pygmi.clust.segmentation#

Image segmentation routines, following the technique by 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 (parent, optional) – Reference to the parent routine. The default is None.

setupui()#

Set up UI.

Return type:

None.

settings(nodialog=False)#

Entry point into item.

Parameters:

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

Returns:

True if successful, False otherwise.

Return type:

bool

saveproj()#

Save project data from class.

Return type:

None.

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 array) – Input data.

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

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

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

  • doshape (bool, optional) – Perform shape segmentation. The default is True.

  • showlog (function, optional) – Display information. The default is print.

  • piter (function, optional) – 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 array) – Input data.

Returns:

ltmp – Bounding box length.

Return type:

int