55.在手机上使用PaddleMobile实现图像分类-2

作者: 大勇任卷舒 | 来源:发表于2023-05-10 17:33 被阅读0次

创建Android项目

1、首先使用Android Studio创建一个普通的Android项目，包名为com.example.paddlemobile1

2、在main目录下创建l两个assets/paddle_models文件夹，这个文件夹存放PaddleFluid训练好的预测模型。PaddleMobile支持量化模型，使用模型量化可以把模型缩小至原来的四分之一，如果使用量化模型，那加载模型的接口也有修改一下，使用以下的接口加载模型：

public static native boolean loadQualified(String modelDir);

3、在main目录下创建一个jniLibs文件夹，这个文件夹是存放CPP编译库的，在本项目中就存放上一部分编译的libpaddle-mobile.so

4、在Android项目的配置文件夹中加上权限声明，因为我们要使用到读取相册和使用相机，所以加上以下的权限声明：

<uses-permission android:name="android.permission.CAMERA" />
<uses-permission android:name="android.permission.WRITE_EXTERNAL_STORAGE" />
<uses-permission android:name="android.permission.READ_EXTERNAL_STORAGE" />

5、修改activity_main.xml界面，修改成如下：

<?xml version="1.0" encoding="utf-8"?>
<RelativeLayout 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=".MainActivity">
<LinearLayout
    android:id="@+id/btn_ll"
    android:layout_alignParentBottom="true"
    android:layout_width="match_parent"
    android:layout_height="wrap_content"
    android:orientation="horizontal">

    <Button
        android:id="@+id/use_photo"
        android:layout_weight="1"
        android:layout_width="0dp"
        android:layout_height="wrap_content"
        android:text="相册" />

    <Button
        android:id="@+id/start_camera"
        android:layout_weight="1"
        android:layout_width="0dp"
        android:layout_height="wrap_content"
        android:text="拍照" />
</LinearLayout>

<TextView
    android:layout_above="@id/btn_ll"
    android:id="@+id/result_text"
    android:textSize="16sp"
    android:layout_width="match_parent"
    android:hint="预测结果会在这里显示"
    android:layout_height="100dp" />

<ImageView
    android:layout_alignParentTop="true"
    android:layout_above="@id/result_text"
    android:id="@+id/show_image"
    android:layout_width="match_parent"
    android:layout_height="match_parent" />
</RelativeLayout>

6、创建一个ImageRecognition.java的Java程序，这个程序的作用就是调用paddle-mobile/src/jni/paddle_mobile_jni.cpp的函数，对应的是里面的函数。目前支持一下几个接口。

package com.example.paddlemobile1;

public class ImageRecognition {
    // set thread num
    public static native void setThread(int threadCount);

//Load seperated parameters
public static native boolean load(String modelDir);

// load qualified model
public static native boolean loadQualified(String modelDir);

// Load combined parameters
public static native boolean loadCombined(String modelPath, String paramPath);

// load qualified model
public static native boolean loadCombinedQualified(String modelPath, String paramPath);

// object detection
public static native float[] predictImage(float[] buf, int[]ddims);

// predict yuv image
public static native float[] predictYuv(byte[] buf, int imgWidth, int imgHeight, int[] ddims, float[]meanValues);

// clear model
public static native void clear();
}

7、然后编写一个PhotoUtil.java的工具类。

package com.example.paddlemobile1;

import android.app.Activity;
import android.content.Context;
import android.content.Intent;
import android.database.Cursor;
import android.graphics.Bitmap;
import android.graphics.BitmapFactory;
import android.net.Uri;
import android.os.Build;
import android.provider.MediaStore;
import android.support.v4.content.FileProvider;
import android.util.Log;

import java.io.File;
import java.io.IOException;
import java.util.Arrays;

public class PhotoUtil {
// start camera
public static Uri start_camera(Activity activity, int requestCode) {
    Uri imageUri;
    // save image in cache path
    File outputImage = new File(activity.getExternalCacheDir(), "out_image.jpg");
    try {
        if (outputImage.exists()) {
            outputImage.delete();
        }
        outputImage.createNewFile();
    } catch (IOException e) {
        e.printStackTrace();
    }
    if (Build.VERSION.SDK_INT >= 24) {
        // compatible with Android 7.0 or over
        imageUri = FileProvider.getUriForFile(activity,
                "com.example.paddlemobile1", outputImage);
    } else {
        imageUri = Uri.fromFile(outputImage);
    }
    // set system camera Action
    Intent intent = new Intent(MediaStore.ACTION_IMAGE_CAPTURE);
    // set save photo path
    intent.putExtra(MediaStore.EXTRA_OUTPUT, imageUri);
    // set photo quality, min is 0, max is 1
    intent.putExtra(MediaStore.EXTRA_VIDEO_QUALITY, 0);
    activity.startActivityForResult(intent, requestCode);
    return imageUri;
}

