Food Recognition and Calorie Estimation Using AI

Obesity has increasingly become a serious concern in modern society, affecting the health and lifestyle of individuals across all age groups. With the rise in sedentary habits and poor dietary choices, maintaining a healthy weight has become more challenging than ever. To effectively address this issue, it is essential to adopt a well-balanced diet, consume nutritious food, and regulate daily calorie intake. Achieving this level of awareness requires accurate tools for monitoring food consumption and understanding its nutritional content. In promoting better health and well-being. The proposed system provides a practical and efficient solution by allowing users to simply upload an image of their food. Once uploaded, the system processes the image to recognize the food item and then estimates its calorie content along with detailed nutritional values such as carbohydrates, proteins, and fats. At the core of the food recognition process is a Convolutional Neural Network (CNN), specifically the MobileNetV2 model, which has been chosen for its lightweight architecture and high performance in image classification tasks. This deep learning model enables the system to accurately identify a wide variety of food items from user-uploaded images.