test: add percentage-based tolerance for image size verification

[ceberam]

Summary

Implements percentage-based tolerance for image size verification in verify_picture_image_v2() to handle cross-platform rendering differences, following the same pattern as bounding box verification.

Problem

Image verification tests were failing when run on different platforms (Linux vs macOS) due to minor pixel differences in image dimensions caused by platform-specific rendering. These failures occurred even when the code was working correctly, blocking legitimate test runs.

Example failure:

• Ground truth: 254x267 pixels (generated on Linux)
• Test output: 251x267 pixels (generated on macOS)
• Difference: 3 pixels (~1.2%) - within normal cross-platform variance

Solution

Added percentage-based tolerance thresholds similar to existing bbox verification:

Constants added:

• STRICT_IMAGE_SIZE_TOL_RATIO = 0.015 (~1.5% tolerance for cross-platform variance)
• FUZZY_IMAGE_SIZE_TOL_RATIO = 0.05 (~5% tolerance for OCR/image processing variance)

Key features:

1. True percentage-based comparison: Compares actual percentage differences against tolerance ratios
2. Precise for all image sizes: No minimum pixel tolerance that could allow excessive percentage differences
3. Independent width/height checks: Each dimension validated separately
4. Clear error messages: Shows actual values, pixel differences, and percentage differences vs tolerance
5. Consistent with existing patterns: Follows the same approach as _assert_bbox_close()
6. Demonstrates that DOCX images now pass verification in strict mode with the new percentage-based tolerance

Testing

✅ All existing tests pass (15 tests in test_verify_utils.py)
✅ New parameterized test covers 8 scenarios (strict/fuzzy modes, width/height, edge cases)
✅ Original failing case (254x267 vs 251x267) now passes in strict mode
✅ DOCX tests now run with fuzzy=False, demonstrating proper cross-platform handling
✅ Cross-platform compatibility verified on macOS and Fedora Linux

Related Issues

Fixes #3659

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