This repository contains the Food Vision Mini project, an interactive application for classifying images of food.

Project Overview

Food Vision Mini is a deep learning-based application designed to identify and categorize various food items from images. It leverages a pre-trained EfficientNetB2 model fine-tuned on a subset of the Food101 dataset (pizza, steak, sushi).

Key Features & Technologies

• Image Classification: Utilizes a PyTorch-based convolutional neural network.
• Interactive Web Interface: Built using Gradio.
• Containerization: Includes a Dockerfile for easy and consistent deployment across different environments using Docker.
• Cloud Deployment: Live demo available on Hugging Face Spaces.

Getting Started

To run this application locally using Docker:

1. Clone this repository: git clone https://github.com/your_username/Food-Vision-Mini.git
2. Navigate to the project directory: cd Food-Vision-Mini
3. Build the Docker image: docker build -t gradio-app .
4. Run the Docker container: docker run -p 7860:7860 gradio-app
5. Access the Gradio interface in your browser at http://localhost:7860.