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SwiftOCR is a native Swift library designed for extracting text and alphanumeric characters from images. It functions as a neural network text recognizer that identifies characters and strings from visual data. The library includes a custom OCR model trainer and tools for custom font recognition. These capabilities allow for the generation of specialized neural networks tailored to specific fonts and character sets to improve recognition accuracy. The system utilizes connected-component labeling to identify individual character regions and employs image processing to convert short alphanumer
This project is a PyTorch-based framework and toolkit for scene text recognition. It provides a deep learning pipeline for extracting characters and words from images of natural environments, covering the full process from training data preparation to model validation. The framework functions as a standardized benchmark for measuring the accuracy and inference speed of text recognition models. It includes tools for calculating recognition accuracy and measuring GPU processing time per image to evaluate model performance across consistent datasets. The system incorporates visual and sequentia
Tesseract is an optical character recognition engine and tool designed to convert printed or handwritten text from images into machine-readable digital text. It functions as a multilingual text extractor and a document digitization pipeline that transforms scanned images into structured digital formats. The project includes a framework for training custom scripts and language-specific models, allowing the engine to recognize new languages or unique fonts through custom training data. Its capabilities cover automated text extraction, digital archive digitization, and the export of recognized
Synaptic is a JavaScript neural network library used for building, training, and executing neural networks in Node.js and the browser. It provides a framework for constructing architecture-free neural network topologies, a backpropagation training engine for weight optimization, and a toolkit for implementing recurrent neural network frameworks. The library enables the design of custom first or second order network architectures without predefined constraints. It supports a variety of specialized models, including Long Short-Term Memory networks, Hopfield networks, Liquid State Machines, and
SwiftOCR is a Swift library for performing optical character recognition and text extraction from images. It functions as a neural network text recognizer and OCR model trainer designed for iOS and macOS applications.
The main features of nmac427/swiftocr are: Alphanumeric Code Recognition, Custom Font Training, OCR Model Customizers, Model Training Workflows, Neural Networks, Text Recognizers, OCR Model Training, Optical Character Recognition.
Open-source alternatives to nmac427/swiftocr include: garnele007/swiftocr — SwiftOCR is a native Swift library designed for extracting text and alphanumeric characters from images. It functions… clovaai/deep-text-recognition-benchmark — This project is a PyTorch-based framework and toolkit for scene text recognition. It provides a deep learning pipeline… ub-mannheim/tesseract — Tesseract is an optical character recognition engine and tool designed to convert printed or handwritten text from… jaidedai/easyocr — EasyOCR is a deep learning-based computer vision library designed to perform optical character recognition on images… brainjs/brain.js — Brain.js is a JavaScript neural network library for building, training, and running machine learning models in the… cazala/synaptic — Synaptic is a JavaScript neural network library used for building, training, and executing neural networks in Node.js…