Source code for bio_volumentations.core.composition

# ============================================================================================= #
#  Author:       Pavel Iakubovskii, ZFTurbo, ashawkey, Dominik Müller,                          #
#                Samuel Šuľan, Lucia Hradecká, Filip Lux                                        #
#  Copyright:    albumentations:    : https://github.com/albumentations-team                    #
#                Pavel Iakubovskii  : https://github.com/qubvel                                 #
#                ZFTurbo            : https://github.com/ZFTurbo                                #
#                ashawkey           : https://github.com/ashawkey                               #
#                Dominik Müller     : https://github.com/muellerdo                              #
#                Lucia Hradecká     : lucia.d.hradecka@gmail.com                                #
#                Filip Lux          : lux.filip@gmail.com                                       #
#                                                                                               #
#  Volumentations History:                                                                      #
#       - Original:                 https://github.com/albumentations-team/albumentations       #
#       - 3D Conversion:            https://github.com/ashawkey/volumentations                  #
#       - Continued Development:    https://github.com/ZFTurbo/volumentations                   #
#       - Enhancements:             https://github.com/qubvel/volumentations                    #
#       - Further Enhancements:     https://github.com/muellerdo/volumentations                 #
#       - Biomedical Enhancements:  https://gitlab.fi.muni.cz/cbia/bio-volumentations           #
#                                                                                               #
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#  SOFTWARE.                                                                                    #
# ============================================================================================= #


import random
from ..augmentations import transforms as T
from ..conversion import transforms as CT


[docs] class Compose: """Compose a list of transforms into a callable transformation pipeline. In addition, basic input image checks and conversions are performed. Optionally, datatype conversion (e.g. from ``numpy.ndarray`` to ``torch.Tensor``) is performed. Args: transforms (List[Transform]): a list of transforms. p (float, optional): chance of applying the whole pipeline. Defaults to 1. targets (Tuple[List[str]] | List[List[str]], optional): a list of targets. Defaults to (['image'], ['mask'], ['float_mask']). conversion (Transform | None, optional): image datatype conversion transform, applied after the transformations. Defaults to None. """ def __init__(self, transforms, p=1.0, targets=(['image'], ['mask'], ['float_mask']), conversion=None): assert 0 <= p <= 1 self.transforms = ([T.Float(always_apply=True), CT.ConversionToFormat(always_apply=True)] + transforms + [T.Contiguous(always_apply=True)] + [CT.NoConversion() if conversion is None else conversion]) self.p = p self.targets = targets
[docs] def get_always_apply_transforms(self): res = [] for tr in self.transforms: if tr.always_apply: res.append(tr) return res
def __call__(self, force_apply=False, **data): need_to_run = force_apply or random.random() < self.p transforms = self.transforms if need_to_run else self.get_always_apply_transforms() for tr in transforms: data = tr(force_apply, self.targets, **data) return data def __repr__(self): return f'Compose({self.transforms[1:-2]}, {self.p}, {self.targets}, {self.transforms[-1]})'