dsys/match
:crystal_ball: Scalable reverse image search built on Kubernetes and Elasticsearch observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases no_license
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 3827
- days_rel: n/a
- days_push: 2230
- n_releases_24m: 0
Adoption not part of the score
1265 stars · 150 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
Match is a scalable reverse image search service built on Kubernetes and Elasticsearch, using perceptual hashing to find visually similar images. It exposes an HTTP API and is distributed as a Docker container, scaling to billions of images.
Use cases
- find duplicate or similar images in a large collection
- build a reverse image search API
- detect near-duplicate images at scale
- search images by visual similarity
- index billions of image signatures on Kubernetes
When to choose
- you need a self-hosted, scalable reverse image search with an HTTP API
- you already run Elasticsearch and Kubernetes infrastructure
- you need hash-based matching invariant to scaling and rotation
When to avoid
- you need deep-learning-based semantic image similarity rather than perceptual hashing
- you want a managed SaaS solution
- you need active development - the project's last release was 2020
Facets
service · maturity maintenance
search-engine image-processing http-server api-framework computer-vision image-processing databases python self-hosted reverse-image-search perceptual-hash elasticsearch image-signatures docker search kubernetes
1 source
- readme: https://github.com/dsys/match · fetched 2026-08-28 · 6d5406287719
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| dsys/match | main | 32 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem