<commit_before># Android Demo App

An example Android application using TensorFLow Lite is available
[on GitHub](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/java/demo/app).
The demo is a sample camera app that classifies images continuously
using either a quantized Mobilenet model or a floating point Inception-v3 model.
To run the demo, a device running Android 5.0 ( API 21) or higher is required.

In the demo app, inference is done using the TensorFlow Lite Java API. The demo
app classifies frames in real-time, displaying the top most probable
classifications. It also displays the time taken to detect the object.

There are three ways to get the demo app to your device:

* Download the [prebuilt binary APK](http://download.tensorflow.org/deps/tflite/TfLiteCameraDemo.apk).
* Use Android Studio to build the application.
* Download the source code for TensorFlow Lite and the demo and build it using
  bazel.


## Download the pre-built binary

The easiest way to try the demo is to download the
[pre-built binary APK](https://storage.googleapis.com/download.tensorflow.org/deps/tflite/TfLiteCameraDemo.apk)

Once the APK is installed, click the app icon to start the program. The first
time the app is opened, it asks for runtime permissions to access the device
camera. The demo app opens the back-camera of the device and recognizes objects
in the camera's field of view. At the bottom of the image (or at the left
of the image if the device is in landscape mode), it displays top three objects
classified and the classification latency.


## Build in Android Studio with TensorFlow Lite AAR from JCenter<commit_msg>[Docs]: Fix #20270<commit_after># Android Demo App

An example Android application using TensorFLow Lite is available
[on GitHub](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/lite/java/demo).
The demo is a sample camera app that classifies images continuously
using either a quantized Mobilenet model or a floating point Inception-v3 model.
To run the demo, a device running Android 5.0 ( API 21) or higher is required.

In the demo app, inference is done using the TensorFlow Lite Java API. The demo
app classifies frames in real-time, displaying the top most probable
classifications. It also displays the time taken to detect the object.

There are three ways to get the demo app to your device:

* Download the [prebuilt binary APK](http://download.tensorflow.org/deps/tflite/TfLiteCameraDemo.apk).
* Use Android Studio to build the application.
* Download the source code for TensorFlow Lite and the demo and build it using
  bazel.


## Download the pre-built binary

The easiest way to try the demo is to download the
[pre-built binary APK](https://storage.googleapis.com/download.tensorflow.org/deps/tflite/TfLiteCameraDemo.apk)

Once the APK is installed, click the app icon to start the program. The first
time the app is opened, it asks for runtime permissions to access the device
camera. The demo app opens the back-camera of the device and recognizes objects
in the camera's field of view. At the bottom of the image (or at the left
of the image if the device is in landscape mode), it displays top three objects
classified and the classification latency.


## Build in Android Studio with TensorFlow Lite AAR from JCenter
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