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IIUC, in the current implementation, the rate between original images and augmented variants will be a fixed 1 : N for N kinds of augmentation that have been enabled:
This makes it hard to control what kind of degradation to learn how fast. IMHO the precomputed files should be somehow indexed in such a way that the randomized generator can mix in augmented images (of any kind) at a well-defined rate. You would then be able to configure, say, rotation at p = 0.2. Think imgaug!
Also, I believe it should at least be possible to increase that rate throughout the training procedure.
The text was updated successfully, but these errors were encountered:
IIUC, in the current implementation, the rate between original images and augmented variants will be a fixed
1 : N
forN
kinds of augmentation that have been enabled:sbb_pixelwise_segmentation/utils.py
Line 92 in 63fcb96
This makes it hard to control what kind of degradation to learn how fast. IMHO the precomputed files should be somehow indexed in such a way that the randomized generator can mix in augmented images (of any kind) at a well-defined rate. You would then be able to configure, say, rotation at
p = 0.2
. Thinkimgaug
!Also, I believe it should at least be possible to increase that rate throughout the training procedure.
The text was updated successfully, but these errors were encountered: