pyvista.ImageDataFilters

class ImageDataFilters(*args, **kwargs)

An internal class to manage filters/algorithms for uniform grid datasets.

Methods

ImageDataFilters.cells_to_points([scalars, copy])	Re-mesh image data from a cell-based to a point-based representation.
ImageDataFilters.contour_labeled([n_labels, ...])	Generate labeled contours from 3D label maps.
ImageDataFilters.extract_subset(voi[, rate, ...])	Select piece (e.g., volume of interest).
ImageDataFilters.fft([output_scalars_name, ...])	Apply a fast Fourier transform (FFT) to the active scalars.
ImageDataFilters.gaussian_smooth([...])	Smooth the data with a Gaussian kernel.
ImageDataFilters.high_pass(x_cutoff, ...[, ...])	Perform a Butterworth high pass filter in the frequency domain.
ImageDataFilters.image_dilate_erode([...])	Dilates one value and erodes another.
ImageDataFilters.image_threshold(threshold)	Apply a threshold to scalar values in a uniform grid.
ImageDataFilters.low_pass(x_cutoff, ...[, ...])	Perform a Butterworth low pass filter in the frequency domain.
ImageDataFilters.median_smooth([...])	Smooth data using a median filter.
ImageDataFilters.pad_image([pad_value, ...])	Enlarge an image by padding its boundaries with new points.
ImageDataFilters.points_to_cells([scalars, copy])	Re-mesh image data from a point-based to a cell-based representation.
ImageDataFilters.rfft([output_scalars_name, ...])	Apply a reverse fast Fourier transform (RFFT) to the active scalars.