.github | ||
design | ||
docker | ||
fastlane | ||
machine_learning | ||
microservices | ||
mobile | ||
server | ||
.gitignore | ||
LICENSE | ||
Makefile | ||
PR_CHECKLIST.md | ||
README.md |
Immich
Self-hosted photo and video backup solution directly from your mobile phone.
Loading ~4000 images/videos
Screenshots
Note
!! NOT READY FOR PRODUCTION! DO NOT USE TO STORE YOUR ASSETS !!
This project is under heavy development, there will be continous functions, features and api changes.
Features
- Upload and view assets (videos/images).
- Download asset to local device.
- Multi-user supported.
- Quick navigation with drag scroll bar.
- Auto Backup.
- Support HEIC/HEIF Backup.
- Extract and display EXIF info.
- Real-time render from multi-device upload event.
- Image Tagging/Classification based on ImageNet dataset
- Object detection based on COCO SSD.
- Search assets based on tags and exif data (lens, make, model, orientation)
- [Optional] Reverse geocoding using Mapbox (Generous free-tier of 100,000 search/month)
- Show asset's location information on map (OpenStreetMap).
- Show curated places on the search page
- Show curated objects on the search page
- Shared album with users on the same server
Development
You can use docker compose for development, there are several services that compose Immich
- NestJs
- PostgreSQL
- Redis
- Nginx
- TensorFlow
Populate .env file
Navigate to docker
directory and run
cp .env.example .env
Then populate the value in there.
Notice that if set ENABLE_MAPBOX
to true
, you will have to provide MAPBOX_KEY
for the server to run.
Pay attention to the key UPLOAD_LOCATION
, this directory must exist and is owned by the user that run the docker-compose
command below.
To start, run
docker-compose -f ./docker/docker-compose.yml up --build -V
The server will be running at http://your-ip:2283
through Nginx
Register User
Use the command below on your terminal to create user as we don't have user interface for this function yet.
curl --location --request POST 'http://your-server-ip:2283/auth/signUp' \
--header 'Content-Type: application/json' \
--data-raw '{
"email": "testuser@email.com",
"password": "password"
}'
Run mobile app
F-Droid
You can get the app on F-droid by clicking the image below.
Android
Download the latest apk
in the release tab and run on your phone. You can follow this guide on how to do that
You can also download the app from Google Play Store here
The App version might be lagging behind the latest release due to the review process.
iOS
You can download the app from Apple AppStore here:
The App version might be lagging behind the latest release due to the review process.
Support
If you like the app, find it helpful, and want to support me to offset the cost of publishing to AppStores, you can sponsor the project with Github Sponsore.
This is also a meaningful way to give me motivation and encounragment to continue working on the app.
Cheer! 🎉
Known Issue
TensorFlow Build Issue
This is a known issue on RaspberryPi 4 arm64-v7 and incorrect Promox setup
TensorFlow doesn't run with older CPU architecture, it requires 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 Promox, the VM doesn't have the flag enable.
You need to change the CPU type from kvm64
to host
under VMs hardware tab.
Hardware > Processors > Edit > Advanced > Type (dropdown menu) > host
Otherwise you can:
- edit
docker-compose.yml
file and comment the wholeimmich_microservices
service which will disable machine learning features like object detection and image classification - switch to a different VM/desktop with different architecture.