8.1.1

__init__.py

@@ -34,7 +34,7 @@ def description():
 
 
 def version():
-    return 'Version 8.1.0 - Infinity'
+    return 'Version 8.1.1 - Infinity'
 
 
 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="8.1.0" plugin_id="284">
+    <pyqgis_plugin name="Semi-Automatic Classification Plugin - master" version="8.1.1" 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 Landsat, Sentinel-2 images. Several algorithms are available for the land cover classification. This plugin requires the installation of Remotior Sensus, GDAL, OGR, Numpy, SciPy, and Matplotlib. For more information please visit https://fromgistors.blogspot.com .]]></about>
-        <version>8.1.0</version>
+        <version>8.1.1</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>

interface/bandset_tab.py

@@ -779,11 +779,12 @@ def perform_bandset_tools():
 
 
 # perform bandset tools
-def bandset_tools(output_directory, batch=True):
+def bandset_tools(output_directory, bandset_number=None, batch=True):
     if batch is False:
         cfg.ui_utils.add_progress_bar()
     cfg.logger.log.info('bandset_tools: %s' % output_directory)
-    bandset_number = cfg.project_registry[cfg.reg_active_bandset_number]
+    if bandset_number is None:
+        bandset_number = cfg.project_registry[cfg.reg_active_bandset_number]
     name = cfg.bandset_catalog.get_name(bandset_number)
     if cfg.rs.configurations.action:
         if cfg.dialog.ui.band_calc_checkBox.isChecked() is True:
@@ -879,9 +880,7 @@ def band_set_to_table(bandset_number):
         cfg.dialog.ui.bandset_tableWidget.blockSignals(True)
         names = str(bandset_x.get_band_attributes('name')).replace(
             "'", ''
-        ).replace(
-            '[', ''
-        ).replace(']', '')
+        ).replace('[', '').replace(']', '')
         if names == 'None':
             names = ''
         cfg.util_qt.add_table_item(

interface/clip_bands_tab.py

@@ -238,7 +238,10 @@ def clip_bands():
                 # temporary layer
                 date_time = cfg.utils.get_time()
                 t_vector_name = cfg.temp_roi_name + date_time + '.shp'
-                t_vector = cfg.temp_dir + '/' + date_time + t_vector_name
+                t_vector = (
+                        cfg.rs.configurations.temp.dir + '/' + date_time
+                        + t_vector_name
+                )
                 # get layer crs
                 crs = cfg.util_gdal.get_crs_gdal(reference)
                 # create a temp shapefile with a field
@@ -380,7 +383,8 @@ def set_script():
             # temporary layer
             date_time = cfg.utils.get_time()
             t_vector_name = cfg.temp_roi_name + date_time + '.shp'
-            t_vector = cfg.temp_dir + '/' + date_time + t_vector_name
+            t_vector = (cfg.rs.configurations.temp.dir+ '/' + date_time
+                        + t_vector_name)
             # get layer crs
             crs = cfg.util_gdal.get_crs_gdal(reference)
             # create a temp shapefile with a field