// get picture in photo
public static void use_photo(Activity activity, int requestCode){
    Intent intent = new Intent(Intent.ACTION_PICK);
    intent.setType("image/*");
    activity.startActivityForResult(intent, requestCode);
}

// get photo from Uri
public static String get_path_from_URI(Context context, Uri uri) {
    String result;
    Cursor cursor = context.getContentResolver().query(uri, null, null, null, null);
    if (cursor == null) {
        result = uri.getPath();
    } else {
        cursor.moveToFirst();
        int idx = cursor.getColumnIndex(MediaStore.Images.ImageColumns.DATA);
        result = cursor.getString(idx);
        cursor.close();
    }
    return result;
}

// Compress the image to the size of the training image，and change RGB
public static float[] getScaledMatrix(Bitmap bitmap, int desWidth,
                               int desHeight) {
    float[] dataBuf = new float[3 * desWidth * desHeight];
    int rIndex;
    int gIndex;
    int bIndex;
    int[] pixels = new int[desWidth * desHeight];
    Bitmap bm = Bitmap.createScaledBitmap(bitmap, desWidth, desHeight, false);
    bm.getPixels(pixels, 0, desWidth, 0, 0, desWidth, desHeight);
    int j = 0;
    int k = 0;
    for (int i = 0; i < pixels.length; i++) {
        int clr = pixels[i];
        j = i / desHeight;
        k = i % desWidth;
        rIndex = j * desWidth + k;
        gIndex = rIndex + desHeight * desWidth;
        bIndex = gIndex + desHeight * desWidth;
        dataBuf[rIndex] = (float) ((clr & 0x00ff0000) >> 16) - 148;
        dataBuf[gIndex] = (float) ((clr & 0x0000ff00) >> 8) - 148;
        dataBuf[bIndex] = (float) ((clr & 0x000000ff)) - 148;

    }
    if (bm.isRecycled()) {
        bm.recycle();
    }
    return dataBuf;
}

// compress picture
public static Bitmap getScaleBitmap(String filePath) {
    BitmapFactory.Options opt = new BitmapFactory.Options();
    opt.inJustDecodeBounds = true;
    BitmapFactory.decodeFile(filePath, opt);

    int bmpWidth = opt.outWidth;
    int bmpHeight = opt.outHeight;

    int maxSize = 500;

    // compress picture with inSampleSize
    opt.inSampleSize = 1;
    while (true) {
        if (bmpWidth / opt.inSampleSize < maxSize || bmpHeight / opt.inSampleSize < maxSize) {
            break;
        }
        opt.inSampleSize *= 2;
    }
    opt.inJustDecodeBounds = false;
    return BitmapFactory.decodeFile(filePath, opt);
}
}

start_camera()方法是启动相机并返回图片的URI。
use_photo()方法是打开相册，获取到的图片URI在回到函数中获取。
get_path_from_URI()方法是把图片的URI转换成绝对路径。
getScaledMatrix()方法是把图片压缩成跟训练时的大小，并转换成预测需要用的数据格式浮点数组。
getScaleBitmap()方法是对图片进行等比例压缩，减少内存的支出。

8、最后修改MainActivity.java，修改如下：

package com.example.paddlemobile1;

import android.Manifest;
import android.annotation.SuppressLint;
import android.app.Activity;
import android.content.Context;
import android.content.Intent;
import android.content.pm.PackageManager;
import android.graphics.Bitmap;
import android.net.Uri;
import android.os.Bundle;
import android.os.Environment;
import android.support.annotation.NonNull;
import android.support.annotation.Nullable;
import android.support.v4.app.ActivityCompat;
import android.support.v4.content.ContextCompat;
import android.support.v7.app.AppCompatActivity;
import android.util.Log;
import android.view.View;
import android.widget.Button;
import android.widget.ImageView;
import android.widget.TextView;
import android.widget.Toast;

