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Hi, Recently I found a repo about data augmentation with excellent programming, named TensorPipe. But it's implemented with tensorflow, do you mind to add this similar features based in PyTorch in our quickvision repo?
Motivation
Augmentation play an important role in practical application especially when the collection of images and its labels is restricted by various reasons or the cost is very high.
Pitch
Supports Mosiac Augmentation
Supports CutOut
The text was updated successfully, but these errors were encountered:
Yes we can have such augmentation. Especially bounding box augmentations. As of now torchvision itself is getting upgrade for transforms. So maybe after a few releases we will have this.
Once we have a nice nested tensor support in PyTorch as pointed out in torchvision (vmap, etc)
It wil be possible for torchvision itself to have params such as probablistic transforms, keep some batches from transforms.
This will make transforms even more powerful.
🚀 Feature
Hi, Recently I found a repo about data augmentation with excellent programming, named TensorPipe. But it's implemented with tensorflow, do you mind to add this similar features based in PyTorch in our quickvision repo?
Motivation
Augmentation play an important role in practical application especially when the collection of images and its labels is restricted by various reasons or the cost is very high.
Pitch
The text was updated successfully, but these errors were encountered: