Self-hosted, AI-powered photo app to index, search, and organize your RAW and image library privately.
Organize, tag, and search RAW photos and videos on your own hardware without cloud lock-in.
PhotoPrism is a self-hosted web app that uses machine learning to automatically tag, map, and organize your photo collection. You can browse high-resolution RAW files, view hover-animated Live Photos, and sync mobile backups directly to your private server.
It extracts metadata from EXIF and XMP tags, runs facial recognition and object detection locally using TensorFlow, and builds searchable indexes by color, resolution, and location. It connects directly to your file system via WebDAV, letting you edit underlying files in desktop software like Finder or Windows Explorer.
It suits photographers who want complete control over their asset archives and prefer self-hosting on local servers or NAS devices. It does not suit casual users who want a zero-configuration cloud service without managing Docker containers.
Labels images based on content, visual composition, and detected facial features using local machine learning models.
Parses camera RAW files and renders animated previews for Live Photos when hovering over thumbnails.
Combines queries across color palettes, image quality scores, camera resolution, locations, and EXIF attributes.
Integrates with desktop file managers and tools like PhotoSync for automated background backups from mobile devices.
The core self-hosted Community Edition is completely free under the AGPL-3.0 licence. Optional paid memberships offer expanded perks such as interactive world maps, priority feature requests, and direct team support.
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Yes, PhotoPrism parses RAW formats alongside JPEG and video files, extracting metadata from EXIF and XMP sidecars.
No, AI classification and face recognition run locally on your server without sending media to third-party APIs.
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