Hi MarkusM,
Working on segmentation parameter optimization with fairly large images
we have stumbled upon some questions (ISTR that we've discussed this
before, but I cannot find traces of that discussion). As a reminder,
i.segment.uspo works by looping through a series of threshold parameter
values, segmenting a series of test regions at each parameter value and
then comparing the results in order to identify the "optimal" threshold.
Two issues have popped up:
- One approach we tried was to optimize thresholds separately for
different types of morphological zones. For each type we have several
polygons distributed across the image. These polygons are used as input
for a mask. However, it does seem that even if most of the image is
masked, open_files() takes a long time, as if it does read the entire
image. Is this expected / normal ? Would it be possible to reduce the
read time when most of the area is masked ?
- More generally: for every i.segment call, open_files() goes through
the reading of the input files and, AFAIU, checks for min/max values and
creates the seglib temp files (+ possibly other operations). When
segmenting the same image several times just using different thresholds,
it would seem that most of what open_files() does is repeated in exactly
the same manner at each call. Would it be possible to cache that
information somehow and to instruct i.segment to reuse that info each
time it is called on the same image and region ?
Just trying to crunch larger and larger images... :-)
Moritz
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