7.9.6

__init__.py

@@ -42,7 +42,7 @@ def description():
 
 
 def version():
-    return 'Version 7.9.5 - Matera'
+    return 'Version 7.9.6 - Matera'
 
 
 def icon():

docs/repository.xml

@@ -1,9 +1,9 @@
 <?xml version = '1.0' encoding = 'UTF-8'?>
 <plugins>
-    <pyqgis_plugin name="Semi-Automatic Classification Plugin - master" version="7.9.5" plugin_id="284">
+    <pyqgis_plugin name="Semi-Automatic Classification Plugin - master" version="7.9.6" plugin_id="284">
         <description><![CDATA[The Semi-Automatic Classification Plugin (SCP) allows for the supervised classification of remote sensing images, providing tools for the download, the preprocessing and postprocessing of images.]]></description>
         <about><![CDATA[Developed by Luca Congedo, the Semi-Automatic Classification Plugin (SCP) allows for the supervised classification of remote sensing images, providing tools for the download, the preprocessing and postprocessing of images. Search and download is available for ASTER, GOES, Landsat, MODIS, Sentinel-1, Sentinel-2, and Sentinel-3 images. Several algorithms are available for the land cover classification. This plugin requires the installation of GDAL, OGR, Numpy, SciPy, and Matplotlib. Some tools require also the installation of SNAP (ESA Sentinel Application Platform). For more information please visit https://fromgistors.blogspot.com .]]></about>
-        <version>7.9.5</version>
+        <version>7.9.6</version>
         <qgis_minimum_version>3.0.0</qgis_minimum_version>
         <qgis_maximum_version>3.99.0</qgis_maximum_version>
         <homepage><![CDATA[https://fromgistors.blogspot.com/p/semi-automatic-classification-plugin.html]]></homepage>

maininterface/clusteringTab.py

@@ -598,7 +598,7 @@ def isodataIteration(self, inputGDALRaster, bandList, iteration, k_or_sigs, clas
 			try:
 				# values finder
 				cfg.parallelArrayDict = {}
-				o = cfg.utls.multiProcessRaster(rasterPath = tPMDV, functionBand = 'No', functionRaster = cfg.utls.rasterStandardDeviationISODATA, progressMessage = cfg.QtWidgetsSCP.QApplication.translate('semiautomaticclassificationplugin', 'Calculate raster values iteration ') + str(iteration + 1).replace('-1', '*').replace('0', '*'), nodataValue = nD, functionVariable = [classes, cfg.rasterClustering])
+				o = cfg.utls.multiProcessRaster(rasterPath = tPMDV, functionBand = 'No', functionRaster = cfg.utls.rasterStandardDeviationISODATA, progressMessage = cfg.QtWidgetsSCP.QApplication.translate('semiautomaticclassificationplugin', 'Calculate raster values iteration ') + str(iteration + 1).replace('-1', '*').replace('0', '*'), nodataValue = nD, functionVariable = [classesMP, cfg.rasterClustering])
 			except Exception as err:
 				# logger
 				cfg.utls.logCondition(str(__name__) + '-' + str(cfg.inspectSCP.stack()[0][3])+ ' ' + cfg.utls.lineOfCode(), ' ERROR exception: ' + str(err))

maininterface/sentinel1Tab.py

@@ -405,7 +405,7 @@ def processS1toDB(self, inputRaster, outputRaster):
 		# reprojection
 		if reproject == 'Yes':
 			tPMD2 = cfg.utls.createTempRasterPath('tif')
-			cfg.utls.GDALReprojectRaster(input = oM, output = tPMD2, outFormat = 'GTiff', s_srs = None, t_srs = 'EPSG:' + str(rEPSG), rasterDataType = 'Float32', noDataVal = nD)
+			cfg.utls.GDALReprojectRaster(input = oM, output = tPMD2, outFormat = 'GTiff', s_srs = None, t_srs = str(rEPSG.ExportToWkt()), rasterDataType = 'Float32', noDataVal = nD)
 			# remove temp
 			try:
 				cfg.osSCP.remove(oM)

metadata.txt

@@ -2,7 +2,7 @@
 name=Semi-Automatic Classification Plugin
 qgisMinimumVersion=3.00
 description=The Semi-Automatic Classification Plugin (SCP) allows for the supervised classification of remote sensing images, providing tools for the download, the preprocessing and postprocessing of images.
-version=7.9.5
+version=7.9.6
 about=Developed by Luca Congedo, the Semi-Automatic Classification Plugin (SCP) allows for the supervised classification of remote sensing images, providing tools for the download, the preprocessing and postprocessing of images. Search and download is available for ASTER, GOES, Landsat, MODIS, Sentinel-1, Sentinel-2, and Sentinel-3 images. Several algorithms are available for the land cover classification. This plugin requires the installation of GDAL, OGR, Numpy, SciPy, and Matplotlib. Some tools require also the installation of SNAP (ESA Sentinel Application Platform). For more information please visit https://fromgistors.blogspot.com .
 
 author=Luca Congedo
@@ -14,6 +14,10 @@ icon=semiautomaticclassificationplugin.png
 ; start of optional metadata
 changelog=
 
+	7.9.6
+	-fixed Sentinel-1 preprocessing reprojection issue
+	-fixed clustering ISODATA issue
+
 	7.9.5
 	-fixed Landsat processing error