pytorch / pytorch/vision

GaussianNoise uint8 [0,255] compatibility

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Python
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Description

🚀 The feature

Adding compatibility to uint8-dtype [0,255]-range image format to the GaussianNoise transform.

Motivation, pitch

Found this transformation to be useful, but had an experimental pipeline that did some transformations out of order to try and keep uint8 dtype for as long as possible.

The solution is also very simple, as we just have to move the normally-distributed array from [0-1] to the [0-255] representation range and optionally do rounding. I already have a version of this implemented, and with uint8s being the regular way to open standard images I think some other people might also find it convenient :)

Also, it's just a bit more performant than doing a cast from uint8 to float_ and back :v

Alternatives

No response

Additional context

No response

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by locating the GaussianNoise transform and its existing tests. Check how image dtype and value ranges are handled, then define coverage for uint8 images in the [0,255] range, including the optional rounding behavior. Done means the transform accepts this format without requiring a float conversion and the relevant tests pass.

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

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