Support PIL images in v2.GaussianNoise
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Description
Description
torchvision.transforms.v2.functional.gaussian_noise (and thus v2.GaussianNoise) currently stubs out PIL images:
raise ValueError("Gaussian Noise is not implemented for PIL images.")
The tensor kernels already support uint8 and float inputs. We should implement the PIL kernel the same way as gaussian_blur: convert with pil_to_tensor, run the existing image kernel, then convert back with to_pil_image.
Proposed change
- Register a PIL kernel for
gaussian_noisethat reusesgaussian_noise_image. - Document that PIL images are supported (uint8 path via
pil_to_tensor). - Replace the current negative PIL test with a positive one.
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 at torchvision.transforms.v2.functional.gaussian_noise and compare its PIL handling with gaussian_blur, including the existing gaussian_noise_image kernel. Replace the negative PIL test with a positive case, document PIL support, and confirm the kernel converts through pil_to_tensor and to_pil_image while preserving the expected noise behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- computer-vision
- Issue type
- Feature
- Difficulty
- 2/5
- Estimated time
- 1-3 hours
- Activity status
- Active
- Clarity
- Clearly specified
- Newbie friendliness
- 85/100