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I have implemented various preprocessing functions in tensorflow, compatible with tf.data.Dataset API for augmenting pointclouds including jitter, random_cutout, random_translation, random_rotation, random_zoom, etc..
I was curious to know if they would fall in the scope of tfg so I could submit a PR.
These could be implemented as augmentation layers just like keras-cv augmentations. I am not sure if these fall into the scope of tfg or keras-cv
The text was updated successfully, but these errors were encountered:
Hello,
I have implemented various preprocessing functions in tensorflow, compatible with
tf.data.Dataset
API for augmenting pointclouds includingjitter
,random_cutout
,random_translation
,random_rotation
,random_zoom
, etc..I was curious to know if they would fall in the scope of tfg so I could submit a PR.
These could be implemented as augmentation layers just like
keras-cv
augmentations. I am not sure if these fall into the scope of tfg or keras-cvThe text was updated successfully, but these errors were encountered: