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LibrePhotos LibrePhotos/librephotos

Self-hosted photo library with face recognition, semantic search, timeline, map, shared albums and public links; Docker or Windows standalone.

LibrePhotos at a glance

Checked 16 Oct 2026

LibrePhotos (8.1k stars, 1.3.0 Oct 2026) scans your photo folders and uploads from its web and Expo mobile apps, then adds face detection and clustering, object tags, generated captions, semantic search, a timeline by day and place, a map, event albums, shared albums and public links. Code is MIT, but face detection uses InsightFace, whose pretrained models are non-commercial research only. Needs 4 GB RAM and 2 cores (8 GB recommended for ML). Runs as a single container, Docker Compose, Kubernetes or a Windows standalone build. Automatic phone backup is not documented.

Cite this pageRepoQuarry. “LibrePhotos.” Checked 16 Oct 2026. https://repoquarry.dev/projects/librephotos

How much of Google Photos does it replace?

3 of 4 jobs. Search, sharing and timeline/map; background phone backup is not documented.

No: Automatic phone photo and video backup Not covered
Partial: Search photos by faces Partial replacement
Partial: Shared albums and links Partial replacement
Partial: Timeline and map browsing Partial replacement

For automatic phone photo and video backup, see other Google Photos alternatives. You may also need to build an interface, an API server and hosting yourself.

Facts, with sources

Every answer links to where we found it. We read the documentation; we did not install it.

Report a correction
QuestionAnswerSourceChecked
Runs on my machine? Confirmed: Self-hosted (Docker, Compose, Kubernetes, Unraid) or Windows standalone one folder with `librephotos.exe`, no Docker or Python github.com · librephotos#installation ↗ today
Code licence Confirmed: MIT MIT License github.com · LICENSE ↗ today
Model weights licence No: Face detection uses InsightFace, whose pretrained models are non-commercial research only; captioning uses LFM2.5-VL (LFM licence); OpenCLIP is MIT The training data containing the annotation (and the models trained with these data) are available for non-commercial research purposes only. github.com · insightface#license ↗ today
Commercial use No: MIT code, but the InsightFace face models it relies on are non-commercial The training data containing the annotation (and the models trained with these data) are available for non-commercial research purposes only. github.com · insightface#license ↗ today
Paid services needed? Confirmed: None A self-hosted, open-source photo management service github.com · librephotos#readme ↗ today
Hardware Confirmed: Minimum 4 GB RAM, 2 cores, 10 GB storage plus library; 8 GB+ RAM recommended for ML 8 GB+ RAM is strongly recommended for smooth operation. github.com · librephotos#system-requirements ↗ today
Operating systems Confirmed: Any Docker-compatible OS (Linux recommended) or Windows standalone; Android and iOS app Any Docker-compatible OS, or Windows github.com · librephotos#system-requirements ↗ today
Setup effort Confirmed: Medium; single Docker container recommended, or Compose with optional NVIDIA GPU one image serves the API and the web app, recommended for most people github.com · librephotos#installation ↗ today

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