Imagenet normalization
Nick-Morgan opened this issue · comments
The pytorch docs (link) say to normalize images via
normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406],
std=[0.229, 0.224, 0.225])
However, the notebook in this repo normalizes via
transforms.Normalize(mean=[0.40760392, 0.45795686, 0.48501961],
std=[1,1,1]
I am trying to re-create the results from the original paper, so I am just curious about this. Is this method of normalization specific to this task, did the imagenet normalizations for pytorch change over time, or is there some other reason I may be missing?
The original VGG network (same as AlexNet etc.) did not rescale the input images. This was only done for the pytorch re-implementation. We used the original VGG network.