Class NumpyReader

monai/data/image_reader.py:1224–1340

Load NPY or NPZ format data based on Numpy library, they can be arrays or pickled objects. A typical usage is to load the `mask` data for classification task. It can load part of the npz file with specified `npz_keys`. Args: npz_keys: if loading npz file, only load the spec

class NumpyReader(ImageReader):
    """
    Load NPY or NPZ format data based on Numpy library, they can be arrays or pickled objects.
    A typical usage is to load the `mask` data for classification task.
    It can load part of the npz file with specified `npz_keys`.

    Args:
        npz_keys: if loading npz file, only load the specified keys, if None, load all the items.
            stack the loaded items together to construct a new first dimension.
        channel_dim: if not None, explicitly specify the channel dim, otherwise, treat the array as no channel.
        allow_pickle: if True, allows loading pickled contents from NPY/NPZ files. Note that the default value of False
            prevents the risk of remote code execution, set this to True only for loading known trusted data. If this
            argument is False and pickled data is loaded, a ValueError will be raised.
        kwargs: additional args for `numpy.load` API except `allow_pickle`. more details about available args:
            https://numpy.org/doc/stable/reference/generated/numpy.load.html
    """

    def __init__(
        self,
        npz_keys: KeysCollection | None = None,
        channel_dim: str | int | None = None,
        allow_pickle: bool = False,
        **kwargs,
    ):
        super().__init__()
        if npz_keys is not None:
            npz_keys = ensure_tuple(npz_keys)
        self.npz_keys = npz_keys
        self.channel_dim = float("nan") if channel_dim == "no_channel" else channel_dim
        self.allow_pickle = allow_pickle
        self.kwargs = kwargs

    def verify_suffix(self, filename: Sequence[PathLike] | PathLike) -> bool:
        """
        Verify whether the specified file or files format is supported by Numpy reader.

        Args:
            filename: file name or a list of file names to read.
                if a list of files, verify all the suffixes.
        """
        suffixes: Sequence[str] = ["npz", "npy"]
        return is_supported_format(filename, suffixes)

    def read(self, data: Sequence[PathLike] | PathLike, **kwargs):
        """
        Read image data from specified file or files, it can read a list of data files
        and stack them together as multi-channel data in `get_data()`.
        Note that the returned object is Numpy array or list of Numpy arrays.

        Args:
            data: file name or a list of file names to read.
            kwargs: additional args for `numpy.load` API except `allow_pickle`, will override `self.kwargs` for existing keys.
                More details about available args:
                https://numpy.org/doc/stable/reference/generated/numpy.load.html

        Raises:
            ValueError: when `self.allow_pickle` is False but loaded data contains pickled objects.
        """