photoprism/docker/examples/armv7/README

54 lines
2.7 KiB
Text

# Running PhotoPrism on an older Raspberry Pi or other ARMv7-based devices (32-bit)
If your device meets the system requirements, mostly the same installation instructions as for regular Linux
servers apply:
https://docs.photoprism.org/getting-started/docker-compose/
Use `photoprism/photoprism:armv7` for the stable release or `photoprism/photoprism:armv7-preview` for testing
preview builds. Make sure to explicitly pull the most recent image from Docker Hub. Existing users are advised to
update their `docker-compose.yml` config based on our example:
https://dl.photoprism.org/docker/armv7/docker-compose.yml
You also have to revert to an alternative image if they want to use MariaDB, for example:
https://hub.docker.com/r/linuxserver/mariadb
The [official image](https://hub.docker.com/_/mariadb) is available for AMD64 and ARM64 only.
Pay close attention to changed directory and environment variable names.
### System Requirements ###
- Your device should have at least 4 GB of memory. Running PhotoPrism on a server with less than 4 GB of swap space
or setting a memory/swap limit can cause unexpected restarts, especially when the indexer temporarily needs more
memory to process large files.
- If you see Docker errors related to "cgroups", it may help to add the following to `/boot/firmware/cmdline.txt`:
```
cgroup_enable=cpuset cgroup_enable=memory cgroup_memory=1
```
- We recommend disabling Linux kernel security in your `docker-compose.yml`, especially if you do not have experience
with the configuration:
```yaml
photoprism:
security_opt:
- seccomp:unconfined
- apparmor:unconfined
```
- If you install PhotoPrism on a public server outside your home network, please always run it behind a secure
HTTPS reverse proxy such as Traefik, Caddy, or NGINX. Your files and passwords will otherwise be transmitted in
clear text and can be intercepted by anyone, including your provider, hackers, and governments.
!!! Note
Indexing large photo and video collections significantly benefits from fast, local SSD storage,
and plenty of memory for caching. Especially the conversion of RAW images and the transcoding of
videos are very demanding.
!!! Reducing System Load
If you're running out of memory - or other system resources - while indexing, try reducing the
[number of workers](https://docs.photoprism.org/getting-started/config-options/) by setting
`PHOTOPRISM_WORKERS` to a reasonably small value in `docker-compose.yml` (depending on the performance of the server).
As a measure of last resort, you may disable using TensorFlow for image classification and facial recognition.
Big thank you to [Guy Sheffer](https://github.com/guysoft)
for [building](https://github.com/photoprism/photoprism/issues/109) this!