Self-hosted photo and video backup solution directly from your mobile phone.
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License: MIT

Immich - High performance self-hosted photo and video backup solution



Disclaimer

  • ⚠️ The project is under very active development.
  • ⚠️ Expect bugs and breaking changes.
  • ⚠️ Do not use it as the only way to store your photos and videos!

Content

Documentation

You can find the main documentation, including installation guides, at https://immich.app/.

Demo

You can access the web demo at https://demo.immich.app

For the mobile app, you can use https://demo.immich.app/api for the Server Endpoint URL

The credential
email: demo@immich.app
password: demo
Spec: Free-tier Oracle VM - Amsterdam - 2.4Ghz quad-core ARM64 CPU, 24GB RAM

Features

Features Mobile Web
Upload and view videos and photos Yes Yes
Auto backup when the app is opened Yes N/A
Selective album(s) for backup Yes N/A
Download photos and videos to local device Yes Yes
Multi-user support Yes Yes
Album Yes Yes
Shared Albums Yes Yes
Quick navigation with draggable scrollbar Yes Yes
Support RAW (HEIC, HEIF, DNG, Apple ProRaw) Yes Yes
Metadata view (EXIF, map) Yes Yes
Search by metadata, objects and image tags Yes No
Administrative functions (user management) N/A Yes
Background backup Android N/A
Virtual scroll N/A Yes

Support the project

I've committed to this project, and I will not stop. I will keep updating the docs, adding new features, and fixing bugs. But I can't do it alone. So I need your help to give me additional motivation to keep going.

As our hosts in the selfhosted.show - In the episode 'The-organization-must-not-be-name is a Hostile Actor' said, this is a massive undertaking of what the team and I are doing. And I would love to someday be able to do this full-time, and I am asking for your help to make that happen.

If you feel like this is the right cause and the app is something you are seeing yourself using for a long time, please consider supporting the project with the option below.

Donation

Known Issues

TensorFlow Build Issue

This is a known issue for incorrect Proxmox setup

TensorFlow doesn't run with older CPU architecture, it requires a CPU with AVX and AVX2 instruction set. If you encounter the error illegal instruction core dump when running the docker-compose command above, check for your CPU flags with the command and make sure you see AVX and AVX2:

more /proc/cpuinfo | grep flags

If you are running virtualization in Proxmox, the VM doesn't have the flag enabled.

You need to change the CPU type from kvm64 to host under VMs hardware tab.

Hardware > Processors > Edit > Advanced > Type (dropdown menu) > host