Android sample for DNN module

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Dmitry Kurtaev 2017-08-26 21:40:12 +03:00
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# How to run deep networks on Android device {#tutorial_dnn_android}
## 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. At this moment it's an `opencv-3.3.0-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/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)

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<?xml version="1.0" encoding="utf-8"?>
<manifest xmlns:android="http://schemas.android.com/apk/res/android"
package="org.opencv.samples.opencv_mobilenet">
<application
android:allowBackup="true"
android:icon="@mipmap/ic_launcher"
android:label="@string/app_name"
android:roundIcon="@mipmap/ic_launcher_round"
android:supportsRtl="true"
android:theme="@style/Theme.AppCompat.NoActionBar"> <!--Full screen mode-->
<activity android:name=".MainActivity"
android:screenOrientation="landscape"> <!--Screen orientation-->
<intent-filter>
<action android:name="android.intent.action.MAIN" />
<category android:name="android.intent.category.LAUNCHER" />
</intent-filter>
</activity>
</application>
<!--Allow to use a camera-->
<uses-permission android:name="android.permission.CAMERA"/>
<uses-feature android:name="android.hardware.camera" android:required="false"/>
<uses-feature android:name="android.hardware.camera.autofocus" android:required="false"/>
<uses-feature android:name="android.hardware.camera.front" android:required="false"/>
<uses-feature android:name="android.hardware.camera.front.autofocus" android:required="false"/>
</manifest>

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set(sample example-mobilenet-objdetect)
add_android_project(${sample} "${CMAKE_CURRENT_SOURCE_DIR}" LIBRARY_DEPS ${OpenCV_BINARY_DIR} SDK_TARGET 11 ${ANDROID_SDK_TARGET})
if(TARGET ${sample})
add_dependencies(opencv_android_examples ${sample})
endif()

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<?xml version="1.0" encoding="utf-8"?>
<FrameLayout xmlns:android="http://schemas.android.com/apk/res/android"
xmlns:app="http://schemas.android.com/apk/res-auto"
xmlns:tools="http://schemas.android.com/tools"
android:layout_width="match_parent"
android:layout_height="match_parent"
tools:context="org.opencv.samples.opencv_mobilenet.MainActivity">
<org.opencv.android.JavaCameraView
android:id="@+id/CameraView"
android:layout_width="match_parent"
android:layout_height="match_parent"
android:visibility="visible" />
</FrameLayout>

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<resources>
<string name="app_name">opencv_mobilenet</string>
</resources>

