Smart Photo Storage is a personal flagship project aimed at building a modern, intelligent photo management application. Unlike basic cloud storage apps, this system not only stores and organizes your photos but also uses machine learning to make them searchable through natural language queries like "family beach" or "birthday at night".
This project is designed to showcase real-world engineering skills across backend, ML integration, and scalable architecture — built to reflect production-quality complexity while still being achievable as a solo developer.
- Secure photo upload and storage
- Web-based gallery for browsing photos
- Natural language search for finding specific photos
- Machine learning model integration (image embedding, object detection, etc.)
- Asynchronous photo processing using message brokers
- Containerized microservices architecture
- ✅ Build a full-stack product from scratch
- ✅ Apply modern software engineering practices
- ✅ Learn and integrate ML models into a real-world scenario
- ✅ Design a scalable and maintainable system
- ✅ Create a strong showcase project for job applications
- Basic user auth and photo upload
- Photo listing & viewing in web UI
- Store metadata (e.g., upload time, tags) in database
- Dockerized backend and frontend setup
- Integrate image-to-text embedding model (e.g., CLIP/BLIP)
- Store image embeddings for fast semantic search
- Implement natural language photo search
- Add message broker (e.g., RabbitMQ/Kafka)
- Move ML processing to background workers
- Improve system scalability and modularity
- CI/CD setup (GitHub Actions or similar)
- Cloud deployment (e.g., Render / Railway / VPS)
- Record demo video and write developer blog
- Finalize README with diagrams and setup guide
This section will include:
- System architecture diagram
- ML pipeline diagram
- API and data flow overview
The specific stack is still being decided. Some technologies being considered include:
- Backend: Python, Node.js, Go
- Frontend: React, Vue, Svelte
- DB: PostgreSQL, MongoDB
- ML: OpenAI CLIP, BLIP, YOLO, OCR
- Broker: RabbitMQ, Kafka
All development progress and learnings will be tracked in this repo to document the journey.
This is a personal project under the MIT License.