Awesome GitHub RepositoriesText Orientation Detection

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

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

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

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

PaddleX is a PaddlePaddle-based framework for building, deploying, and fine-tuning AI model pipelines, with pre-built support for computer vision, OCR, document analysis, and time series tasks. It offers a toolkit of ready-to-use pipelines for image classification, object detection, segmentation, and pose estimation, alongside an end-to-end OCR document analysis pipeline that extracts text, tables, formulas, and layout information. The platform also includes a dedicated time series forecasting pipeline for analyzing historical data to detect anomalies, classify patterns, and predict future val

chineseocr is an end-to-end deep learning pipeline for detecting and recognizing Chinese and English text in images. The project combines text region detection using YOLOv3 with sequence-based recognition via Convolutional Recurrent Neural Networks (CRNN) and dense OCR models, forming a complete optical character recognition workflow. The pipeline includes orientation detection to handle text rotated at 0, 90, 180, or 270 degrees before recognition, and supports structured field extraction from identity cards and train tickets. A multi-framework model converter enables trained models to be co