# Immich **High performance self-hosted photo and video backup solution.** ![](https://media.giphy.com/media/y8ZeaAigGmNvlSoKhU/giphy.gif) 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=
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. # 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.