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Open Source Computer Vision Library https://opencv.org/
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opencv/doc/tutorials/dnn/dnn_android/dnn_android.markdown

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How to run deep networks on Android device

Introduction

In this tutorial you'll know how to run deep learning networks on Android device using OpenCV deep learning module.

Tutorial was written for the following versions of corresponding software:

  • Android Studio 2.3.3
  • OpenCV 3.3.0+

Requirements

Create an empty Android Studio project

  • Open Android Studio. Start a new project. Let's call it opencv_mobilenet.

  • Keep default target settings.

  • Use "Empty Activity" template. Name activity as MainActivity with a corresponding layout activity_main.

  • Wait until a project was created. Go to Run->Edit Configurations. Choose USB Device as target device for runs. Plug in your device and run the project. It should be installed and launched successfully before we'll go next. @note Read @ref tutorial_android_dev_intro in case of problems.

Add OpenCV dependency

  • Go to File->New->Import module and provide a path to unpacked_OpenCV_package/sdk/java. The name of module detects automatically. Disable all features that Android Studio will suggest you on the next window.

  • Open two files:

    1. AndroidStudioProjects/opencv_mobilenet/app/build.gradle

    2. AndroidStudioProjects/opencv_mobilenet/openCVLibrary330/build.gradle

    Copy both compileSdkVersion and buildToolsVersion from the first file to the second one.

    compileSdkVersion 14 -> compileSdkVersion 26

    buildToolsVersion "25.0.0" -> buildToolsVersion "26.0.1"

  • Make the project. There is no errors should be at this point.

  • Go to File->Project Structure. Add OpenCV module dependency.

  • Install once an appropriate OpenCV manager from unpacked_OpenCV_package/apk to target device. @code adb install OpenCV_3.3.0_Manager_3.30_armeabi-v7a.apk @endcode

  • Congratulations! We're ready now to make a sample using OpenCV.

Make a sample

Our sample will takes pictures from a camera, forwards it into a deep network and receives a set of rectangles, class identifiers and confidence values in [0, 1] range.

  • First of all, we need to add a necessary widget which displays processed frames. Modify app/src/main/res/layout/activity_main.xml: @include android/mobilenet-objdetect/res/layout/activity_main.xml

  • Put downloaded MobileNetSSD_deploy.prototxt and MobileNetSSD_deploy.caffemodel into app/build/intermediates/assets/debug folder.

  • Modify /app/src/main/AndroidManifest.xml to enable full-screen mode, set up a correct screen orientation and allow to use a camera. @include android/mobilenet-objdetect/AndroidManifest.xml

  • Replace content of app/src/main/java/org/opencv/samples/opencv_mobilenet/MainActivity.java: @include android/mobilenet-objdetect/src/org/opencv/samples/opencv_mobilenet/MainActivity.java

  • Launch an application and make a fun!