RRepoGEO

REPOGEO REPORT · LITE

IceClear/StableSR

Default branch main · commit 398ee938 · scanned 6/24/2026, 8:27:06 PM

GitHub: 2,656 stars · 171 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)

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

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 IceClear/StableSR, 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
    Add a concise, user-focused summary after the main title

    Why:

    CURRENT
    ## Exploiting Diffusion Prior for Real-World Image Super-Resolution

Paper | Project Page | Video | WebUI | ModelScope | ComfyUI
    COPY-PASTE FIX
    ## Exploiting Diffusion Prior for Real-World Image Super-Resolution

StableSR is a state-of-the-art solution for real-world image super-resolution, uniquely leveraging latent diffusion models to generate high-fidelity, consistent, and plausible details. It addresses the challenge of upscaling low-resolution images into high-quality, realistic versions by exploiting a diffusion prior.

Paper | Project Page | Video | WebUI | ModelScope | ComfyUI
  • mediumtopics#2
    Expand repository topics for better categorization

    Why:

    CURRENT
    stable-diffusion, stablesr, super-resolution
    COPY-PASTE FIX
    stable-diffusion, stablesr, super-resolution, image-upscaling, diffusion-models, generative-ai, computer-vision, real-world-images, latent-diffusion, image-enhancement
  • lowreadme#3
    Clarify the project's license directly in the README

    Why:

    COPY-PASTE FIX
    ## License
This project is licensed under the terms specified in the `LICENSE` file. Please refer to that file for full details on usage and distribution.

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 IceClear/StableSR
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
SwinIR
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. SwinIR · recommended 2×
  2. Real-ESRGAN · recommended 2×
  3. Stable Diffusion XL (SDXL) · recommended 1×
  4. ControlNet · recommended 1×
  5. Stable Diffusion 1.5 · recommended 1×
  • CATEGORY QUERY
    How to achieve high-quality image super-resolution for real-world photos using diffusion models?
    you: not recommended
    AI recommended (in order):
    1. Stable Diffusion XL (SDXL)
    2. ControlNet
    3. SwinIR
    4. Stable Diffusion 1.5
    5. Stable Diffusion 2.1
    6. Real-ESRGAN
    7. PULSE
    8. GLIDE

    AI recommended 8 alternatives but never named IceClear/StableSR. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What open-source solutions exist for upscaling images with diffusion priors and easy integration?
    you: not recommended
    AI recommended (in order):
    1. Diffusers
    2. ESRGAN
    3. Stability AI's Stable Diffusion Upscalers
    4. SwinIR
    5. Latent Diffusion Models (LDM)
    6. Real-ESRGAN

    AI recommended 6 alternatives but never named IceClear/StableSR. 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 IceClear/StableSR?
    pass
    AI named IceClear/StableSR explicitly

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

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

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

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IceClear/StableSR — 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