# Immich
**High performance self-hosted photo and video backup solution.**
Loading ~4000 images/videos
## Screenshots
### Mobile
### Web
# Note
**!! NOT READY FOR PRODUCTION! DO NOT USE TO STORE YOUR ASSETS !!**
This project is under heavy development, there will be continuous functions, features and api changes.
# Features
| | Mobile | Web |
| - | - | - |
| Upload and view videos and photos | Yes | Yes
| Auto backup when 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
| Shared Albums | Yes | No
| 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) | No | Yes
# System Requirement
**OS**: Preferred unix-based operating system (Ubuntu, Debian, MacOS...etc).
I haven't tested with `Docker for Windows` as well as `WSL` on Windows
*Raspberry Pi can be used but `microservices` container has to be comment out in `docker-compose` since TensorFlow has not been supported in Docker image on arm64v7 yet.*
**RAM**: At least 2GB, preffered 4GB.
**Core**: At least 2 cores, preffered 4 cores.
# Getting Started
You can use docker compose for development and testing out the application, there are several services that compose Immich:
1. **NestJs** - Backend of the application
2. **SvelteKit** - Web frontend of the application
3. **PostgreSQL** - Main database of the application
4. **Redis** - For sharing websocket instance between docker instances and background tasks message queue.
5. **Nginx** - Load balancing and optimized file uploading.
6. **TensorFlow** - Object Detection (COCO SSD) and Image Classification (ImageNet).
## Step 1: 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.
**Example**
```bash
###################################################################################
# Database
###################################################################################
DB_USERNAME=postgres
DB_PASSWORD=postgres
DB_DATABASE_NAME=immich
###################################################################################
# Upload File Config
###################################################################################
UPLOAD_LOCATION=
###################################################################################
# JWT SECRET
###################################################################################
JWT_SECRET=randomstringthatissolongandpowerfulthatnoonecanguess
###################################################################################
# MAPBOX
####################################################################################
# ENABLE_MAPBOX is either true of false -> if true, you have to provide MAPBOX_KEY
ENABLE_MAPBOX=false
MAPBOX_KEY=
###################################################################################
# WEB
###################################################################################
# This is the URL of your vm/server where you host Immich, so that the web frontend
# know where can it make the request to.
# For example: If your server IP address is 10.1.11.50, the environment variable will
# be VITE_SERVER_ENDPOINT=http://10.1.11.50:2283/api
VITE_SERVER_ENDPOINT=http://192.168.1.216:2283/api
```
## Step 2: Start the server
To **start**, run
```bash
docker-compose -f ./docker/docker-compose.yml up
```
To *update* docker-compose with newest image (if you have started the docker-compose previously)
```bash
docker-compose -f ./docker/docker-compose.yml pull && docker-compose -f ./docker/docker-compose.yml up
```
The server will be running at `http://your-ip:2283/api`
## Step 3: Register User
Access the web interface at `http://your-ip:2283` to register an admin account.
Additional accounts on the server can be created by the admin account.
## Step 4: Run mobile app
Login the mobile app with your server address
## F-Droid
You can get the app on F-droid by clicking the image below.
[
](https://f-droid.org/packages/app.alextran.immich)
## Android
#### Get the app on Google Play Store [here](https://play.google.com/store/apps/details?id=app.alextran.immich)
*The App version might be lagging behind the latest release due to the review process.*
## iOS
#### Get the app on Apple AppStore [here](https://apps.apple.com/us/app/immich/id1613945652):
*The App version might be lagging behind the latest release due to the review process.*
# Development
The development environment can be started from the root of the project after populating the `.env` file with the command:
```bash
make dev # required Makefile installed on the system.
```
All servers and web container are hot reload for quick feedback loop.
## Note for developers
### 1 - OpenAPI
OpenAPI is used to generate the client (Typescript, Dart) SDK. `openapi-generator-cli` can be installed [here](https://openapi-generator.tech/docs/installation/). When you add a new or modify an existing endpoint, you must run the generate command below to update the client SDK.
```bash
npm run api:generate # Run from server directory
```
You can find the generated client SDK in the [`web/src/api`](web/src/api) for Typescript SDK and [`mobile/openapi`](mobile/openapi) for Dart SDK.
# 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 Sponsor**](https://github.com/sponsors/alextran1502), or a one time donation with the Buy Me a coffee link below.
[](https://www.buymeacoffee.com/altran1502)
This is also a meaningful way to give me motivation and encouragement to continue working on the app.
Cheers! 🎉
# 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 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`:
```bash
more /proc/cpuinfo | grep flags
```
If you are running virtualization in Promox, 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`
Otherwise you can:
- edit `docker-compose.yml` file and comment the whole `immich-machine-learning` service **which will disable machine learning features like object detection and image classification**
- switch to a different VM/desktop with different architecture.