/Fruit-Detection-App

Fruit and Vegetable Detection App-Building a flutter mobile application using TensorFlow-lite to use on-device machine learning using Python and Convolutional Neural Network. Able to detect and classify info of various categories of fruits and vegetables. Furthermore it will also provide some brief details of that fruit/vegetable.

Primary LanguageDart

Transfer-Learning-App-TensorfowLite-and-Flutter

  1. Built and Trained a Convolutional Neural Network using Transfer Learning in Tensorflow and Keras inside of Jupyter Notebook.

The script is stored inside the pythonscripts.ipynb file.

  1. Converted and Exported it as a .tflite asset into a blank Flutter Project

All app files are in the transfer_learning_fruit_veggies folder.

  1. Finally, wrote a fully functional Flutter mobile app that uses plugins such as tflite and image_picker to use on-device machine learning and now is able to detect 30+ different types of fruits and vegetables, from either a photo taken in real time or an image selected from a camera roll with 97.76% training accuracy and 78.56% validation accuracy

Test this project out yourself, by cloning the repository into Visual Studio Code

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