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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
EasyOCR is a deep learning-based computer vision library designed to perform optical character recognition on images and video frames. It functions as a comprehensive pipeline that automates the transformation of visual text into machine-readable strings, enabling the digitization of physical documents, forms, and receipts into searchable data. The engine distinguishes itself through a multi-stage processing workflow that combines convolutional neural networks for spatial feature extraction with sequence-based decoding mechanisms. This architecture allows the system to identify and interpret
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
Paperless is a self-hosted document management system designed to digitize, index, and archive paper documents. It functions as an optical character recognition system that converts scanned images and PDFs into a searchable digital library, providing a web-based interface for querying and retrieving documents from a database. The system features an automated file ingestion pipeline that monitors specific directories and email inboxes to process and import documents without manual uploading. To maintain a private archive, it includes on-disk encryption for sensitive files and the ability to or
Deep OCR is a deep learning framework designed for the recognition of Chinese characters within images. It functions as an optical character recognition library that converts scanned documents or image files into digital text, providing an alternative to traditional template matching methods.
The main features of jinpengli/deep_ocr are: Chinese OCR Tools, Chinese Text Recognition, Image Recognition Engines, Optical Character Recognition, OCR, Connectionist Temporal Classification, Convolutional Neural Networks, Font Training Pipelines.
Projects with overlapping indexed features include: daybreak-u/chineseocr_lite — chineseocr_lite is a lightweight Chinese optical character recognition engine designed to detect text regions, analyze… jaidedai/easyocr — EasyOCR is a deep learning-based computer vision library designed to perform optical character recognition on images… clovaai/deep-text-recognition-benchmark — This project is a PyTorch-based framework and toolkit for scene text recognition. It provides a deep learning pipeline… the-paperless-project/paperless — Paperless is a self-hosted document management system designed to digitize, index, and archive paper documents. It… aladdinpersson/machine-learning-collection — This project is a machine learning educational repository providing a collection of implementations and guides for… open-mmlab/mmocr — mmocr is a PyTorch-based optical character recognition framework designed for training and deploying text detection,…