Lightning Detection with Deep Learning and Tensorflow on Android: Setting Up a TFLite Model

Ruturaj Raval

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16 Nov 2020CPOL3 min read

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In this article we’ll set up the TFLite model in the Android environment and create a working demo application.

Here we’ll look at the MainActivity.java file, the graphic overlay on the portion of the screen where we detect lightning while in camera mode, and other class files.

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This article is part of the series 'Live Lightning Detection with Deep Learning and Tensorflow on Android ◁ Prev View All Next ▷

License

This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)

Written By

Ruturaj Raval

Technical Writer

Canada

www.ruturaj.me | Technical Specialist & Author

Comments and Discussions

Live Lightning Detection with Deep Learning and Tensorflow on Android: Getting Started

Live Lightning Detection with Deep Learning and Tensorflow on Android: Training and Exporting Model

Lightning Detection with Deep Learning and Tensorflow on Android: Building UI with Android Studio

Lightning Detection with Deep Learning and Tensorflow on Android: Setting Up a TFLite Model

Live Lightning Detection with Deep Learning and Tensorflow on Android: Real-time Testing

Live Lightning Detection with Deep Learning and Tensorflow on Android: Exploring the Outcome

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