![Discord][discord]

LibrePhotos

_{Mockup designed by rawpixel.com / Freepik}

A self-hosted, open-source photo management service with automatic face recognition, object detection, and semantic search — powered by modern machine learning.

Repository layout

This is a monorepo that consolidates what was previously five separate repositories.

| Path | What it is | Previous repo | |---|---|---| | apps/backend/ | Django 5 API, machine-learning pipelines, background jobs | librephotos | | apps/frontend/ | React 18 + Vite web client, i18next localization | librephotos-frontend | | apps/mobile/ | Expo mobile app (Android and iOS), offline-first | librephotos-mobile | | apps/docs/ | Docusaurus site published to https://docs.librephotos.com | librephotos.docs | | deploy/ | Dockerfiles, Compose configs, proxy, Kubernetes manifests | librephotos-docker |

Commit history from all five repositories is preserved — git log --follow apps// works across the move.

Installation

Step-by-step installation instructions are available in our documentation.

System Requirements

| Resource | Minimum | Recommended | |----------|---------|-------------| | RAM | 4 GB | 8 GB+ | | Storage | 10 GB (plus your photo library) | SSD recommended | | CPU | 2 cores | 4+ cores | | OS | Any Docker-compatible OS | Linux |

Note: Machine learning features (face recognition, scene classification, image captioning) are memory-intensive. 8 GB+ RAM is strongly recommended for smooth operation.

Features

- Support for all types of photos including raw photos - Support for videos - Timeline view - Scans pictures on the file system - Multiuser support - Generate albums based on events like "Thursday in Berlin" - Face recognition / Face classification - Reverse geocoding - Object / Scene detection - Semantic image search - Search by metadata

Tech Stack

Backend

• Framework: Django 5 with Django REST Framework
• Database: PostgreSQL
• Task Queue: Django-Q2
• RAW Conversion: LibRaw via rawpy
• Video Conversion: FFmpeg
• Exif Support: ExifTool

Frontend

• UI: React 18 with TypeScript
• Build Tool: Vite
• Component Library: Mantine
• Routing: TanStack Router
• Data Fetching: TanStack Query
• Maps: MapLibre GL
• Internationalization: i18next

Machine Learning

• Face detection: InsightFace
• Face classification/clustering: scikit-learn and hdbscan
• Image captioning: LFM2.5-VL, prompted with the recognised people and the place
• Tagging: MobileCLIP-S2 or SigLIP 2
• Semantic search: CLIP ViT-B/32 with FAISS
• ML runtime: ONNX Runtime for every model, no PyTorch
• Reverse geocoding: geopy

Infrastructure

• Deployment: Docker & Docker Compose
• Reverse Proxy: Nginx

API Documentation

After starting LibrePhotos, interactive API docs are available at:

• Swagger UI: http://localhost:3000/api/swagger
• ReDoc: http://localhost:3000/api/redoc

Development

See CONTRIBUTING.md and the per-app READMEs:

• Backend
• Frontend
• Mobile
• Docs site

How to help out

• ⭐ Star this repository if you like this project!
• 🚀 Developing: Get started in less than 30 minutes by following this guide. Also see our CONTRIBUTING.md for detailed development setup, code quality standards, and PR guidelines.
• 🗒️ Documentation: Improving the documentation is as simple as submitting a pull request here
• 🧪 Testing: If you want to help find bugs, use the ``dev`` tag and update it regularly. If you find a bug, open an issue.
• 🧑‍🤝‍🧑 Outreach: Talk about this project with other people and help them to get started too!
• 🌐 Translations: Make LibrePhotos accessible to more people with weblate.
• 💸 Donate to the developers of LibrePhotos

License

This project is licensed under the MIT License.

[discord]: https://discord.gg/xwRvtSDGWb