In augmentation, elastic_transform, it only applies a random transform on one input image array. I would think to be used for training, the image and mask pair should be transform in the same way. However, this single-input-image, single-output-image method makes it very inconvenient. Could we deform a list of images (np.arrays) using the same transformation in this method ? Thanks!

Description

The ApplyScriptToRemotes script applies a script to all remote modules whose build status reports a successful build.

There are a number of aspects -many of them were already mentioned in PR #781- that could be improved to make the script more robust.

• May be th

There are many transformations, such as transforms.Resample and transforms.ElasticTransform that aren't documented (with the Sphinx format).

🚀 Feature
I notice that by default you choose the minimum as default_pad_value for elastic deformation
whereas the default method is otsu for randomAffine

Motivation
it seems to me more natural to take the min, as noise is expected in the image border (at least for brain, in 5 of the 6 border slices )
no ?
and it makes more sense to have the same default for both transform

<!

There are all sorts of odd or even non-conformant DICOMs out in the world.

When we encounter parser failures on a DICOM (for both the current and the in progress rewrite), it would be good to be able to toggle a debug mode flag that can help us better dig into parsing failures and provide helpful information. Ideally if this information is not PHI (e.g. just DICOM tags, other general info), it