RRepoGEO

REPOGEO REPORT · LITE

becauseofAI/awesome-face

Default branch master · commit 640700c2 · scanned 5/9/2026, 5:22:42 AM

GitHub: 1,295 stars · 211 forks

AI VISIBILITY SCORE
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
2 pass · 0 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 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 becauseofAI/awesome-face, 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
    Reposition the README's main heading to emphasize its 'awesome list' nature

    Why:

    CURRENT
    # HelloFace
    COPY-PASTE FIX
    # awesome-face: A Curated Repository of Face Technology Resources
  • mediumreadme#2
    Expand the README's introductory description to clarify its scope as a collection of resources

    Why:

    CURRENT
    An Awesome Face Technology Repository. (**Updating**)
    COPY-PASTE FIX
    This repository is a curated, comprehensive collection of papers, datasets, benchmarks, and tools related to face detection, recognition, alignment, and manipulation, designed for researchers, developers, and students.
  • lowtopics#3
    Add 'awesome-list' to the repository topics

    Why:

    CURRENT
    artificial-intelligence, awesome-face, deep-learning, face, face-3d, face-action, face-anti-spoofing, face-benchmark, face-clustering, face-code, face-deblurring, face-detection, face-expression, face-gan, face-landmark, face-manipulation, face-paper, face-recognition, face-super-resolution, machine-learning
    COPY-PASTE FIX
    artificial-intelligence, awesome-face, awesome-list, deep-learning, face, face-3d, face-action, face-anti-spoofing, face-benchmark, face-clustering, face-code, face-deblurring, face-detection, face-expression, face-gan, face-landmark, face-manipulation, face-paper, face-recognition, face-super-resolution, machine-learning

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 becauseofAI/awesome-face
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
OpenCV
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. OpenCV · recommended 2×
  2. FaceNet · recommended 2×
  3. Awesome Face Recognition · recommended 1×
  4. Papers With Code - Face Recognition · recommended 1×
  5. DLIB · recommended 1×
  • CATEGORY QUERY
    Where can I find a comprehensive list of deep learning resources for various face technologies?
    you: not recommended
    AI recommended (in order):
    1. Awesome Face Recognition
    2. Papers With Code - Face Recognition
    3. OpenCV
    4. DLIB
    5. FaceNet
    6. PyTorch
    7. TensorFlow Hub
    8. Medium
    9. Towards Data Science

    AI recommended 9 alternatives but never named becauseofAI/awesome-face. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the leading machine learning tools for accurate face detection, recognition, and manipulation?
    you: not recommended
    AI recommended (in order):
    1. OpenCV
    2. Dlib
    3. FaceNet
    4. MediaPipe
    5. Microsoft Azure Face API
    6. Amazon Rekognition
    7. Google Cloud Vision AI
    8. InsightFace
    9. DeepFace

    AI recommended 9 alternatives but never named becauseofAI/awesome-face. This is the gap to close.

    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 becauseofAI/awesome-face?
    pass
    AI named becauseofAI/awesome-face explicitly

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

  • If a team adopts becauseofAI/awesome-face in production, what risks or prerequisites should they evaluate first?
    pass
    AI named becauseofAI/awesome-face 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 becauseofAI/awesome-face solve, and who is the primary audience?
    pass
    AI named becauseofAI/awesome-face explicitly

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

Embed your GEO score

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MARKDOWN (README)
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