photoprism/docker/examples/armv7
2022-04-06 17:46:41 +02:00
..
docker-compose.yml Config: Add option to skip all RAW images when indexing #2227 2022-04-06 17:46:41 +02:00
README Docker: Add newline to ARMv7 and ARM64 README heading 2022-03-02 16:13:00 +01:00

          >> Running PhotoPrism on ARMv7-based devices (32-bit) <<

You may use the following 32-bit Docker images to run PhotoPrism and MariaDB
on ARMv7-based devices:

  Stable Release     : photoprism/photoprism:armv7
  Development Preview: photoprism/photoprism:preview-armv7
  MariaDB            : linuxserver/mariadb:latest

Docker Hub URL:

  https://hub.docker.com/r/photoprism/photoprism/tags?page=1&name=armv7

Note that Darktable is not included in the ARMv7 image because it is not 32-bit
compatible. Always choose the regular 64-bit version if your device supports it.

If your device meets the system requirements, mostly the same installation
instructions as for regular Linux servers apply:

  https://docs.photoprism.app/getting-started/docker-compose/

Please pay close attention to changed directory and environment variable names!

Existing users are advised to check their "docker-compose.yml" against our examples
at <dl.photoprism.app/docker> from time to time in case there are new configuration
options or other improvements. Update instructions can be found at the bottom of
this README file.

### System Requirements ###

- Your device should have at least 3 GB of physical memory and a 64-bit operating
  system (always use our ARM64 image if possible)
- While PhotoPrism has been reported to work on devices with less memory, we take
  no responsibility for instability or performance problems
- RAW image conversion and TensorFlow are disabled on systems with 1 GB or
  less memory
- Indexing large photo and video collections significantly benefits from local SSD
  storage and plenty of memory for caching, especially the conversion of RAW
  images and the transcoding of videos are very demanding
- If less than 4 GB of swap space is configured or a manual memory/swap limit is
  set, this can cause unexpected restarts, for example, when the indexer
  temporarily needs more memory to process large files
- High-resolution panoramic images may require additional swap space and/or
  physical memory above the recommended minimum
- We recommend disabling kernel security in your docker-compose.yml, especially
  if you do not have experience with the configuration:
  ```
  photoprism:
    security_opt:
      - seccomp:unconfined
      - apparmor:unconfined
  ```
- If you install PhotoPrism on a public server outside your home network, always
  run it behind a secure HTTPS reverse proxy such as Traefik or Caddy:
  https://docs.photoprism.app/getting-started/proxies/traefik/

### Troubleshooting ###

If your server runs out of memory, the index is frequently locked, or other
system resources are running low:

- Try reducing the number of workers by setting PHOTOPRISM_WORKERS to a reasonably
  small value in docker-compose.yml, depending on the performance of your device
  or cloud server:

  https://docs.photoprism.app/getting-started/config-options/

- If you are using SQLite, switch to MariaDB, which is better optimized for
  high concurrency

- As a last measure, you can disable the use of TensorFlow for image
  classification and facial recognition

Other issues? Our troubleshooting checklists help you quickly diagnose and
solve them:

  https://docs.photoprism.app/getting-started/troubleshooting/

### Getting Updates ###

Open a terminal and change to the folder where the "docker-compose.yml" file
was saved. Now run the following commands to download the most recent image
from Docker Hub and restart your instance in the background:

  docker-compose pull --platform=arm photoprism
  docker-compose stop photoprism
  docker-compose up -d photoprism

Pulling a new version can take several minutes, depending on your internet
connection speed.

Note that running an image with ":latest" tag does not cause Docker to
automatically download new images.

### Credits ###

A big thank you to Guy Sheffer (https://github.com/guysoft) for helping us
build a Raspberry Pi version!