If you see a build error related to compatibility with Tensorflow Lite's Java API (example: method X is undefined for type Interpreter), there has likely been a backwards compatible change to the API. You will need to pull new app code that's compatible with the nightly build and may need to first wait a few days for our external and internal code to merge.

Building from Source with Bazel

Follow the Bazel steps for the TF Demo App:
Install Bazel and Android Prerequisites. It's easiest with Android Studio.
- You'll need at least SDK version 23.
- Make sure to install the latest version of Bazel. Some distributions ship with Bazel 0.5.4, which is too old.
- Bazel requires Android Build Tools 28.0.0 or higher.
- You also need to install the Android Support Repository, available through Android Studio under Android SDK Manager -> SDK Tools -> Android Support Repository.
Edit your WORKSPACE to add SDK and NDK targets.

NOTE: As long as you have the SDK and NDK installed, the ./configure script will create these rules for you. Answer "Yes" when the script asks to automatically configure the ./WORKSPACE.
- Make sure the api_level in WORKSPACE is set to an SDK version that you have installed.
- By default, Android Studio will install the SDK to ~/Android/Sdk and the NDK to ~/Android/Sdk/ndk-bundle.
Build the app with Bazel. The demo needs C++11:

bazel build -c opt //tensorflow/lite/java/demo/app/src/main:TfLiteCameraDemo

Install the demo on a debug-enabled device:

adb install bazel-bin/tensorflow/lite/java/demo/app/src/main/TfLiteCameraDemo.apk