Photofield

Experimental fast photo viewer.

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Table of Contents

1. About
   • Features
   • Limitations
   • Built With
2. Getting Started
3. Configuration
4. Usage
5. Maintenance
6. Development Setup
7. Contributing
8. License
9. Acknowledgements

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. Thanks to tiled image loading supported by OpenLayers and the API implementing tile rendering, you can switch between levels of detail seamlessly without loading a special detailed or fullscreen view.

  

• Progressive multi-resolution loading. Not only are thumbnails used to show a single photo quicker, the whole layout is progressively loaded, so even if you move through photos quickly or zoom around, you will almost always have some form of feedback to not lose track.

  

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

  • Album: chronological photos grouped by event
  • Timeline: reverse-chronological timeline similar to Google Photos
  • Wall: a square collage of all the photos, because zooming is fun!
  • Map: all the photos on a map? Sure!
  • More future ideas?

• Semantic search using photofield-ai (alpha). If you set up an AI server and configure it in the ai section of the configuration, you should be able to search for photo contents using words like "beach sunset", "a couple kissing", or "cat eyes".

• Tagging (alpha). You can tag photos with arbitrary tags. Currently tags are only stored in the database and not in the photos themselves. You need to enable them in the tags section of the configuration and restart the server. This forms a foundation for many other features, see below (checked - implemented).

  • Persistent photo selection. You can Ctrl+Click or Ctrl+Drag to select photos. This creates a new randomly generated "selection" tag that is persistent and shareable. It also means you can select tens of thousands of photos without losing your progress. These tags are currently never cleaned up and you can't do anything with it yet, so it's not useful yet, but it's a start.
  • Custom tags. You canadd your own tags to photos, e.g. #family or #vacation. Batch tagging not supported yet, but should be relatively easy to add considering the selections (above) are already tags.
  • EXIF tags. Tags are automatically added from the EXIF data, e.g. exif:make:sony or exif:model:sm-g950f. You need to enable this in the exif section of the configuration. Only make and model are currently supported (hardcoded).
  • Filter by tags. You can filter by a tag by searching for tag:TAG. For example, you can search for tag:fav to only show favorited photos, or tag:hello tag:world to only show photos with both hello and world tags. This is an early version of filtering and should be more user-friendly in the future.
  • Location tags. Photos could be automatically tagged with the location, e.g. city:berlin or country:germany. See #59.
  • Face recognition. Photos could be automatically tagged with the person's name. This would be a great way to search for photos of a specific person.

• Reverse geolocation. Local, embedded reverse geolocation via tinygpkg. Does not need any API calls, has negligible performance impact, and supports ~50 thousand places. Currently only supported for photos with GPS coordinates in the EXIF data and the Timeline view.

• Flexible media/thumbnail system. Do you have hundreds of gigabytes of existing thumbnails from an existing system? Me too! Let's reuse those. Don't have any? No worries, they will be generated automatically to speed up display. Here are the currently supported thumbnail sources:

  • Bespoke SQLite thumbnail database - photofield.thumbs.db.
  • Synology Moments / Photo Station auto-generated thumbnails in @eaDir.
  • Embedded JPEG thumbnails - ThumbnailImage Exif tag.
  • Native Go image package.
  • FFmpeg on-the-fly conversion - thumbnails and full sized variants.
  • Configurable via the sources section of the Configuration.
  • Please open an issue for other systems, bonus points for an idea on how to integrate!

• Single file binary. Thanks to Go and GoReleaser, all the dependencies are packed into a single binary file for most major OSes.

• Read-only file system based collections. Photofield never changes your photos, thumbnails or directories. 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.

• Basic video support. Videos are supported, however the user experience is not great yet as there are some usability quirks. Different resolutions are supported if they have been previously transcoded, but there is no on-the-fly transcoding supported right now.

Limitations

• No photo details (yet). There is no way to show metadata of a photo in the UI at this point.
• 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, but it's currently not stable over time as IDs can change.

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 previously
• + 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.

docker-compose.yaml example

This example binds the usual Synology Moments photo directories and assumes a certain path structure, modify to your needs graciously. It also assumes you have configured the /photo and /user directories as collections in the configuration.yaml.

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)
• ⚪ Set the PHOTOFIELD_DATA_DIR environment variable to change the path where the app looks for the configuration.yaml and cache database

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

Usage

This section will cover some obvious uses, but also some possibly unintuitive UI quirks that exist in the current version.

App Bar

Photo Viewer

• Click to zoom to a photo

  • Escape or pinch out to get back to the list of photos

• Zoom in/out directly with Ctrl/Cmd+Wheel

• Pinch-to-zoom on touch devices

• Press/hold Arrow Left or Arrow Right to quickly switch between photos

• Right-click or long-tap as usual to open a custom context menu allowing you to copy or download original photos or thumbnails.

  

  You can open/copy/copy link the original or access any existing thumbnails that already exist for it with the bottom list of thumbnails by pixel width.

Maintenance

Over time the cache database can grow in size due to version upgrades and so on. To shrink the database to its minimum size, you can vacuum it. Multiple vacuums in a row have no effect as the vacuum itself rewrites the database from the ground up.

While the vacuum is in progress, it will take twice the database size and may take several minutes if you have lots of photos and a low-power system.

As an example it took around 5 minutes to vacuum a 260 MiB database containing around 500k photos on a DS418play. The size after vacuuming was 61 MiB as all the leftover data from database upgrades was cleaned up.

# CLI
./photofield -vacuum

# Docker
docker exec -it photofield ./photofield -vacuum

Development Setup

Prerequisites

• Go - for the backend / API server
• Node.js - for the frontend
• just - to run common commands conveniently
• watchexec - for auto-reloading the Go server
• sh-like shell (e.g. sh, bash, busybox) - required by just
• exiftool - for testing metadata extraction

Scoop (Windows): scoop install busybox just 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 3000.

just is just as defined in the prerequisites.

API

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

UI

• just 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