Hi ,
I am new to OTB and am trying to implement LargeScaleMeanShift Segmentation in python by referring to the documention “LargeScaleMeanShift — Orfeo ToolBox 9.0.0 documentation”
I have 10 cores and want to utilize all the cores while implementing LargeScaleMeanShift Segmentation. However, I don’t seem to see any parameter which suggests that multicore processing is supported. I can only see RAM and tilesize. So is multicore processing supported?
I have gone through the forum and have seen that in the discussion “Large Scale Mean Shift Takes a Long Time - #3 by acanion” it was mentioned to try using RAM and Tilesize but nothing about multicores.
In another discussion “Is otbcli_TrainVectorClassifier supporting multi-core processing?” pertaining to training a machine learning model it mentioned that OPENMP has to be used. Can OPENMP be used to enable multicore processing for LargeScaleMeanShift Segmentation? If yes, what would be the steps to enable it?
Thanks in advance!