RRepoGEO

REPOGEO REPORT · LITE

rinongal/StyleGAN-nada

Default branch main · commit dc8406ae · scanned 6/27/2026, 4:57:56 PM

GitHub: 1,194 stars · 143 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
53 /100
Needs work
Category recall
1 / 2
Avg rank #7.0 when recommended
Rule findings
1 pass · 1 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 rinongal/StyleGAN-nada, 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
  • highabout#1
    Add a concise 'About' description

    Why:

    COPY-PASTE FIX
    A text-driven method for CLIP-guided domain adaptation of StyleGAN image generators, enabling zero-shot domain transfer without requiring any target domain images.
  • mediumreadme#2
    Enhance the README's opening statement to highlight zero-shot capability

    Why:

    CURRENT
    # StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators (SIGGRAPH 2022)
    COPY-PASTE FIX
    # StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators (SIGGRAPH 2022)

Adapt StyleGAN models to new domains using only text prompts, without needing any target domain images.
  • lowtopics#3
    Add 'zero-shot' and 'clip-guidance' to repository topics

    Why:

    CURRENT
    domain-adaptation, generative-adversarial-network, stylegan
    COPY-PASTE FIX
    domain-adaptation, generative-adversarial-network, stylegan, zero-shot, clip-guidance

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
1 / 2
50% of queries surface rinongal/StyleGAN-nada
Avg rank
#7.0
Lower is better. #1 = top recommendation.
Share of voice
5%
Of all named tools, what % are you?
Top rival
ControlNet
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. ControlNet · recommended 2×
  2. Midjourney · recommended 2×
  3. DreamBooth · recommended 1×
  4. LoRA · recommended 1×
  5. Textual Inversion · recommended 1×
  • CATEGORY QUERY
    How can I adapt a generative image model to new domains using only text prompts?
    you: #7
    AI recommended (in order):
    1. DreamBooth
    2. LoRA
    3. Textual Inversion
    4. ControlNet
    5. StyleGAN
    6. StyleCLIP
    7. StyleGAN-NADA ← you
    8. GLIDE
    9. DALL-E 2
    10. Midjourney
    Show full AI answer
  • CATEGORY QUERY
    What are effective techniques for zero-shot domain transfer in image generation without datasets?
    you: not recommended
    AI recommended (in order):
    1. Stable Diffusion
    2. Midjourney
    3. DALL-E 3
    4. ControlNet
    5. InstructPix2Pix
    6. CLIPstyler
    7. StyleGAN-XL
    8. SPADE
    9. GauGAN

    AI recommended 9 alternatives but never named rinongal/StyleGAN-nada. 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 rinongal/StyleGAN-nada?
    pass
    AI named rinongal/StyleGAN-nada explicitly

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

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

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

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rinongal/StyleGAN-nada — 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