Photofield

A self-hosted non-invasive single-binary photo gallery with a focus on speed and simplicity.

Demo · Quick Start · Docs

About

Zoom to logo within a sample of 43k images from open-images-dataset, i7-5820K 6-Core CPU, NVMe SSD

Photofield is a photo viewer built to mainly push the limits of what is possible in terms of the number of photos visible at the same time and at the speed at which they are displayed. The goal is to be as fast or faster than Google Photos on commodity hardware while displaying more photos at the same time. It is non-invasive and can be used either completely standalone or complementing other photo gallery software.

Features

• Seamless zoomable interface. Every view is zoomable if you ever need to see just a little more detail.

  

• Progressive multi-resolution loading. The whole layout is progressively loaded from a low-res preview to a full quality photo.

  

• Different layouts. Collections of photos can be displayed with different layouts.

• Semantic search using photofield-ai. If enabled, you can search for photo contents using words like "beach sunset", "a couple kissing", or "cat eyes".

• Tagging (alpha). You can tag and search photos with arbitrary tags. If enabled, tags are stored in the cache database and can be used to filter photos.

• Face detection (alpha). Detect and display individual faces in your photos using photofield-ai. The Faces layout shows detected face crops, and you can search by face ID.

• Reverse geolocation. Local, embedded reverse geolocation of ~50 thousand places via tinygpkg with negligible overhead supported in the Timeline and Flex layouts.

• Flexible media/thumbnail system. Stores small thumbnails using SQLite, uses FFmpeg for on-the-fly format conversion, extracts embedded thumbnails from JPEG files, re-uses Synology Moments / Photo Station thumbnails, and uses djpeg (libjpeg-turbo) to efficiently decode lower resolutions.

• Single file binary. The server is a single static binary with optional dependencies for easy and flexible deployment (Docker images also available).

• Read-only file system based collections. The original files are not touched. You are encouraged to even mount your photos as read-only to ensure this. The file system is the source of truth, everything else is just a more or less stale cache.

• Fast indexing. Thanks to godirwalk, file indexing practically runs at the speed of the file system 1000-10000 files/sec on fast SSD and hot cache. EXIF metadata and prominent color are extracted as separate follow-up operations and run at up to ~200 files/sec and ~1000 files/sec on a fast system.

• Video support. Videos are supported along with multiple resolutions (if as pre-generated by e.g. Synology Moments), however on-the-fly transcoding is not supported.

Limitations

• Not optimized for many clients. As a lot of the normally client-side state is kept on the server, you will likely run into CPU or Memory problems with more than a few simultaneous users.
• No user accounts. Not the focus right now. You can define separate collections for separate users based on the directory structure, but there is no authentication or authorization support.
• Initial load can be slow. All the photos need to be laid out when you first load a page in a specific window size and configuration, which can take some time with a slow CPU and cold HDD cache.
• No permalinks. Deep linking to images works, however if you remove the database or move the files around, the links may break.

See the documentation for more information.

Built With

• Go - API and server-side tile rendering
• Canvas (tdewolff) - vector rendering in Go
• SQLite 3 (zombiezen) - fast single-file database/cache
• Vue 3 - frontend framework
• BalmUI - Material UI components
• OpenLayers - in-browser tiled image rendering
• OpenSeadragon (honorary mention) - tiled image rendering library used in the past
• + more Go libraries
• + more npm libraries

Getting Started

Docker

Make sure you create an empty data directory in the working directory and that you put some photos in a photos directory.

docker run -p 8080:8080 -v "$PWD/data:/app/data" -v "$PWD/photos:/app/photos:ro" ghcr.io/smilyorg/photofield

The cache database will be persisted to the data dir and the app should be accessible at http://localhost:8080. It should show the photos collection by default. For further configuration, create a configuration.yaml in the data dir.

version: '3.3'
services:

  photofield:
    image: ghcr.io/smilyorg/photofield:latest
    ports:
      - 8080:8080
    volumes:
      - /volume1/docker/photofield/data:/app/data
      - /volume1/photo/:/photo:ro
      - /volume1/homes/ExampleUser/Drive/Moments:/exampleuser:ro

Binaries

1. Download and unpack a release.
2. Run ./photofield or double-click on photofield.exe to start the server.
3. Open http://localhost:8080, folders in the working directory will be displayed as collections. 🎉

• 📝 Create a configuration.yaml in the working dir to configure the app
• 🕵️‍♀️ Install exiftool and add it to PATH for better metadata support (esp. for video)
• ⚡ Install djpeg (libjpeg-turbo) for faster JPEG processing (optional but recommended)
• ⚪ Set environment variables to override defaults:
  • PHOTOFIELD_ADDRESS=:1200 – listen on a different port (default :8080)
  • PHOTOFIELD_DATA_DIR=/path/to/data – change the directory where configuration.yaml and the cache databases are stored

Configuration

You can configure the app via configuration.yaml.

The location of the file depends on the installation method, see Getting Started.

The following is a minimal configuration.yaml example, see defaults.yaml for all options.

collections:
  # Normal Album-type collection
  - name: Vacation Photos
    dirs:
      - /photo/vacation-photos

  # Timeline collection (similar to Google Photos)
  - name: My Timeline
    layout: timeline
    dirs:
      - /photo/myphotos
      - /exampleuser

  # Create collections from sub-directories based on their name
  - expand_subdirs: true
    expand_sort: desc
    dirs:
      - /photo

Development Setup

Prerequisites

• Go - for the backend / API server
• Node.js - for the frontend
• Task - to run common commands conveniently via Taskfile
• watchexec - for auto-reloading the Go server
• exiftool - for testing metadata extraction
• djpeg (libjpeg-turbo) - for optimized JPEG decoding (optional but recommended for better performance)

Scoop (Windows): scoop install go-task exiftool watchexec

Installation

1. Clone the repo

   git clone https://github.com/smilyorg/photofield.git
   

2. Install Go dependencies

   go get
   

3. Install NPM packages

   cd ui
   npm install
   

Running

Run both the API server and the UI server in separate terminals. They are set up to work with each other by default with the API server running at port 8080 and the UI server on port 5173.

task is Task as defined in the prerequisites.

API

• task watch the source files and auto-reload the server using watchexec
• or task run the server

UI

• task ui to start a hot-reloading development server
• or run from within the ui folder

  cd ui
  npm run dev
  

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

License

Distributed under the MIT License. See LICENSE for more information.

Acknowledgements

• Open Images Dataset
• geoBoundaries for geographic boundary data used for reverse geolocation
• sams96/rgeo for previous reverse geolocation implementation and inspiration
• Best-README-Template
• readme.so