Rishabh1925/foodvisionai
📦 Open Source ProjectRishabh1925
An AI-powered food recognition web application leveraging Vision Transformers to identify 101 food categories with 94% accuracy.
FoodVisionAI is a comprehensive computer vision project designed to bridge the gap between complex deep learning models and user-friendly web interfaces. At its core, the application employs a Vision Transformer (ViT) architecture, which has been fine-tuned to recognize 101 distinct food categories. The model achieves a high performance benchmark of 94% accuracy, making it a reliable tool for automated food classification.
The technical architecture is split into a responsive React frontend, which handles user interactions and image processing, and a Flask-based backend that manages model inference. By leveraging the Hugging Face ecosystem, the project streamlines the deployment of heavy machine learning models. This repository serves as an excellent reference for developers looking to integrate pre-trained transformer models into full-stack applications, providing a clear blueprint for handling image data, API communication, and real-time prediction feedback.
💡Highlights
- ├─94% accuracy on 101 food classes
- ├─Vision Transformer (ViT) powered
- └─React and Flask full-stack integration
🎯For
- ├─Web Developers
- └─AI Engineers