Closed sazippe closed 5 years ago
I think you could get similar results after moving 111-113.
It's data normalization but doesn't have much influence on the final performance.
Thank you! But why normalization is done only in monocular model? Is it because monocular model use pretrained vgg16 weight?
I think the normalization is not so important. You can add or remove the normalization for the mono/stereo models and the performance will not change.
Learning-Monocular-Depth-by-Stereo/models/monocular_model.py
110 def forward(self, x): 111 mean = Variable(torch.FloatTensor([0.485, 0.456, 0.406])).cuda() 112 var = Variable(torch.FloatTensor([0.229, 0.224, 0.225])).cuda() 113 x = (x - mean.view(1, -1, 1, 1)) / (var.view(1, -1, 1, 1))
Why is this done in monocular model, but does not done this in stereo model? Thank you.