interface/download_products_tab.py

@@ -692,7 +692,7 @@ def display_sentinel2(row, preview=False):
         image_id = '%s_p.jp2' % image_name
     url = str(table.item(row, 13).text())
     # image preview
-    image_output = '%s//%s' % (cfg.temp_dir, image_id)
+    image_output = '%s/%s' % (cfg.rs.configurations.temp.dir, image_id)
     if preview is True and cfg.utils.check_file(image_output):
         preview_in_label(image_output)
         return image_output
@@ -739,29 +739,33 @@ def display_nasa_images(row, preview=False):
     max_lon = str(table.item(row, 10).text())
     url = str(table.item(row, 13).text())
     # image preview
-    image_output = '%s//%s_thumb.jpg' % (cfg.temp_dir, image_id)
+    image_output = '%s/%s_thumb.jpg' % (
+        cfg.rs.configurations.temp.dir, image_id
+    )
     if preview is True and cfg.utils.check_file(image_output):
         preview_in_label(image_output)
         return image_output
-    elif cfg.utils.check_file('%s//%s.vrt' % (cfg.temp_dir, image_id)):
+    elif cfg.utils.check_file(
+            '%s/%s.vrt' % (cfg.rs.configurations.temp.dir, image_id)
+    ):
         layer = cfg.util_qgis.select_layer_by_name(image_id)
         if layer is not None:
             cfg.util_qgis.set_layer_visible(layer, True)
             cfg.util_qgis.move_layer_to_top(layer)
         else:
             r = cfg.util_qgis.add_raster_layer(
-                '%s//%s.vrt'
-                % (cfg.temp_dir, image_id)
+                '%s/%s.vrt' % (cfg.rs.configurations.temp.dir, image_id)
             )
             cfg.util_qgis.set_raster_color_composite(r, 1, 2, 3)
     else:
         download_nasa_thumbnail(
             image_id, min_lat, min_lon, max_lat, max_lon, url, sat, preview
         )
-        if cfg.utils.check_file('%s//%s.vrt' % (cfg.temp_dir, image_id)):
+        if cfg.utils.check_file(
+                '%s/%s.vrt' % (cfg.rs.configurations.temp.dir, image_id)
+        ):
             r = cfg.util_qgis.add_raster_layer(
-                '%s//%s.vrt'
-                % (cfg.temp_dir, image_id)
+                '%s//%s.vrt' % (cfg.rs.configurations.temp.dir, image_id)
             )
             cfg.util_qgis.set_raster_color_composite(r, 1, 2, 3)
 
@@ -901,7 +905,9 @@ def onthefly_georef_image(
 def download_nasa_thumbnail(
         image_id, min_lat, min_lon, max_lat, max_lon, url, sat, preview=False
 ):
-    image_output = '%s//%s_thumb.jpg' % (cfg.temp_dir, image_id)
+    image_output = '%s/%s_thumb.jpg' % (
+        cfg.rs.configurations.temp.dir, image_id
+    )
     check = False
     if (sat == cfg.rs.configurations.landsat_hls
             or sat == cfg.rs.configurations.sentinel2_hls):
@@ -913,6 +919,7 @@ def download_nasa_thumbnail(
             preview_in_label(image_output)
             return image_output
         onthefly_georef_image(
-            image_output, '%s//%s.vrt' % (cfg.temp_dir, image_id), min_lon,
+            image_output,
+            '%s/%s.vrt' % (cfg.rs.configurations.temp.dir, image_id), min_lon,
             max_lon, min_lat, max_lat
         )

interface/image_conversion_tab.py

@@ -136,10 +136,15 @@ def perform_conversion(output_path=None, load_in_qgis=False):
         else:
             cfg.mx.msg_err_1()
         if add_bandset is True:
+            bandset_number = None
             for bandset_number in range(
                     1, cfg.bandset_catalog.get_bandset_count() + 1
             ):
                 cfg.bst.band_set_to_table(bandset_number)
+            cfg.bst.bandset_tools(
+                output_directory=output_path,
+                bandset_number=bandset_number
+            )
         cfg.mx.msg_inf_6()
         cfg.ui_utils.remove_progress_bar(smtp=str(__name__))
 

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=8.1.0
+version=8.1.1
 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 Landsat, Sentinel-2 images. Several algorithms are available for the land cover classification. This plugin requires the installation of Remotior Sensus, GDAL, OGR, Numpy, SciPy, and Matplotlib. For more information please visit https://fromgistors.blogspot.com .
 
 author=Luca Congedo
@@ -13,6 +13,9 @@ icon=semiautomaticclassificationplugin.png
 
 changelog=
 
+	8.1.1
+	-fixed band set tools integration with image conversion
+
 	8.1.0
 	-added function to automatically download Remotior Sensus if not found in the environment