def __init__(self, iface, working_dir=None):
QtGui.QDialog.__init__(self)
QtGui.QApplication.restoreOverrideCursor()
self.app_dir = os.path.join(os.path.abspath(os.path.join(os.path.dirname(__file__), os.pardir)), "win32", "bin")
logger.debug( "self.app_dir" + str(self.app_dir) )
#self.setupUi()
QGisLayers.setInterface(iface)
self.output_dir = None
def __init__(self, iface, working_dir=None):
QtGui.QDialog.__init__(self)
QtGui.QApplication.restoreOverrideCursor()
self.app_dir = os.path.join(
os.path.abspath(os.path.join(os.path.dirname(__file__),
os.pardir)), "win32", "bin")
logger.debug("self.app_dir" + str(self.app_dir))
#self.setupUi()
QGisLayers.setInterface(iface)
self.output_dir = None
def update_layers(self, layers):
self.layers = layers
# for layer in self.layers:
# print layer.name()
vectorlayers = QGisLayers.getVectorLayers(QGisLayerType.POLYGON)
self.vectorlayerselector.set_layers(vectorlayers)
rasterlayers = layers
self.rasterlayerselector.set_layers(rasterlayers)
def update_layers(self, layers):
self.layers = layers
# for layer in self.layers:
# print layer.name()
vectorlayers = QGisLayers.getVectorLayers(QGisLayerType.POLYGON)
self.vectorlayerselector.set_layers(vectorlayers)
rasterlayers = layers
self.rasterlayerselector.set_layers(rasterlayers)
def setupUi(self):
self.setWindowTitle(u"Classification Supervisée")
self.mainlayout = QtGui.QVBoxLayout()
#rasterlayers = QGisLayers.getRasterLayers()
rasterlayers = self.layers
self.rasterlayerselector = RasterLayerSelectorTable(
rasterlayers, self.output_dir, self.main_layer,
self.main_layer_bands)
vectorlayers = QGisLayers.getVectorLayers(QGisLayerType.POLYGON)
self.vectorlayerselector = VectorLayerSelectorTable(vectorlayers)
self.layerlayout = QtGui.QHBoxLayout()
self.layerlayout.addWidget(self.rasterlayerselector)
self.layerlayout.addWidget(self.vectorlayerselector)
# self.outputlayout = QtGui.QHBoxLayout()
#
# self.outputdirwidget = QtGui.QLineEdit()
# self.outputdirselectorbutton = QtGui.QPushButton("...")
# #self.setOutputDir( tempfile.mkdtemp(prefix='ClassificationSupervisee_', dir=None) )
# self.setOutputDir( self.output_dir )
#
# self.outputlayout.addWidget( QtGui.QLabel(u"Répertoire de sortie") )
# self.outputlayout.addWidget( self.outputdirwidget )
# self.outputlayout.addWidget( self.outputdirselectorbutton )
self.buttonBox = QtGui.QDialogButtonBox()
self.buttonBox.setOrientation(QtCore.Qt.Horizontal)
self.classifButton = QtGui.QPushButton("Classification")
self.cancelButton = QtGui.QPushButton("Annuler")
self.bottomLayout = QtGui.QHBoxLayout()
self.statusLabel = QtGui.QLabel()
self.buttonBox.addButton(self.classifButton,
QtGui.QDialogButtonBox.AcceptRole)
self.buttonBox.addButton(self.cancelButton,
QtGui.QDialogButtonBox.RejectRole)
self.bottomLayout.addWidget(self.statusLabel)
self.bottomLayout.addStretch()
self.bottomLayout.addWidget(self.buttonBox)
self.mainlayout.addLayout(self.layerlayout)
