awesome-repositories.com
Blog
MCP
awesome-repositories.com

Discover the best open-source repositories with AI-powered search.

ExploreCurated searchesOpen-source alternativesSelf-hosted softwareBlogSitemap
ProjectMCP serverAboutHow we rankPress
LegalPrivacyTerms
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
hiroi-sora avatar

hiroi-sora/Umi-OCR

0
View on GitHub↗
45,273 stars·4,454 forks·Python·MIT·45 views

Umi OCR

Umi-OCR is an optical character recognition engine designed to convert visual text from images and documents into machine-readable character data. It functions as a local-first toolkit, processing all visual data directly on the host machine using embedded neural network models to maintain privacy and offline availability.

The project distinguishes itself through its focus on automated document digitization and integrated barcode and QR code decoding. By utilizing a modular, Python-based orchestration layer, it enables users to transform static image files and multi-page documents into searchable text formats. The system is built to handle high-volume tasks, employing asynchronous task queueing to maintain throughput during batch processing operations.

Beyond its core recognition capabilities, the software provides a command-line interface that allows for the automation of repetitive extraction workflows. This interface exposes internal processing functions to external scripts, enabling the execution of batch recognition tasks without manual intervention. The project maintains consistent functionality across different operating system environments through its cross-platform native integration.

Features

  • Optical Character Recognition - Performs optical character recognition on image files to extract text and associated metadata.
  • Local Inference Engines - Processes visual data entirely on the host machine using embedded neural network models for privacy and offline use.
  • Document Analysis Tools - Converts document pages into readable text by analyzing page layouts and returning identified character strings.
  • Barcode Decoders - Extracts hidden text from image files by identifying and decoding visual patterns found within scanned codes.
  • Optical Character Recognition - Performs high-speed offline text recognition from images.
  • Digital Preservation Tools - Converts large volumes of scanned documents or images into searchable text files automatically.
  • Orchestration Frameworks - Coordinates image processing pipelines and document parsing tasks through a modular script-based architecture.
  • Workflow Automation Tools - Executes repetitive text extraction tasks across multiple files using command line tools to improve efficiency.
  • Automation Scripts - Executes batch text recognition processes through command line scripts to handle multiple files without manual intervention.
  • Task Queues - Distributes document and image analysis jobs across a non-blocking execution pipeline for improved throughput.

Star history

Star history chart for hiroi-sora/umi-ocrStar history chart for hiroi-sora/umi-ocr

How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.

AI search

Explore more awesome repositories

Describe what you need in plain English — the AI ranks thousands of curated open-source projects by relevance.

Start searching with AI

Frequently asked questions

What does hiroi-sora/umi-ocr do?

Umi-OCR is an optical character recognition engine designed to convert visual text from images and documents into machine-readable character data. It functions as a local-first toolkit, processing all visual data directly on the host machine using embedded neural network models to maintain privacy and offline availability.

What are the main features of hiroi-sora/umi-ocr?

The main features of hiroi-sora/umi-ocr are: Optical Character Recognition, Local Inference Engines, Document Analysis Tools, Barcode Decoders, Digital Preservation Tools, Orchestration Frameworks, Workflow Automation Tools, Automation Scripts.

Which projects share features with hiroi-sora/umi-ocr?

Projects with overlapping indexed features include: awesome-selfhosted/awesome-selfhosted — This project is a community-curated directory of open-source software designed for deployment in private server… react-native-camera/react-native-camera — This project provides cross-platform programmatic interfaces and UI components for integrating camera hardware into… xushengfeng/esearch — eSearch is a desktop tool that combines screen capture, image annotation, screen recording, optical character… oobabooga/text-generation-webui — This project is a comprehensive platform for hosting and interacting with large language models directly on local… vysheng/tg — This project is a Telegram command line interface and MTProto client. It functions as a userbot framework, providing a… ggml-org/whisper.cpp — Whisper.cpp is a high-performance, local-first speech recognition engine designed to run large-scale machine learning…

Projects sharing features with Umi OCR

These projects share indexed features with Umi OCR. Shared tags can include platform or build tooling; verify the primary use case before treating a result as a replacement.
  • awesome-selfhosted/awesome-selfhostedawesome-selfhosted avatar

    awesome-selfhosted/awesome-selfhosted

    299,516View on GitHub↗

    This project is a community-curated directory of open-source software designed for deployment in private server environments and home labs. It serves as a comprehensive resource for discovering independent, self-hosted alternatives to mainstream cloud services, enabling users to maintain full data ownership and control over their digital infrastructure. The directory is structured through a hierarchical taxonomy that organizes a vast collection of applications into logical categories, ranging from media management and data analytics to private communication and team productivity tools. It dis

    awesomeawesome-listcloud
    View on GitHub↗299,516
  • react-native-camera/react-native-camerareact-native-camera avatar

    react-native-camera/react-native-camera

    9,638View on GitHub↗

    This project provides cross-platform programmatic interfaces and UI components for integrating camera hardware into mobile applications. It serves as a tool for implementing image and video capture, as well as specialized scanning and recognition tasks. The library includes specialized capabilities for computer vision, including a barcode scanner for decoding various barcode types, a face detection tool to identify human faces in a live feed, and an optical character recognition engine for extracting written text from the camera stream. The system covers hardware configuration and control, i

    Javacameraface-detectionreact-native
    View on GitHub↗9,638
  • xushengfeng/esearchxushengfeng avatar

    xushengfeng/eSearch

    6,275View on GitHub↗

    eSearch is a desktop tool that combines screen capture, image annotation, screen recording, optical character recognition (OCR), and text search and translation into a single application. It is built around a modular architecture that coordinates these tasks through an event-driven capture pipeline, allowing users to capture screen regions, annotate them with drawing and shape tools, and then extract text using a local-first OCR engine or optional cloud services. The project distinguishes itself by integrating a command-line interface for triggering capture and recognition tasks, enabling scr

    TypeScriptclipboardcolor-pickercross-platform
    View on GitHub↗6,275
  • oobabooga/text-generation-webuioobabooga avatar

    oobabooga/text-generation-webui

    47,323View on GitHub↗

    This project is a comprehensive platform for hosting and interacting with large language models directly on local hardware. It provides a web-based graphical interface that allows users to manage model loading, configure generation parameters, and execute text or chat interactions entirely offline. By running models locally, the software ensures complete data privacy and eliminates reliance on external cloud services for generative tasks. Beyond basic inference, the platform functions as a versatile workbench for generative AI development. It includes an integrated pipeline for fine-tuning mo

    Python
    View on GitHub↗47,323
  • Compare all 30 related projects→