I want to use a pre-trained VGG16 in keras. My question is simple. Should I normalize the input image before predicting its label?
According to Very Deep Convolutional Networks for Large-Scale Image Recognition, which is the paper that first presented VGG: "...The only pre-processing we do is subtracting the mean RGB value, computed on the training set, from each pixel."- (Karen Simonyan, Andrew Zisserman).
I am certain that Keras provides a preprocess function based on the above mentioned principle.
If it is in the TF version, its certainly in the other version.