pygmi.clust.segmentation

Image segmentation routines, following Baatz and Schäpe (2000).

Classes

ImageSeg

Image Segmentation GUI.

Functions

segment1(data, *[, scale, wcolor, wcompact, doshape, ...])	Perform image segmentation.
get_l(data)	Get bounding box length.

Module Contents

class pygmi.clust.segmentation.ImageSeg(parent=None)

Bases: pygmi.misc.BasicModule

Image Segmentation GUI.

Parameters:

parent – Reference to the parent routine. The default is None.

setupui()

Set up UI.

settings(nodialog=False)

Entry point into item.

Parameters:

nodialog (bool) – Run settings without a dialog. The default is False.

Returns:

True if successful, False otherwise.

Return type:

bool

saveproj()

Save project data from class.

pygmi.clust.segmentation.segment1(data, *, scale=500, wcolor=0.5, wcompact=0.5, doshape=True, showlog=print, piter=iter)

Perform image segmentation.

Parameters:

• data (numpy.typing.NDArray) – Input data.

• scale (int) – Scale. The default is 500.

• wcolor (float) – Colour weight. The default is 0.5.

• wcompact (float) – Compactness weight. The default is 0.5.

• doshape (float) – Perform shape segmentation. The default is True.

• showlog (collections.abc.Callable[..., None]) – Display information. The default is print.

• piter (collections.abc.Iterable) – Progress bar iterator. The default is iter.

Returns:

omap – Output data.

Return type:

numpy array

pygmi.clust.segmentation.get_l(data)

Get bounding box length.

Parameters:

data (numpy.typing.NDArray) – Input data.

Returns:

Bounding box length.

Return type:

float