Hi all, Thanks for fixing pb 7.1. I'm looking forward to test it.
For very Basic OBIA classification (on OBIA my personal use is mainly teaching, on a small areas , for the moment i make the student switch to scikit-learn for the classification after the attributes are produced in OTB...) - As Jordi says, the ObjectsRadiometricStatistics in the OTB-contrib package or compiled from source works OK to derive radiometric attributes and basic shape attributes (elong, perim). However there is still the common issue of small vector areas compared to pixel size. In that case "nan" or empty attributes are produced. it would be good to make it more robust to small vector region. - There are steps in the common classification pipeline that are still dependant on an image (XML for mean and variance of each feature in the OGR LayerClassifier, XML image stats file in the TrainVectorClassifier app) and prevent the use of all the radiometric attributes or extra attributes that could be calculated at object level. - Maybe it would be interesting to adapt the SampleExtraction or TrainVectorClassifier so that the OBIA pipeline could benefit from the sample selection strategies. I'm OK to spend time testing things on that if you want to validate the modification, or to add an OBIA exercice in the OTB workshop ++ Sébastien Le vendredi 19 mai 2017 10:43:48 UTC+2, Julien Michel a écrit : > > Le 24/01/2017 à 17:38, Sébastien G. a écrit : > > *step 7- *otbgui_OGRLayerClassifier that takes as input the previous > > shapefile and the image statistics and add a new "predicted" > > attributes in the shapefile. > > > > pb7.1 : The OGRLayerClassifier only seem to accept SVM models. It > > worked for a SVM classifier but failed for a Random Forest with error > > messages related to itk SVM .... need to develop an otbapp > > VectorClassifier ? > > Hi all, > > I am just getting back to that thread, with a lot of activity and > comments. I just wanted to stress that pb7.1 is fixed in OTB 6.0 : you > know have access to all learning algorithm (including the unsupervised > shark K-Means we introduced in 6.0) in the TrainVectorClassifier app. > One step at a time ... There might also be in a near future a remote > module that allows to fix pb2.1. > > Given all the insightful comments here, I think we could plan a working > group on this OBIA topic during next user days, to sum up what has been > said in the thread, add more ideas and write a good RFC to capture all > that. Then we could put it into action. > > Thanks a lot for all your comments, > > Regards, > > Julien > > -- > Julien MICHEL > CNES - DSO/SI/2A > > -- -- Check the OTB FAQ at http://www.orfeo-toolbox.org/FAQ.html You received this message because you are subscribed to the Google Groups "otb-users" group. To post to this group, send email to [email protected] To unsubscribe from this group, send email to [email protected] For more options, visit this group at http://groups.google.com/group/otb-users?hl=en --- You received this message because you are subscribed to the Google Groups "otb-users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
