PadIfNeeded3D
Pads the sides of a 3D volume if its dimensions are less than specified minimum dimensions.
If the pad_divisor_zyx is specified, the function additionally ensures that the volume
dimensions are divisible by these values.
Supported Targets
keypoints
Arguments
Name | Type | Default | Description |
---|---|---|---|
min_zyx | tuple[int, int, int] | None | Minimum desired size as (depth, height, width). Ensures volume dimensions are at least these values. If not specified, pad_divisor_zyx must be provided. | |
pad_divisor_zyx | tuple[int, int, int] | None | If set, pads each dimension to make it divisible by corresponding value in format (depth_div, height_div, width_div). If not specified, min_zyx must be provided. | |
position | Literal["center", "random"] | Position where the volume is to be placed after padding. Default is 'center'. | |
fill | tuple[float, ...] | float | Value to fill the border voxels for volume. Default: 0 | |
fill_mask | tuple[float, ...] | float | Value to fill the border voxels for masks. Default: 0 | |
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 a transform with both min_zyx and pad_divisor_zyx
>>> transform = A.Compose([
... A.PadIfNeeded3D(
... min_zyx=(16, 128, 128), # Minimum size (depth, height, width)
... pad_divisor_zyx=(8, 16, 16), # Make dimensions divisible by these values
... position="center", # Center the volume in the padded space
... fill=0, # Fill value for volume
... fill_mask=1, # Fill value for mask
... 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: (16, 128, 128)
>>> padded_mask3d = transformed["mask3d"] # Shape: (16, 128, 128)
>>> padded_keypoints = transformed["keypoints"] # Keypoints shifted by padding
>>> padded_keypoint_labels = transformed["keypoint_labels"] # Labels remain unchanged