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Case StudyDeveloper

ImgNet

ImgNet is a web app built to make image workflows simple for teams. It combines a friendly upload and browsing experience with backend services that handle tagging, storage, and delivery. The goal was to let people focus on their creative work while the platform takes care of the plumbing.

ImgNet hero
Stack
Next.js, Node.js, Python, TensorFlow
Focus
Real-time AI tagging

ImgNet — Image management for teams who move fast

Overview ImgNet is a web app built to make image workflows simple for teams. It combines a friendly upload and browsing experience with backend services that handle tagging, storage, and delivery. The goal was to let people focus on their creative work while the platform takes care of the plumbing.

Key features

  • User authentication (signup, signin, verification) and per-user profiles.
  • Image upload, card-based browsing, and basic asset management (edit, delete, metadata).
  • Admin panel with user management and coupon tools for administrative tasks.
  • Dashboard and profile pages for a personalized experience.
  • Responsive UI and a theme toggle for light/dark modes.
  • Clear error handling and helpful feedback for users.

Tech stack

  • Frontend: React + TypeScript
  • Styling: Tailwind CSS, PostCSS
  • Build: Vite for fast local iteration
  • State: React Context for lightweight shared state
  • APIs: Custom services for backend communication and integrations

Implementation highlights

  • Modular component structure kept the UI easy to maintain and extend.
  • Context-based theming allowed a single source of truth for light/dark modes.
  • Admin features were separated into their own routes and guards to keep concerns isolated.
  • Routing and asset handling were optimized so large galleries stay snappy.

Challenges & solutions

  • Performance: Large image sets were slowing initial loads — solved by lazy-loading assets, code-splitting, and using Vite’s fast HMR for development.
  • UX polish: Upload flows needed to feel fast and forgiving — we added progress indicators, retry logic, and clear validations.
  • Scalability: As the feature set grew, we kept clear boundaries between UI, state, and network layers so future backend or storage changes are low-friction.

Conclusion ImgNet is a practical, team-focused image platform: easy for creators to use, and engineered so developers can integrate and scale it. It’s intentionally modular, so the experience can be tuned to different products and workflows without rewiring the whole app.