import com.bumptech.glide.Glide;
import com.bumptech.glide.load.engine.DiskCacheStrategy;
import com.bumptech.glide.request.RequestOptions;

import java.io.File;
import java.io.FileOutputStream;
import java.io.InputStream;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;

public class MainActivity extends AppCompatActivity {
    private static final String TAG = MainActivity.class.getName();
    private static final int USE_PHOTO = 1001;
    private static final int START_CAMERA = 1002;
    private Uri image_uri;
    private ImageView show_image;
    private TextView result_text;
    private String assets_path = "paddle_models";
    private boolean load_result = false;
    private int[] ddims = {1, 3, 224, 224};
private static final String[] PADDLE_MODEL = {
        "lenet",
        "alexnet",
        "vgg16",
        "resnet",
        "googlenet",
        "mobilenet_v1",
        "mobilenet_v2",
        "inception_v1",
        "inception_v2",
        "squeezenet"
};

// load paddle-mobile api
static {
    try {
        System.loadLibrary("paddle-mobile");

    } catch (SecurityException e) {
        e.printStackTrace();

    } catch (UnsatisfiedLinkError e) {
        e.printStackTrace();

    } catch (NullPointerException e) {
        e.printStackTrace();

    }

}

@Override
protected void onCreate(Bundle savedInstanceState) {
    super.onCreate(savedInstanceState);
    setContentView(R.layout.activity_main);

    init();
}

// initialize view
private void init() {
    request_permissions();
    show_image = (ImageView) findViewById(R.id.show_image);
    result_text = (TextView) findViewById(R.id.result_text);
    Button use_photo = (Button) findViewById(R.id.use_photo);
    Button start_photo = (Button) findViewById(R.id.start_camera);

    // use photo click
    use_photo.setOnClickListener(new View.OnClickListener() {
        @Override
        public void onClick(View view) {
            PhotoUtil.use_photo(MainActivity.this, USE_PHOTO);
            //                load_model();
            }
        });

    // start camera click
    start_photo.setOnClickListener(new View.OnClickListener() {
        @Override
        public void onClick(View view) {
            image_uri = PhotoUtil.start_camera(MainActivity.this, START_CAMERA);
        }
    });

    // copy file from assets to sdcard
    String sdcard_path = Environment.getExternalStorageDirectory()
            + File.separator + assets_path;
    copy_file_from_asset(this, assets_path, sdcard_path);

    // load model
    load_model();
}

// load infer model
private void load_model() {
    String model_path = Environment.getExternalStorageDirectory()
            + File.separator + assets_path + File.separator + PADDLE_MODEL[4];
    Log.d(TAG, model_path);
    load_result = ImageRecognition.load(model_path);
    if (load_result) {
        Log.d(TAG, "model load success");
    } else {
        Log.d(TAG, "model load fail");
    }
}

// clear infer model
private void clear_model() {
    ImageRecognition.clear();
    Log.d(TAG, "model is clear");
}

// copy file from asset to sdcard
public void copy_file_from_asset(Context context, String oldPath, String newPath) {
    try {
        String[] fileNames = context.getAssets().list(oldPath);
        if (fileNames.length > 0) {
            // directory
            File file = new File(newPath);
            if (!file.exists()) {
                file.mkdirs();
            }
            // copy recursivelyC
            for (String fileName : fileNames) {
                copy_file_from_asset(context, oldPath + "/" + fileName, newPath + "/" + fileName);
            }
            Log.d(TAG, "copy files finish");
        } else {
            // file
            File file = new File(newPath);
            // if file exists will never copy
            if (file.exists()) {
                return;
            }

            // copy file to new path
            InputStream is = context.getAssets().open(oldPath);
            FileOutputStream fos = new FileOutputStream(file);
            byte[] buffer = new byte[1024];
            int byteCount;
            while ((byteCount = is.read(buffer)) != -1) {
                fos.write(buffer, 0, byteCount);
            }
            fos.flush();
            is.close();
            fos.close();
        }
    } catch (Exception e) {
        e.printStackTrace();
    }
}

