You're reading from Hands-On Machine Learning with C++

Product typeBook

Published inMay 2020

Reading LevelIntermediate

PublisherPackt

ISBN-139781789955330

Edition1st Edition

Languages

C++

Tools

Caffe

Concepts

Machine Learning

Author (1)

Kirill Kolodiazhnyi

Image classification on Android mobile

There are two popular approaches regarding how to deploy a machine learning model to a mobile device with Android. We can either use the PyTorch framework, which now incorporates Caffe2, or we can use the TensorFlow Lite framework. We'll use the PyTorch framework in this chapter since we have discussed it in the previous chapters.

The mobile version of the PyTorch framework

There is no available binary distribution of PyTorch for mobile devices, so we need to build it from source code. We can do this in the same way as we compile its regular version but with additional CMake parameters to enable mobile mode. You also have to install the Android Native Development Kit (NDK), which...

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Hands-On Machine Learning with C++

Published in: May 2020Publisher: PacktISBN-13: 9781789955330

Author (1)

Kirill Kolodiazhnyi

Kirill Kolodiazhnyi is a seasoned software engineer with expertise in custom software development. He has several years of experience building machine learning models and data products using C++. He holds a bachelor degree in Computer Science from the Kharkiv National University of Radio-Electronics. He currently works in Kharkiv, Ukraine where he lives with his wife and daughter.
Read more about Kirill Kolodiazhnyi

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