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Visualizing TensorFlow Lite AI Results on Android

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21 Sep 2020CPOL2 min read
In the previous installation of this series, a TensorFlow Lite interpreter had examined an image and produced its output. In this article we learn how to interpret these results and create visualizations for them.
Here we complete building a TensorFlow Lite-based application for performing recognition of objects using a network model that came from the ONNX Model Zoo.

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

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About the Author

Joel Ivory Johnson
Software Developer
United States United States
I attended Southern Polytechnic State University and earned a Bachelors of Science in Computer Science and later returned to earn a Masters of Science in Software Engineering. I've largely developed solutions that are based on a mix of Microsoft technologies with open source technologies mixed in. I've got an interest in astronomy and you'll see that interest overflow into some of my code project articles from time to time.



Twitter:@j2inet

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