def __init__(
self,
keys: KeysCollection,
output_postfixes: Optional[Sequence[str]] = None,
output_names: Optional[Sequence[str]] = None,
channel_dim: int = 0,
remove_origin: bool = False,
allow_missing_keys: bool = False,
meta_key_postfix='meta_dict',
) -> None:
"""
Args:
keys: keys of the corresponding items to be transformed.
See also: :py:class:`monai.transforms.compose.MapTransform`
output_postfixes: the postfixes to construct keys to store split data.
for example: if the key of input data is `pred` and split 2 classes, the output
data keys will be: pred_(output_postfixes[0]), pred_(output_postfixes[1])
if None, using the index number: `pred_0`, `pred_1`, ... `pred_N`.
channel_dim: which dimension of input image is the channel, default to 0.
allow_missing_keys: don't raise exception if key is missing.
"""
super().__init__(keys, allow_missing_keys)
self.output_postfixes = output_postfixes
self.output_names = output_names
self.remove_origin = remove_origin
self.meta_key_postfix = meta_key_postfix
self.splitter = SplitChannel(channel_dim=channel_dim)
def test_shape(self, input_param, test_data, expected_shape):
result = SplitChannel(**input_param)(test_data)
for data in result:
self.assertTupleEqual(data.shape, expected_shape)