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Last Post 06 Apr 2017 07:00 AM by
anon
ML classification performing process: how pass the statistics from a roi
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anon
New Member
Posts:24
06 Apr 2017 07:00 AM
Hi all, i am trying to perform a ML classification using ENVI API ENVIMaximumLikelihoodClassificationTask. I had seen the example https://www.harrisgeospatial.com/docs/ENVIMaximumLikelihoodClassificationTask.html where it is used a vector to calcolate the needed statistics. How implemenmt the same ML workflow using a set of ROI in xml or envi classic .roi format?
Deleted User
New Member
Posts:24
07 Apr 2017 04:01 AM
I found a temporary solutions, producing a ESRI shapefile from classic roi and using it. Howover this is not a solution for me. In fact, I need to: verify if a ESRI Shapefile exists. if yes, use it for the ML classification vector statistic computation, following the example I have linked before. if not, convert the roi classic file into a vector and then re-try to execute the ML classification I need to execute the workflow described above in batch mode through the idlpy bridge, so definitively using envi api, envi classic, idl or a combination of that. Any suggestion?
MariM
Veteran Member
Posts:2396
07 Apr 2017 08:50 AM
You can get the statistics from an ROI using the method shown in this example:
http://www.harrisgeospatial.com/docs/...
Once you calculate the stats for the classification method you want to use, you can pass them to the classification task.
Deleted User
New Member
Posts:24
07 Apr 2017 10:26 AM
It seems an interesting solution. I will try soon and I will report any problems, consideration. Thank you.
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