# GarrettGunnell/AcerolaFX

A suite of GShade shaders for Final Fantasy XIV

Repository: https://github.com/GarrettGunnell/AcerolaFX
Canonical: https://ross.abutalabs.com/products/acerolafx
Language: HLSL
License: MIT
License Family: permissive
Last push: 2024-06-29T14:04:46+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 1556, "days_push": 795, "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 1269, forks 51 (observed 2026-08-28T04:04:11.707103+00:00)

## What it is
A modular HDR post-processing shader suite written in HLSL for GShade, targeting Final Fantasy XIV gameplay and gpose screenshots. It provides customizable effects like contrast-adaptive sharpening, exposure, ambient occlusion, and Kuwahara filtering.

## Use cases
- enhance Final Fantasy XIV gameplay visuals with post-processing shaders
- improve gpose screenshot quality in FFXIV
- apply HDR post-processing effects to a game
- customize a modular shader pipeline for GShade
- add ambient occlusion and sharpening effects to FFXIV

## When to choose
- you play Final Fantasy XIV and want better visuals or screenshots
- you use GShade and want a modular, customizable post-processing pipeline
- you want community-maintained shaders with per-effect configurability

## When to avoid
- you need shaders for a game other than Final Fantasy XIV
- you don't use GShade or a compatible shader loader
- you want a general-purpose image editing tool rather than real-time game shaders

## Facets
- artifact type: plugin
- maturity: active
- function: image-processing, graphics
- domain: gaming-tools, graphics, media
- platform: windows, cross-platform
- tags: gshade, final-fantasy-xiv, post-processing, shaders, hlsl, hdr, gaming

## Member repositories
- GarrettGunnell/AcerolaFX (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:11.707103+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 2026-08-30T05:03:29.902117+00:00, confidence not recorded.
  - readme: https://github.com/GarrettGunnell/AcerolaFX (fetched 2026-08-28T04:04:11.707103+00:00, sha f5c3dd7584d3)
- Data as of 2026-08-30T08:39:29.467469+00:00.