Pytesseract is a Python library that wraps Google's Tesseract OCR engine to extract text from images. It provides a straightforward interface for optical character recognition, supporting multiple languages and a variety of output formats.
Principalele funcționalități ale madmaze/pytesseract sunt: Python Library Wrappers, Multi-Language OCR Recognizers, Multi-Language Recognition Models, Custom OCR Engine Configurations, Optical Character Recognitions, Character Bounding Box Retrievers, Script and Orientation Detectors, Structured OCR Outputs.
Alternativele open-source pentru madmaze/pytesseract includ: tesseract-ocr/tessdata — This repository provides the pre-trained neural network and legacy data files used by Tesseract to recognize and… rapidai/rapidocr — RapidOCR is an offline deep-learning OCR engine that detects and recognizes text in images using ONNX Runtime,… tesseract-ocr/tesseract — Tesseract is a neural network-based optical character recognition engine designed to convert scanned images and… erikbern/ann-benchmarks — ann-benchmarks is a standardized benchmarking suite for evaluating approximate nearest neighbor (ANN) search… ta-lib/ta-lib-python — This project is a Python wrapper for the TA-Lib library, providing a technical analysis library for computing moving… dicklesworthstone/llm_aided_ocr — This project is a document digitization utility that combines traditional optical character recognition with language…
This repository provides the pre-trained neural network and legacy data files used by Tesseract to recognize and extract printed text from images. It serves as a multilingual training data repository and a collection of Long Short-Term Memory models designed for high-accuracy optical character recognition across various global scripts and languages. The data includes specialized models for analyzing image layouts to determine text rotation and script direction. It provides the necessary language-specific datasets and linguistic patterns required to enable Tesseract OCR engines to function. T
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
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
This project is a Python wrapper for the TA-Lib library, providing a technical analysis library for computing moving averages, momentum, and volatility metrics for financial time series analysis. It serves as a financial indicator calculator that processes price and volume arrays to generate technical signals and pattern recognition. The library includes an incremental data processor capable of computing the most recent technical indicator values as new streaming market data arrives. This allows for real-time price monitoring and the processing of streaming data without recalculating entire d