This folder contains a simple camera-based demo application utilizing Tensorflow.

This demo uses a Google Inception model to classify camera frames in real-time, displaying the top results in an overlay on the camera image.

As a prerequisite, Bazel, the Android NDK, and the Android SDK must all be installed on your system. The Android build tools may be obtained from: https://developer.android.com/tools/revisions/build-tools.html

The Android entries in <workspace_root>/WORKSPACE must be uncommented with the paths filled in appropriately depending on where you installed the NDK and SDK. Otherwise an error such as: "The external label '//external:android/sdk' is not bound to anything" will be reported.

The TensorFlow GraphDef that contains the model definition and weights is not packaged in the repo because of its size. Instead, you must first download the file to the assets directory in the source tree:

$ wget https://storage.googleapis.com/download.tensorflow.org/models/inception5h.zip -O /tmp/inception5h.zip

$ unzip /tmp/inception5h.zip -d tensorflow/examples/android/assets/

The labels file describing the possible classification will also be in the assets directory.

Then, after editing your WORKSPACE file, you must build the APK. Run this from your workspace root:

$ bazel build //tensorflow/examples/android:tensorflow_demo

If adb debugging is enabled on your Android 5.0 or later device, you may then use the following command from your workspace root to install the APK once built:

$ adb install -r -g bazel-bin/tensorflow/examples/android/tensorflow_demo_incremental.apk

Alternatively, a streamlined means of building, installing and running in one command is:

$ bazel mobile-install //tensorflow/examples/android:tensorflow_demo --start_app

If camera permission errors are encountered (possible on Android Marshmallow or above), then the adb install command above should be used instead, as it automatically grants the required camera permissions with -g.