Method __init__

monai/transforms/post/dictionary.py:501–513

Args: keys: keys of the corresponding items to be stack and execute ensemble. if only 1 key provided, suppose it's a PyTorch Tensor with data stacked on dimension `E`. output_key: the key to store ensemble result in the dictionary. if

(self, keys: KeysCollection, output_key: str | None = None, num_classes: int | None = None)

    backend = VoteEnsemble.backend

    def __init__(self, keys: KeysCollection, output_key: str | None = None, num_classes: int | None = None) -> None:
        """
        Args:
            keys: keys of the corresponding items to be stack and execute ensemble.
                if only 1 key provided, suppose it's a PyTorch Tensor with data stacked on dimension `E`.
            output_key: the key to store ensemble result in the dictionary.
                if only 1 key provided in `keys`, `output_key` can be None and use `keys` as default.
            num_classes: if the input is single channel data instead of One-Hot, we can't get class number
                from channel, need to explicitly specify the number of classes to vote.

        """
        ensemble = VoteEnsemble(num_classes=num_classes)
        super().__init__(keys, ensemble, output_key)


class GenerateHeatmapd(MapTransform):