Is your feature request related to a problem? Please describe.
RandZoom uses Zoom which uses torch.nn.functional.interpolate under the hood to extract randomly zoomed images. Although torch.nn.functional.interpolate is capable of being applied on batch x channels x [optional depth] x [optional height] x width, Zoom and RandZoom don't.
Instead, they treat the channel dimension as spatial dimension. This is causing an issue since there is no error and warning if user apply it on a batched dataset.
This requires to distinguish between 3D multi-channel images vs 2D multi-channel batched images. Although an automatic logic would be hard to achieve, a simple flag can do the work.
Is your feature request related to a problem? Please describe.
RandZoomusesZoomwhich usestorch.nn.functional.interpolateunder the hood to extract randomly zoomed images. Althoughtorch.nn.functional.interpolateis capable of being applied on batch x channels x [optional depth] x [optional height] x width,ZoomandRandZoomdon't.Instead, they treat the channel dimension as spatial dimension. This is causing an issue since there is no error and warning if user apply it on a batched dataset.
This requires to distinguish between 3D multi-channel images vs 2D multi-channel batched images. Although an automatic logic would be hard to achieve, a simple flag can do the work.