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Hi, I'm using DivisiblePad to pad images on the fly. It's very handy because I have variable-size images and all I care is that they can fit into the model. At test time I also have variable-size images, and I need to undo this operation, i.e., the model gets a padded image and the prediction needs to be unpadded (cropped) to be compared with its ground truth. CenterSpatialCrop could be useful but it only allows for a fixed roi_size for every image. Is there any nice way to solve this? Thanks! |
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Hi @jmlipman, thanks for your interest here. I think you mean Hope it helps, thanks! |
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Hi @jmlipman, thanks for your interest here.
I think you mean
inverse
andDivisiblePad
is invertible, you could refer to this tutorial.Hope it helps, thanks!