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Image-MetaHub LuqP2/Image-MetaHub

A local-first workspace that keeps your generated media connected to the prompts, models and workflows that created them. Search, compare and send anything straight back into ComfyUI — nothing leaves your machine.

https://imagemetahub.com ↗
HEALTH 95 / Healthy
// solo builder// funded ai-toolsautomatic1111comfyuielectronimage-browserinvokeaimetadatareactstable-diffusiontypescript

// readme

Image MetaHub

A local-first workspace that keeps your generated media connected to the prompts, models and workflows that created them.

Every image and video stays linked to how it was made — so you can find it, compare it against its siblings, and send the workflow straight back into ComfyUI. Nothing is uploaded.

Join the community on Discord — feature requests, bug reports, metadata parsing help, and early builds.

What is Image MetaHub?

Image MetaHub is a desktop app for browsing large local libraries of AI outputs without uploading anything to the cloud. It scans your folders, extracts metadata from popular generators, caches results for fast reuse, and lets you filter by prompt, model, LoRA, sampler, seed, dimensions, tags, and more.

It started as a local browser for InvokeAI outputs and has since grown into a broader metadata hub for Stable Diffusion ecosystems, ComfyUI workflows, and related tools.

Highlights

  • Local-first browsing with no mandatory account, no cloud sync, and no outbound telemetry
  • Fast indexing and thumbnail caching for large libraries
  • Find Similar — Local Visual Search for discovering…
The Undervalued Score +

How much a project earns versus how much attention it actually gets. Above 50 means the work is outrunning its audience. Recomputed nightly from commit velocity, contributor effort, issue resolution, fork utility, release cadence, and project maturity — divided by a logarithmic reach factor.

score  = signal / reach

signal = 0.25·commit_velocity   // commits in last 90 days (cap 30)
       + 0.20·contributor_work  // unique authors × velocity (cap 100)
       + 0.20·issue_resolution  // closed ÷ total issues
       + 0.20·fork_ratio        // forks ÷ stars (proxy for real usage)
       + 0.10·release_cadence   // releases in 90 days (cap 3)
       + age_bonus              // +0 to +0.30 after 6 months
       + homepage_bonus         // +0.05 if homepage is set

reach  = log₁₀(stars + watchers + 10)
The Health Score +

Is the project alive and maintained right now? A 0–100 pulse recomputed nightly from commit recency, rhythm, how fast issues close, and how quickly PRs get merged.

health = 0.35·recency       // days since last commit (90d decay)
       + 0.25·cadence       // commit rhythm consistency
       + 0.20·issue_health  // closed ÷ total issues
       + 0.20·pr_health     // merged ÷ total PRs
Health bands +

The colour and label on every card come straight from the health score.

Healthy   80 – 100   active, responsive, regular releases
Stable    60 – 79    maintained, steady, no alarms
Quiet     40 – 59    slowing down — watch this one
At Risk    0 – 39    going dark · candidate for rescue
// Tags — what each label means +

Tags are independent behavioral signals computed nightly. A project can hold multiple at once. They drive the home page sections.

solo_builder      one person holds > 80% of commits (last 180d)
needs_contributors has open "help wanted" or "good first issue" labels
hidden_gem        < 100 stars · active in last 3 months · documented
legacy_hero       repo > 5 years old · committed this year
fork_magnet       forks/stars > 0.5 · used as template or dependency
release_machine   5+ releases in the last 90 days
under_pressure    > 10 open issues · ≤ 2 contributors · health ≥ 60
community_watch   watchers > stars · devs tracking before the public
community_hub     GitHub Discussions enabled · > 20 discussions
funded            maintainer has active funding channel
Why rank against stars at all? +

Stars are an outcome, not effort. A project with 8 stars and daily commits is doing more interesting work than one coasting on 8k. We measure the building, then divide by the attention already received — so the genuinely undervalued rise to the top.

// stars   = lagging indicator
// commits = leading indicator
// we rank by the leading one