RRepoGEO

REPOGEO REPORT · LITE

andreas128/RePaint

Default branch main · commit 8e2a0552 · scanned 5/14/2026, 10:57:47 PM

GitHub: 2,253 stars · 200 forks

AI VISIBILITY SCORE
35 /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
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 andreas128/RePaint, 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 opening statement to clarify its research focus and purpose

    Why:

    CURRENT
    # RePaint
**Inpainting using Denoising Diffusion Probabilistic Models**
CVPR 2022 [[Paper]](https://bit.ly/3b1ABEb)
    COPY-PASTE FIX
    # RePaint: Official PyTorch Code and Models for Inpainting using Denoising Diffusion Probabilistic Models (CVPR 2022)
[[Paper]](https://bit.ly/3b1ABEb)
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    COPY-PASTE FIX
    Create a LICENSE file (e.g., MIT, Apache-2.0, or a custom license if applicable) in the repository root to clearly state the terms of use.
  • mediumhomepage#3
    Add the paper link as the repository homepage

    Why:

    COPY-PASTE FIX
    https://bit.ly/3b1ABEb

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 andreas128/RePaint
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Stable Diffusion
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Stable Diffusion · recommended 1×
  2. Hugging Face Diffusers Library · recommended 1×
  3. AUTOMATIC1111 Stable Diffusion web UI · recommended 1×
  4. DALL-E 2 · recommended 1×
  5. OpenAI API · recommended 1×
  • CATEGORY QUERY
    How can I fill in missing regions of an image using advanced generative AI models?
    you: not recommended
    AI recommended (in order):
    1. Stable Diffusion
    2. Hugging Face Diffusers Library
    3. AUTOMATIC1111 Stable Diffusion web UI
    4. DALL-E 2
    5. OpenAI API
    6. RunwayML
    7. Gen-1
    8. Gen-2
    9. RunwayML Platform
    10. LaMa (NVIDIA/LaMa)
    11. BigGAN
    12. TensorFlow Hub
    13. PyTorch Hub
    14. Pytorch-GAN
    15. Pix2Pix
    16. CycleGAN
    17. Contextual Attention for Image Inpainting

    AI recommended 17 alternatives but never named andreas128/RePaint. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best PyTorch libraries for image reconstruction with diffusion models?
    you: not recommended
    AI recommended (in order):
    1. Diffusers (huggingface/diffusers)
    2. PyTorch-Image-Models (timm) (rwightman/pytorch-image-models)
    3. Kornia (kornia/kornia)
    4. TorchMetrics (Lightning-AI/torchmetrics)
    5. einops (arogozhnikov/einops)
    6. PyTorch Lightning (Lightning-AI/pytorch-lightning)

    AI recommended 6 alternatives but never named andreas128/RePaint. 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 andreas128/RePaint?
    pass
    AI named andreas128/RePaint explicitly

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

  • If a team adopts andreas128/RePaint in production, what risks or prerequisites should they evaluate first?
    pass
    AI named andreas128/RePaint 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 andreas128/RePaint solve, and who is the primary audience?
    pass
    AI named andreas128/RePaint explicitly

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

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andreas128/RePaint — 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