cupyx.scipy.ndimage.maximum_filter#

cupyx.scipy.ndimage.maximum_filter(input, size=None, footprint=None, output=None, mode='reflect', cval=0.0, origin=0, axes=None)[source]#

Multi-dimensional maximum filter.

Parameters:

input (cupy.ndarray) – The input array.
size (int or sequence of int) – One of size or footprint must be provided. If footprint is given, size is ignored. Otherwise footprint = cupy.ones(size) with size automatically made to match the number of dimensions in input.
footprint (cupy.ndarray) – a boolean array which specifies which of the elements within this shape will get passed to the filter function.
output (cupy.ndarray, dtype or None) – The array in which to place the output. Default is is same dtype as the input.
mode (str or sequence of str) – The array borders are handled according to the given mode ('reflect', 'constant', 'nearest', 'mirror', 'wrap'). Default is 'reflect'. By passing a sequence of modes with length equal to the number of axes along which the input array is being filtered, different modes can be specified along each axis. For more details on the supported modes, see scipy.ndimage.minimum_filter().
cval (scalar) – Value to fill past edges of input if mode is 'constant'. Default is 0.0.
origin (int or sequence of int) – The origin parameter controls the placement of the filter, relative to the center of the current element of the input. Default of 0 is equivalent to (0,)*input.ndim.
axes (tuple of int or None) – If None, input is filtered along all axes. Otherwise, input is filtered along the specified axes. When axes is specified, any tuples used for size, mode and/or origin must match the length of axes. The ith entry in any of these tuples corresponds to the ith entry in axes. Default is None.

Returns:

The result of the filtering.

Return type:

cupy.ndarray