compose

data.transform.augmentation.compose.compose

BaseCompose

BaseCompose(transforms: Sequence[Union[BaseTransform, BaseCompose]], prob: float = 1.0)

여러 Data Transform들을 하나로 묶어서 관리해주는 Compose의 기본 interface를 정의합니다.

Source code in SaigeToolkit/data/transform/augmentation/compose/base_compose.py

def __init__(
    self, transforms: Sequence[Union[BaseTransform, BaseCompose]], prob: float = 1.0
) -> None:
    self.transforms = transforms
    self.prob = prob

transforms instance-attribute

transforms = transforms

prob instance-attribute

prob = prob

__call__

__call__(*args, force_apply: bool = False, **data) -> Dict

Source code in SaigeToolkit/data/transform/augmentation/compose/base_compose.py

def __call__(self, *args, force_apply: bool = False, **data) -> Dict:
    if args:
        raise KeyError("Data must be passed as named arguments, for example: aug(image=image)")

    if (random.random() < self.prob) or force_apply:
        data = self.apply(**data)

    return data

apply

apply(**data) -> Dict

Source code in SaigeToolkit/data/transform/augmentation/compose/base_compose.py

def apply(self, **data) -> Dict:
    raise NotImplementedError

__len__

__len__() -> int

Source code in SaigeToolkit/data/transform/augmentation/compose/base_compose.py

def __len__(self) -> int:
    return len(self.transforms)

__getitem__

__getitem__(index: int) -> Union[BaseTransform, BaseCompose]

Source code in SaigeToolkit/data/transform/augmentation/compose/base_compose.py

def __getitem__(self, index: int) -> Union[BaseTransform, BaseCompose]:
    return self.transforms[index]

add_targets

add_targets(additional_targets: Dict[str, str]) -> None

Source code in SaigeToolkit/data/transform/augmentation/compose/base_compose.py

def add_targets(self, additional_targets: Dict[str, str]) -> None:
    for t in self.transforms:
        t.add_targets(additional_targets)

Compose

Compose(transforms: Sequence[Union[BaseTransform, BaseCompose]], prob: float = 1.0)

Bases: BaseCompose

Source code in SaigeToolkit/data/transform/augmentation/compose/base_compose.py

def __init__(
    self, transforms: Sequence[Union[BaseTransform, BaseCompose]], prob: float = 1.0
) -> None:
    self.transforms = transforms
    self.prob = prob

apply

apply(**data) -> Dict

Source code in SaigeToolkit/data/transform/augmentation/compose/compose.py

def apply(self, **data) -> Dict:
    for t in self.transforms:
        data = t(**data)

    return data

SomeOf

SomeOf(k: int, replacement: bool = False, **kwargs)

Bases: BaseCompose

Source code in SaigeToolkit/data/transform/augmentation/compose/compose.py

def __init__(self, k: int, replacement: bool = False, **kwargs) -> None:
    super().__init__(**kwargs)
    self.k = k
    self.replacement = replacement

k instance-attribute

k = k

replacement instance-attribute

replacement = replacement

apply

apply(**data) -> Dict

Source code in SaigeToolkit/data/transform/augmentation/compose/compose.py

def apply(self, **data) -> Dict:
    if self.replacement:
        cur_transforms = random.choices(self.transforms, k=self.k)
    else:
        cur_transforms = random.sample(self.transforms, k=min(len(self.transforms), self.k))

    for t in cur_transforms:
        data = t(**data)

    return data