Trying different input for mnv2 model

Hi!

I'm hoping to test out running classification on some of my own images using the CFU-Playground framework with the mnv2 model. I wanted to ask exactly what kind of preprocessing was applied to the [mnv2 input files](https://github.com/google/CFU-Playground/tree/main/common/src/models/mnv2) provided.

From taking a look at them, it seems that they're 3 channel 160 x 160 pixel images with uint8 data (correct me if I'm wrong), but I'm unsure if any extra processing was applied to the image data. Any info would be helpful.

So far, I tried using something like this to get the model input data from a 160x160 jpeg, but I didn't get a good classification:
```
img_jpeg = tf.io.read_file(filename)
img = tf.image.decode_image(img_jpeg, dtype=tf.dtypes.uint8)

img.numpy().tofile("out.dat")
```

Also, I was wondering if you have any info on interpreting the output of the model. Does it directly correspond to the mnv2 label?