Book Image

Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter

By : Anubhav Singh, Rimjhim Bhadani
Book Image

Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter

By: Anubhav Singh, Rimjhim Bhadani

Overview of this book

Deep learning is rapidly becoming the most popular topic in the mobile app industry. This book introduces trending deep learning concepts and their use cases with an industrial and application-focused approach. You will cover a range of projects covering tasks such as mobile vision, facial recognition, smart artificial intelligence assistant, augmented reality, and more. With the help of eight projects, you will learn how to integrate deep learning processes into mobile platforms, iOS, and Android. This will help you to transform deep learning features into robust mobile apps efficiently. You’ll get hands-on experience of selecting the right deep learning architectures and optimizing mobile deep learning models while following an application oriented-approach to deep learning on native mobile apps. We will later cover various pre-trained and custom-built deep learning model-based APIs such as machine learning (ML) Kit through Firebase. Further on, the book will take you through examples of creating custom deep learning models with TensorFlow Lite. Each project will demonstrate how to integrate deep learning libraries into your mobile apps, right from preparing the model through to deployment. By the end of this book, you’ll have mastered the skills to build and deploy deep learning mobile applications on both iOS and Android.
Table of Contents (13 chapters)

Understanding the camera plugin

The Camera plugin, available as a camera dependency, allows us to access the device's camera freely. It provides support for both Android and iOS devices. The plugin is open sourced and is hosted on GitHub so that anyone can freely access the code, fix errors, and suggest enhancements to the current version.

The plugin can be used to display the live camera preview on a widget, capture images, and store them locally on a device. It can also be used to record a video. Further more, it has the capability to access the image stream.

The Camera plugin can be added to any application with the following three simple steps:

  1. Installing the package
  2. Adding methods for persistent storage and proper execution
  3. Coding

Let's now discuss each of these steps in detail.