# self.mainlayout.addLayout(self.outputlayout)
self.mainlayout.addLayout(self.bottomLayout)
self.setLayout(self.mainlayout)
QtCore.QObject.connect(self.classifButton, QtCore.SIGNAL("clicked()"),
self.setClassifyingStatus)
QtCore.QObject.connect(self.classifButton, QtCore.SIGNAL("clicked()"),
self.classify)
QtCore.QObject.connect(self.cancelButton, QtCore.SIGNAL("clicked()"),
self.cancelPressed)
def __init__(self, iface):
# Save reference to the QGIS interface
self.iface = iface
QGisLayers.setInterface(iface)
# initialize plugin directory
self.plugin_dir = QFileInfo(QgsApplication.qgisUserDbFilePath()).path(
) + "/python/plugins/supervisedclassification"
# initialize locale
localePath = ""
locale = QSettings().value("locale/userLocale")[0:2]
if QFileInfo(self.plugin_dir).exists():
localePath = self.plugin_dir + "/i18n/supervisedclassification_" + locale + ".qm"
if QFileInfo(localePath).exists():
self.translator = QTranslator()
self.translator.load(localePath)
if qVersion() > '4.3.3':
QCoreApplication.installTranslator(self.translator)
def __init__(self, iface):
# Save reference to the QGIS interface
self.iface = iface
QGisLayers.setInterface(iface)
# initialize plugin directory
self.plugin_dir = (
QFileInfo(QgsApplication.qgisUserDbFilePath()).path() + "/python/plugins/supervisedclassification"
)
# initialize locale
localePath = ""
locale = QSettings().value("locale/userLocale")[0:2]
if QFileInfo(self.plugin_dir).exists():
localePath = self.plugin_dir + "/i18n/supervisedclassification_" + locale + ".qm"
if QFileInfo(localePath).exists():
self.translator = QTranslator()
self.translator.load(localePath)
if qVersion() > "4.3.3":
QCoreApplication.installTranslator(self.translator)
def setupUi(self):
self.setWindowTitle(u"Classification Supervisée")
self.mainlayout = QtGui.QVBoxLayout()
#rasterlayers = QGisLayers.getRasterLayers()
rasterlayers = self.layers
self.rasterlayerselector = RasterLayerSelectorTable(rasterlayers, self.output_dir, self.main_layer, self.main_layer_bands)
vectorlayers = QGisLayers.getVectorLayers(QGisLayerType.POLYGON)
self.vectorlayerselector = VectorLayerSelectorTable(vectorlayers)
self.layerlayout = QtGui.QHBoxLayout()
self.layerlayout.addWidget(self.rasterlayerselector)
self.layerlayout.addWidget(self.vectorlayerselector)
# self.outputlayout = QtGui.QHBoxLayout()
#
# self.outputdirwidget = QtGui.QLineEdit()
# self.outputdirselectorbutton = QtGui.QPushButton("...")
# #self.setOutputDir( tempfile.mkdtemp(prefix='ClassificationSupervisee_', dir=None) )
# self.setOutputDir( self.output_dir )
#
# self.outputlayout.addWidget( QtGui.QLabel(u"Répertoire de sortie") )
# self.outputlayout.addWidget( self.outputdirwidget )
# self.outputlayout.addWidget( self.outputdirselectorbutton )
self.buttonBox = QtGui.QDialogButtonBox()
self.buttonBox.setOrientation(QtCore.Qt.Horizontal)
self.classifButton = QtGui.QPushButton("Classification")
self.cancelButton = QtGui.QPushButton("Annuler")
self.bottomLayout = QtGui.QHBoxLayout()
