[Feature Request] Support same_on_batch option for transforms
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- Python
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Description
🚀 Feature
In the latest torchvison, transforms support tensor input (very nice feature, cheers!).
Motivation
As titled, same_on_batch option is not available for torchvision transforms. For example, RandomResizedCrop will crop at the same location for all images in the batch (which is ideal for video, but not for batched images).
Pitch
Kornia has this feature off the shelf. Maybe torchvision could follow the same API.
cc @vfdev-5
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reading the torchvision transforms implementation, especially RandomResizedCrop, and inspect how tensor batches are currently handled. Compare the requested behavior with Kornia's same_on_batch API; done means the option is consistently supported by the relevant transforms with batch semantics documented and tested.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- computer-vision
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100