5 مستودعات
Tools for executing optical character recognition tasks via terminal commands.
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Tesseract is a neural network-based optical character recognition engine designed to convert scanned images and digital documents into machine-readable, searchable text. It functions as both a command-line utility for automating large-scale digitization workflows and a cross-platform library that can be embedded into desktop, mobile, or server-side applications. By utilizing long short-term memory networks, the engine provides robust text extraction across more than one hundred languages and dozens of scripts. The project distinguishes itself through a sophisticated document layout analysis f
Executes character recognition tasks directly from the terminal by specifying input images, language models, and output requirements.
chineseocr_lite is a lightweight Chinese optical character recognition engine designed to detect text regions, analyze orientation, and convert Chinese characters from images into digital text. It supports both horizontal and vertical reading layouts and can be deployed as a web service for image uploads and result visualization. The system utilizes a multi-backend inference framework that supports ncnn, mnn, and tnn, allowing it to run across diverse hardware and platforms. It is specifically engineered for lightweight deployment on mobile and desktop environments through the use of small mo
Provides a command line interface for performing OCR tasks and exporting structured results.
Kreuzberg is a document extraction engine that converts PDFs, Office files, images, and over 90 other formats into clean, structured text and metadata. It is built around a compiled Rust core that can be used as a native library, a command-line tool, a REST API server, or a WebAssembly module for browser-based processing. The system is designed to run entirely on self-hosted infrastructure, with no data leaving the user's environment. What distinguishes Kreuzberg is its breadth of integration surfaces and its pipeline architecture. It exposes extraction capabilities through native bindings fo
Performs OCR extraction on files directly from the terminal with configurable backends.
RapidOCR is an offline deep-learning OCR engine that detects and recognizes text in images using ONNX Runtime, operating entirely without an internet connection. It provides a unified inference pipeline that runs across multiple platforms including Windows, Linux, macOS, Android, and Raspberry Pi, with programming language bindings for Python, C++, Java, and C#. The engine separates text detection and recognition into independent modules that can be swapped or fine-tuned individually, and abstracts the inference backend behind a unified interface allowing seamless switching between ONNX Runti
Provides a command-line tool for extracting text from images and URLs with bounding boxes and confidence scores.
هذا المشروع عبارة عن محرك للتعرف الضوئي على الحروف (OCR) يعتمد على الطرفية، ويستخدم نماذج الشبكات العصبية لاستخراج النصوص وبيانات التخطيط المكاني من الصور. يعمل كأداة سطر أوامر لمعالجة النصوص المؤتمتة وكمكتبة لدمج التعرف المدعوم بالتعلم الآلي في سير العمل الأوسع. يتميز المحرك بخط معالجة معياري يدعم تحميل النماذج المخصصة وتهيئة الأوزان المعينة في الذاكرة (memory-mapped) للتنفيذ الفعال. وهو يحافظ على بنية المستند من خلال تتبع إحداثيات هندسية دقيقة لكل عنصر نصي مكتشف، ويسمح بتحسين المخرجات من خلال قواعد التحقق على مستوى الحرف. يتضمن النظام أدوات شاملة لاستيعاب الصور، بما في ذلك الالتقاط المباشر من حافظة النظام ومحتوى المتصفح. كما يوفر قدرات تشخيصية من خلال إنشاء تراكبات بصرية وقطع أثرية للمعالجة الوسيطة للتحقق من دقة التعرف واستكشاف أخطاء أداء خط المعالجة وإصلاحها. يتم توزيع البرنامج كملف ثنائي ثابت (static binary) لضمان إمكانية النقل عبر البيئات دون الحاجة إلى تبعيات خارجية.
Provides a terminal-based utility for processing images and clipboard data into structured text with spatial coordinates.