On 02/08/17 21:43, Markus Metz wrote:
Hi Moritz,
On Wed, Aug 2, 2017 at 2:52 PM, Moritz Lennert
<[email protected] <mailto:[email protected]>> wrote:
>
> 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 ?
You could reduce the read time by zooming to the current mask with
g.region zoom=current_mask
Yes, but this doesn't help for situations where the mask areas are
distributed across the entire image, so that the region will be almost
as large as the original image.
>
> - 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 ?
The most time (and disk space) consuming part of open_files() is
creating temporary files for the input files and the current region and
the current mask. These temporary files are temporary because too many
things can change between two consecutive runs of any module using the
segment library. First of all, the input files could change (same name,
but different cell values), then region and mask settings could change.
Agreed, but here I'm talking about the situation where I run i.segment
multiple times in a loop with exactly the same input, and only threshold
value (and possibly minsize) changing. So we hoped that it would be
possible to reuse the segment library files.
>
> Just trying to crunch larger and larger images... :-)
As in, it's working but a bit slow?
i.segment is definitely not slow compared to other similar software, but
in this specific case of looping the accumulated time used in the phase
of reading the input files grows to a significant duration.
I have one or two ideas about how to speed up i.segment a little bit,
but unfortunately no time to implement them right now :-(
Don't worry. I'll just keep sending itches, until you can't bare not
scratching them ;-)
Moritz
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