Search Results for "ocr a"
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Showing 73 open source projects for "ocr a"
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Umi-OCR
OCR software, free and offline
Umi-OCR is a free and open-source optical character recognition (OCR) tool designed to provide fast, offline text extraction from images, screenshots, PDFs, and more without requiring a network connection. It includes a highly efficient offline OCR engine with built-in multilingual recognition libraries, so users can extract text across multiple languages with high accuracy directly on their machines. -
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DeepSeek-OCR
Contexts Optical Compression
DeepSeek-OCR is an open-source optical character recognition solution built as part of the broader DeepSeek AI vision-language ecosystem. It is designed to extract text from images, PDFs, and scanned documents, and integrates with multimodal capabilities that understand layout, context, and visual elements beyond raw character recognition. The system treats OCR not simply as “read the text” but as “understand what the text is doing in the image”—for example distinguishing captions from body text, interpreting tables, or recognizing handwritten versus printed words. ... -
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Zerox OCR
PDF to Markdown with vision models
A dead simple way of OCR-ing a document for AI ingestion. Documents are meant to be a visual representation after all. With weird layouts, tables, charts, etc. The vision models just make sense. ZeroX is an open-source machine learning framework designed for fast experimentation and production deployment, optimized for speed and ease of use. -
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GLM-OCR
Accurate × Fast × Comprehensive
GLM-OCR is an open-source multimodal optical character recognition (OCR) model built on a GLM-V encoder–decoder foundation that brings robust, accurate document understanding to complex real-world layouts and modalities. Designed to handle text recognition, table parsing, formula extraction, and general information retrieval from documents containing mixed content, GLM-OCR excels across major benchmarks while remaining highly efficient with a relatively compact parameter size (~0.9B), enabling deployment in high-concurrency services and edge environments. ... -
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Unlimited OCR Works
Welcome the Era of One-shot Long-horizon Parsing
Unlimited-OCR is an OCR and document parsing model project focused on one-shot long-horizon parsing. It is designed to push OCR beyond short, isolated image recognition and into longer document understanding workflows. The project supports single-image parsing as well as multi-page and PDF-style parsing by converting pages into images. It provides inference paths for Hugging Face Transformers, vLLM, and SGLang, which gives users several deployment options. -
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DeepSeek-OCR 2
Visual Causal Flow
DeepSeek-OCR-2 is the second-generation optical character recognition system developed to improve document understanding by introducing a “visual causal flow” mechanism, enabling the encoder to reorder visual tokens in a way that better reflects semantic structure rather than strict raster scan order. It is designed to handle complex layouts and noisy documents by giving the model causal reasoning capabilities that mimic human visual scanning behavior, enhancing OCR performance on documents with rich spatial structure. ... -
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Rapid LaTeX OCR
Formula recognition based on LaTeX-OCR and ONNXRuntime
Formula recognition based on LaTeX-OCR and ONNXRuntime. rapid_latex_ocr is a tool to convert formula images to latex format. The reasoning code in the repo is modified from LaTeX-OCR, the model has all been converted to ONNX format, and the reasoning code has been simplified, Inference is faster and easier to deploy. The repo only has codes based on ONNXRuntime or OpenVINO inference in onnx format and does not contain training model codes. -
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OCRmyPDF
OCRmyPDF adds an OCR text layer to scanned PDF files
OCRmyPDF adds an optical character recognition (OCR) text layer to scanned PDF files, allowing them to be searched. PDF is the best format for storing and exchanging scanned documents. Unfortunately, PDFs can be difficult to modify. OCRmyPDF makes it easy to apply image processing and OCR (recognized, searchable text) to existing PDFs. -
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OpenOCR
An Open-Source Toolkit for General-OCR Research and Applications
OpenOCR is an open-source General OCR toolkit developed by the OCR team at Fudan University for research and real-world document processing applications. It provides a unified platform for text detection, text recognition, formula recognition, table recognition, and document parsing. Built on advanced OCR technologies such as SVTRv2 and UniRec-0.1B, OpenOCR delivers high accuracy while maintaining efficient inference performance. -
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PaddleOCR
Awesome multilingual OCR toolkits based on PaddlePaddle
PaddleOCR offers exceptional, multilingual, and practical Optical Character Recognition (OCR) tools that can help users train better models and apply them into practice. Inspired by PaddlePaddle, PaddleOCR is an ultra lightweight OCR system, with multilingual recognition, digit recognition, vertical text recognition, as well as long text recognition. It features a PPOCR series of high-quality pre-trained models, which includes: ultra lightweight ppocr_mobile series models, general ppocr_server series models, and ultra lightweight compression ppocr_mobile_slim series models. ... -
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LLM-Aided OCR Project
Enhances Tesseract OCR output using LLMs (local or API)
LLM Aided OCR is an open-source system designed to improve optical character recognition accuracy by combining traditional OCR tools with large language models. The project addresses common OCR challenges such as distorted text, unusual fonts, historical documents, and complex layouts that often produce inaccurate results with standard OCR pipelines. -
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MinerU
A high-quality tool for convert PDF to Markdown and JSON
MinerU is an open-source, high-quality document extraction toolkit focused on converting PDFs (and other document formats) into structured Markdown and JSON. It leverages OCR and layout analysis to preserve semantic structure and metadata, ideal for research and data science workflows. -
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Video-subtitle-extractor
A GUI tool for extracting hard-coded subtitle (hardsub) from videos
