Fork of volumentations 3D Volume data augmentation package by @ashawkey. Initially inspired by albumentations library for augmentation of 2D images.
pip install volumentations-3D
from volumentations import *
def get_augmentation(patch_size):
return Compose([
Rotate((-15, 15), (0, 0), (0, 0), p=0.5),
RandomCropFromBorders(crop_value=0.1, p=0.5),
ElasticTransform((0, 0.25), interpolation=2, p=0.1),
Resize(patch_size, interpolation=1, always_apply=True, p=1.0),
Flip(0, p=0.5),
Flip(1, p=0.5),
Flip(2, p=0.5),
RandomRotate90((1, 2), p=0.5),
GaussianNoise(var_limit=(0, 5), p=0.2),
RandomGamma(gamma_limit=(0.5, 1.5), p=0.2),
], p=1.0)
aug = get_augmentation((64, 128, 128))
# with mask
data = {'image': img, 'mask': lbl}
aug_data = aug(**data)
img, lbl = aug_data['image'], aug_data['mask']
# without mask
data = {'image': img}
aug_data = aug(**data)
img = aug_data['image']Check working usage example in tst_volumentations.py
- Much faster 3D-resize method using scipy.zoom.
- Additional augs: RandomCropFromBorders, GridDropout, RandomDropPlane
PadIfNeeded
GaussianNoise
Resize
RandomScale
RotatePseudo2D
RandomRotate90
Flip
Normalize
Float
Contiguous
Transpose
CenterCrop
RandomResizedCrop
RandomCrop
CropNonEmptyMaskIfExists
ResizedCropNonEmptyMaskIfExists
RandomGamma
ElasticTransformPseudo2D
ElasticTransform
Rotate
RandomCropFromBorders
GridDropout
RandomDropPlane