many thanks Guillaume ,
see my code below ...
The number of the channels are good ? if yes , i don't see my error
see you
Michel
otbcli_ConcatenateImages.bat -il LAND*.TIF -out
alldates2014_avignon_landsat.TIF uint16
for f in LAND*.TIF; do otbcli_RadiometricIndices.bat -channels.blue 2
-channels.green 3 -channels.red 4 -channels.nir 5 -in "$f" -out "NDVI_$f"
-list Vegetation:NDVI; done
*(good number ???) *
otbcli_ConcatenateImages.bat -il NDVI*.TIF -out
alldates2014_avignon_landsat_nvdi.TIF uint16
otbcli_ConcatenateImages.bat -il alldates2014_avignon_landsat.TIF
alldates2014_avignon_landsat_nvdi.TIF -out
alldates2014_avignon_landsat_bandes_et_nvdi.TIF uint16
otbcli_PolygonClassStatistics.bat -in alldates2014_avignon_landsat.tif -vec
training_range_rpg.shp -field "code" -out test.xml
otbcli_SampleSelection.bat -in alldates2014_avignon_landsat.tif -field code
-vec training_range_rpg.shp -out training_samples.sqlite -instats test.xml
-strategy smallest
otbcli_SampleExtraction.bat -in alldates2014_avignon_landsat.tif -vec
training_samples.sqlite -outfield prefix -outfield.prefix.name band_ -field
code
otbcli_SampleExtraction.bat -in alldates2014_avignon_landsat_nvdi.TIF -vec
training_samples.sqlite -outfield prefix -outfield.prefix.name ndvi_ -field
code
for i in $(seq 1 7); do var=date$i; otbcli_TrainVectorClassifier.bat -io.vd
training_samples.sqlite -cfield code -classifier rf -classifier.rf.max 20
-io.out model.rf -feat ${bands} | grep Kappa; done OK
for i in $(seq 1 7); do var=date$i; otbcli_TrainVectorClassifier.bat -io.vd
training_samples.sqlite -cfield code -classifier rf -classifier.rf.max 20
-io.out model.rf -feat ${bands} ${ndvi} | grep Kappa; done --* pas de NDVI
!!!!*
pas de ndvi
Le mercredi 9 novembre 2016 15:17:40 UTC+1, Guillaume Pasero a écrit :
>
> Hi,
>
> When you want to perform the training, the "feat" parameter should be fed
> with field names from training_samples.sqlite on which you want to train.
>
> In your pipeline, you should concatenate your NDVI images into one stack (
> otbcli_ConcatenateImages) then use this stack to extract the samples values
> (otbcli_SampleExtraction).
>
> Regards,
>
> Guillaume
>
> On 11/09/2016 11:08 AM, michel M wrote:
>
>
> hello ,
>
> I have a little question I have 7 images (7 months) Landsat 8 (for a year)
>
> i use this fonction
> for f in LAND*.TIF; do otbcli_RadiometricIndices.bat -channels.blue 2
> -channels.green 3 -channels.red 4 -channels.nir 5 -in "$f" -out "NDVI_$f"
> -list Vegetation:NDVI; done
> after i do
>
> ndvi=`for i in $(seq 0 6); do printf "ndvi_$i "; done`
> and
>
>
> otbcli_TrainVectorClassifier.bat -io.vd training_samples.sqlite -cfield
> code -classifier rf -classifier.rf.max 20 -io.out model.rf -feat ${ndvi}
> and i have
>
> 2016 Nov 09 11:04:36 : Application.logger (INFO) Precision of class
> [28] vs all: 0.0697674
> 2016 Nov 09 11:04:36 : Application.logger (INFO) Recall of class
> [28] vs all: 1
> 2016 Nov 09 11:04:36 : Application.logger (INFO) F-score of class
> [28] vs all: 0.130435
> 2016 Nov 09 11:04:36 : Application.logger (INFO) Global performance,
> Kappa index: 0
>
> there is no vegetation very strange ????
>
> is there the good numbers of channels ?
>
> many thanks
>
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