@Override
protected void onActivityResult(int requestCode, int resultCode, @Nullable Intent data) {
    String image_path;
    RequestOptions options = new RequestOptions().skipMemoryCache(true).diskCacheStrategy(DiskCacheStrategy.NONE);
    if (resultCode == Activity.RESULT_OK) {
        switch (requestCode) {
            case USE_PHOTO:
                if (data == null) {
                    Log.w(TAG, "user photo data is null");
                    return;
                }
                image_uri = data.getData();
                Glide.with(MainActivity.this).load(image_uri).apply(options).into(show_image);
                // get image path from uri
                image_path = PhotoUtil.get_path_from_URI(MainActivity.this, image_uri);
                // show result
                result_text.setText(image_path);
                // predict image
                predict_image(PhotoUtil.get_path_from_URI(MainActivity.this, image_uri));
                break;
            case START_CAMERA:
                // show photo
                Glide.with(MainActivity.this).load(image_uri).apply(options).into(show_image);
                // get image path from uri
                image_path = PhotoUtil.get_path_from_URI(MainActivity.this, image_uri);
                // show result
                result_text.setText(image_path);
                // predict image
                predict_image(PhotoUtil.get_path_from_URI(MainActivity.this, image_uri));
                break;
        }
    }
}

@SuppressLint("SetTextI18n")
private void predict_image(String image_path) {
    // picture to float array
    Bitmap bmp = PhotoUtil.getScaleBitmap(image_path);
    float[] inputData = PhotoUtil.getScaledMatrix(bmp, ddims[2], ddims[3]);
    try {
        long start = System.currentTimeMillis();
        // get predict result
        float[] result = ImageRecognition.predictImage(inputData, ddims);
        Log.d(TAG, "origin predict result:" + Arrays.toString(result));
        long end = System.currentTimeMillis();
        long time = end - start;
        Log.d("result length", String.valueOf(result.length));
        // show predict result and time
        int r = get_max_result(result);
        String show_text = "result：" + r + "\nprobability：" + result[r] + "\ntime：" + time + "ms";
        result_text.setText(show_text);
    } catch (Exception e) {
        e.printStackTrace();
    }
}

private int get_max_result(float[] result) {
    float probability = result[0];
    int r = 0;
    for (int i = 0; i < result.length; i++) {
        if (probability < result[i]) {
            probability = result[i];
            r = i;
        }
    }
    return r;
}

// request permissions
private void request_permissions() {

    List<String> permissionList = new ArrayList<>();
    if (ContextCompat.checkSelfPermission(this, Manifest.permission.CAMERA) != PackageManager.PERMISSION_GRANTED) {
        permissionList.add(Manifest.permission.CAMERA);
    }

    if (ContextCompat.checkSelfPermission(this, Manifest.permission.WRITE_EXTERNAL_STORAGE) != PackageManager.PERMISSION_GRANTED) {
        permissionList.add(Manifest.permission.WRITE_EXTERNAL_STORAGE);
    }

    if (ContextCompat.checkSelfPermission(this, Manifest.permission.READ_EXTERNAL_STORAGE) != PackageManager.PERMISSION_GRANTED) {
        permissionList.add(Manifest.permission.READ_EXTERNAL_STORAGE);
    }

    // if list is not empty will request permissions
    if (!permissionList.isEmpty()) {
        ActivityCompat.requestPermissions(this, permissionList.toArray(new String[permissionList.size()]), 1);
    }
}

@Override
public void onRequestPermissionsResult(int requestCode, @NonNull String[] permissions, @NonNull int[] grantResults) {
    super.onRequestPermissionsResult(requestCode, permissions, grantResults);
    switch (requestCode) {
        case 1:
            if (grantResults.length > 0) {
                for (int i = 0; i < grantResults.length; i++) {

                    int grantResult = grantResults[i];
                    if (grantResult == PackageManager.PERMISSION_DENIED) {
                        String s = permissions[i];
                        Toast.makeText(this, s + " permission was denied", Toast.LENGTH_SHORT).show();
                    }
                }
            }
            break;
    }
}

@Override
protected void onDestroy() {
    // clear model before destroy app
    clear_model();
    super.onDestroy();
}
}

load_model()方法是加载预测模型的。
clear_model()方法是清空预测模型的。
copy_file_from_asset()方法是把预测模型复制到内存卡上。
predict_image()方法是预测图片的。
get_max_result()方法是获取概率最大的预测结果。
request_permissions()方法是动态请求权限的。

因为使用到图像加载框架Glide，所以要在build.gradle加入以下的引用。

implementation 'com.github.bumptech.glide:glide:4.3.1'

8、最后运行项目，选择图片预测就会得到结果。
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55.在手机上使用PaddleMobile实现图像分类-2

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