Fix out of bounds albumentations issues and update dependencies

[eberrigan]

Description

• Use conda to install albumentations and qudida instead of pip in pypi build
• Fix opencv version in pypi build
• Do no discard out-of-bound points in augmenter

Types of changes

• [X] Bugfix
• [ ] New feature
• [ ] Refactor / Code style update (no logical changes)
• [ ] Build / CI changes
• [ ] Documentation Update
• [ ] Other (explain)

Does this address any currently open issues?

1722 , #1719

Outside contributors checklist

• [ ] Review the guidelines for contributing to this repository
• [ ] Read and sign the CLA and add yourself to the authors list
• [ ] Make sure you are making a pull request against the develop branch (not main). Also you should start your branch off develop
• [ ] Add tests that prove your fix is effective or that your feature works
• [ ] Add necessary documentation (if appropriate)

Thank you for contributing to SLEAP!

:heart:

Summary by CodeRabbit

• New Features
  • Introduced new dependencies qudida, albumentations, and ndx-pose to enhance functionality.
  • Added support for more robust data augmentation techniques in neural network training.
• Bug Fixes
  • Updated opencv-python version constraint to ensure compatibility.
• Tests
  • Implemented new tests for data augmentation edge cases and configuration-based augmentations.
• Chores
  • Updated and streamlined dependency lists across different environment setups.

[coderabbitai[bot]]

Walkthrough

The changes involve updating dependencies and enhancing data augmentation capabilities. The project transitioned from imaug to albumentations for augmentation, leading to adjustments in dependency files and testing. Updates include adding new dependencies like qudida, albumentations, and ndx-pose, revising version constraints for various packages, and introducing new parameters and tests to handle edge cases in data augmentation more effectively.

Changes

Files	Change Summaries
.conda/bld.bat, .conda/build.sh	Removed the --no-binary qudida,albumentations option from the pip install command.
.conda/meta.yaml	Added qudida, albumentations, ndx-pose to dependencies.
pypi_requirements.txt	Updated opencv-python version to <=4.7.0, added albumentations, ndx-pose.
requirements.txt	Adjusted version constraints for several packages, removed albumentations, ndx-pose.
sleap/nn/data/augmentation.py	Added the remove_invisible=False parameter to A.KeypointParams in the uniform_noise function.
tests/nn/data/test_augmentation.py	Added tests for augmentation edge cases and albumentations augmenter configuration.

Possibly related issues

• talmolab/sleap#1722: The changes in this PR, particularly the shift to albumentations and the addition of new tests for handling edge cases (e.g., points near the edge or with nan values), directly address the objectives mentioned in this issue. It focuses on ensuring robustness in keypoint processing with albumentations, which matches the issue's objectives.

Poem

"In the realm of code, where rabbits dare,
🐇 A leap was taken, into the air.
With albumentations now in play,
Edge cases handled, come what may.
Through fields of data, we hop and parse,
Ensuring keypoints, are first-class.
A celebration, for changes vast,
In augmentation, we're unsurpassed."

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[codecov[bot]]

Codecov Report

All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 73.31%. Comparing base (eb14764) to head (628d2ab).

Additional details and impacted files

```diff @@ Coverage Diff @@ ## develop #1724 +/- ## ======================================== Coverage 73.31% 73.31% ======================================== Files 134 134 Lines 24087 24087 ======================================== Hits 17659 17659 Misses 6428 6428 ```

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