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Food Item Detection with Deep Learning by jeffery lawrence is a document available to read on EtoBox.

What is Food Item Detection with Deep Learning about?

This project aims to detect and classify 22 different food items from input images using a deep learning algorithm. A dataset containing 2600 total images across 22 food classes is collected from online sources and preprocessed. A MobileNetV2 model is used for transfer learning with the food images. The model is implemented in Python and a web app is created using Streamlit to allow users to upload an image for detection. The app outputs the predicted food item name, its category (healthy or unhealthy), and

Author

jeffery lawrence

Language

EN