FOOD NUTRITION AND CALORIES ANALYSIS USING YOLO

Importance of food is self-evident and obvious. Healthy food provides us with the nourishment and energy we require to grow and develop, including carbohydrates, protein, vitamins, minerals, lipids, and other nutrients. Rapid growth of technology has led to increase in ease of people's daily life. Machine learning has contributed a lot to food and dieting a lot in the past years. The notion of machine learning and deep learning models can be applied to image processing to consistently detect the type and quality of food. We developed a user friendly interface that displays the nutrition and calories content of the food that the user is consuming. The system is built on the YOLO algorithm, which uses convolutional neural networks (CNN) to detect the object at once. The accuracy of the system is improved by YOLO algorithm since it moves in only one direction only once to yield the output. The algorithm is proven to be faster that other CNN algorithm, so our application used this algorithm to get the output in a short amount of time.