...A deep learning-based video subtitle extraction framework, including subtitle region detection and subtitle content extraction. A GUI tool for extracting hard-coded subtitles (hardsub) from videos and generating srt files. Use local OCR recognition, no need to set up and call any API, and do not need to access online OCR services such as Baidu and Ali to complete text recognition locally. Support GPU acceleration, after GPU acceleration, you can get higher accuracy and faster extraction speed. (CLI version) No need for users to manually set the subtitle area, the project automatically detects the subtitle area through the text detection model. ... -
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DocTR
Library for OCR-related tasks powered by Deep Learning
DocTR provides an easy and powerful way to extract valuable information from your documents. Seemlessly process documents for Natural Language Understanding tasks: we provide OCR predictors to parse textual information (localize and identify each word) from your documents. Robust 2-stage (detection + recognition) OCR predictors with pretrained parameters. User-friendly, 3 lines of code to load a document and extract text with a predictor. State-of-the-art performances on public document datasets, comparable with GoogleVision/AWS Textract. ... -
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HunyuanOCR
OCR expert VLM powered by Hunyuan's native multimodal architecture
HunyuanOCR is an open-source, end-to-end OCR (optical character recognition) Vision-Language Model (VLM) developed by Tencent‑Hunyuan. It’s designed to unify the entire OCR pipeline, detection, recognition, layout parsing, information extraction, translation, and even subtitle or structured output generation, into a single model inference instead of a cascade of separate tools. -
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dots.ocr
Multilingual Document Layout Parsing in a Single Vision-Language Model
...Beyond standard OCR tasks, it extends its capabilities to parse complex visual elements such as charts, diagrams, and web interfaces, converting them into structured outputs like SVG code. -
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Windrecorder
Windrecorder is a memory search app by records everything
Windrecorder is an open-source personal memory search engine that continuously records on-screen activity in a highly optimized and storage-efficient format. It captures screen content locally and builds a searchable database using OCR and image understanding, allowing users to rewind and rediscover anything they have previously seen. The system indexes only meaningful visual changes, extracting text, browser data, and contextual information to improve search accuracy and reduce storage overhead. It includes a web-based interface where users can browse timelines, analyze activity, and perform semantic queries on recorded content. ... -
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EasyOCR
Ready-to-use OCR with 80+ supported languages
Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc. EasyOCR is a python module for extracting text from image. It is a general OCR that can read both natural scene text and dense text in document. We are currently supporting 80+ languages and expanding. Second-generation models: multiple times smaller size, multiple times faster inference, additional characters and comparable accuracy to the first generation models. ... -
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PDFMathTranslate
PDF scientific paper translation with preserved formats
PDFMathTranslate is a Python-based tool that uses AI translation to convert academic PDFs into bilingual (e.g. Chinese-English) documents while preserving formatting, including math notation. It supports OCR-enhanced content and offers CLI, GUI, Docker, and Zotero integration under AGPL v3. -
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Texify
Math OCR model that outputs LaTeX and markdown
Texify is an OCR model that converts images or pdfs containing math into markdown and LaTeX that can be rendered by MathJax ($$ and $ are delimiters). It can run on CPU, GPU, or MPS. -
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Docling
Get your documents ready for gen AI
...Docling is designed to run efficiently on commodity hardware and can be used both as a Python API and a command-line tool. Its modular architecture allows developers to extend functionality and integrate specialized models for tasks such as OCR and audio transcription. Overall, Docling serves as a comprehensive preprocessing layer for AI applications that require reliable, structured access to complex document data. -
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Papermerge
Open Source Document Management System for Digital Archives
...Papermerge supports multiple users. Each user can be assigned different permissions to perform only a specific kind of action e.g. view only documents from a specific folder. OCR technology is vital part of Papermerge. It extracts text information from scanned documents, PDF, JPEG, TIFF files. -
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Qwen-MM-Plugins
Make any agent harness multimodal-native
...Each capability combines an instructional skill with an optional MCP server that exposes specialized tools. The core package can inspect images, videos, documents, and 3D models while providing OCR, grounding, segmentation, transcription, and visual question answering. Additional modules support long-video memory, audio-video analysis, media generation, video editing, Blender, FreeCAD, and educational content creation. Dynamic-resolution processing automatically adjusts visual inputs according to the detail required by the model. ... -
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Self-Operating Computer
A framework to enable multimodal models to operate a computer
...Notably, it was the first known project to implement a multimodal model capable of viewing and controlling a computer screen. The framework supports features like Optical Character Recognition (OCR) and Set-of-Mark (SoM) prompting to enhance visual grounding capabilities. It is designed to be compatible with macOS, Windows, and Linux (with X server installed), and is released under the MIT license. -
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Unredact
A simple tool for reading in poorly redacted documents
Unredact is a specialized tool that attempts to reconstruct redacted or obscured text in images, PDFs, or screenshots using a combination of image processing and generative AI inference to suggest plausible completions of blurred, black-boxed, or jumbled content. Unlike traditional optical character recognition (OCR), which only reads visible text, Unredact focuses on inferring missing content where redaction has been applied by analyzing surrounding context, font characteristics, and linguistic patterns to produce candidate reconstructions. It accepts a variety of input formats, automatically identifies redacted regions, and then generates text suggestions that are presented alongside visual overlays so users can choose or refine outputs.
