REPOGEO REPORT · LITE

PRIS-CV/DemoFusion

Default branch main · commit 6aa190a8 · scanned 6/21/2026, 11:58:06 PM

GitHub: 2,040 stars · 216 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)

2 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 PRIS-CV/DemoFusion, 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 statement to clarify its role as a framework

Why:

CURRENT

Code release for "DemoFusion: Democratising High-Resolution Image Generation With No 💰"

COPY-PASTE FIX

DemoFusion is an open-source framework that extends existing Latent Diffusion Models (LDMs) to generate high-resolution images efficiently, making advanced GenAI accessible even on limited computational resources.

hightopics#2

Expand repository topics to include 'framework' and 'extension' terms

Why:

CURRENT

["aigc", "genai", "high-resolution", "low-resource", "stable-diffusion"]

COPY-PASTE FIX

["aigc", "genai", "high-resolution", "low-resource", "stable-diffusion", "diffusion-model-extension", "image-upscaling", "generative-ai-framework", "resource-efficient"]

mediumcomparison#3

Add a comparison section to the README highlighting unique differentiators

Why:

COPY-PASTE FIX

Add a new section, e.g., '## How DemoFusion Compares', explaining its unique approach (e.g., 'Unlike traditional upscalers or iterative methods, DemoFusion fuses multiple low-resolution diffusion samples in a single forward pass, offering efficient and coherent high-resolution output without requiring extensive retraining or specialized models.').

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 PRIS-CV/DemoFusion

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

Stable Diffusion

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

Stable Diffusion · recommended 2×
ControlNet · recommended 2×
ESRGAN · recommended 2×
DeepFloyd IF · recommended 2×
GLIDE · recommended 2×

CATEGORY QUERY
How to generate high-resolution images using AI on limited computational resources?
you: not recommended
AI recommended (in order):
1. Stable Diffusion
2. diffusers library (huggingface/diffusers)
3. LoRAs
4. Automatic1111's web UI (AUTOMATIC1111/stable-diffusion-webui)
5. ComfyUI (comfyanonymous/ComfyUI)
6. ControlNet
7. ESRGAN
8. Real-ESRGAN (xinntao/Real-ESRGAN)
9. DeepFloyd IF
10. GLIDE
AI recommended 10 alternatives but never named PRIS-CV/DemoFusion. This is the gap to close.
Show full AI answer
CATEGORY QUERY
What open-source frameworks extend existing generative AI for higher resolution outputs?
you: not recommended
AI recommended (in order):
1. Stable Diffusion
2. Automatic1111's WebUI
3. ESRGAN
4. SwinIR
5. Latent Diffusion Upscaler
6. ControlNet
7. Upscale Diffusion
8. Real-ESRGAN
9. SwinIR
10. GLIDE
11. DeepFloyd IF
AI recommended 11 alternatives but never named PRIS-CV/DemoFusion. 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 PRIS-CV/DemoFusion?
pass
AI named PRIS-CV/DemoFusion explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts PRIS-CV/DemoFusion in production, what risks or prerequisites should they evaluate first?
pass
AI named PRIS-CV/DemoFusion 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 PRIS-CV/DemoFusion solve, and who is the primary audience?
pass
AI named PRIS-CV/DemoFusion 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 PRIS-CV/DemoFusion. 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)

[![RepoGEO](https://repogeo.com/badge/PRIS-CV/DemoFusion.svg)](https://repogeo.com/en/r/PRIS-CV/DemoFusion)

HTML

<a href="https://repogeo.com/en/r/PRIS-CV/DemoFusion"><img src="https://repogeo.com/badge/PRIS-CV/DemoFusion.svg" alt="RepoGEO" /></a>

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PRIS-CV/DemoFusion — 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