self.statusLabel = QtGui.QLabel()
self.buttonBox.addButton(self.classifButton, QtGui.QDialogButtonBox.AcceptRole)
self.buttonBox.addButton(self.cancelButton, QtGui.QDialogButtonBox.RejectRole)
self.bottomLayout.addWidget(self.statusLabel)
self.bottomLayout.addStretch()
self.bottomLayout.addWidget(self.buttonBox)
self.mainlayout.addLayout(self.layerlayout)
# self.mainlayout.addLayout(self.outputlayout)
self.mainlayout.addLayout(self.bottomLayout)
self.setLayout(self.mainlayout)
QtCore.QObject.connect(self.classifButton, QtCore.SIGNAL("clicked()"), self.setClassifyingStatus)
QtCore.QObject.connect(self.classifButton, QtCore.SIGNAL("clicked()"), self.classify)
QtCore.QObject.connect(self.cancelButton, QtCore.SIGNAL("clicked()"), self.cancelPressed)
def classify(self):
dirDest = QtGui.QFileDialog.getExistingDirectory(
None,
str("Répertoire de destination des fichiers de la classification"),
self.output_dir)
if dirDest:
self.output_dir = dirDest
logger.debug("classify")
simulation = False
# Get rasters
selectedrasterlayers = self.rasterlayerselector.getSelectedOptions()
logger.debug("selectedrasterlayers" + str(selectedrasterlayers))
if len(selectedrasterlayers) < 1:
QtGui.QMessageBox.critical( self, \
u"Erreur", \
u"Aucune couche raster sélectionnée" )
return
# Get vectors
selectedvectorlayers = self.vectorlayerselector.getSelectedOptions()
if len(selectedvectorlayers) < 2:
QtGui.QMessageBox.critical( self, \
u"Erreur", \
u"Au minimum deux couches vecteur doivent être sélectionnées" )
return
try:
errorDuringClassif = False
outputdir = self.getOutputDir()
# Build list of input raster files
rasterlist = ""
for r in selectedrasterlayers:
rasterlist += '"%s" ' % (r.source())
#logger.debug( "rasterlist" + str( rasterlist ) )
#firstraster = '"%s" ' % (unicode(selectedrasterlayers[0].source()))
logger.debug("selectedrasterlayers[0]" +
str(selectedrasterlayers[0]))
firstraster = '"%s" ' % (selectedrasterlayers[0].source())
# Build list of input vector files
vectorlist = ""
labeldescriptor = {}
label = 0
for i in range(len(selectedvectorlayers)):
v = selectedvectorlayers[i]
inputshpfilepath = v[0].source()
classcolor = v[1]
classlabel = v[2]
labeldescriptor[label] = (classcolor, classlabel)
logger.debug("labeldescriptor" + str(labeldescriptor))
label += 1
# Reprocess input shp file to crop it to firstraster extent
vectordir = os.path.join(outputdir, 'class%s' % (str(i)))
ensure_clean_dir(vectordir)
#preprocessedshpfile = os.path.join(vectordir, transform_spaces(os.path.basename(unicode(inputshpfilepath))))
preprocessedshpfile = os.path.join(vectordir,
"preprocessed.shp")
cropcommand = ('%s/cropvectortoimage.bat '
'"%s" '
'"%s" '
'"%s" '
'"%s" '
'"%s" ' %
(self.app_dir, inputshpfilepath,
selectedrasterlayers[0].source(),
os.path.join(vectordir, "imageenveloppe.shp"),
os.path.join(vectordir, "tmp_reprojected.shp"),
preprocessedshpfile))
terre_image_run_process.run_process(cropcommand, True)
