# liyong03/YLGIFImage

Async GIF image decoder and Image viewer supporting play GIF images. It just use very less memory.

Repository: https://github.com/liyong03/YLGIFImage
Canonical: https://ross.abutalabs.com/products/ylgifimage
Language: Objective-C
License: MIT
License Family: permissive
Last push: 2020-12-19T01:04:07+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": 4567, "days_push": 2084, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1764, forks 199 (observed 2026-08-28T04:05:32.985816+00:00)

## What it is
An Objective-C library providing an asynchronous GIF decoder (YLGIFImage) and a UIView-based player (YLImageView) for iOS. It decodes GIF frames on demand to drastically reduce memory usage compared to fully decoded GIFs.

## Use cases
- play animated GIFs in an iOS app with low memory usage
- display large GIF files without crashing on memory
- asynchronously decode GIF frames in Objective-C
- show GIF animations in a UIImageView-like view
- reduce memory footprint when rendering GIFs on iOS

## When to choose
- you need to display GIFs in an Objective-C iOS app with minimal memory overhead
- large GIFs crash your app when fully decoded
- you want a simple drop-in GIF player via CocoaPods

## When to avoid
- you are building in Swift and prefer a native Swift implementation (use YLGIFImage-Swift instead)
- you need animated image support beyond GIF (e.g., APNG, WebP)
- you target modern iOS where SDWebImage or SwiftUI-based solutions suffice

## Facets
- artifact type: library
- maturity: maintenance
- function: image-processing, ui-components
- domain: mobile-development, graphics
- platform: c
- tags: gif, objective-c, uikit, memory-efficient, animation, ios, swift

## Member repositories
- liyong03/YLGIFImage (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:32.985816+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 2026-08-30T03:26:38.674292+00:00, confidence not recorded.
  - readme: https://github.com/liyong03/YLGIFImage (fetched 2026-08-28T04:05:32.985816+00:00, sha d1f7f2262e35)
- Data as of 2026-08-30T08:39:29.467469+00:00.