Zahaab/food-classifier

Food Classifier

This repository contains a pre-trained PyTorch model for classifying food based on images. The model file food_model.pth can be downloaded and used to classify images of pizza, steak or sushi.

Model Overview

The food_model.pth file is a PyTorch model trained on a dataset of food images. It achieves a test accuracy of 84.56%, making it a reliable choice for identifying pizza, steak, and sushi. The model is designed to be lightweight and efficient for real-time applications.

Requirements

• Python 3.7 or higher
• PyTorch 1.8 or higher
• torchvision (for loading and preprocessing images)

Usage

1. Clone this repository and install dependencies.

   git clone <repository-url>
   cd <repository-folder>
   pip install torch torchvision
   

2. Load and use the model in your Python script:

   import torch
   from torchvision import transforms
   from PIL import Image
   
   # Load the model
   model = torch.load('aircraft_classifier.pth')
   model.eval()  # Set to evaluation mode
   
   # Load and preprocess the image
   transform = transforms.Compose([
       transforms.Resize((224, 224)),
       transforms.ToTensor(),
   ])
   img = Image.open('path_to_image.jpg')
   img = transform(img).view(1, 3, 224, 224)  # Reshape to (1, 3, 224, 224) for batch processing
   
   # Predict
   with torch.no_grad():
       output = model(img)
       _, predicted = torch.max(output, 1)
       print("Predicted Food Type:", predicted.item())