# try:
# if (simulation):
# time.sleep(3)
# else:
# proc = subprocess.Popen(cropcommand.encode('mbcs'),
# shell=True,
# stdout=subprocess.PIPE,
# stdin=subprocess.PIPE,
# stderr=subprocess.STDOUT,
# universal_newlines=False)
#
# loglines = []
# for line in iter(proc.stdout.readline, ""):
# loglines.append(line)
#
# proc.wait()
# if proc.returncode != 0:
# raise OSError
#
# except OSError:
# errorDuringClassif = True
#
# mbox = QtGui.QMessageBox()
# mbox.setWindowTitle(u"Erreur")
# mbox.setText(u"Une erreur a été rencontrée lors de la préparation des données vecteurs")
#
# # has no effect...
# #mbox.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Expanding)
# #mbox.setSizeGripEnabled(True)
#
# detailedtext = (u"Code de retour : %s%s"
# "Commande : %s%s"
# "Sortie standard :%s%s"
# % ( proc.returncode, 2*os.linesep,
# cropcommand, 2*os.linesep,
# os.linesep, u''.join([u'%s%s' % (unicode(c, 'mbcs'), os.linesep) for c in loglines]) ) )
#
# mbox.setDetailedText(detailedtext)
# mbox.setIcon(QtGui.QMessageBox.Critical)
# mbox.setStandardButtons(QtGui.QMessageBox.Ok | QtGui.QMessageBox.Cancel)
# ret = mbox.exec_()
# raise OSError
vectorlist += '"%s" ' % (preprocessedshpfile)
# Build classifcommand
outputlog = os.path.join(outputdir, 'output.log')
outputclassification = os.path.join(outputdir,
'classification.tif')
outputresults = os.path.join(outputdir,
'classification.resultats.txt')
launcher = "%s/classification.bat" % self.app_dir
classifcommand = ('%s '
'-io.il %s '
'-io.vd %s '
'-io.out "%s" '
'-io.results "%s"' %
(launcher, rasterlist, vectorlist,
outputclassification, outputresults))
terre_image_run_process.run_process(classifcommand, True)
# Execute commandline
# try:
# if (simulation):
# time.sleep(3)
# else:
# proc = subprocess.Popen(classifcommand.encode('mbcs'),
# shell=True,
# stdout=subprocess.PIPE,
# stdin=subprocess.PIPE,
# stderr=subprocess.STDOUT,
# universal_newlines=False)
#
# loglines = []
# with open(outputlog, "w") as logfile:
# for line in iter(proc.stdout.readline, ""):
# loglines.append(line)
# logfile.writelines(line)
# logfile.flush()
# os.fsync(logfile.fileno())
#
# proc.wait()
# if proc.returncode != 0:
# raise OSError
#
# except OSError:
# errorDuringClassif = True
#
# mbox = QtGui.QMessageBox()
# mbox.setWindowTitle(u"Erreur")
# mbox.setText(u"Une erreur a été rencontrée lors de la classification")
#
# # has no effect...
# #mbox.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Expanding)
# #mbox.setSizeGripEnabled(True)
#
# detailedtext = (u"Code de retour : %s%s"
# "Commande : %s%s"
# "Sortie standard :%s%s"
# % ( proc.returncode, 2*os.linesep,
# classifcommand, 2*os.linesep,
# os.linesep, u''.join([u'%s%s' % (unicode(c, 'mbcs'), os.linesep) for c in loglines]) ) )
#
# mbox.setDetailedText(detailedtext)
# mbox.setIcon(QtGui.QMessageBox.Critical)
# mbox.setStandardButtons(QtGui.QMessageBox.Ok | QtGui.QMessageBox.Cancel)
# ret = mbox.exec_()
#
# saferemovefile(outputlog)
# saferemovefile(outputclassification)
# saferemovefile(outputresults)
if (not simulation and not errorDuringClassif):
QGisLayers.loadLabelImage(outputclassification,
labeldescriptor)
notificationDialog = ConfusionMatrixViewer(
selectedvectorlayers, outputresults)
self.clearStatus()
QtGui.QApplication.restoreOverrideCursor()
notificationDialog.setModal(True)
notificationDialog.show()
pixmap = QtGui.QPixmap(notificationDialog.size())
notificationDialog.render(pixmap)
pixmap.save(os.path.join(outputdir, 'resultats.png'))
notificationDialog.exec_()
# except:
# raise
finally:
self.clearStatus()
QtGui.QApplication.restoreOverrideCursor()
return # this discards exception
def classify(self):
dirDest = QtGui.QFileDialog.getExistingDirectory( None, str( "Répertoire de destination des fichiers de la classification" ), self.output_dir )
if dirDest :
self.output_dir = dirDest
