Android图片分类器

implementation (group: 'org.deeplearning4j', name: 'deeplearning4j-core', version: '{{page.version}}') {
    exclude group: 'org.bytedeco', module: 'opencv-platform'
    exclude group: 'org.bytedeco', module: 'leptonica-platform'
    exclude group: 'org.bytedeco', module: 'hdf5-platform'
    exclude group: 'org.nd4j', module: 'nd4j-base64'
}
implementation group: 'org.nd4j', name: 'nd4j-native', version: '{{page.version}}'
implementation group: 'org.nd4j', name: 'nd4j-native', version: '{{page.version}}', classifier: "android-arm"
implementation group: 'org.nd4j', name: 'nd4j-native', version: '{{page.version}}', classifier: "android-arm64"
implementation group: 'org.nd4j', name: 'nd4j-native', version: '{{page.version}}', classifier: "android-x86"
implementation group: 'org.nd4j', name: 'nd4j-native', version: '{{page.version}}', classifier: "android-x86_64"
implementation group: 'org.bytedeco', name: 'openblas', version: '0.3.7-1.5.2'
implementation group: 'org.bytedeco', name: 'openblas', version: '0.3.7-1.5.2', classifier: "android-arm"
implementation group: 'org.bytedeco', name: 'openblas', version: '0.3.7-1.5.2', classifier: "android-arm64"
implementation group: 'org.bytedeco', name: 'openblas', version: '0.3.7-1.5.2', classifier: "android-x86"
implementation group: 'org.bytedeco', name: 'openblas', version: '0.3.7-1.5.2', classifier: "android-x86_64"
implementation group: 'org.bytedeco', name: 'opencv', version: '4.1.2-1.5.2'
implementation group: 'org.bytedeco', name: 'opencv', version: '4.1.2-1.5.2', classifier: "android-arm"
implementation group: 'org.bytedeco', name: 'opencv', version: '4.1.2-1.5.2', classifier: "android-arm64"
implementation group: 'org.bytedeco', name: 'opencv', version: '4.1.2-1.5.2', classifier: "android-x86"
implementation group: 'org.bytedeco', name: 'opencv', version: '4.1.2-1.5.2', classifier: "android-x86_64"
implementation group: 'org.bytedeco', name: 'leptonica', version: '1.78.0-1.5.2'
implementation group: 'org.bytedeco', name: 'leptonica', version: '1.78.0-1.5.2', classifier: "android-arm"
implementation group: 'org.bytedeco', name: 'leptonica', version: '1.78.0-1.5.2', classifier: "android-arm64"
implementation group: 'org.bytedeco', name: 'leptonica', version: '1.78.0-1.5.2', classifier: "android-x86"
implementation group: 'org.bytedeco', name: 'leptonica', version: '1.78.0-1.5.2', classifier: "android-x86_64"

implementation 'com.google.code.gson:gson:2.8.2'
annotationProcessor 'org.projectlombok:lombok:1.16.16'

//This corrects for a junit version conflict.
configurations.all {
    resolutionStrategy.force 'junit:junit:4.12'
}

multiDexEnabled true

configurations.all {
    resolutionStrategy.force 'junit:junit:4.12'
}

private class AsyncTaskRunner extends AsyncTask<String, Integer, INDArray> {

       //在调用后台线程之前在UI中运行。
        @Override
        protected void onPreExecute() {
            super.onPreExecute();
        }

        @Override
        protected INDArray doInBackground(String... params) {
            //主后台线程，这将加载模型并测试输入图像
            //图像的尺寸设置在这里
            int height = 28;
            int width = 28;
            int channels = 1;

            //现在我们使用try/catch块从raw文件夹加载模型
            try {
                // Load the pretrained network.
                InputStream inputStream = getResources().openRawResource(R.raw.trained_mnist_model);
                MultiLayerNetwork model = ModelSerializer.restoreMultiLayerNetwork(inputStream);

                //加载要测试的图像文件
                File f=new File(absolutePath, "drawn_image.jpg");

               //使用nativeImageLoader转换为数值矩阵
                NativeImageLoader loader = new NativeImageLoader(height, width, channels);

                //将图像放入INDArray
                INDArray image = loader.asMatrix(f);

                //值需要缩放
                DataNormalization scalar = new ImagePreProcessingScaler(0, 1);

                //然后调用图像数据集上的标量
                scalar.transform(image);

           
                //通过神经网络存储在输出数组中
                output = model.output(image);

            } catch (IOException e) {
                e.printStackTrace();
            }
            return output;
        }

    //图形输入代码
    public class DrawingView extends View {

        private Path    mPath;
        private Paint   mBitmapPaint;
        private Paint   mPaint;
        private Bitmap  mBitmap;
        private Canvas  mCanvas;

        public DrawingView(Context c) {
            super(c);

            mPath = new Path();
            mBitmapPaint = new Paint(Paint.DITHER_FLAG);
            mPaint = new Paint();
            mPaint.setAntiAlias(true);
            mPaint.setStrokeJoin(Paint.Join.ROUND);
            mPaint.setStrokeCap(Paint.Cap.ROUND);
            mPaint.setStrokeWidth(60);
            mPaint.setDither(true);
            mPaint.setColor(Color.WHITE);
            mPaint.setStyle(Paint.Style.STROKE);
        }

        @Override
        protected void onSizeChanged(int W, int H, int oldW, int oldH) {
            super.onSizeChanged(W, H, oldW, oldH);
            mBitmap = Bitmap.createBitmap(W, H, Bitmap.Config.ARGB_4444);
            mCanvas = new Canvas(mBitmap);
        }

