content: package com.taobao.android.mnndemo;
  
  import android.content.res.AssetManager;
  import android.graphics.Bitmap;
  import android.graphics.BitmapFactory;
  import android.graphics.Matrix;
  import android.os.AsyncTask;
  import android.support.v7.app.AppCompatActivity;
  import android.os.Bundle;
  import android.util.Log;
  import android.view.View;
  import android.widget.ImageView;
  import android.widget.TextView;
  
  import com.taobao.android.mnn.MNNForwardType;
  import com.taobao.android.mnn.MNNImageProcess;
  import com.taobao.android.mnn.MNNNetInstance;
  import com.taobao.android.utils.Common;
  import com.taobao.android.utils.TxtFileReader;
  
  import java.io.InputStream;
  import java.util.AbstractMap;
  import java.util.ArrayList;
  import java.util.Collections;
  import java.util.Comparator;
  import java.util.List;
  import java.util.Map;
  
  public class ImageActivity extends AppCompatActivity implements View.OnClickListener {
  
      private final String TargetPic = "MobileNet/testcat.jpg";
      private final String MobileWordsFileName = "MobileNet/synset_words.txt";
  
      private List<String> mMobileTaiWords;
  
      private ImageView mImageView;
      private TextView mTextView;
      private TextView mResultText;
      private TextView mTimeText;
      private Bitmap mBitmap;
  
      private MNNNetInstance mNetInstance;
      private MNNNetInstance.Session mSession;
      private MNNNetInstance.Session.Tensor mInputTensor;
  
      private final int InputWidth = 224;
      private final int InputHeight = 224;
  
      private class NetPrepareTask extends AsyncTask<String, Void, String> {
          protected String doInBackground(String... tasks) {
              prepareMobileNet();
              return "success";
          }
  
          protected void onPostExecute(String result) {
              mTextView.setText("Start MobileNet Inference");
              mTextView.setClickable(true);
          }
      }
  
      private class ImageProcessResult {
          public String result;
          public float inferenceTimeCost;
      }
  
      private class ImageProcessTask extends AsyncTask<String, Void, ImageProcessResult> {
  
          protected ImageProcessResult doInBackground(String... tasks) {
              /*
               *  convert data to input tensor
               */
              final MNNImageProcess.Config config = new MNNImageProcess.Config();
              // normalization params
              config.mean = new float[]{103.94f, 116.78f, 123.68f};
              config.normal = new float[]{0.017f, 0.017f, 0.017f};
              // input data format
              config.dest = MNNImageProcess.Format.BGR;
              // bitmap transform
              Matrix matrix = new Matrix();
              matrix.postScale(InputWidth / (float) mBitmap.getWidth(), InputHeight / (float) mBitmap.getHeight());
              matrix.invert(matrix);
  
              MNNImageProcess.convertBitmap(mBitmap, mInputTensor, config, matrix);
  
              final long startTimestamp = System.nanoTime();
              /**
               * inference
               */
              mSession.run();
  
              final long endTimestamp = System.nanoTime();
              final float inferenceTimeCost = (endTimestamp - startTimestamp) / 1000000.0f;
  
              /**
               * also you can use runWithCallback if you concern about some outputs of the middle layers,
               * this method execute inference and also return middle Tensor outputs synchronously.
               */
  //                MNNNetInstance.Session.Tensor[] tensors =  mSession.runWithCallback(new String[]{"conv1"});
  
              /**
               * get output tensor
               */
              MNNNetInstance.Session.Tensor output = mSession.getOutput(null);
              float[] result = output.getFloatData();// get float results
  
  
              // 显示结果
              List<Map.Entry<Integer, Float>> maybes = new ArrayList<>();
              for (int i = 0; i < result.length; i++) {
                  float confidence = result[i];
                  if (confidence > 0.01) {
                      maybes.add(new AbstractMap.SimpleEntry<Integer, Float>(i, confidence));
                  }
              }
  
              Log.i(Common.TAG, "Inference result size=" + result.length + ", maybe=" + maybes.size());
  
              Collections.sort(maybes, new Comparator<Map.Entry<Integer, Float>>() {
                  @Override
                  public int compare(Map.Entry<Integer, Float> o1, Map.Entry<Integer, Float> o2) {
                      if (Math.abs(o1.getValue() - o2.getValue()) <= Float.MIN_NORMAL) {
                          return 0;
                      }
                      return o1.getValue() > o2.getValue() ? -1 : 1;
                  }
              });
  
              final StringBuilder sb = new StringBuilder();
              for (Map.Entry<Integer, Float> entry : maybes) {
                  sb.append("物体:");
                  sb.append(mMobileTaiWords.get(entry.getKey()));
                  sb.append(" 自信度:");
                  sb.append(entry.getValue());
                  sb.append("\n");
              }
  
              final ImageProcessResult processResult = new ImageProcessResult();
              processResult.result = sb.toString();
              processResult.inferenceTimeCost = inferenceTimeCost;
              return processResult;
          }
  
          protected void onPostExecute(ImageProcessResult result) {
              mResultText.setText(result.result);
              mTimeText.setText("cost time：" + result.inferenceTimeCost + "ms");
          }
      }
  
  
      @Override
      protected void onCreate(Bundle savedInstanceState) {
          super.onCreate(savedInstanceState);
          setContentView(R.layout.activity_image);
  
          mImageView = findViewById(R.id.imageView);
          mTextView = findViewById(R.id.textView);
          mResultText = findViewById(R.id.editText);
          mTimeText = findViewById(R.id.timeText);
  
          mTextView.setOnClickListener(this);
  
          // show image
          AssetManager am = getAssets();
          try {
              final InputStream picStream = am.open(TargetPic);
              mBitmap = BitmapFactory.decodeStream(picStream);
              picStream.close();
              mImageView.setImageBitmap(mBitmap);
          } catch (Throwable t) {
              t.printStackTrace();
          }
  
  
          mTextView.setText("prepare Mobile Net ...");
          mTextView.setClickable(false);
          final NetPrepareTask prepareTask = new NetPrepareTask();
          prepareTask.execute("");
      }
  
  
      private void prepareMobileNet() {
  
          String modelPath = getCacheDir() + "mobilenet_v1.caffe.mnn";
  
          try {
              mMobileTaiWords = TxtFileReader.getUniqueUrls(getBaseContext(), MobileWordsFileName, Integer.MAX_VALUE);
          } catch (Throwable t) {
              t.printStackTrace();
          }
  
          // create net instance
          mNetInstance = MNNNetInstance.createFromFile(modelPath);
  
          // create session with config
          MNNNetInstance.Config config = new MNNNetInstance.Config();
          config.numThread = 4;// set threads
          config.forwardType = MNNForwardType.FORWARD_CPU.type;// set CPU/GPU
          /**
           * config middle layer names, if you concern about the output of the middle layer.
           * use session.getOutput("layer name") to get the output of the middle layer.
           */
  //        config.saveTensors = new String[]{"conv1"};
          mSession = mNetInstance.createSession(config);
  
          // get input tensor
          mInputTensor = mSession.getInput(null);
      }
  
      @Override
      public void onClick(View view) {
          if (mBitmap == null) {
              return;
          }
  
          mResultText.setText("inference result ...");
          ImageProcessTask imageProcessTask = new ImageProcessTask();
          imageProcessTask.execute("");
      }
  
      @Override
      protected void onDestroy() {
  
          /**
           * instance release
           */
          if (mNetInstance != null) {
              mNetInstance.release();
              mNetInstance = null;
          }
  
          super.onDestroy();
      }
  }
  