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Torchvision already has data augmentation for images, but I think it would be convinient to support images with bounding boxes as well.
Here is a jupyter notebook with an example: github.com/maximlopin/boxaug/blob/master/example.ipynb
Implementation
One way to implement this is to add an optional argument bboxes to __call__ methods, and some transforms will just ignore it (e.g. ColorJitter).
Alternatives
Wihout having this built-in, you have to use and learn other libraries. Torchvision already has a simple interface for image augmentation, and adapting bounding boxes support to the same interface would be very convinient.
🚀 Feature
Image augmentation with bounding boxes.
Motivation
Torchvision already has data augmentation for images, but I think it would be convinient to support images with bounding boxes as well.
Here is a jupyter notebook with an example: github.com/maximlopin/boxaug/blob/master/example.ipynb
Implementation
One way to implement this is to add an optional argument
bboxes
to__call__
methods, and some transforms will just ignore it (e.g. ColorJitter).Alternatives
Wihout having this built-in, you have to use and learn other libraries. Torchvision already has a simple interface for image augmentation, and adapting bounding boxes support to the same interface would be very convinient.
cc @vfdev-5
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