opencv/doc/tutorials/dnn/dnn_android/dnn_android.markdown

# How to run deep networks on Android device {#tutorial_dnn_android}

@tableofcontents

@prev_tutorial{tutorial_dnn_halide_scheduling}
@next_tutorial{tutorial_dnn_yolo}

|    |    |
| -: | :- |
| Original author | Dmitry Kurtaev |
| Compatibility | OpenCV >= 3.3 |

## 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

- Download and install Android Studio from https://developer.android.com/studio.

- Get the latest pre-built OpenCV for Android release from https://github.com/opencv/opencv/releases and unpack it (for example, `opencv-4.X.Y-android-sdk.zip`).

- Download MobileNet object detection model from https://github.com/chuanqi305/MobileNet-SSD. We need a configuration file `MobileNetSSD_deploy.prototxt` and weights `MobileNetSSD_deploy.caffemodel`.

## Create an empty Android Studio project
- Open Android Studio. Start a new project. Let's call it `opencv_mobilenet`.
![](1_start_new_project.png)

- Keep default target settings.
![](2_start_new_project.png)

- Use "Empty Activity" template. Name activity as `MainActivity` with a
corresponding layout `activity_main`.
![](3_start_new_project.png)

  ![](4_start_new_project.png)

- Wait until a project was created. Go to `Run->Edit Configurations`.
Choose `USB Device` as target device for runs.
![](5_setup.png)
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.

![](6_run_empty_project.png)

## 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.
![](7_import_module.png)

  ![](8_import_module.png)

- 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.
![](9_opencv_dependency.png)

  ![](10_opencv_dependency.png)

- 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/gradle/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!
![](11_demo.jpg)