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# Immich Self-hosted photo and video backup solution directly from your mobile phone. ![](https://media.giphy.com/media/y8ZeaAigGmNvlSoKhU/giphy.gif) Loading ~4000 images/videos ## Screenshots ### Mobile client

### Web client

# 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 - Upload and view assets (videos/images). - Auto Backup. - Download asset to local device. - Multi-user supported. - Quick navigation with drag scroll bar. - 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 - Selective backup - albums can be included and excluded during the backup process. - Web interface is available for administrative tasks (creating new users) and viewing assets on the server - additional features are coming. # 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 and Image Classification. ## 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 VITE_SERVER_ENDPOINT=http://192.168.1.216:2283 ``` ## Step 2: Start the server To **start**, run ```bash docker-compose -f ./docker/docker-compose.yml up ``` If you have a few thousand photos/videos, I suggest running docker-compose with *scaling* option for the `immich_server` container to handle high I/O load when using fast scrolling. ```bash docker-compose -f ./docker/docker-compose.yml up --scale immich-server=5 ``` 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` through `Nginx` ## Step 3: Register User Access the web interface at `http://your-ip:2285` to register an admin account.

Additional accounts on the server can be created by the admin account.

## Step 4: Run mobile app The app is distributed on several platforms below. ## F-Droid You can get the app on F-droid by clicking the image below. [Get it on F-Droid](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. # 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. [!["Buy Me A Coffee"](https://www.buymeacoffee.com/assets/img/custom_images/orange_img.png)](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.