feat(mathvista): add image resizing flags

[lee-groq]

Summary

Adds image resizing flags to mathvista. -T max_dimension=... and quality=... and max_size_mb=...

Examples
-T quality=0:

-T quality=0 and -T max_dimension=100:

-T max_dimension=150:

What are you adding?

• Bug fix (non-breaking change which fixes an issue)
• New benchmark/evaluation
• New model provider
• CLI enhancement
• Performance improvement
• Documentation update
• API/SDK feature
• Integration (CI/CD, tools)
• Export/import functionality
• Code refactoring
• Breaking change
• Other

Changes Made

• Adds image resizing flags to mathvista

Testing

• I have run the existing test suite (pytest)
• I have added tests for my changes
• I have tested with multiple model providers (if applicable)
• I have run pre-commit hooks (pre-commit run --all-files)

Checklist

• My code follows the project's style guidelines
• I have performed a self-review of my own code
• I have commented my code, particularly in hard-to-understand areas
• I have made corresponding changes to the documentation (if applicable)
• My changes generate no new warnings
• I have added tests that prove my fix is effective or that my feature works
• New and existing unit tests pass locally with my changes

Related Issues

Closes #

Additional Context

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Note

Adds max_dimension, quality, and max_size_mb flags to MathVista dataset/task and implements a PIL-based image resize/re-encode pipeline.

• Dataset Loader (src/openbench/datasets/mathvista.py):
  • Refactor record_to_sample into a factory accepting max_dimension, quality, max_size_mb and returning a converter.
  • Add PIL-based image processing: ensure RGB, optional resize to max_dimension, JPEG re-encode at quality, then size-based compression and data URI encoding.
  • get_dataset now forwards these parameters to record_to_sample.
• Eval Task (src/openbench/evals/mathvista.py):
  • Expose and pass through max_dimension, quality, and max_size_mb to the dataset loader.

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