>>> import numpy as np
>>> import albumentations as A
>>>
>>> # Prepare sample data
>>> image = np.random.randint(0, 256, (100, 100, 3), dtype=np.uint8)
>>> # Create a mask with non-empty region in the center
>>> mask = np.zeros((100, 100), dtype=np.uint8)
>>> mask[25:75, 25:75] = 1  # Create a non-empty region in the mask
>>>
>>> # Create bounding boxes and keypoints in the mask region
>>> bboxes = np.array([
...     [20, 20, 60, 60],     # Box overlapping with non-empty region
...     [30, 30, 70, 70],     # Box mostly inside non-empty region
... ], dtype=np.float32)
>>> bbox_labels = ['cat', 'dog']
>>>
>>> # Add some keypoints inside mask region
>>> keypoints = np.array([
...     [40, 40],             # Inside non-empty region
...     [60, 60],             # At edge of non-empty region
...     [90, 90]              # Outside non-empty region
... ], dtype=np.float32)
>>> keypoint_labels = ['eye', 'nose', 'ear']
>>>
>>> # Define transform that will crop around the non-empty mask region
>>> transform = A.Compose([
...     A.CropNonEmptyMaskIfExists(
...         height=50,
...         width=50,
...         ignore_values=None,
...         ignore_channels=None,
...         p=1.0
...     ),
... ], bbox_params=A.BboxParams(
...     format='pascal_voc',
...     label_fields=['bbox_labels']
... ), keypoint_params=A.KeypointParams(
...     format='xy',
...     label_fields=['keypoint_labels']
... ))
>>>
>>> # Apply the transform
>>> transformed = transform(
...     image=image,
...     mask=mask,
...     bboxes=bboxes,
...     bbox_labels=bbox_labels,
...     keypoints=keypoints,
...     keypoint_labels=keypoint_labels
... )
>>>
>>> # Get the transformed data
>>> transformed_image = transformed['image']  # 50x50 image centered on mask region
>>> transformed_mask = transformed['mask']    # 50x50 mask showing part of non-empty region
>>> transformed_bboxes = transformed['bboxes']  # Bounding boxes adjusted to new coordinates
>>> transformed_bbox_labels = transformed['bbox_labels']  # Labels preserved for visible boxes
>>> transformed_keypoints = transformed['keypoints']  # Keypoints adjusted to new coordinates
>>> transformed_keypoint_labels = transformed['keypoint_labels']  # Labels for visible keypoints
Parameters

Bounding Box Parameters
