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Android app to recognize the Indian currency using deep learning. Useful for visually impaired people.

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TF Lite Android App

Building from Source with Bazel

  1. Follow the Bazel steps for the TF Demo App:

  2. Install Bazel and Android Prerequisites. It's easiest with Android Studio.

    • You'll need at least SDK version 23.
    • Bazel requires Android Build Tools 26.0.1 or higher.
    • You also need to install the Android Support Repository, available through Android Studio under Android SDK Manager -> SDK Tools -> Android Support Repository.
  3. Edit your WORKSPACE to add SDK and NDK targets.

    • 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.
  4. Build the app with Bazel. The demo needs C++11:

bazel build -c opt --cxxopt='--std=c++11' \
  //tensorflow/contrib/lite/java/demo/app/src/main:TfLiteCameraDemo
  1. Install the demo on a debug-enabled device:
adb install bazel-bin/tensorflow/contrib/lite/java/demo/app/src/main/TfLiteCameraDemo.apk

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