Food Classification with 22 Class

This project is focused on developing a deep learning-based food classification system using the Food-101 dataset. It involves preparing and processing image data, building and training models to classify 22 food categories, and fine-tuning the models for improved accuracy.

The project integrates data augmentation, transfer learning, and hyperparameter tuning to optimize performance. It trained or fine tuned a Baseline Model, a VGG Model, a Inception Model and a ResNet Model. The goal is to create an efficient, accurate system capable of classifying food images. This project is hosted within my home server

Try to classify a food photo below! Support food types include: Apple Pie, Baby Back Ribs, Bibimbap, Caesar Salad, Cheesecake, Chicken Curry, Chicken Wings, Club Sandwich, Donuts, Dumplings, French Fries, Hot Dog, Hamburger, Frozen Yogust, Pizza, Ramen, Steak, Ice Cream, Waffles, Spring Rolls, Sushi, Fish and Chips.