Skip to content

Latest commit

 

History

History
103 lines (73 loc) · 3.45 KB

README.md

File metadata and controls

103 lines (73 loc) · 3.45 KB

PhotoGo

PhotoGo is an event-focused photo management and sharing application. It provides flexible gallery views, a focused image viewer, real-time activity, and tools for photographers to manage events and assets.

What PhotoGo offers

  • Gallery views: grid, masonry, and date-wise grouping for fast browsing.
  • Focused image viewer: two-column layout showing the image and a details panel with actions and metadata.
  • Likes and favourites: like photos and mark them as favourites.
  • Tagging and comments: tag users in photos and add comments; both support real-time updates.
  • Real-time notifications: WebSocket-based notifications for likes, tags, comments, and other activity.
  • Profile management: profile picture, bio, and basic account info.

PhotoGo

PhotoGo is an event-focused photo management and sharing application. It provides flexible gallery views, a two-column focused viewer, real-time activity, and tools for photographers to manage events and assets.

Highlights

  • Flexible gallery views: grid, masonry, and date-wise grouping.
  • Two-column viewer: image plus details panel with actions and metadata.
  • Interactions: likes, favourites, tagging, and comments.
  • Real-time notifications via WebSockets (Django Channels).
  • Background AI tag generation (Celery) and EXIF extraction.

Tech stack

  • Frontend: React + Vite
  • Backend: Django + Django REST Framework
  • Real-time: Django Channels
  • Background jobs: Celery (Redis)
  • Storage: AWS S3

Getting started (development)

  1. Create and activate a Python virtual environment:
python -m venv venv
.\venv\Scripts\activate
  1. Install backend dependencies:
pip install -r requirements.txt

3.Start a broker and a Celery worker:

redis-server
celery -A myproject.celery worker --loglevel=info
  1. Run migrations and start the Django server:
python manage.py migrate
python manage.py runserver
  1. Start the frontend dev server:
cd frontend
npm install
npm run dev

Useful commands

  • Run backend tests: python manage.py test
  • Run frontend dev: cd frontend && npm run dev
  • Build frontend assets: cd frontend && npm run build
  • Start Celery worker: celery -A myproject.celery worker --loglevel=info

API & features (summary)

  • Authentication: OTP registration and Omniport/OAuth entry points.
  • Photos: upload, download, properties, search, favourites, and tags.
  • Events: create/update/delete events and manage per-event upload access.
  • Interactions: toggle_like, toggle_favourite, add_comment, tagUser (with optional WebSocket notifications).
  • AI tags: background task that generates and stores ai_tags on the Photo model.

Watermarking

  • On upload, a background Celery task generates a watermarked JPEG containing the uploader's username and stores it.
  • Guests receive the watermarked image when they download a photo; members and other users receive the original image.
  • Watermark generation is asynchronous (Celery) and non-blocking; if watermarking fails the upload still completes and the original image remains available.

Real-time behavior

Notifications are sent through Channels to per-user groups. The client connects via WebSocket to receive toast notifications and the notification list.

Contributing

Fork the repo, create a feature branch, add tests, and open a pull request describing your changes.

Contact

Open an issue with reproduction steps and logs for support or feature requests.

Author

Rudra Pratap Singh