Delete ImageClassification.java

Count/ImageClassification.java

-package com.example.count;
-
-import android.app.Activity;
-import android.content.DialogInterface;
-import android.content.Intent;
-import android.graphics.Bitmap;
-import android.net.Uri;
-import android.os.Bundle;
-import android.util.Log;
-import android.widget.Toast;
-
-import androidx.annotation.NonNull;
-import androidx.appcompat.app.AlertDialog;
-
-import com.example.count.imageclsicifiaction.Classifier;
-import com.example.count.imageclsicifiaction.TensorFlowImageClassifier;
-
-import java.io.ByteArrayOutputStream;
-import java.text.SimpleDateFormat;
-import java.util.ArrayList;
-import java.util.Arrays;
-import java.util.Calendar;
-import java.util.Date;
-import java.util.List;
-import java.util.Random;
-import java.util.TimeZone;
-import java.util.concurrent.Executor;
-import java.util.concurrent.Executors;
-
-public class ImageClassification extends Activity {
-    private static final String MODEL_PATH = "model.tflite";
-    private static final boolean QUANT = false;
-    private static final String LABEL_PATH = "labels.txt";
-    private static final int INPUT_SIZE = 128;
-    private Classifier classifier;
-    private Executor executor = Executors.newSingleThreadExecutor();
-    public ArrayList<Bitmap> byteArrayPicture = new ArrayList<Bitmap>();
-    public Boolean Othertype=false;
-    public int OtherImagePosition;
-    public Boolean DetectOrNot=false;
-    public Boolean DetectOrNotmodel=false;
-    public Boolean freeOrNot=false;
-
-    @Override
-    protected void onCreate(Bundle savedInstanceState) {
-        super.onCreate(savedInstanceState);
-        setContentView(R.layout.clasifiation_layout);
-        backgroundCacification newbackGP = new backgroundCacification();
-        newbackGP.start();
-        freeOrNot=false;
-
-    }
-    class backgroundCacification extends Thread{
-        List<Integer> listDitect= new ArrayList<Integer>();
-        List<Integer> listMarkOnly= new ArrayList<Integer>();
-        @Override
-        public void run(){
-            initTensorFlowAndLoadModel();
-            while(true){
-                if (DetectOrNotmodel){
-                    //GlobleVariable.bitmapArrayPicture.size()
-                    for (int i = 0; i <GlobleVariable.bitmapArrayPicture.size() ; i++) {
-                        final Bitmap bmpimageDetected = Bitmap.createScaledBitmap(GlobleVariable.bitmapArrayPicture.get(i), INPUT_SIZE, INPUT_SIZE, false);
-                        final List<Classifier.Recognition> results = classifier.recognizeImage(bmpimageDetected);
-                        if(results.get(0).getTitle().equals("Y")){
-                            listMarkOnly.add(i);
-                        }
-                        final int k=i;
-                        try {
-                            // code runs in a thread
-                            runOnUiThread(new Runnable() {
-                                @Override
-                                public void run() {
-                                    Toast.makeText(ImageClassification.this, Integer.toString(k), Toast.LENGTH_SHORT).show();
-
-
-                                }
-                            });
-                        } catch (final Exception ex) {
-                            Log.i("---","Exception in thread");
-                        }
-
-                    }
-                    break;
-                }
-            }
-            int Right=0;
-            int Wrong=0;
-            for(int x=0;x<listMarkOnly.size();x++){
-                if(GlobleVariable.listOriginal.get(listMarkOnly.get(x))==3 || GlobleVariable.listOriginal.get(listMarkOnly.get(x))==4){
-                    Right=Right+1;
-                }
-                else{
-                    Wrong=Wrong+1;
-                }
-            }
-            GlobleVariable.RightGloble=Right;
-            GlobleVariable.WrongGloble=Wrong;
-            GlobleVariable.resultList.add(Right-Wrong);
-            startActivity(new Intent(ImageClassification.this, ResultActivity.class));
-        }
-
-
-        private void initTensorFlowAndLoadModel() {
-            executor.execute(new Runnable() {
-                @Override
-                public void run() {
-                    try {
-                        classifier = TensorFlowImageClassifier.create(
-                                getAssets(),
-                                MODEL_PATH,
-                                LABEL_PATH,
-                                INPUT_SIZE,
-                                QUANT);
-                        DetectOrNotmodel=true;
-
-                    } catch (final Exception e) {
-                        throw new RuntimeException("Error initializing TensorFlow!", e);
-                    }
-                }
-            });
-        }
-    }
-
-
-}