在android中使用tensorflow lite解释器显示图片

implementation 'org.tensorflow:tensorflow-lite:2.5.0'

import org.tensorflow.lite.Interpreter;

Interpreter interpreter = new Interpreter(loadModelFile());

private MappedByteBuffer loadModelFile() throws IOException {
    AssetFileDescriptor fileDescriptor = getAssets().openFd("model.tflite");
    FileInputStream inputStream = new FileInputStream(fileDescriptor.getFileDescriptor());
    FileChannel fileChannel = inputStream.getChannel();
    long startOffset = fileDescriptor.getStartOffset();
    long declaredLength = fileDescriptor.getDeclaredLength();
    return fileChannel.map(FileChannel.MapMode.READ_ONLY, startOffset, declaredLength);
}

import android.graphics.Bitmap;
import android.graphics.BitmapFactory;
import android.graphics.Matrix;

Bitmap bitmap = BitmapFactory.decodeResource(getResources(), R.drawable.image);
Matrix matrix = new Matrix();
matrix.postScale(scaleX, scaleY); // 根据模型要求的尺寸进行缩放
Bitmap resizedBitmap = Bitmap.createBitmap(bitmap, 0, 0, bitmap.getWidth(), bitmap.getHeight(), matrix, true);
int inputSize = interpreter.getInputTensor(0).shape()[1]; // 获取模型输入的尺寸
Bitmap resizedImage = Bitmap.createScaledBitmap(resizedBitmap, inputSize, inputSize, true);

import org.tensorflow.lite.Tensor;

float[][] output = new float[1][OUTPUT_CLASSES]; // 假设输出结果是一个浮点数数组
interpreter.run(resizedImage, output);

// 处理输出结果
float maxConfidence = 0;
int maxIndex = -1;
for (int i = 0; i < OUTPUT_CLASSES; i++) {
    if (output[0][i] > maxConfidence) {
        maxConfidence = output[0][i];
        maxIndex = i;
    }
}

// 输出结果
String result = "识别结果：" + labels[maxIndex] + "，置信度：" + maxConfidence;
textView.setText(result);