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Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter

You're reading from   Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter Build scalable real-world projects to implement end-to-end neural networks on Android and iOS

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Product type Paperback
Published in Apr 2020
Publisher Packt
ISBN-13 9781789611212
Length 380 pages
Edition 1st Edition
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Authors (2):
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Rimjhim Bhadani Rimjhim Bhadani
Author Profile Icon Rimjhim Bhadani
Rimjhim Bhadani
Anubhav Singh Anubhav Singh
Author Profile Icon Anubhav Singh
Anubhav Singh
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Table of Contents (13) Chapters Close

Preface 1. Introduction to Deep Learning for Mobile 2. Mobile Vision - Face Detection Using On-Device Models FREE CHAPTER 3. Chatbot Using Actions on Google 4. Recognizing Plant Species 5. Generating Live Captions from a Camera Feed 6. Building an Artificial Intelligence Authentication System 7. Speech/Multimedia Processing - Generating Music Using AI 8. Reinforced Neural Network-Based Chess Engine 9. Building an Image Super-Resolution Application 10. Road Ahead 11. Other Books You May Enjoy Appendix

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.

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