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Stash Sense

ML-powered performer identification and library curation for Stash.

What It Does

  • Identifies performers in scenes and images using face recognition against a database of 108,000+ performers sourced from multiple Stash-Box endpoints
  • Tags scenes from Stash-Box by searching untagged scenes across Stash-Box endpoints using file fingerprints
  • Detects duplicate scenes using face fingerprints, Stash-Box IDs, and metadata overlap — catches duplicates that phash matching misses
  • Syncs upstream changes from Stash-Box endpoints with per-field merge controls for performers, studios, and scenes
  • Runs locally on your hardware — no cloud dependencies, no data leaves your network

Getting Started

Stash Sense has three components that work together:

  • Stash — Your media organizer (already running). Stash Sense reads your library data and writes back performer tags, metadata updates, etc.
  • Stash Sense Sidecar — A Docker container running ML models and analysis engines. It connects to Stash via API key and handles all the heavy lifting (face recognition, upstream diffing, duplicate detection).
  • Stash Sense Plugin — Installed inside Stash, provides the UI (dashboard, settings, scene-level controls). It talks to the sidecar through a backend proxy.

Stash-Box endpoints (StashDB, FansDB, ThePornDB, etc.) are configured in Stash's Settings > Metadata Providers — the sidecar reads credentials from there automatically.

Next steps:

  • Installation — Docker setup, plugin install, database and model download
  • Configuration — environment variables, plugin settings, Stash-Box auto-discovery
  • Plugin Usage — navigating the dashboard, identifying performers, understanding results

Requirements

Component Requirement
Stash v0.25+
Docker With nvidia-container-toolkit for GPU acceleration
GPU NVIDIA with 4GB+ VRAM (Recommended) — not required, CPU fallback available
Disk ~2.5 GB for face recognition data, models, and working space
Generated content Some features require Stash-generated content — see each feature page for prerequisites

Generated content

Performer identification requires sprite sheets (Settings > Tasks > Generate > Sprites). Scene tagger requires perceptual hashes (Settings > Tasks > Generate > Perceptual Hashes). Details are on each feature's page under "Prerequisites."