Hi Sebastien, It's seems that you've been trying to do object based classification by OTB. I've noticed that there are some new apps added to OTB 5.10. I was wondering if you were able to do the object based classification by OTB apps and not using any other external programs like Qgis. I'm struggling with these steps you've mentioned here and also the available documentations. For instance there is one documentation called recipes about classification on the OTB website. that recipe is about pixel-based classification. If you were able to do the object based classification, would you please go over the steps you have taken to accomplish the result one more time?
Best, Ghassem On Tuesday, January 24, 2017 at 1:08:26 PM UTC-3:30, Sébastien G. wrote: > > Hi Julien, > > Thanks for your answer. Here is the steps we used and possible problems > based on your answer and some problems identified. > > *step 1*- otbcli_Segmentation or otbcli_LSMSSegmentation to produce a > labeled (id region polygon) raster segmentation > > *step 2*- Build a concatenate images with otbgui_ConcatenateImages, with > desired N attributes (spectral channels, texture images from otb > applictations) > > pb2.1 : there used to be an otb command to produce shape attributes > and statistics attributes based on otb filters (OBIA in software > documentation). I think this has not been put into an application. It could > be nice for object based to have these features such as the otb app for > texture > > *step 3-* otbgui_ComputeImagesStatistics to produce an .xml with > mean,variance for the N channels of the Concatenate Images > > *step 4- *otbgui_LSMSVectorization to produce a shapefile with 2*N > features (mean,variance) + id + nbpixels per region > > *step 5- *Add a class feature to this shapefile and manually give a class > for training > > pb5.1 : Ok with your comment i don't know any method to produce > automatically these attributes with vector data that is not consistent with > the segmentation but i am not familiar with vector analysis (join > attributes by location, qgis ?) > > *step 6- *otbcli_TrainVectorClassifier to produce a model > > pb6.1 : It is impossible to keep the variance features of the > shapefile for the model estimation since the statistics per band from > otbcli_ComputeImagesStatistics only give stats for the means. (N bands)... > difficult to explain ;-) > > > *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 > ? > > (I did the tests on OTB 5.6.1, i'll have to to this test again with the > 5.8 version) > > Sébastien Giordano / Cécile Cazals > > > Le mardi 24 janvier 2017 16:07:04 UTC+1, Julien Michel a écrit : >> >> Hi, >> >> Please find my answers enclosed. Bottom line is that we have some >> components but we are still missing other ones to perform a complete >> OBIA scheme. This thread could be an opportunity to start a discussion >> on what is missing. We could then write a Request For Comments about >> that. >> >> Regards, >> >> Julien >> >> Le 24/01/2017 à 15:46, Sébastien G. a écrit : >> > Hi, >> > >> > Since recent OTB versions there is a very nice new framework for >> > classifictaion (PolygonStatistics, SampleSelection, >> > SampleExtraction,TrainVectorClassifier) that allow to train model on >> > vector data. >> > >> > Can anyone tell me an OTB recipee to use these new tools for >> > object-based classification, including the following steps : >> > 1- Derive features from a raster images on a segmentation (mean, >> > standard deviation of radiometric channels, or shape features) >> There is this step from the Large Scale MeanShift segmentation workflow : >> >> >> https://www.orfeo-toolbox.org/CookBook/recipes/improc.html#step-4-vectorization >> >> >> Will work with any pair of segmentation/input image as long as they >> share the same sampling grid (i.e. same size/orgin/spacing). >> >> There are also similar things in this remote module : >> >> https://github.com/sertit/SertitObject >> >> > 2- Train a vectorClassifier knowing a class attributes on a sample of >> > the (segmentation with features). >> This is covered by TrainVectorClassifier application, which can learn >> from points but also from polylines or polygons. The problem is to get >> the labels to train the polygons. Aside from manual editing, we are >> missing some tools to perform automatic labelling of polygons from a >> reference layer. >> >> > 3- Apply the model on the vector data (segmentation with features) >> >> This is covered by OGRLayerClassifier application; >> > >> > >> > Best regards, >> > Sébastien >> > -- >> > -- >> > 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] >> > <mailto:[email protected]>. >> > For more options, visit https://groups.google.com/d/optout. >> >> >> -- >> 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.
