RRepoGEO

REPOGEO REPORT · LITE

yfeng95/GAN

Default branch master · commit 45bde57d · scanned 5/10/2026, 10:02:59 PM

GitHub: 3,101 stars · 798 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 yfeng95/GAN, 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
    Prominently state TensorFlow as the primary framework in README

    Why:

    CURRENT
    All have been tested with python2.7+ and tensorflow1.0+ in linux.
    COPY-PASTE FIX
    Add a line like: "This repository provides implementations of classical Generative Adversarial Networks (GANs) **primarily using TensorFlow 1.x** for learning and experimentation." at the very beginning of the README.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    Create a `LICENSE` file (e.g., MIT License) in the repository root.
  • mediumhomepage#3
    Add a homepage URL to the repository settings

    Why:

    COPY-PASTE FIX
    Add a relevant URL (e.g., a project page, documentation, or even the GitHub repo URL itself) to the 'Homepage' field in the repository settings.

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 yfeng95/GAN
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
TensorFlow's Official GAN Tutorials
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. TensorFlow's Official GAN Tutorials · recommended 1×
  2. Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play · recommended 1×
  3. Coursera's "Generative Adversarial Networks (GANs) Specialization" · recommended 1×
  4. NVIDIA's StyleGAN repositories · recommended 1×
  5. Kaggle · recommended 1×
  • CATEGORY QUERY
    How can I learn to implement various generative adversarial network architectures using TensorFlow?
    you: not recommended
    AI recommended (in order):
    1. TensorFlow's Official GAN Tutorials
    2. Generative Deep Learning: Teaching Machines to Paint, Write, Compose, and Play
    3. Coursera's "Generative Adversarial Networks (GANs) Specialization"
    4. NVIDIA's StyleGAN repositories
    5. Kaggle

    AI recommended 5 alternatives but never named yfeng95/GAN. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Where can I find simple implementations of classical GAN models for learning purposes?
    you: not recommended
    AI recommended (in order):
    1. PyTorch GANs by Nathan Inkawhich
    2. Keras Examples
    3. TensorFlow Tutorials
    4. Generative Adversarial Networks (GANs) in PyTorch by Aladdin Persson
    5. GANs in Action by Jakub Langr and Vladimir Bok
    6. Awesome GANs

    AI recommended 6 alternatives but never named yfeng95/GAN. 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 yfeng95/GAN?
    pass
    AI named yfeng95/GAN explicitly

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

  • If a team adopts yfeng95/GAN in production, what risks or prerequisites should they evaluate first?
    pass
    AI named yfeng95/GAN 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 yfeng95/GAN solve, and who is the primary audience?
    pass
    AI did not name yfeng95/GAN — 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?

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yfeng95/GAN — 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