如何在 Android phone GPU 上 运行 TFLite 网络?

How to run TFLite network on Android phone GPU?

我在对象检测中使用了 tensorflow 示例教程并且它有效,但是当我尝试添加 GpuDelegate 时它中断了:

try {
  GpuDelegate delegate = new GpuDelegate();
  Interpreter.Options options = (new Interpreter.Options()).addDelegate(delegate);
  d.tfLite = new Interpreter(loadModelFile(assetManager, modelFilename),options);
} catch (Exception e) {
  throw new RuntimeException(e);
}

错误 cannot find symbol class GpuDelegate

我对 Java 和 Android 很陌生,我猜这与进口有关?所以这是我的进口商品:

package org.tensorflow.lite.examples.detection.tflite;

import android.content.res.AssetFileDescriptor;
import android.content.res.AssetManager;
import android.graphics.Bitmap;
import android.graphics.RectF;
import android.os.Trace;
import java.io.BufferedReader;
import java.io.FileInputStream;
import java.io.IOException;
import java.io.InputStream;
import java.io.InputStreamReader;
import java.nio.ByteBuffer;
import java.nio.ByteOrder;
import java.nio.MappedByteBuffer;
import java.nio.channels.FileChannel;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Vector;
import org.tensorflow.lite.Interpreter;
import org.tensorflow.lite.examples.detection.env.Logger;

并且在org.tensorflow.lite中没有GpuDelegate

我能得到解决这个问题的指导吗?

编辑: 这是 build.gradle(:app)

中的依赖项
dependencies {
    implementation fileTree(dir: 'libs', include: ['*.jar','*.aar'])
    implementation 'androidx.appcompat:appcompat:1.0.0'
    implementation 'androidx.coordinatorlayout:coordinatorlayout:1.0.0'
    implementation 'com.google.android.material:material:1.0.0'
    implementation('org.tensorflow:tensorflow-lite:0.0.0-nightly') { changing = true }
    androidTestImplementation 'androidx.test.ext:junit:1.1.1'
    androidTestImplementation 'com.android.support.test:rules:1.0.2'
    androidTestImplementation 'com.google.truth:truth:1.0.1'
}

要使用 GpuDelegate class 你必须在应用 build.gradle 文件中导入这些依赖项:

dependencies {
...
implementation 'org.tensorflow:tensorflow-lite:0.0.0-nightly'
implementation 'org.tensorflow:tensorflow-lite-gpu:0.0.0-nightly'
}