About the Muffin vs Chihuahua Classifier

Welcome to the Muffin vs Chihuahua Image Classifier! This web app uses a machine learning model that was trained from scratch to classify images into two categories: Chihuahua or Muffin. The project integrates several cutting-edge technologies to ensure robust performance and easy deployment.

Technologies Used:

• Docker: Docker is used to containerize the application, ensuring consistent behavior across development, staging, and production environments.
• Terraform: Terraform is used to manage the infrastructure as code, automating the deployment of the app to Azure with scalability and reliability.
• Django: The backend of the application is powered by Django, a robust web framework that handles routing, image uploads, and prediction requests.
• TensorFlow: The machine learning model is built using TensorFlow, trained from scratch to distinguish between images of Chihuahuas and muffins.
• Azure: The app is deployed on Azure using Azure App Service and Azure Container Registry, offering a scalable and reliable platform for hosting the classifier.

How It Works:

Users upload an image, and the trained TensorFlow model predicts whether the image contains a Chihuahua or a muffin. The result is then displayed along with the uploaded image for comparison.