DeepCalorieCam: An iOS App for Dish Detection and Calorie Estimation

DeepCalorieCam: An iOS App for Dish Detection and Calorie Estimation


In this demo, we present a CNN-based dish detection and calorie estimation system, DeepCalorieCam, running on iOS. The proposed app can estimate the calorie after detecting dishes from the video stream captured from the built-in camera of an iPhone. For dish detection, we implemented the network proposed as a real-time object detection network called YOLOv2 by Redmon et al. For food calorie estimation, we implemented the multi-task CNN proposed as a simultaneous estimation of food categories and calories by Ege et al. For the deep learning framework, we use Keras (backend TensorFlow) to train and convert the model for CoreML to use it. For more information, please refer to the following project page.
http://foodcam.mobi/deepcaloriecam/

3 thoughts on “DeepCalorieCam: An iOS App for Dish Detection and Calorie Estimation

  1. If you have any questions or anything, please do not hesitate to contact me!! 🙂

  2. Great job! I am currently working on an internship and am working on the same subject. My internship topic is about that. Please, can you give me a link to your code?
    [email protected] thank you 🙂

  3. Hello brother , nice application , did you use python for training? can i have the model? thank you.

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