FitFood is a multi-label image classification system designed to identify over 40 types of Indonesian traditional foods from photographs, built as part of a health-related mobile application.
The model leverages Transfer Learning with InceptionV3 as the base architecture, with fine-tuning of 60+ top layers to adapt the pre-trained features specifically for Indonesian food recognition.
For mobile deployment, the trained model is converted to TensorFlow Lite (.tflite) format, enabling real-time on-device inference on Android smartphones without requiring network connectivity for predictions.