def __init__(
self,
train_transform: Optional[Union[Dict[str, Callable]]] = None,
val_transform: Optional[Union[Dict[str, Callable]]] = None,
test_transform: Optional[Union[Dict[str, Callable]]] = None,
predict_transform: Optional[Union[Dict[str, Callable]]] = None,
image_size: int = 256,
):
if val_transform:
raise_not_supported("validation")
if test_transform:
raise_not_supported("test")
if isinstance(image_size, int):
image_size = (image_size, image_size)
self.image_size = image_size
super().__init__(
train_transform=train_transform,
val_transform=val_transform,
test_transform=test_transform,
predict_transform=predict_transform,
data_sources={
DefaultDataSources.FILES: ImagePathsDataSource(),
DefaultDataSources.FOLDERS: ImagePathsDataSource(),
DefaultDataSources.NUMPY: ImageNumpyDataSource(),
DefaultDataSources.TENSORS: ImageTensorDataSource(),
DefaultDataSources.TENSORS: ImageTensorDataSource(),
},
default_data_source=DefaultDataSources.FILES,
)
def __init__(
self,
train_transform: Optional[Dict[str, Callable]] = None,
val_transform: Optional[Dict[str, Callable]] = None,
test_transform: Optional[Dict[str, Callable]] = None,
predict_transform: Optional[Dict[str, Callable]] = None,
**data_source_kwargs: Any,
):
super().__init__(
train_transform=train_transform,
val_transform=val_transform,
test_transform=test_transform,
predict_transform=predict_transform,
data_sources={
DefaultDataSources.FIFTYONE:
ObjectDetectionFiftyOneDataSource(**data_source_kwargs),
DefaultDataSources.FILES:
ImagePathsDataSource(),
DefaultDataSources.FOLDERS:
ImagePathsDataSource(),
"coco":
COCODataSource(),
},
default_data_source=DefaultDataSources.FILES,
)
def __init__(
self,
train_transform: Optional[Dict[str, Callable]] = None,
val_transform: Optional[Dict[str, Callable]] = None,
test_transform: Optional[Dict[str, Callable]] = None,
predict_transform: Optional[Dict[str, Callable]] = None,
image_size: Tuple[int, int] = (196, 196),
deserializer: Optional[Deserializer] = None,
**data_source_kwargs: Any,
):
self.image_size = image_size
super().__init__(
train_transform=train_transform,
val_transform=val_transform,
test_transform=test_transform,
predict_transform=predict_transform,
data_sources={
DefaultDataSources.FIFTYONE: ImageFiftyOneDataSource(**data_source_kwargs),
DefaultDataSources.FILES: ImagePathsDataSource(),
DefaultDataSources.FOLDERS: ImagePathsDataSource(),
DefaultDataSources.NUMPY: ImageNumpyDataSource(),
DefaultDataSources.TENSORS: ImageTensorDataSource(),
},
deserializer=deserializer or ImageClassificationDeserializer(),
default_data_source=DefaultDataSources.FILES,
)
def __init__(
self,
train_transform: Optional[Dict[str, Callable]] = None,
val_transform: Optional[Dict[str, Callable]] = None,
test_transform: Optional[Dict[str, Callable]] = None,
predict_transform: Optional[Dict[str, Callable]] = None,
):
super().__init__(
train_transform=train_transform,
val_transform=val_transform,
test_transform=test_transform,
predict_transform=predict_transform,
data_sources={
DefaultDataSources.FILES: ImagePathsDataSource(),
DefaultDataSources.FOLDERS: ImagePathsDataSource(),
"coco": COCODataSource(),
},
default_data_source=DefaultDataSources.FILES,
)
def __init__(
self,
train_transform: Optional[Dict[str, Callable]] = None,
val_transform: Optional[Dict[str, Callable]] = None,
test_transform: Optional[Dict[str, Callable]] = None,
predict_transform: Optional[Dict[str, Callable]] = None,
image_size: Tuple[int, int] = (196, 196),
):
self.image_size = image_size
super().__init__(
train_transform=train_transform,
val_transform=val_transform,
test_transform=test_transform,
predict_transform=predict_transform,
data_sources={
DefaultDataSources.FILES: ImagePathsDataSource(),
DefaultDataSources.FOLDERS: ImagePathsDataSource(),
DefaultDataSources.NUMPY: ImageNumpyDataSource(),
DefaultDataSources.TENSORS: ImageTensorDataSource(),
},
default_data_source=DefaultDataSources.FILES,
)