Scan for food in image in real-time => User can read info about the food => User can book the food through Foody.vn website.
- Firebase ML Kit Object Detection Integration
- Training a Food Classification model with Tensorflow
- Convert the model to TFLite
- Integrate model to classify output by Firebase ML Kit as food categories
- Handling Asynchronous nature of Inference by the model
- Carousel view with image
- Network handling and HTTP request with Volley library
- Use API from Shutterstock to build
- Get image by Picasso library
- Food info database for 101 types of food
- Firestore from Firebase
- The model is not extremely accurate. Therefore, it can predict the wrong type of food.
- Improving the model for food recognition and classification. I am thinking about trying a YOLO model, which should improve the accuracy from our current model - Conv Net.
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