🍔 Food Classification Model 🍰

This repository contains a TensorFlow implementation of a food classification model using the EfficientNetV2B0 architecture. The model is trained to classify images into 10 different food classes.

Table of Contents

• Directory Structure
• Prerequisites
• Setup
• Training
• Inference

Directory Structure

• 📁 Data/
  • 📁 10_food_classes_all_data/
    • 📁 train/
    • 📁 test/
• 📄 model.py
• 📄 README.md

Prerequisites

Ensure you have the following prerequisites installed on your system:

• 🧠 TensorFlow
• 🧮 NumPy
• 📊 Matplotlib

You can install the required Python packages using the following command:

pip install -r requirements.txt

Setup

Clone the Repository:

git clone https://github.com/shriharshan/Food_Vision_Project.git
cd your-repo 

Download the Dataset:

I've used Food101 dataset from kaggle and used only 10 classes for this model. Download the dataset and organize it in the Data/10_food_classes_all_data directory. The dataset should have separate train and test folders containing images for training and testing.

Training

The model will be trained for 5 epochs using data augmentation and the EfficientNetV2B0 base model.