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perf(RandCropBoxByPosNegLabeld): avoid N-fold mask allocation in randomize #8993

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perf(RandCropBoxByPosNegLabeld): avoid N-fold mask allocation in randomize #8993

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3312b93
perf(RandCropBoxByPosNegLabeld): avoid N-fold mask allocation in rand…
aymuos15 Jul 13, 2026
916ede3
Merge branch 'dev' into perf/randcropboxbyposneglabeld-randomize
aymuos15 Jul 13, 2026
464a142
fix: remove stray blank line breaking isort in detection dictionary t…
aymuos15 Jul 13, 2026
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12 changes: 7 additions & 5 deletions monai/apps/detection/transforms/dictionary.py
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Original file line number Diff line number Diff line change
Expand Up @@ -37,7 +37,6 @@
StandardizeEmptyBox,
ZoomBox,
)
from monai.apps.detection.transforms.box_ops import convert_box_to_mask
from monai.config import KeysCollection, SequenceStr
from monai.config.type_definitions import DtypeLike, NdarrayOrTensor
from monai.data.box_utils import COMPUTE_DTYPE, BoxMode, clip_boxes_to_image
Expand Down Expand Up @@ -1154,10 +1153,13 @@ def randomize( # type: ignore
# As along as the cropped patch contains a box, it is considered as a foreground patch.
# Positions within extended_boxes are crop centers for foreground patches
extended_boxes_np = self.generate_fg_center_boxes_np(boxes, image_size)
mask_img = convert_box_to_mask(
extended_boxes_np, np.ones(extended_boxes_np.shape[0]), image_size, bg_label=0, ellipse_mask=False
)
mask_img = np.amax(mask_img, axis=0, keepdims=True)[0:1, ...]
spatial_dims = len(image_size)
mask_img = np.zeros((1,) + tuple(image_size), dtype=np.int16)
for b in range(extended_boxes_np.shape[0]):
slicing = (0,) + tuple(
slice(extended_boxes_np[b, d], extended_boxes_np[b, d + spatial_dims]) for d in range(spatial_dims)
)
mask_img[slicing] = 1
fg_indices_, bg_indices_ = map_binary_to_indices(mask_img, thresh_image, self.image_threshold)
else:
fg_indices_ = fg_indices
Expand Down
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