On 10-02-17 18:41, Moritz Lennert wrote:
Hi Raphael,
On 10/02/17 12:08, Raphael Knevels wrote:
Hello Moritz,
thank you for your help, and sorry for my late response to this
topic.
The slic algorithm works really great :-) for my image (... which is
a slope) it needs around 27 minutes (11 000 superpixels and 0.6
compactness) - compared to SAGA GIS 45 min and GRASS GIS 700 min. To
use SLIC as Seed in i.segment it reduced the processing time to ~ 250
min.
Both are good to hear. Thanks for the feedback !
Is there any prospect to add the SLIC algorithm to i.segment as an
option for "Segmentation method"?- It would be very cool to do
multiscale/hierarchical segmentation with this algorithm.
The choice was to make this into a separate module, amongst others to
follow the general principle in GRASS that each module should do one
thing and only that (I know that with this logic, we probably should
have created i.segment.regiongrowing and i.segment.meanshift, but
there was sufficiently common code between the two to put them into
one module). We felt that the superpixel approach was different enough
from the other segmentation methods to warrant a separate modue.
When you speak of multiscale/hierarchical segmentation, what exactly
are you missing in i.superpixels.slic ? Some sort of "seeds" map as in
i.segment ?
For curiosity, I also tried out your suggestion to use the Saga Seeds
output modified by r.mapcalc "int_map = int(map)". However, during
i.segment I received following Error-message: " ERROR: Invalid region
id -3573".
That's weird. Does SAGA create negative segment ids ? Which outcome
did you use from the SAGA seed module ? For me it worked.
Meanwhile, I also tested the i.segment.uspo add-on. It works fine -
just the green progress bar does not.
No, I never implemented a progress measure in the module. A ToDo...
Besides, manually, I calculated
Moran's I and Intrasegment Variance by i.segment with 8 instead of 4
neighbors (default). Even if the object looks kind of " pixelated" at
the border, I received smaller Moran's I and Intrasegment Variance
values with i.segment 8 NB in comparison to 4 NB (same settings for
minsize and threshold). Maybe the "-d" flag of i.segment could also
be added to i.segment.uspo...
That shouldn't be too difficult. Internally, i.segment.uspo uses the
addon r.neighborhoodmatrix which has a '-d' flag. I just really do not
have the time to implement this right now. You could try yourself by
opening the i.segment.uspo (or on Windows i.segment.uspo.py) file and
adding "flags='d'" to the call to r.neighborhoodmatrix (lines 535 and
following):
res = gscript.read_command('r.neighborhoodmatrix',
input_=mapname,
output='-',
sep='comma',
flags='d',
quiet=True)
This will always apply the flag. When I have time I can add this as a
flag to i.segment.uspo.
A slightly larger project I have is to actually extract the code for
the calculation of the spatial autocorrelation and create a
"r.spatialautocorrelation" module. But not now... ;-)
+1 (or make that a double plus) that would be really great!
Moritz
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