PhotoStructure on Raspberry Pi

PhotoStructure on Raspberry Pi

The Raspberry Pi is a power-efficient single-board computer. Both the Pi 4 and Pi 5 can serve the web-based UI and import your library at the same time. The Pi 4 runs 4–10× slower than a modern laptop or desktop; the Pi 5 is fast enough that most libraries import without much pain.

PhotoStructure requires at least 2GB of RAM on a Raspberry Pi.

If you have a large library (50,000+ images) and a faster computer available, consider doing your initial import there and then moving the library to your Pi. Moving PhotoStructure to a new computer explains how.

🥧 PhotoStructure tries to be nice to your Pi

PhotoStructure detects that you’re running on a Raspberry Pi and automatically disables its more expensive features to help imports go 10× faster. It also extends timeout settings to match the slower processing times on Pi hardware.

These disabled features are a compromise:

  • invalid JPEG, Raw, and video files may be imported into your library, as they won’t be validated for bitrot
  • browsing will require more network bandwidth due to larger, less-optimally-encoded preview images
  • preview images will look a bit blurry, as they haven’t been sharpened after reduction
  • non-mp4-encoded videos will not be viewable, as they haven’t been transcoded
  • images missing metadata won’t be repaired by inference from sibling files

If you’re patient and don’t mind slow imports, set PS_QUICK_SYNC_MODE=false to keep these features enabled.

Features disabled by PS_QUICK_SYNC_MODE:

  • validateJpegImages
  • validateRawImages
  • validateVideos
  • transcodeVideos
  • previewMinimized
  • previewProgressive
  • previewSharpen
  • inferenceSiblingRadius (set to 0)

Read more about advanced settings here.

Install!

PhotoStructure’s Docker images include native linux/arm64 builds. Use the Docker Compose Wizard to generate a compose.yaml, then follow the Docker reference for bind mounts, permissions, and networking.

The Node edition also runs on arm64 if you prefer to manage your own Node.js runtime.