# sublimehq/anim_encoder

Repository: https://github.com/sublimehq/anim_encoder
Canonical: https://ross.abutalabs.com/products/anim_encoder
Language: Python
License Family: other
Last push: 2021-04-29T18:37:11+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 5098, "days_push": 1952, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1433, forks 147 (observed 2026-08-28T04:04:43.222769+00:00)

## What it is
A Python CLI tool from Sublime HQ that converts a series of PNG screenshots into small JavaScript+HTML animations. It includes a capture script for recording frames and a configurable encoder pipeline built on OpenCV, NumPy, and SciPy.

## Use cases
- convert png frames into a lightweight html animation
- record screen frames and encode them as javascript animation
- create small animated demos without gif files
- compress a sequence of images into an embeddable animation
- capture screenshots of a task and turn them into a web animation

## When to choose
- you need tiny file-size animations instead of large GIFs
- you want a simple scriptable pipeline from PNG frames to HTML
- you're embedding animated demos in documentation or web pages

## When to avoid
- you need standard GIF or video output formats
- you want a GUI-based animation tool
- you need actively maintained software with ongoing support

## Facets
- artifact type: cli-tool
- maturity: maintenance
- function: image-processing, video-processing, cli
- domain: graphics, web-development, media
- platform: python, cross-platform, cli
- tags: animation, png-to-html, opencv, frame-capture, javascript-animation, linux

## Member repositories
- sublimehq/anim_encoder (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:43.222769+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 2026-08-30T04:36:58.555475+00:00, confidence not recorded.
  - readme: https://github.com/sublimehq/anim_encoder (fetched 2026-08-28T04:04:43.222769+00:00, sha 25d963e78f3a)
- Data as of 2026-08-30T08:39:29.467469+00:00.