EatEase

Live

FlutterDartPythonFlaskPostgreSQLSQLAlchemyGoogle Cloud Vision APIJWTRenderGitHub PagesGoogle Custom Search APIREST API

The Challenge

"What do I cook with what I have?" — that question wastes more time, food, and money than most people realize. Started as a class prototype, I decided to build it from scratch into a fully working app.

Overview

AI-Powered Ingredient Detection & Recipe Recommendation. "What do I cook with what I have?" — that one question wastes more time, food, and money than most people realize. This was the problem we identified for our Technopreneurship class project, where EatEase started as just documentation and a prototype. I decided to build it from scratch into a fully working app. EatEase is a full-stack cross-platform application that uses AI to identify ingredients from photos and recommend recipes based on what you have available. Simply snap a picture of your ingredients, and the app detects them using Google Cloud Vision API with 400+ trained label-to-ingredient mappings, then suggests recipes you can cook right away. What started as a school prototype is now a live, cross-platform app with real AI integration, a self-improving feedback system, and a full recipe management system — built end-to-end by me.

My Approach

Built a full-stack cross-platform app using Flutter + Flask with Google Cloud Vision API, 400+ trained label-to-ingredient mappings, a self-improving feedback system, and 33 automated tests.

Key Features

Real-time ingredient detection via camera — live detection and photo scan using Google Cloud Vision API

AI-powered label mapping with 400+ trained label-to-ingredient mappings

Self-improving feedback system — user corrections are learned and applied to future detections with growing confidence

Smart recipe recommendations based on detected and pantry ingredients

Pantry management to track ingredients you have on hand

Shopping list generation for missing recipe ingredients

PWA support for installable web experience

JWT-based user authentication via Flask-JWT-Extended

Cross-platform Flutter app — runs on Android, iOS, and Web

Automated testing with pytest — 33 tests covering detection, mapping, and feedback

The Impact

From school prototype to live cross-platform app with real AI integration — runs on Web Application. Built end-to-end as a solo developer.