Updating the input image sizes to have a higher resolution. Currently unclean data is reaching 70% accuracy.
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# TF Lite Android App
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## Building from Source with Bazel
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1. Follow the [Bazel steps for the TF Demo App](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/examples/android#bazel):
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1. [Install Bazel and Android Prerequisites](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/examples/android#install-bazel-and-android-prerequisites).
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It's easiest with Android Studio.
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- You'll need at least SDK version 23.
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- Bazel requires Android Build Tools `26.0.1` or higher.
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- You also need to install the Android Support Repository, available
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through Android Studio under `Android SDK Manager -> SDK Tools ->
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Android Support Repository`.
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2. [Edit your `WORKSPACE`](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/examples/android#edit-workspace)
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to add SDK and NDK targets.
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- Make sure the `api_level` in `WORKSPACE` is set to an SDK version that
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you have installed.
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- By default, Android Studio will install the SDK to `~/Android/Sdk` and
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the NDK to `~/Android/Sdk/ndk-bundle`.
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2. Build the app with Bazel. The demo needs C++11:
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```shell
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bazel build -c opt --cxxopt='--std=c++11' \
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//tensorflow/contrib/lite/java/demo/app/src/main:TfLiteCameraDemo
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```
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3. Install the demo on a
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[debug-enabled device](https://github.com/tensorflow/tensorflow/tree/master/tensorflow/examples/android#install):
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```shell
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adb install bazel-bin/tensorflow/contrib/lite/java/demo/app/src/main/TfLiteCameraDemo.apk
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```
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