An example of a image classifier with TensorFlow Mobilenet on Android

An example Android application using TensorFLow Lite. The demo is a sample camera app that classifies images continuously using either a quantized Mobilenet model or a floating point Inception-v3 model. To run the demo, a device running Android 5.0 ( API 21) or higher is required.

This python code will help you Image Classifier. This is a multiclass image classification project using Convolutional Neural Networks and TensorFlow API on Python, deployed on Android via Tensorflow Lite. We will be using transfer learning, which means we are starting with a model that has been already trained on another problem. We will then retrain it on a similar problem. Deep learning from scratch can take days but transfer learning can be done in short order. We are going to use a model trained on the MobileNet dataset. These models can differentiate between 1,000 different classes, like Dalmatian or dishwasher. We will use this same model, but retrain it to tell apart a small number of classes based on our own example, i.e. classifying rotten and fresh fruits!