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jingsongliujing/OnnxOCR

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. observed · 2026-08-28

github.com/jingsongliujing/OnnxOCR · Python · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

74/100

  • Activity 87
  • Release rhythm 54
  • Longevity 82
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 1152
  • days_rel: 99
  • days_push: 83
  • n_releases_24m: 1

Full methodology

Adoption not part of the score

1860 stars · 200 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A lightweight multilingual OCR library rebuilt from PaddleOCR models to run on ONNXRuntime, removing the PaddlePaddle dependency for fast inference. It also bundles ONNX-based license plate recognition, table recognition, document layout analysis with Markdown export, and an optional Qwen3.5-2B ONNX information-extraction workflow.

Use cases

  • extract text from images without installing paddlepaddle
  • run OCR on ARM or x86 devices with onnxruntime
  • recognize license plates from photos
  • convert scanned documents to markdown with layout analysis
  • recognize tables in images
  • extract structured fields from ID cards using OCR plus a small LLM
  • deploy fast multilingual OCR including Chinese, English, and Japanese

When to choose

  • you need PaddleOCR-quality OCR but cannot ship the PaddlePaddle framework
  • you need cross-architecture deployment (ARM/x86) via ONNX models
  • you want OCR plus table, layout, or license-plate recognition in one Python package
  • inference speed and lightweight deployment matter more than training capability

When to avoid

  • you need to train or fine-tune OCR models yourself
  • you need OCR languages outside the supported multilingual model set
  • you require a managed cloud OCR API rather than a self-run Python library

Facets

library · maturity active

ocr image-processing machine-learning llm-inference http-server computer-vision image-processing developer-tools python cross-platform cli onnxruntime paddleocr pp-ocrv5 table-recognition layout-analysis license-plate-recognition text-detection text-recognition onnx-models document-parsing natural-language-processing

2 sources

Member repositories

RepositoryRoleHealth v2
jingsongliujing/OnnxOCRmain74

For agents

markdown · JSON · MCP: product_card(name="jingsongliujing/OnnxOCR")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem