Diet Snap using Transfer Learning

Ensuring a well-balanced diet is crucial for maintaining overall health., yet many individuals struggle to track their nutritional intake effectively. This application leverages Yolov5 for object detection to analyze uploaded food images, identifying food items and estimating their calorie content. Beyond basic tracking, the system evaluates the detected food and provides dietary recommendations by identifying missing nutrients. It suggests adjustments to ensure a well-rounded diet, such as increasing protein intake, incorporating fiber-rich foods, or reducing excessive fats and sugars. By offering personalized insights, the application allow users to create and promote properly discovered nutritional decisions.