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package org.opencv.samples.opencv_mobilenet;
import android.content.Context;
import android.content.res.AssetManager;
import android.os.Bundle;
import android.support.v7.app.AppCompatActivity;
import android.util.Log;
import org.opencv.android.BaseLoaderCallback;
import org.opencv.android.CameraBridgeViewBase;
import org.opencv.android.CameraBridgeViewBase.CvCameraViewFrame;
import org.opencv.android.CameraBridgeViewBase.CvCameraViewListener2;
import org.opencv.android.LoaderCallbackInterface;
import org.opencv.android.OpenCVLoader;
import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.dnn.Net;
import org.opencv.dnn.Dnn;
import org.opencv.imgproc.Imgproc;
import java.io.BufferedInputStream;
import java.io.File;
import java.io.FileOutputStream;
import java.io.IOException;
public class MainActivity extends AppCompatActivity implements CvCameraViewListener2 {
// Initialize OpenCV manager.
private BaseLoaderCallback mLoaderCallback = new BaseLoaderCallback(this) {
@Override
public void onManagerConnected(int status) {
switch (status) {
case LoaderCallbackInterface.SUCCESS: {
Log.i(TAG, "OpenCV loaded successfully");
mOpenCvCameraView.enableView();
break;
}
default: {
super.onManagerConnected(status);
break;
}
}
}
};
@Override
public void onResume() {
super.onResume();
OpenCVLoader.initAsync(OpenCVLoader.OPENCV_VERSION, this, mLoaderCallback);
}
@Override
protected void onCreate(Bundle savedInstanceState) {
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_main);
// Set up camera listener.
mOpenCvCameraView = (CameraBridgeViewBase)findViewById(R.id.CameraView);
mOpenCvCameraView.setVisibility(CameraBridgeViewBase.VISIBLE);
mOpenCvCameraView.setCvCameraViewListener(this);
}
// Load a network.
public void onCameraViewStarted(int width, int height) {
String proto = getPath("MobileNetSSD_deploy.prototxt", this);
String weights = getPath("MobileNetSSD_deploy.caffemodel", this);
net = Dnn.readNetFromCaffe(proto, weights);
Log.i(TAG, "Network loaded successfully");
}
public Mat onCameraFrame(CvCameraViewFrame inputFrame) {
final int IN_WIDTH = 300;
final int IN_HEIGHT = 300;
final float WH_RATIO = (float)IN_WIDTH / IN_HEIGHT;
final double IN_SCALE_FACTOR = 0.007843;
final double MEAN_VAL = 127.5;
final double THRESHOLD = 0.2;
// Get a new frame
Mat frame = inputFrame.rgba();
Imgproc.cvtColor(frame, frame, Imgproc.COLOR_RGBA2RGB);
// Forward image through network.
Mat blob = Dnn.blobFromImage(frame, IN_SCALE_FACTOR,
new Size(IN_WIDTH, IN_HEIGHT),
new Scalar(MEAN_VAL, MEAN_VAL, MEAN_VAL), true);
net.setInput(blob);
Mat detections = net.forward();
int cols = frame.cols();
int rows = frame.rows();
Size cropSize;
if ((float)cols / rows > WH_RATIO) {
cropSize = new Size(rows * WH_RATIO, rows);
} else {
cropSize = new Size(cols, cols / WH_RATIO);
}
int y1 = (int)(rows - cropSize.height) / 2;
int y2 = (int)(y1 + cropSize.height);
int x1 = (int)(cols - cropSize.width) / 2;
int x2 = (int)(x1 + cropSize.width);
Mat subFrame = frame.submat(y1, y2, x1, x2);
cols = subFrame.cols();
rows = subFrame.rows();
detections = detections.reshape(1, (int)detections.total() / 7);
for (int i = 0; i < detections.rows(); ++i) {
double confidence = detections.get(i, 2)[0];
if (confidence > THRESHOLD) {
int classId = (int)detections.get(i, 1)[0];
int xLeftBottom = (int)(detections.get(i, 3)[0] * cols);
int yLeftBottom = (int)(detections.get(i, 4)[0] * rows);
int xRightTop = (int)(detections.get(i, 5)[0] * cols);
int yRightTop = (int)(detections.get(i, 6)[0] * rows);
// Draw rectangle around detected object.
Imgproc.rectangle(subFrame, new Point(xLeftBottom, yLeftBottom),
new Point(xRightTop, yRightTop),
new Scalar(0, 255, 0));
String label = classNames[classId] + ": " + confidence;
int[] baseLine = new int[1];
Size labelSize = Imgproc.getTextSize(label, Core.FONT_HERSHEY_SIMPLEX, 0.5, 1, baseLine);
// Draw background for label.
Imgproc.rectangle(subFrame, new Point(xLeftBottom, yLeftBottom - labelSize.height),
new Point(xLeftBottom + labelSize.width, yLeftBottom + baseLine[0]),
new Scalar(255, 255, 255), Core.FILLED);
// Write class name and confidence.
Imgproc.putText(subFrame, label, new Point(xLeftBottom, yLeftBottom),
Core.FONT_HERSHEY_SIMPLEX, 0.5, new Scalar(0, 0, 0));
}
}
return frame;
}
public void onCameraViewStopped() {}
// Upload file to storage and return a path.
private static String getPath(String file, Context context) {
AssetManager assetManager = context.getAssets();
BufferedInputStream inputStream = null;
try {
// Read data from assets.
inputStream = new BufferedInputStream(assetManager.open(file));
byte[] data = new byte[inputStream.available()];
inputStream.read(data);
inputStream.close();
// Create copy file in storage.
File outFile = new File(context.getFilesDir(), file);
FileOutputStream os = new FileOutputStream(outFile);
os.write(data);
os.close();
// Return a path to file which may be read in common way.
return outFile.getAbsolutePath();
} catch (IOException ex) {
Log.i(TAG, "Failed to upload a file");
}
return "";
}
private static final String TAG = "OpenCV/Sample/MobileNet";
private static final String[] classNames = {"background",
"aeroplane", "bicycle", "bird", "boat",
"bottle", "bus", "car", "cat", "chair",
"cow", "diningtable", "dog", "horse",
"motorbike", "person", "pottedplant",
"sheep", "sofa", "train", "tvmonitor"};
private Net net;
private CameraBridgeViewBase mOpenCvCameraView;
}