A/B: 4-fold weight symmetrisation — shape impact and S/N cost
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 35/100
- Issue type
- Feature
- Clarity
- Mostly clear
- Activity status
- Quiet
- Tech stack
- python
- Domain
- computer-vision
Research direction
Start with the existing UberSeg implementation and the follow-on context in issues #770 and #776. Run the rider UberSeg A/B setup with the third symmetrisation variant, then compare shape/B-mode differences and the S/N cost; done requires the group decision on the bias-versus-noise trade.
Written by the indexing model from the issue text.
Description
Per @aguinot (#776): UberSeg partially removes the one-sided "pull" of asymmetric weights on the model fit; 4-fold weight symmetrisation removes it completely — the least-biased option. Implemented as an off-by-default option (follow-on PR to #770).
Setup: rider on the uberseg A/B runs — same tile set, third config variant (uberseg + symmetrisation).
Metrics: shape/B-mode difference vs plain uberseg, plus the S/N cost (symmetrisation quadruples the masked area).
Decider: group call on the bias-vs-noise trade, informed by image-sim m/c where available.
— Claude, on behalf of Cail
- Dominant language
- Python
- Stars
- 18
- Forks
- 14
- Avg merge
- 8h 40m
- Merged PRs (30d)
- 10
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.
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