Hi,
Glad it worked!
I am not sure about what you mean by scaling and normalization. If you are asking about scaling the values in [0,1] range by dividing RGB values with 255 (pixel value max), then yes, you should use scaling. It will help the model with faster convergence.
I generally don’t use normalization very often as it tends to hurt color consistency in image generation task (I work with image inpainting task). But I have seen some strong arguments for normalization for classification tasks. Most of the normalization values are from ImageNet and work well with most of the images.
I would suggest going through some well-known classification architectures to get some pointers on input processing.
Maybe, you can start from here  1.