Android Studio tslite application wrong result problem

Question

Hello everyone I am working about android application that classify marble types. I've learned a model with Resnet Model. After that I copied a code from github and changed tslite model with mine.I selected a marble photo from my test files and upload to the app. But every photo gives me same result. I think problem is on bytebuffer set part. How can I solve this problem? Thank you All!.

public void classifyImage(Bitmap image){

    try {
        Model model = Model.newInstance(getApplicationContext());

        // Creates inputs for reference.
        TensorBuffer inputFeature0 = TensorBuffer.createFixedSize(new int[]{1, 224, 224, 3}, DataType.FLOAT32);
        ByteBuffer byteBuffer = ByteBuffer.allocateDirect(4 * imageSize * imageSize * 3);
        byteBuffer.order(ByteOrder.nativeOrder());

        int[] intValues = new int[imageSize * imageSize];
        image.getPixels(intValues, 0, image.getWidth(), 0, 0, image.getWidth(), image.getHeight());
        int pixel = 0;
        //iterate over each pixel and extract R, G, and B values. Add those values individually to the byte buffer.
        for(int i = 0; i < imageSize; i ++){
            for(int j = 0; j < imageSize; j++){
                int val = intValues[pixel++]; // RGB
                byteBuffer.putFloat(((val >> 16) & 0xFF) * (1.f / 255));
                byteBuffer.putFloat(((val >> 8) & 0xFF) * (1.f / 255));
                byteBuffer.putFloat((val & 0xFF) * (1.f / 255));
            }
        }

        inputFeature0.loadBuffer(byteBuffer);

        // Runs model inference and gets result.
        Model.Outputs outputs = model.process(inputFeature0);
        TensorBuffer outputFeature0 = outputs.getOutputFeature0AsTensorBuffer();

        float[] confidences = outputFeature0.getFloatArray();
        // find the index of the class with the biggest confidence.
        int maxPos = 0;
        float maxConfidence = 0;
        for (int i = 0; i < confidences.length; i++) {
            if (confidences[i] > maxConfidence) {
                maxConfidence = confidences[i];
                maxPos = i;
            }
        }
        String[] classes = {"AfyonBeyaz","AfyonGrey", "Bejmermer", "Kaplanpostu", "Karacabeysiyah", "KristalEmprador"};
        result.setText(classes[maxPos]);

        // Releases model resources if no longer used.
        model.close();
    } catch (IOException e) {
        // TODO Handle the exception
    }
}