pyvista.ImageDataFilters.open

ImageDataFilters.open(

kernel_size: int | VectorLike[int] = (3, 3, 3),

scalars: str | None = None,

*,

binary: bool | VectorLike[float] | None = None,

progress_bar: bool = False,

)

Perform morphological opening on continuous or binary data.

Opening is an erosion followed by a dilation. It is used to remove small objects/noise while preserving the shape and size of larger objects.

Added in version 0.47.

Parameters:

kernel_sizeint | VectorLike[int], default: (3, 3, 3)

Determines the size of the kernel along the xyz-axes. Only non-singleton dimensions are opened, e.g. a kernel size of (3, 3, 1) and (3, 3, 3) produce the same result for 2D images.

scalarsstr, optional

Name of scalars to process. Defaults to currently active scalars.

binarybool | VectorLike[float], optional

Control if binary opening or continuous opening is used. Refer to erode() and/or dilate() for details about using this keyword.

progress_barbool, default: False

Display a progress bar to indicate progress.

Returns:

pyvista.ImageData

Dataset that has been opened.

See also

close, erode, dilate

Notes

This filter only supports point data. For inputs with cell data, consider re-meshing the cell data as point data with cells_to_points() or resampling the cell data to point data with cell_data_to_point_data().

Examples

Load a grayscale image download_chest() and show it for context.

>>> from pyvista import examples
>>> im = examples.download_chest()
>>> clim = im.get_data_range()
>>> kwargs = dict(
...     cmap='grey',
...     clim=clim,
...     lighting=False,
...     cpos='xy',
...     zoom='tight',
...     show_axes=False,
...     show_scalar_bar=False,
... )
>>> im.plot(**kwargs)

Static Scene

Interactive Scene

Use open to remove small objects in the lungs.

>>> opened = im.open(kernel_size=15)
>>> opened.plot(**kwargs)

Static Scene

Interactive Scene