Automatic CenterCrop to the image smallest size
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module: transforms
new feature
- Dominant language
- Python
- Stars
- 17.9k
- Forks
- 7.3k
- Avg merge
- 1d 15h
- Merged PRs (30d)
- 13
Description
🚀 The feature
The idea here is that centercrop allows for automatic size inference and center_crop to the smallest of HxW.
Motivation, pitch
That allows to keep the most information before resizing the image. We maximize the amount of pixels kept in the center_crop for a given aspect ratio.
Alternatives
No response
Additional context
No response
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 locating the center_crop implementation and its existing tests in torchvision. Review how image HxW and aspect ratio are currently handled, then define the expected smallest-size inference behavior. Done means center_crop can infer the crop size while preserving the maximum central image area before resizing, with tests covering the new behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-vision
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100