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221 lines
8.1 KiB
Markdown
221 lines
8.1 KiB
Markdown
<p align="center">
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<a href="https://opensource.org/licenses/MIT"><img src="https://img.shields.io/badge/license-MIT-green.svg?color=3F51B5&style=for-the-badge&label=License&logoColor=000000&labelColor=ececec" alt="License: MIT"></a>
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<a href="https://github.com/alextran1502/immich"><img src="https://img.shields.io/github/stars/alextran1502/immich.svg?style=for-the-badge&logo=github&color=3F51B5&label=Stars&logoColor=000000&labelColor=ececec" alt="Star on Github"></a>
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<a href="https://immichci.little-home.net/viewType.html?buildTypeId=Immich_BuildAndroidAndGetArtifact&guest=1">
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<img src="https://img.shields.io/teamcity/http/immichci.little-home.net/s/Immich_BuildAndroidAndGetArtifact.svg?style=for-the-badge&label=Android&logo=teamcity&logoColor=000000&labelColor=ececec" alt="Android Build"/>
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</a>
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<a href="https://immichci.little-home.net/viewType.html?buildTypeId=Immich_BuildAndPublishIOSToTestFlight&guest=1">
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<img src="https://img.shields.io/teamcity/http/immichci.little-home.net/s/Immich_BuildAndPublishIOSToTestFlight.svg?style=for-the-badge&label=iOS&logo=teamcity&logoColor=000000&labelColor=ececec" alt="iOS Build"/>
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</a>
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<a href="https://actions-badge.atrox.dev/alextran1502/immich/goto?ref=main">
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<img alt="Build Status" src="https://img.shields.io/endpoint.svg?url=https%3A%2F%2Factions-badge.atrox.dev%2Falextran1502%2Fimmich%2Fbadge%3Fref%3Dmain&style=for-the-badge&label=Server Docker&logo=docker&labelColor=ececec" />
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</a>
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<br/>
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<br/>
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<br/>
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<br/>
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<p align="center">
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<img src="design/immich-logo.svg" width="200" title="Immich Logo">
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</p>
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</p>
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# Immich
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Self-hosted photo and video backup solution directly from your mobile phone.
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Loading ~4000 images/videos
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## Screenshots
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<p align="left">
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<img src="design/login-screen.png" width="150" title="Login With Custom URL">
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<img src="design/backup-screen.png" width="150" title="Backup Setting Info">
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<img src="design/selective-backup-screen.png" width="150" title="Backup Setting Info">
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<img src="design/home-screen.jpeg" width="150" title="Home Screen">
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<img src="design/search-screen.jpeg" width="150" title="Curated Search Info">
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<img src="design/shared-albums.png" width="150" title="Shared Albums">
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<img src="design/nsc6.png" width="150" title="EXIF Info">
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</p>
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# Note
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**!! NOT READY FOR PRODUCTION! DO NOT USE TO STORE YOUR ASSETS !!**
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This project is under heavy development, there will be continous functions, features and api changes.
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# Features
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- Upload and view assets (videos/images).
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- Auto Backup.
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- Download asset to local device.
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- Multi-user supported.
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- Quick navigation with drag scroll bar.
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- Support HEIC/HEIF Backup.
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- Extract and display EXIF info.
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- Real-time render from multi-device upload event.
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- Image Tagging/Classification based on ImageNet dataset
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- Object detection based on COCO SSD.
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- Search assets based on tags and exif data (lens, make, model, orientation)
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- [Optional] Reverse geocoding using Mapbox (Generous free-tier of 100,000 search/month)
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- Show asset's location information on map (OpenStreetMap).
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- Show curated places on the search page
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- Show curated objects on the search page
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- Shared album with users on the same server
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- Selective backup - albums can be included and excluded during the backup process.
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# System Requirement
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**OS**: Preferred Linux-based operating system (Ubuntu, Debian, MacOS...etc).
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I haven't tested with `Docker for Windows` as well as `WSL` on Windows
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*Raspberry Pi can be used but `microservices` container has to be comment out in `docker-compose` since TensorFlow has not been supported in Dockec image on arm64v7 yet.*
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**RAM**: At least 2GB, preffered 4GB.
