Working with TensorFlow Lite on Android with C++

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 (Adobe) 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.

Prerequisite knowledge

• 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