ml-explore / ml-explore/mlx-data
Selecting a resampling algorithm for various image operations
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- Dominant language
- C++
- Stars
- 483
- Forks
- 62
- PR merge metrics
- No merged PRs in 30d
Description
Can we support a selection of resampling algorithm (e.g. bilinear, bicubic, nearest ...) for operations such as image_resize and image_resize_smallest_side?
This may be necessary to implement some models, such as CLIP (https://github.com/ml-explore/mlx-examples/pull/315).
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 implementations and tests for image_resize and image_resize_smallest_side. Review how those operations currently choose resampling, then define how callers select bilinear, bicubic, nearest, or other algorithms and add coverage for the supported choices, including the CLIP use case.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- cpp
- Domain
- computer-vision
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100