Developer Builds Self-Hosted Photo Organizer with Face Recognition Using Open-Source Tools

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A software developer has built a fully self-hosted photo organization system that replicates Google Photos-style face grouping, running entirely on local hardware via Docker with no external API calls. The project combines a FastAPI service powered by InsightFace models for face detection and embedding generation, a Laravel dashboard for browsing and managing photos, and pgvector for fast vector similarity search. To avoid costly full re-clustering on every upload, the system uses incremental centroid matching, comparing new faces against existing cluster averages before flagging unknowns for review. Quality filters including blur scoring and face-size checks are applied before clustering to prevent poor embeddings from distorting results. The open-source project is split across three repositories and deployed via Docker Compose, making it reproducible for anyone wanting privacy-focused photo management on their own infrastructure.

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