[GRASS-user] Question to the input seed grid of i.segment

[Paulo van Breugel]

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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