RRepoGEO

REPOGEO REPORT · LITE

wanghaisheng/awesome-ocr

Default branch master · commit c7109189 · scanned 5/18/2026, 2:58:14 PM

GitHub: 1,700 stars · 351 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

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 wanghaisheng/awesome-ocr, 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
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    awesome-list, ocr, optical-character-recognition, research-papers, paper-tracking, computer-vision, deep-learning, machine-learning
  • highreadme#2
    Clarify the primary purpose and scope in the README's opening

    Why:

    CURRENT
    # **make a update of daily paper tracking tool **

# awesome-ocr

 A curated list of promising OCR resources
    COPY-PASTE FIX
    # awesome-ocr: A Curated List of Promising OCR Resources & Daily Paper Tracking

This repository serves as a comprehensive, curated list of high-quality resources for Optical Character Recognition (OCR), including tools, datasets, and projects. It also features a dedicated section for daily tracking and collection of new OCR and AI research papers.
  • mediumhomepage#3
    Update homepage to reflect the full scope of the awesome list

    Why:

    CURRENT
    http://wanghaisheng.github.io/ocr-arxiv-daily/
    COPY-PASTE FIX
    https://github.com/wanghaisheng/awesome-ocr

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 wanghaisheng/awesome-ocr
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
kessl/awesome-ocr
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. kessl/awesome-ocr · recommended 1×
  2. tesseract-ocr/tesseract · recommended 1×
  3. Papers With Code · recommended 1×
  4. Kaggle · recommended 1×
  5. Medium · recommended 1×
  • CATEGORY QUERY
    Where can I find a curated list of promising resources and tools for optical character recognition?
    you: not recommended
    AI recommended (in order):
    1. Awesome OCR (kessl/awesome-ocr)
    2. Tesseract OCR (tesseract-ocr/tesseract)
    3. Papers With Code
    4. Kaggle
    5. Medium
    6. Towards Data Science

    AI recommended 6 alternatives but never named wanghaisheng/awesome-ocr. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good options for automating the collection and tracking of new OCR and AI research papers?
    you: not recommended
    AI recommended (in order):
    1. Semantic Scholar
    2. Connected Papers
    3. ResearchRabbit
    4. ArXiv Sanity Preserver (karpathy/arxiv-sanity-preserver)
    5. Google Scholar Alerts
    6. Mendeley
    7. Zotero
    8. Paper Digest
    9. Twitter
    10. TweetDeck

    AI recommended 10 alternatives but never named wanghaisheng/awesome-ocr. 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 wanghaisheng/awesome-ocr?
    pass
    AI named wanghaisheng/awesome-ocr explicitly

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

  • If a team adopts wanghaisheng/awesome-ocr in production, what risks or prerequisites should they evaluate first?
    pass
    AI named wanghaisheng/awesome-ocr 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 wanghaisheng/awesome-ocr solve, and who is the primary audience?
    pass
    AI did not name wanghaisheng/awesome-ocr — 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?

Embed your GEO score

Drop this badge into the README of wanghaisheng/awesome-ocr. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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wanghaisheng/awesome-ocr — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

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  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite