SnugShopper

SnugShopper is an intelligent apparel-fitting solution designed to reduce e-commerce return rates caused by inconsistent sizing standards. The system automatically extracts garment measurements from seller-uploaded product images using computer vision techniques such as OpenCV and MediaPipe, eliminating the need for manual measurement entry or reliance on brand-specific sizing charts.

Customers upload their own photos, and SnugShopper calculates key body measurements to generate a visual fitting analysis. This report highlights how well a garment matches the user's body dimensions and provides personalized size recommendations, helping shoppers make confident, accurate purchase decisions.

Built using Oracle APEX for the front-end, Python + Flask for backend processing, and Oracle Database for secure data storage, SnugShopper aims to create a more inclusive, transparent, and sustainable shopping experience—especially for senior users and those who are not tech-savvy.

By enabling accurate fits before purchase, it helps reduce carbon footprint, improve customer satisfaction, and enhance overall trust in apparel e-commerce.

🏆 Winner — Oracle APEX Hackathon