document structures during the extraction process.
• Layout-Preserving Export - Generates formatted Markdown files from extracted document text while excluding page headers and footers.
• Raster-to-Vector Conversions - Transforms rasterized charts, diagrams, and chemical formulas into scalable vector graphics.
• Model Serving Engines - Implements high-performance model serving engines to provide scalable text extraction API endpoints.
• Model Serving Servers - Serves machine learning models as scalable API endpoints using high-performance inference servers.
• Text Detection Models - Locates and digitizes text embedded within natural scene images and complex backgrounds.
• OCR Accuracy Evaluators - Measures text and table extraction accuracy against ground truth images to refine OCR performance.
• Visual Layout Parsing - Extracts structured text and layout information specifically from screenshots of web pages.
• Vector Graphics Export - Converts technical graphics like charts and chemical formulas from images into scalable vector graphics.
• Raster-to-SVG Transformers - Converts charts, diagrams, and chemical formulas from raster images into scalable vector graphics code.

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