Add LoMa keypoint matching model
Author: Gitanaskhan26
Pull request: yes

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## What does this PR do?

Fixes #47004

Adds LoMa (davnords/LoMa), a local feature matcher that outperforms LightGlue and is
competitive with dense matchers on standard benchmarks (WxBS, IMC22, HPatches),
accepted at ECCV 2024. 

Paper: https://arxiv.org/abs/2604.04931 (base), https://arxiv.org/abs/2604.11809 (rotation-invariant)
Code: https://github.com/davnords/LoMa

This is a work in progress; opening as a draft early per the contribution guide, to
track progress and get feedback before going further.

### Scope for this PR
LoMa pairs with several external keypoint detectors in the original repo (DaD, DeDoDe-v2,
DISK, ALIKED), none of which are currently native `transformers` models, and `trust_remote_code`
for non-SuperPoint detectors was removed from LightGlue in #45122 for security reasons.
Proposing to scope this first PR to **LoMa + SuperPoint**, matching that existing precedent,
and follow up with native detector support (DaD in particular, since it's what the paper's
headline numbers use) as a separate PR once this lands. Flagging this early in case there's
a different preference; happy to adjust scope based on feedback here.

**Architectural note:** Currently planning to implement the DeDoDe-style descriptor network 
as a reusable, standalone component (to enable a future native DeDoDe integration). 
Open to feedback on this approach --> see comment in #47004.

### Plan
- [ ] `LoMaConfig`
- [ ] Descriptor network (DeDoDe-style, new relative to LightGlue)
- [ ] Matching transformer (adapted from LightGlue's self-/cross-attention blocks, dual-softmax matching head)
- [ ] `LoMaForKeypointMatching` + Auto registration
- [ ] Image processor (likely reusable from LightGlue)
- [ ] Conversion script for the B/L/G checkpoints
- [ ] Tests + integration test against the reference implementation
- [ ] Docs

## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the contributor guideline, Pull Request section?
- [x] Was this discussed/approved via a Github issue or the forum? Please add a link to it if that's the case. → #47004
- [ ] Did you make sure to update the documentation with your changes?
- [ ] Did you write any new necessary tests?

*(Note: Documentation and comprehensive tests are currently unchecked as this is a draft PR. They will be fully implemented and checked in subsequent commits before merging.)*

## Who can review?

@zucchini-nlp  @guarin, @molbap

Comments:
**[For maintainers]** Suggested jobs to run (before merge)

run-slow: auto, loma

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### CI recap

**Dashboard:** [View test results in Grafana](https://transformers-ci.lor-e.huggingface.cool/d/pytest-observability-by-pr/pytest-observability-branch?var-pr=47401)
**Latest run:** [29660683793:2](https://github.com/huggingface/transformers/actions/runs/29660683793)
**Result:** `success` | **Jobs:** 15 | **Tests:** 172,400 | **Failures:** 0 | **Duration:** 15h 40m

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