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

<!

AT(Attribute Tag) is an ordered pair of 16-bit unsigned integers, so it should not be treated as a simple string. I think it can be parsed as uint32 or a formatted string (e.g. '0x00020001', '0002,0001').