# h2non/imaginary

Fast, simple, scalable, Docker-ready HTTP microservice for high-level image processing

Repository: https://github.com/h2non/imaginary
Canonical: https://ross.abutalabs.com/products/imaginary
Homepage: https://fly.io/docs/app-guides/run-a-global-image-service/
Language: Go
License: MIT
License Family: permissive
Topics: image, image-processing, resize-images, libvips, crop-image, microservice, docker, watermark, jpeg, png, webp, gif
Last push: 2025-11-08T19:49:48+00:00

## Health v2 (maintenance only)
Score: 46/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 51, release rhythm 8, longevity 100
- inputs: {"age_days": 4200, "days_push": 298, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 6079, forks 500 (observed 2026-08-28T04:09:34.853538+00:00)

## What it is
Imaginary is a fast HTTP microservice written in Go for high-level image processing, backed by bimg and libvips. It exposes image operations like resizing, cropping, and watermarking via a simple HTTP API, with first-class Docker support and formats including JPEG, PNG, WEBP, HEIF, GIF, and more.

## Use cases
- resize and crop images via an HTTP API
- generate thumbnails on the fly for a website
- convert images between JPEG, PNG, and WEBP
- add watermarks to uploaded images at scale
- run a self-hosted image processing service in Docker
- process images faster than ImageMagick with low memory usage

## When to choose
- you need a standalone, scalable image-processing service decoupled from your app
- you want high throughput and low memory footprint via libvips
- you deploy with Docker, Fly.io, Cloud Run, or Kubernetes
- you need URL-based image fetching plus API token and URL signature protection

## When to avoid
- you only need simple image manipulation inside a single app process (use a library like bimg or sharp directly)
- you need advanced editing features like complex filters or layered compositions
- you cannot run a separate service or container in your infrastructure

## Facets
- artifact type: service
- maturity: stable
- function: image-processing, http-server, api-framework, microservices
- domain: image-processing, web-development, media
- platform: go, self-hosted, cloud
- tags: libvips, bimg, image-resizing, thumbnail-generation, watermarking, image-conversion, http-api, microservice, docker, linux

## Member repositories
- h2non/imaginary (main) score 46

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:34.853538+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T17:48:20.322423+00:00, confidence not recorded.
  - readme: https://github.com/h2non/imaginary (fetched 2026-08-28T04:09:34.853538+00:00, sha 2de4cecb085c)
  - homepage: https://fly.io/docs/app-guides/run-a-global-image-service/ (fetched 2026-08-29T08:45:04.329449+00:00, sha f8b5010bd730)
  - site_page: https://fly.io/docs (fetched 2026-08-29T08:45:04.339370+00:00, sha 979fe7b8a11b)
  - site_page: https://fly.io/docs/about/brand (fetched 2026-08-29T08:45:04.341232+00:00, sha 034cf3d47a9b)
  - site_page: https://fly.io/docs/about/support (fetched 2026-08-29T08:45:04.344618+00:00, sha bfbc2167612f)
  - site_page: https://fly.io/docs/getting-started/launch (fetched 2026-08-29T08:45:04.346554+00:00, sha b3ced55b80af)
  - site_page: https://fly.io/docs/getting-started/launch-demo (fetched 2026-08-29T08:45:04.348155+00:00, sha 808c5d60f526)
  - site_page: https://fly.io/docs/deep-dive (fetched 2026-08-29T08:45:04.350183+00:00, sha cca09878688f)
  - site_page: https://fly.io/docs/getting-started/get-started-by-framework (fetched 2026-08-29T08:45:04.351970+00:00, sha 7945e49b5041)
  - site_page: https://fly.io/pricing (fetched 2026-08-29T08:45:04.343007+00:00, sha 01c2f0d6b1a2)
- Data as of 2026-08-30T08:39:29.467469+00:00.