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Pad3D
Pad the sides of a 3D volume by specified number of voxels.
Supported Targets
keypoints
Arguments
NameTypeDefaultDescription
padding
int, tuple[int, int, int] or tuple[int, int, int, int, int, int]
Padding values. Can be: * int - pad all sides by this value * tuple[int, int, int] - symmetric padding (depth, height, width) where each value is applied to both sides of the corresponding dimension * tuple[int, int, int, int, int, int] - explicit padding per side in order: (depth_front, depth_back, height_top, height_bottom, width_left, width_right)
fill
tuple[float, ...] | float
Padding value for image
fill_mask
tuple[float, ...] | float
Padding value for mask
p
float
probability of applying the transform. Default: 1.0.
Image Types
uint8, float32
Notes
Input volume should be a numpy array with dimensions ordered as (z, y, x) or (depth, height, width), with optional channel dimension as the last axis.
Examples
>>> import numpy as np
>>> import albumentations as A
>>>
>>> # Prepare sample data
>>> volume = np.random.randint(0, 256, (10, 100, 100), dtype=np.uint8)  # (D, H, W)
>>> mask3d = np.random.randint(0, 2, (10, 100, 100), dtype=np.uint8)    # (D, H, W)
>>> keypoints = np.array([[20, 30, 5], [60, 70, 8]], dtype=np.float32)  # (x, y, z)
>>> keypoint_labels = [1, 2]  # Labels for each keypoint
>>>
>>> # Create the transform with symmetric padding
>>> transform = A.Compose([
...     A.Pad3D(
...         padding=(2, 5, 10),  # (depth, height, width) applied symmetrically
...         fill=0,
...         fill_mask=1,
...         p=1.0
...     )
... ], keypoint_params=A.KeypointParams(format='xyz', label_fields=['keypoint_labels']))
>>>
>>> # Apply the transform
>>> transformed = transform(
...     volume=volume,
...     mask3d=mask3d,
...     keypoints=keypoints,
...     keypoint_labels=keypoint_labels
... )
>>>
>>> # Get the transformed data
>>> padded_volume = transformed["volume"]  # Shape: (14, 110, 120)
>>> padded_mask3d = transformed["mask3d"]  # Shape: (14, 110, 120)
>>> padded_keypoints = transformed["keypoints"]  # Keypoints shifted by padding
>>> padded_keypoint_labels = transformed["keypoint_labels"]  # Labels remain unchanged