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Machine Learning for Mobile

You're reading from  Machine Learning for Mobile

Product type Book
Published in Dec 2018
Publisher Packt
ISBN-13 9781788629355
Pages 274 pages
Edition 1st Edition
Languages
Authors (2):
Revathi Gopalakrishnan Revathi Gopalakrishnan
Profile icon Revathi Gopalakrishnan
Avinash Venkateswarlu Avinash Venkateswarlu
Profile icon Avinash Venkateswarlu
View More author details

Table of Contents (19) Chapters

Title Page
Copyright and Credits
About Packt
Contributors
Preface
1. Introduction to Machine Learning on Mobile 2. Supervised and Unsupervised Learning Algorithms 3. Random Forest on iOS 4. TensorFlow Mobile in Android 5. Regression Using Core ML in iOS 6. The ML Kit SDK 7. Spam Message Detection 8. Fritz 9. Neural Networks on Mobile 10. Mobile Application Using Google Vision 11. The Future of ML on Mobile Applications 1. Question and Answers 2. Other Books You May Enjoy Index

Creating a text recognition app using Firebase on-device APIs


To get started in ML Kit, you need to sign in to your Google account, activate your Firebase account, and create a Firebase project. Follow these steps:

  • Go to https://firebase.google.com/.
  • Sign in to your Google account, if you are not already signed in.
  • Click Go to console in the menu bar.
  • Click Add project to create a project and open it.

Now open Android Studio, and create a project with an empty activity. Note down the app package name that you have given while creating the project—for example,  com.packt.mlkit.textrecognizationondevice.

Next, go to the Firebase console. In the Project overview menu, click Add app and give the required information. It will give you a JSON file to download. Add to the app folder of your project in project view in Android Studio, as shown in the following screenshot:

Next, add the following lines of code to the manifest file:

<uses-feature android:name="android.hardware.camera2.full" /<
<uses...
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