RRepoGEO

REPOGEO REPORT · LITE

jingsongliujing/OnnxOCR

Default branch main · commit 23b9798c · scanned 5/31/2026, 1:31:34 AM

GitHub: 1,795 stars · 198 forks

AI VISIBILITY SCORE
28 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
2 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface jingsongliujing/OnnxOCR, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

3 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Strengthen README's opening to highlight advanced ONNX capabilities

    Why:

    CURRENT
    # OnnxOCR

If this project helps you, please consider giving it a **Star**.

**A high-performance multilingual OCR project based on ONNXRuntime**
    COPY-PASTE FIX
    # OnnxOCR: Framework-Free, ONNX-Optimized OCR for Advanced Document Intelligence

If this project helps you, please consider giving it a **Star**.

**OnnxOCR delivers high-performance, multilingual OCR with ultra-fast ONNXRuntime inference, completely decoupled from deep learning frameworks. It offers a comprehensive suite for document intelligence, including layout analysis, table recognition, and Qwen3.5-2B-powered information extraction.**
  • hightopics#2
    Add specific topics for advanced features and ONNX integration

    Why:

    CURRENT
    document-layout-analysis, general-ocr, license-plate-recognition, ocr, onnx-models, onnxocr, onnxruntime, structured-ocr, tablerecognition
    COPY-PASTE FIX
    document-layout-analysis, general-ocr, license-plate-recognition, ocr, onnx-models, onnxocr, onnxruntime, structured-ocr, tablerecognition, rapidtable, rapidlayout, rapiddoc, qwen-onnx, information-extraction, llm-inference-onnx
  • mediumhomepage#3
    Add the GitHub repository URL as the homepage

    Why:

    COPY-PASTE FIX
    https://github.com/jingsongliujing/OnnxOCR

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface jingsongliujing/OnnxOCR
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Tesseract OCR
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Tesseract OCR · recommended 1×
  2. GOCR · recommended 1×
  3. Cuneiform · recommended 1×
  4. Ocrad · recommended 1×
  5. OCRopus · recommended 1×
  • CATEGORY QUERY
    Looking for a fast, lightweight OCR library for various languages, independent of deep learning frameworks.
    you: not recommended
    AI recommended (in order):
    1. Tesseract OCR
    2. GOCR
    3. Cuneiform
    4. Ocrad
    5. OCRopus

    AI recommended 5 alternatives but never named jingsongliujing/OnnxOCR. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Need an ONNX-based solution for document layout analysis and table recognition from scanned documents.
    you: not recommended
    AI recommended (in order):
    1. Azure AI Document Intelligence
    2. PaddleOCR (PaddlePaddle/PaddleOCR)
    3. LayoutParser (Layout-Parser/layout-parser)
    4. DocTR (mindee/doctr)
    5. Hugging Face Transformers (huggingface/transformers)

    AI recommended 5 alternatives but never named jingsongliujing/OnnxOCR. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of jingsongliujing/OnnxOCR?
    pass
    AI did not name jingsongliujing/OnnxOCR — likely talking about a different project

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts jingsongliujing/OnnxOCR in production, what risks or prerequisites should they evaluate first?
    pass
    AI named jingsongliujing/OnnxOCR explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo jingsongliujing/OnnxOCR solve, and who is the primary audience?
    pass
    AI named jingsongliujing/OnnxOCR explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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jingsongliujing/OnnxOCR — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite