RRepoGEO

REPOGEO REPORT · LITE

kongzhecn/OMG

Default branch master · commit e1bd7a88 · scanned 6/4/2026, 2:38:33 PM

GitHub: 698 stars · 47 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 kongzhecn/OMG, 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 direct statement about the project's core function immediately after the main title in the README

    Why:

    COPY-PASTE FIX
    Insert this line right after the H1: `This repository presents OMG, an ECCV 2024 framework for occlusion-friendly personalized multi-concept image generation using diffusion models.`
  • 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 in the repository root with a standard open-source license (e.g., MIT, Apache-2.0, GPL-3.0) that aligns with the project's goals.
  • mediumtopics#3
    Expand repository topics with more specific terms related to diffusion models and personalized image generation

    Why:

    CURRENT
    image-customization, image-generation
    COPY-PASTE FIX
    image-customization, image-generation, diffusion-models, stable-diffusion, lora, instantid, multi-concept-generation, personalized-generation, eccv-2024

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 kongzhecn/OMG
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 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Stable Diffusion · recommended 2×
  2. ControlNet · recommended 2×
  3. Automatic1111 · recommended 2×
  4. ComfyUI · recommended 2×
  5. Midjourney · recommended 2×
  • CATEGORY QUERY
    How can I generate images with multiple custom characters and specific styles using diffusion models?
    you: not recommended
    AI recommended (in order):
    1. Stable Diffusion
    2. ControlNet
    3. LoRAs
    4. Textual Inversion
    5. Automatic1111
    6. ComfyUI
    7. Midjourney
    8. Fooocus
    9. IP-Adapter
    10. Leonardo.Ai
    11. RunwayML Gen-1
    12. Gen-2

    AI recommended 12 alternatives but never named kongzhecn/OMG. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What tools help generate personalized images with multiple identities, even with occlusions?
    you: not recommended
    AI recommended (in order):
    1. Stable Diffusion
    2. ControlNet
    3. Dreambooth
    4. LoRA
    5. SAM
    6. Automatic1111
    7. ComfyUI
    8. Midjourney
    9. DALL-E 3
    10. ChatGPT Plus
    11. Adobe Firefly
    12. Creative Cloud
    13. FaceFusion

    AI recommended 13 alternatives but never named kongzhecn/OMG. 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 kongzhecn/OMG?
    pass
    AI named kongzhecn/OMG explicitly

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

  • If a team adopts kongzhecn/OMG in production, what risks or prerequisites should they evaluate first?
    pass
    AI named kongzhecn/OMG 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 kongzhecn/OMG solve, and who is the primary audience?
    pass
    AI named kongzhecn/OMG 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 kongzhecn/OMG. 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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HTML
<a href="https://repogeo.com/en/r/kongzhecn/OMG"><img src="https://repogeo.com/badge/kongzhecn/OMG.svg" alt="RepoGEO" /></a>
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kongzhecn/OMG — 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