I want to make an object detection app with sound alarm when I detect on specific objects. I first want to try with tutorial https://github.com/bendahouwael/Vehicle-Detection-App-Android. This code is an application that detects car.
First I want to make sound alarm when it detects car. Have any ideas?
Here's the code about objectDetectorClass.java in that github link.
package com.example.imagepro;
import android.content.res.AssetFileDescriptor;
import android.content.res.AssetManager;
import android.graphics.Bitmap;
import org.checkerframework.checker.units.qual.A;
import org.opencv.android.Utils;
import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.Point;
import org.opencv.core.Scalar;
import org.opencv.imgproc.Imgproc;
import org.tensorflow.lite.Interpreter;
import org.tensorflow.lite.gpu.GpuDelegate;
import java.io.BufferedReader;
import java.io.File;
import java.io.FileInputStream;
import java.io.IOException;
import java.io.InputStreamReader;
import java.lang.reflect.Array;
import java.nio.ByteBuffer;
import java.nio.ByteOrder;
import java.nio.channels.FileChannel;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
import java.util.TreeMap;
public class objectDetectorClass {
private Interpreter interpreter;
private List<String> labelList;
private int INPUT_SIZE;
private int PIXEL_SIZE=3;
private int IMAGE_MEAN=0;
private float IMAGE_STD=255.0f;
private GpuDelegate gpuDelegate;
private int height=0;
private int width=0;
objectDetectorClass(AssetManager assetManager,String modelPath, String labelPath,int inputSize) throws IOException{
INPUT_SIZE=inputSize;
Interpreter.Options options=new Interpreter.Options();
gpuDelegate=new GpuDelegate();
options.addDelegate(gpuDelegate);
options.setNumThreads(4);
interpreter=new Interpreter(loadModelFile(assetManager,modelPath),options);
labelList=loadLabelList(assetManager,labelPath);
}
private List<String> loadLabelList(AssetManager assetManager, String labelPath) throws IOException {
List<String> labelList=new ArrayList<>();
BufferedReader reader=new BufferedReader(new InputStreamReader(assetManager.open(labelPath)));
String line;
while ((line=reader.readLine())!=null ){
labelList.add(line);
}
reader.close();
return labelList;
}
private ByteBuffer loadModelFile(AssetManager assetManager, String modelPath) throws IOException {
AssetFileDescriptor fileDescriptor=assetManager.openFd(modelPath);
FileInputStream inputStream=new FileInputStream(fileDescriptor.getFileDescriptor());
FileChannel fileChannel=inputStream.getChannel();
long startOffset =fileDescriptor.getStartOffset();
long declaredLength=fileDescriptor.getDeclaredLength();
return fileChannel.map(FileChannel.MapMode.READ_ONLY,startOffset,declaredLength);
}
public Mat recognizeImage(Mat mat_image){
Mat rotated_mat_image=new Mat();
Core.flip(mat_image.t(),rotated_mat_image,1);
Bitmap bitmap=null;
bitmap=Bitmap.createBitmap(rotated_mat_image.cols(),rotated_mat_image.rows(),Bitmap.Config.ARGB_8888);
Utils.matToBitmap(rotated_mat_image,bitmap);
height=bitmap.getHeight();
width=bitmap.getWidth();
Bitmap scaledBitmap=Bitmap.createScaledBitmap(bitmap,INPUT_SIZE,INPUT_SIZE,false);
ByteBuffer byteBuffer=convertBitmapToByteBuffer(scaledBitmap);
Object[] input=new Object[1];
input[0]=byteBuffer;
Map<Integer,Object> output_map=new TreeMap<>();
float[][][]boxes =new float[1][10][4];
float[][] scores=new float[1][10];
float[][] classes=new float[1][10];
output_map.put(0,boxes);
output_map.put(1,classes);
output_map.put(2,scores);
interpreter.runForMultipleInputsOutputs(input,output_map);
Object value=output_map.get(0);
Object Object_class=output_map.get(1);
Object score=output_map.get(2);
for (int i=0;i<10;i++){
float class_value=(float) Array.get(Array.get(Object_class,0),i);
float score_value=(float) Array.get(Array.get(score,0),i);
if(score_value>0.5){
Object box1=Array.get(Array.get(value,0),i);
float top=(float) Array.get(box1,0)*height;
float left=(float) Array.get(box1,1)*width;
float bottom=(float) Array.get(box1,2)*height;
float right=(float) Array.get(box1,3)*width;
if(class_value==2 || class_value==3 || class_value==5 || class_value==7 ){
Imgproc.rectangle(rotated_mat_image,new Point(left,top),new Point(right,bottom),new Scalar(0, 255, 0, 255),2);
Imgproc.putText(rotated_mat_image,labelList.get((int) class_value),new Point(left,top),3,1,new Scalar(255, 0, 0, 255),2);}
}
}
Core.flip(rotated_mat_image.t(),mat_image,0);
return mat_image;
}
private ByteBuffer convertBitmapToByteBuffer(Bitmap bitmap) {
ByteBuffer byteBuffer;
int quant=0;
int size_images=INPUT_SIZE;
if(quant==0){
byteBuffer=ByteBuffer.allocateDirect(1*size_images*size_images*3);
}
else {
byteBuffer=ByteBuffer.allocateDirect(4*1*size_images*size_images*3);
}
byteBuffer.order(ByteOrder.nativeOrder());
int[] intValues=new int[size_images*size_images];
bitmap.getPixels(intValues,0,bitmap.getWidth(),0,0,bitmap.getWidth(),bitmap.getHeight());
int pixel=0;
for (int i=0;i<size_images;++i){
for (int j=0;j<size_images;++j){
final int val=intValues[pixel++];
if(quant==0){
byteBuffer.put((byte) ((val>>16)&0xFF));
byteBuffer.put((byte) ((val>>8)&0xFF));
byteBuffer.put((byte) (val&0xFF));
}
else {
byteBuffer.putFloat((((val >> 16) & 0xFF))/255.0f);
byteBuffer.putFloat((((val >> 8) & 0xFF))/255.0f);
byteBuffer.putFloat((((val) & 0xFF))/255.0f);
}
}
}
return byteBuffer;
}
}
Thank you for reading!
