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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

Product type Book
Published in Apr 2020
Publisher Packt
ISBN-13 9781789611212
Pages 380 pages
Edition 1st Edition
Languages
Authors (2):
Anubhav Singh Anubhav Singh
Profile icon Anubhav Singh
Rimjhim Bhadani Rimjhim Bhadani
Profile icon Rimjhim Bhadani
View More author details
Toc

Table of Contents (13) Chapters close

Preface 1. Introduction to Deep Learning for Mobile 2. Mobile Vision - Face Detection Using On-Device Models 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

Adding Firebase authentication

As discussed earlier, in the Simple login application section, we will be using the user's email and password for authentication integrated through Firebase.

To create and configure a Firebase project on Firebase Console, refer to the Appendix.

The following steps discuss in detail about how to set up the project on Firebase Console:

  1. We begin by selecting the project on Firebase Console:

  1. Next, we will click on the Authentication option from the Develop menu:

This will take us to the authentication screen.

  1. Migrate to the sign-in tab and enable the Email/Password option under Sign-in providers:

This is all that is required to set up Firebase Console.

Next, we will integrate Firebase in the code. This is done as follows:

  1. Migrate to the project in your Flutter SDK and add firebase-auth to the app level build.gradle file:
implementation...
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