Food-Lens: Improving Culinary Experiences with AI-Driven Meal Analysis and Recipe Generation

This research work introduces an innovative system designed to accurately identify food classes and generate appropriate meal recipes from images using Convolutional Neural Network (CNN) architecture and MobileNetV2. By leveraging pre-trained datasets such as Food-101, the proposed system can be customized to cover a wide variety of food items, promoting healthy eating habits and enhancing cooking experiences. The proposed system includes the entire process from data preparation and model training to deployment on mobile and cloud-based platforms. Beyond food identification, it offers recipe suggestions and ingredient details, and features text-to-speech capabilities for broader accessibility. This approach highlights the potential of advanced AI technology combined with nutritional science to significantly improve public health outcomes and drive the food industry towards sustainability.