Hi,

First thing to know is that during TrainImagesClassifier, some parts of the processing are mono-threaded (only 1 CPU used). This is a design limitation. However, the multi-threaded parts of this application should be able to use all the CPUs available.

About the memory consumption, the RAM parameter in the application should set the maximum RAM amount to be used. I think that in the case of TrainImagesClassifier, this setting is difficult to derive because it depends on the polygon density in your training/validation vector layer.

If you use an other application that is more like an "image to image" processing, you should see the expected behaviour more clearly.

Regards,
Guillaume

On 11/24/2017 11:23 AM, Hristo Nikolov wrote:
Hello,
I'd like to share my opinion on using the standalone version of OTB namely otbcli_TrainImagesClassifier. 
On workstation with 8 core processor and 48GB RAM what I see is that only one of the cores is used at 100%
and only small amount of RAM is used. Is there way to set the number of cores to be used during this processing
as well as the amount of RAM.

Thank you.
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