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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

Running image recognition

Now, the image chosen from the gallery can be used as an input for the two prediction methods of the Cloud Vision API and TensorFlow Lite model. Next, let's define methods for running both of them.

Using the Cloud Vision API

In this section, we simply define a visionAPICall method that is used to make an http Post request to the CloudVision API, passing in the request string encoded as json, which returns a json response that is parsed to get the values from the desired labels:

  1. First of all, we define an http plugin dependency in the pubspec.yaml file, as follows:
http: ^0.12.0+2
  1. Import the plugin in PlantSpeciesRecognition.dart to assist in making http requests, like...
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