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**Core**: At least 2 cores, preffered 4 cores.
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# Development and Testing out the application
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You can use docker compose for development and testing out the application, there are several services that compose Immich:
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1. **NestJs** - Backend of the application
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2. **PostgreSQL** - Main database of the application
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3. **Redis** - For sharing websocket instance between docker instances and background tasks message queue.
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4. **Nginx** - Load balancing and optimized file uploading.
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5. **TensorFlow** - Object Detection and Image Classification.
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## Step 1: Populate .env file
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Navigate to `docker` directory and run
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```
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cp .env.example .env
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```
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Then populate the value in there.
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Notice that if set `ENABLE_MAPBOX` to `true`, you will have to provide `MAPBOX_KEY` for the server to run.
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Pay attention to the key `UPLOAD_LOCATION`, this directory must exist and is owned by the user that run the `docker-compose` command below.
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**Example**
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```bash
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# Database
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DB_USERNAME=postgres
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DB_PASSWORD=postgres
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DB_DATABASE_NAME=immich
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# Upload File Config
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UPLOAD_LOCATION=<put-the-path-of-the-upload-folder-here>
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# JWT SECRET
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JWT_SECRET=randomstringthatissolongandpowerfulthatnoonecanguess
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# MAPBOX
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## ENABLE_MAPBOX is either true of false -> if true, you have to provide MAPBOX_KEY
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ENABLE_MAPBOX=false
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MAPBOX_KEY=
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```
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## Step 2: Start the server
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To start, run
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```bash
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docker-compose -f ./docker/docker-compose.yml up
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```
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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.
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```bash
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docker-compose -f ./docker/docker-compose.yml up --scale immich_server=5
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```
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The server will be running at `http://your-ip:2283` through `Nginx`
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## Step 3: Register User
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Use the command below on your terminal to create user as we don't have user interface for this function yet.
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```bash
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curl --location --request POST 'http://your-server-ip:2283/auth/signUp' \
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--header 'Content-Type: application/json' \
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--data-raw '{
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"email": "testuser@email.com",
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"password": "password"
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}'
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```
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## Step 4: Run mobile app
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The app is distributed on several platforms below.
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## F-Droid
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You can get the app on F-droid by clicking the image below.
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[<img src="https://fdroid.gitlab.io/artwork/badge/get-it-on.png"
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alt="Get it on F-Droid"
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height="80">](https://f-droid.org/packages/app.alextran.immich)
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## Android
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#### Get the app on Google Play Store [here](https://play.google.com/store/apps/details?id=app.alextran.immich)
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*The App version might be lagging behind the latest release due to the review process.*
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<p align="left">
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<img src="design/google-play-qr-code.png" width="200" title="Google Play Store">
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<p/>
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## iOS
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#### Get the app on Apple AppStore [here](https://apps.apple.com/us/app/immich/id1613945652):
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*The App version might be lagging behind the latest release due to the review process.*
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<p align="left">
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<img src="design/ios-qr-code.png" width="200" title="Apple App Store">
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<p/>
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# Support
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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**](https://github.com/sponsors/alextran1502), or one time donation with Buy Me a coffee link below.
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[](https://www.buymeacoffee.com/altran1502)
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This is also a meaningful way to give me motivation and encounragment to continue working on the app.
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Cheer! 🎉
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# Known Issue
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## TensorFlow Build Issue
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*This is a known issue on RaspberryPi 4 arm64-v7 and incorrect Promox setup*
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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`:
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```bash
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more /proc/cpuinfo | grep flags
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```
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If you are running virtualization in Promox, the VM doesn't have the flag enable.
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You need to change the CPU type from `kvm64` to `host` under VMs hardware tab.
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`Hardware > Processors > Edit > Advanced > Type (dropdown menu) > host`
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Otherwise you can:
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- edit `docker-compose.yml` file and comment the whole `immich_microservices` service **which will disable machine learning features like object detection and image classification**
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- switch to a different VM/desktop with different architecture.
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