I need to normalize a bitmap and store it in a TensorImage. Is there any way to do this?

Question

Bitmap holds only integer values (0-255). I need to divide each pixel value by 255. The bitmap is converted to a TensorImage and then getBuffer() is called when passing it to the interpreter that predicts output.(tflite.run()) Somewhere in the middle, I have to divide each RGB pixel by 255. I'm afraid there is another drawback as the getBuffer() function returns a byte buffer. I'm not able to find much documentation on TensorFlow lite functions. So I am unsure if tflite.run() can accept only byte buffers or not. I am coding in Java and am new to Android AppD. Please help as this normalization is essential to predict the right value.

Here is the code that converts the bitmap to tensorimage after resizing. It is here I need to divide each pixel value by 255 but am stumped.

 private TensorImage resizePic(Bitmap bp) {
        ImageProcessor imageProcessor =
                new ImageProcessor.Builder()
                        .add(new ResizeOp(60, 60, ResizeOp.ResizeMethod.BILINEAR))
                        .build();
        TensorImage tImage = new TensorImage(DataType.FLOAT32);
        tImage.load(bp);
        tImage = imageProcessor.process(tImage);
        return tImage;
    }

Here is the line that runs the model

tflite.run(tImage.getBuffer(), probabilityBuffer.getBuffer());

probabilityBuffer holds the output.

Answer 1

I was able to construct suitable functions using the following links-

1. Converting Bitmap to ByteBuffer (float) in Tensorflow-lite Android

2. https://heartbeat.fritz.ai/image-classification-on-android-with-tensorflow-lite-and-camerax-4f72e8fdca79

The second link is in Kotlin. Here is the code:

private ByteBuffer convertBitmapToByteBuffer(Bitmap bp) {
        ByteBuffer imgData = ByteBuffer.allocateDirect(Float.BYTES*60*60*3);
        imgData.order(ByteOrder.nativeOrder());
        Bitmap bitmap = Bitmap.createScaledBitmap(bp,60,60,true);
        int [] intValues = new int[60*60];
        bitmap.getPixels(intValues, 0, bitmap.getWidth(), 0, 0, bitmap.getWidth(), bitmap.getHeight());

        // Convert the image to floating point.
        int pixel = 0;

        for (int i = 0; i < 60; ++i) {
            for (int j = 0; j < 60; ++j) {
                final int val = intValues[pixel++];

                imgData.putFloat(((val>> 16) & 0xFF) / 255.f);
                imgData.putFloat(((val>> 8) & 0xFF) / 255.f);
                imgData.putFloat((val & 0xFF) / 255.f);
            }
        }
        return imgData;
    }

Here, 60 is my required input image height and width. Also, this method doesn't require use of a TensorImage. So the final call of tflite.run() looks like this:

tflite.run(convertBitmapToByteBuffer(bp), probabilityBuffer.getBuffer());

Here, bp is the bitmap image.