{"repo":"jingsongliujing/OnnxOCR","free":true,"listed":false,"github":"https://github.com/jingsongliujing/OnnxOCR","clone":"git clone https://github.com/jingsongliujing/OnnxOCR.git","description":"基于PaddleOCR重构，并且脱离PaddlePaddle深度学习训练框架的轻量级OCR，推理速度超快 —— A lightweight OCR system based on PaddleOCR, decoupled from the PaddlePaddle deep learning training framework, with ultra-fast inference speed.","language":"Python","stars":1855,"topics":["document-layout-analysis","license-plate-recognition","ocr","onnx-models","onnxocr","onnxruntime","general-ocr","structured-ocr","tablerecognition"],"license":"Apache-2.0","category":"media-processing","readme_excerpt":"# OnnxOCR If this project helps you, please consider giving it a Star . A high-performance multilingual OCR project based on ONNXRuntime English 简体中文 日本語 Version Updates - 2026.05.27 1. Added a new OCR + Qwen3.5-2B ONNX information-extraction workflow. 2. Added onnxocr.qwen35 2b as the package-level Qwen3.5-2B ONNX download, verification, and pure Python inference module. 3. Added examples/id card extract with qwen.py as an end-to-end example: OnnxOCR full-text recognition first, then Qwen3.5-2B extracts structured ID-card fields. 4. Qwen3.5-2B ONNX uses a dedicated ModelScope repository: supersong/qwen2bonnx. - 2026.05.01 1. Added ONNX license plate detection and recognition. 2. Added RapidTable-based ONNX table recognition. 3. Added RapidLayout-based Chinese and English layout analysis. 4. Added RapidDoc-based document layout analysis and Markdown export. 5. Added /plate , /table , /layout , /layout markdown , and related HTTP endpoints. - 2025.05.21 1. Added PP-OCRv5 models, supporting Simplified Chinese, Traditional Chinese, Chinese Pinyin, English, and Japanese in one model. 2. Improved overall recognition accuracy compared with PP-OCRv4. 3. Recognition accuracy is consistent with PaddleOCR 3.0. Core Advantages 1. Deep learning framework free : a general OCR project ready for deployment. 2. Cross-architecture support : PaddleOCR-converted ONNX models can run on ARM and x86 devices. 3. Unified inference engine : all ONNX models create ONNXRuntime sessions through onnxocr/","default_branch":null,"files":null,"tree":[],"storefront":"/r/jingsongliujing","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/jingsongliujing/OnnxOCR/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}