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Friendly Foods - Allergy Detection API - Python Final Project - MPCS University of Chicago - 2024
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Developers: Kate Kim, Jovanay Carter
Description: Friendly Foods is a Food Allergen Detection API, designed to help people with allergy restrictions navigate food choices safely and easily. We're presenting our final project for Python Programming for the University of Chicago’s Masters Program in Computer Science (MPCS).
Sources: Open Foods USA, USDA
Programming Language: Python
Libraries Used: Pillow library for barcode detection image recognition, Python-JOSE and OAuth for secure token authentication, SQLite and Pydantic for database, and FastAPI for RESTful web framework
Timestamps:
00:00 Introduction
00:51 Project Motivation and Practical Applications
02:05 Product Demo
04:55 Backend Walk Through: Product, Allergies, User Classes
08:30 Backend Walk Through: Databases
10:26 Concluding Summary and Potential Future Additions
Description: Friendly Foods is a Food Allergen Detection API, designed to help people with allergy restrictions navigate food choices safely and easily. We're presenting our final project for Python Programming for the University of Chicago’s Masters Program in Computer Science (MPCS).
Sources: Open Foods USA, USDA
Programming Language: Python
Libraries Used: Pillow library for barcode detection image recognition, Python-JOSE and OAuth for secure token authentication, SQLite and Pydantic for database, and FastAPI for RESTful web framework
Timestamps:
00:00 Introduction
00:51 Project Motivation and Practical Applications
02:05 Product Demo
04:55 Backend Walk Through: Product, Allergies, User Classes
08:30 Backend Walk Through: Databases
10:26 Concluding Summary and Potential Future Additions
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