AI-powered wardrobe management system built on AWS serverless architecture, enabling users to store clothing items and generate AI-based outfit recommendations.
Wardrobe AI Platform is an AI-powered wardrobe management application originally developed during an AWS hackathon. The platform allows users to upload clothing images, organize them into a digital wardrobe, and receive outfit recommendations generated through AI.
This repository represents my personal portfolio version of the project, with a focus on backend architecture, AWS integration, and system design.
I focused on backend infrastructure and cloud integration, using AI-assisted development tools to accelerate implementation and debugging.
My contributions centered on integrating core AWS services and enabling data flow across the system:
- Configured AWS S3 for storing user-uploaded clothing images
- Structured DynamoDB tables for wardrobe data and AI-generated metadata
- Implemented backend logic using AWS Lambda
- Connected frontend and backend through API Gateway
- Used AWS Amplify to support deployment and service integration
AI tools were used to assist with code generation, debugging, and understanding AWS service interactions. I verified, adapted, and integrated outputs to ensure the system functioned cohesively.
Frontend:
- React
Cloud & Backend:
- AWS Amplify
- AWS Cognito
- AWS S3
- AWS DynamoDB
- AWS Lambda
- API Gateway
AI & Processing:
- AWS Rekognition
- OpenAI API
- Secure user authentication via AWS Cognito
- Image upload and storage using AWS S3
- Digital wardrobe management with DynamoDB
- Serverless backend powered by AWS Lambda
- RESTful API communication via API Gateway
- Clothing detection using AWS Rekognition
- AI-generated outfit recommendations using OpenAI APIs
Frontend (React) → API Gateway → AWS Lambda → (S3 for image storage, DynamoDB for structured data)
The application follows a serverless architecture:
- Users interact with the React frontend
- Requests are routed through API Gateway
- AWS Lambda handles backend processing
- Clothing images are stored in AWS S3
- Structured wardrobe data and AI outputs are stored in DynamoDB
- AWS Rekognition analyzes clothing attributes
- OpenAI APIs generate outfit recommendations
AWS Amplify is used to deploy the frontend and connect it with backend services.
This project was deployed using AWS services during a hackathon environment.
Cloud resources are not currently active due to limited AWS access after the event. This repository is maintained as a portfolio project to demonstrate system architecture, AWS integration, and backend design.
The project can be redeployed by reconfiguring AWS services and environment variables.
Originally developed as part of a team during an AWS hackathon, this repository represents my personal portfolio version of the project.
It highlights my contributions to backend infrastructure, cloud integration, and system-level design.
- Original Repository: https://github.com/EricDeanRoss808/wardrobe-app
- Demo Video: https://youtu.be/pnm0jRh5hFI?si=ZM79SS-bcES7QvNR
- Devpost: https://devpost.com/software/drip-management