RRepoGEO

REPOGEO REPORT · LITE

omriav/blended-diffusion

Default branch master · commit 86ed6ced · scanned 6/11/2026, 12:28:14 PM

GitHub: 588 stars · 43 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 omriav/blended-diffusion, 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 README's opening to emphasize local, text-guided editing of natural images

    Why:

    COPY-PASTE FIX
    Add this sentence immediately after the main title (H1) and before the abstract: 'This repository provides the official implementation for **Blended Diffusion**, a novel method for **localized, text-guided editing of natural images** using natural language prompts and ROI masks.'
  • mediumtopics#2
    Add more specific topics related to localized image editing

    Why:

    CURRENT
    blended-diffusion, deep-learning, diffusion, multimodal, openai, openai-clip, text-guided-manipulation, text-to-image
    COPY-PASTE FIX
    blended-diffusion, deep-learning, diffusion, multimodal, openai, openai-clip, text-guided-manipulation, text-to-image, image-editing, localized-editing, natural-image-editing, region-based-editing
  • lowreadme#3
    Add a 'Key Differentiators' section to the README

    Why:

    COPY-PASTE FIX
    Add a new section to the README, e.g., 'Key Differentiators', explaining how Blended Diffusion stands apart from general text-to-image generation: '### Key Differentiators: Blended Diffusion vs. General Text-to-Image Models Unlike broad text-to-image generators such as Midjourney or Stable Diffusion, Blended Diffusion specializes in **localized, region-based editing of *existing natural images***. Our method allows precise modifications to specific areas of an image based on text prompts, ensuring seamless blending and preservation of the original image's context.'

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 omriav/blended-diffusion
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Midjourney
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Midjourney · recommended 2×
  2. Stable Diffusion · recommended 2×
  3. Adobe Firefly · recommended 1×
  4. DALL-E 2 · recommended 1×
  5. RunwayML · recommended 1×
  • CATEGORY QUERY
    How can I perform localized image editing using natural language prompts?
    you: not recommended
    AI recommended (in order):
    1. Adobe Firefly
    2. Midjourney
    3. Stable Diffusion
    4. DALL-E 2
    5. RunwayML
    6. Fooocus

    AI recommended 6 alternatives but never named omriav/blended-diffusion. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are the best techniques for text-driven natural image manipulation?
    you: not recommended
    AI recommended (in order):
    1. Stable Diffusion
    2. DALL-E 2 / DALL-E 3
    3. Midjourney
    4. Imagen
    5. StyleGAN-XL / StyleGAN-T
    6. StyleCLIP
    7. TediGAN
    8. GLIDE
    9. ControlNet

    AI recommended 9 alternatives but never named omriav/blended-diffusion. 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 omriav/blended-diffusion?
    pass
    AI named omriav/blended-diffusion explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of omriav/blended-diffusion. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

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MARKDOWN (README)
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omriav/blended-diffusion — 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