        @Override
        protected void onDraw(Canvas canvas) {
            canvas.drawBitmap(mBitmap, 0, 0, mBitmapPaint);
            canvas.drawPath(mPath, mPaint);
        }

        private float mX, mY;
        private static final float TOUCH_TOLERANCE = 4;

        private void touch_start(float x, float y) {
            mPath.reset();
            mPath.moveTo(x, y);
            mX = x;
            mY = y;
        }
        private void touch_move(float x, float y) {
            float dx = Math.abs(x - mX);
            float dy = Math.abs(y - mY);
            if (dx >= TOUCH_TOLERANCE || dy >= TOUCH_TOLERANCE) {
                mPath.quadTo(mX, mY, (x + mX)/2, (y + mY)/2);
                mX = x;
                mY = y;
            }
        }
        private void touch_up() {
            mPath.lineTo(mX, mY);
            mCanvas.drawPath(mPath, mPaint);
            mPath.reset();
        }

        @Override
        public boolean onTouchEvent(MotionEvent event) {
            float x = event.getX();
            float y = event.getY();

            switch (event.getAction()) {
                case MotionEvent.ACTION_DOWN:
                    invalidate();
                    clear();
                    touch_start(x, y);
                    invalidate();
                    break;
                case MotionEvent.ACTION_MOVE:
                    touch_move(x, y);
                    invalidate();
                    break;
                case MotionEvent.ACTION_UP:
                    touch_up();
                    absolutePath = saveDrawing();
                    invalidate();
                    clear();
                    loadImageFromStorage(absolutePath);
                    onProgressBar();
                    //保存图像后立即启动asyncTask
                    AsyncTaskRunner runner = new AsyncTaskRunner();
                    runner.execute(absolutePath);
                    break;

            }
            return true;
        }

        public void clear(){
            mBitmap.eraseColor(Color.TRANSPARENT);
            invalidate();
            System.gc();
        }

    }

public String saveDrawing(){
        drawingView.setDrawingCacheEnabled(true);
        Bitmap b = drawingView.getDrawingCache();

        ContextWrapper cw = new ContextWrapper(getApplicationContext());
        //设置存储路径
        File directory = cw.getDir("imageDir", Context.MODE_PRIVATE);
        //创建imageDir并将文件存储在那里。每个新图形都将覆盖上一个
        File mypath=new File(directory,"drawn_image.jpg");

       //使用fileOutputStream将文件写入try/catch块中的位置
        FileOutputStream fos = null;
        try {
            fos = new FileOutputStream(mypath);
            b.compress(Bitmap.CompressFormat.JPEG, 100, fos);
        } catch (Exception e) {
            e.printStackTrace();
        } finally {
            try {
                fos.close();
            } catch (IOException e) {
                e.printStackTrace();
            }
        }
        return directory.getAbsolutePath();
    }

    private void loadImageFromStorage(String path)
    {

        //使用fileOutputStream将文件写入try/catch块中的位置
        try {
            File f=new File(path, "drawn_image.jpg");
            Bitmap b = BitmapFactory.decodeStream(new FileInputStream(f));
            ImageView img=(ImageView)findViewById(R.id.outputView);
            img.setImageBitmap(b);
        }
        catch (FileNotFoundException e)
        {
            e.printStackTrace();
        }

    }

    //helper类返回输出数组中的最大值
    public static double arrayMaximum(double[] arr) {
        double max = Double.NEGATIVE_INFINITY;
        for(double cur: arr)
            max = Math.max(max, cur);
        return max;
    }

     //helper类查找最大置信分数的索引（因此是数值）
    public int getIndexOfLargestValue( double[] array )
    {
        if ( array == null || array.length == 0 ) return -1;
        int largest = 0;
        for ( int i = 1; i < array.length; i++ )
        {if ( array[i] > array[largest] ) largest = i;            }
        return largest;
    }

    public void onProgressBar(){
        TextView bar = findViewById(R.id.processing);
        bar.setVisibility(View.VISIBLE);
    }

    public void offProgressBar(){
        TextView bar = findViewById(R.id.processing);
        bar.setVisibility(View.INVISIBLE);
    }

public class MainActivity extends AppCompatActivity {

    MainActivity.DrawingView drawingView;
    String absolutePath;
    public static INDArray output;

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

        RelativeLayout parent = findViewById(R.id.layout2);
        drawingView = new MainActivity.DrawingView(this);
        parent.addView(drawingView);
    }

        @Override
        protected void onProgressUpdate(Integer... values) {
            super.onProgressUpdate(values);
        }

        @Override
        protected void onPostExecute(INDArray result) {
            super.onPostExecute(result);

            //用于控制输出概率的小数位数
            DecimalFormat df2 = new DecimalFormat(".##");

            //将神经网络输出传输到数组
            double[] results = {result.getDouble(0,0),result.getDouble(0,1),result.getDouble(0,2),
                    result.getDouble(0,3),result.getDouble(0,4),result.getDouble(0,5),result.getDouble(0,6),
                    result.getDouble(0,7),result.getDouble(0,8),result.getDouble(0,9),};

            //找到UI tvs以显示预测值和置信值
            TextView out1 = findViewById(R.id.prediction);
            TextView out2 = findViewById(R.id.confidence);

            //使用下面定义的助手函数显示值
            out2.setText(String.valueOf(df2.format(arrayMaximum(results))));
            out1.setText(String.valueOf(getIndexOfLargestValue(results)));

            //关闭进度测试的助手函数
            offProgressBar();
        }