Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Image Data Normalization #2

Open
yongduek opened this issue Oct 19, 2019 · 0 comments
Open

Image Data Normalization #2

yongduek opened this issue Oct 19, 2019 · 0 comments

Comments

@yongduek
Copy link

As presented in https://pytorch.org/hub/pytorch_vision_deeplabv3_resnet101/, any input image data must be normalized because the backbone (resnet) was trained with it, I guess.

All pre-trained models expect input images normalized in the same way, i.e. mini-batches of 3-channel RGB images of shape (N, 3, H, W), where N is the number of images, H and W are expected to be at least 224 pixels. The images have to be loaded in to a range of [0, 1] and then normalized using mean = [0.485, 0.456, 0.406] and std = [0.229, 0.224, 0.225].

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant