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Hi,

In order of processing:

Segmentation identifies "islands" of contiguous pixels above the noise threshold as potential sources.

Partitioning can then split those islands into several sources (multi-thresholding) , it also removes some that don't have some minimum area.

Grouping identifies sources that are close enough to possibly overlap and puts them into a group.

The Deblending stage is currently a bit of a misnomer as it takes groups and removes sources in it that are considered to be false detections due to a nearby bright source (cleaning).

The model fitting works on groups and fits all the sources in a group so we don't need actual deblending before that.

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@cylammarco
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