feat(compressors): add OWLv2 bbox crop to HashPipeline and refactor image utilities

- Add crop_batch method to HashPipeline for cropping images using OWLv2 detection boxes
- Integrate crop_batch into pipeline forward pass (extract_hash and extract_features)
- Move extract_masked_region from compressors/proposal/utils.py to utils/image.py
- Add crop_image_by_bbox utility function in utils/image.py
- Update type annotations to use dict[str, Any] instead of bare dict
- Update .justfile to add memory server command
- Update marimo dependency to >=0.22.0
- Update nvidia CUDA package markers for platform compatibility

mini-nav/compressors/proposal/__init__.py

@@ -6,12 +6,10 @@ from .core import (
     generate_proposals,
     generate_proposals_batch,
 )
-from .utils import extract_masked_region
 
 __all__ = [
     "detect_objects",
     "detect_objects_batch",
     "generate_proposals",
     "generate_proposals_batch",
-    "extract_masked_region",
 ]

mini-nav/compressors/proposal/utils.py

@@ -1,25 +0,0 @@
-"""Mask extraction utilities."""
-
-import numpy as np
-from PIL import Image
-
-
-def extract_masked_region(
-    image: Image.Image,
-    mask: np.ndarray,
-) -> Image.Image:
-    """Extract masked region from image.
-
-    Args:
-        image: Original PIL Image.
-        mask: Binary mask as numpy array (True = keep).
-
-    Returns:
-        PIL Image with only the masked region visible.
-    """
-    image_np = np.array(image.convert("RGB"))
-
-    # Apply mask.
-    masked_np = image_np * mask[:, :, np.newaxis]
-
-    return Image.fromarray(masked_np.astype(np.uint8))