Working with TensorFlow Lite on Android with C++
Who is this presentation for?
- Intermediate software developers
There are many cases where developers on mobile write lower-level C++ code for their Android applications using the Android NDK, OpenCV and other technologies. Joe Bowser explores how to use TF Lite’s C++ API on Android with existing code so the code can interact directly with TF Lite without having to make a round trip through Java Native Interface (JNI) and the Android subsystem, allowing for cleaner, more portable code so that can even be used in iOS or other platforms. You’ll also discover common pitfalls when working with TFLite as a C++ library, using TFLite with OpenCV and/or Halide on Android, as well as some techniques to do integration testing to allow your tests to work in a CI/CD environment.
- Experience with mobile development
What you'll learn
- Discover with the pros and cons of various approaches to using TensorFlow Lite in a production environment and whether using Java or C++ is the best choice for you project
Joe Bowser is a senior computer scientist at Adobe, where he’s the lead developer on the sensei on device team that’s deploying machine learning technologies into various products at Adobe. Previously, he was the creator of PhoneGap for Android and the longest contributing committer to the PhoneGap and Apache Cordova projects. When he’s not contributing to open source at Adobe, he spends his spare time working on various hardware projects, most of which involve first-person-view miniquadcopters.
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