logger.debug( "classify" )
simulation = False
# Get rasters
selectedrasterlayers = self.rasterlayerselector.getSelectedOptions()
logger.debug( "selectedrasterlayers" + str(selectedrasterlayers) )
if len(selectedrasterlayers) < 1:
QtGui.QMessageBox.critical( self, \
u"Erreur", \
u"Aucune couche raster sélectionnée" )
return
# Get vectors
selectedvectorlayers = self.vectorlayerselector.getSelectedOptions()
if len(selectedvectorlayers) < 2:
QtGui.QMessageBox.critical( self, \
u"Erreur", \
u"Au minimum deux couches vecteur doivent être sélectionnées" )
return
try:
errorDuringClassif = False
outputdir = self.getOutputDir()
# Build list of input raster files
rasterlist = ""
for r in selectedrasterlayers:
rasterlist += '"%s" ' % (r.source())
#logger.debug( "rasterlist" + str( rasterlist ) )
#firstraster = '"%s" ' % (unicode(selectedrasterlayers[0].source()))
logger.debug( "selectedrasterlayers[0]" + str(selectedrasterlayers[0]) )
firstraster = '"%s" ' % (selectedrasterlayers[0].source())
# Build list of input vector files
vectorlist = ""
labeldescriptor = {}
label = 0
for i in range(len(selectedvectorlayers)):
v = selectedvectorlayers[i]
inputshpfilepath = v[0].source()
classcolor = v[1]
classlabel = v[2]
labeldescriptor[label] = (classcolor, classlabel)
logger.debug( "labeldescriptor" + str(labeldescriptor) )
label += 1
# Reprocess input shp file to crop it to firstraster extent
vectordir = os.path.join(outputdir, 'class%s' % (str(i)))
ensure_clean_dir(vectordir)
#preprocessedshpfile = os.path.join(vectordir, transform_spaces(os.path.basename(unicode(inputshpfilepath))))
preprocessedshpfile = os.path.join(vectordir, "preprocessed.shp")
cropcommand = ('%s/cropvectortoimage.bat '
'"%s" '
'"%s" '
'"%s" '
'"%s" '
'"%s" '
% ( self.app_dir,
inputshpfilepath,
selectedrasterlayers[0].source(),
os.path.join(vectordir,"imageenveloppe.shp"),
os.path.join(vectordir,"tmp_reprojected.shp"),
preprocessedshpfile) )
terre_image_run_process.run_process(cropcommand, True)
# try:
# if (simulation):
# time.sleep(3)
# else:
# proc = subprocess.Popen(cropcommand.encode('mbcs'),
# shell=True,
# stdout=subprocess.PIPE,
# stdin=subprocess.PIPE,
# stderr=subprocess.STDOUT,
# universal_newlines=False)
#
# loglines = []
# for line in iter(proc.stdout.readline, ""):
# loglines.append(line)
#
# proc.wait()
# if proc.returncode != 0:
# raise OSError
#
# except OSError:
# errorDuringClassif = True
#
# mbox = QtGui.QMessageBox()
# mbox.setWindowTitle(u"Erreur")
# mbox.setText(u"Une erreur a été rencontrée lors de la préparation des données vecteurs")
#
# # has no effect...
# #mbox.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Expanding)
# #mbox.setSizeGripEnabled(True)
#
# detailedtext = (u"Code de retour : %s%s"
# "Commande : %s%s"
# "Sortie standard :%s%s"
# % ( proc.returncode, 2*os.linesep,
# cropcommand, 2*os.linesep,
# os.linesep, u''.join([u'%s%s' % (unicode(c, 'mbcs'), os.linesep) for c in loglines]) ) )
#
# mbox.setDetailedText(detailedtext)
# mbox.setIcon(QtGui.QMessageBox.Critical)
# mbox.setStandardButtons(QtGui.QMessageBox.Ok | QtGui.QMessageBox.Cancel)
# ret = mbox.exec_()
# raise OSError
vectorlist += '"%s" ' % (preprocessedshpfile)
# Build classifcommand
outputlog = os.path.join(outputdir, 'output.log')
outputclassification = os.path.join(outputdir, 'classification.tif')
outputresults = os.path.join(outputdir, 'classification.resultats.txt')
launcher = "%s/classification.bat" % self.app_dir
classifcommand = ( '%s '
'-io.il %s '
'-io.vd %s '
'-io.out "%s" '
'-io.results "%s"'
% (launcher,
rasterlist,
vectorlist,
outputclassification,
outputresults) )
terre_image_run_process.run_process(classifcommand, True)
# Execute commandline
# try:
# if (simulation):
# time.sleep(3)
# else:
# proc = subprocess.Popen(classifcommand.encode('mbcs'),
# shell=True,
# stdout=subprocess.PIPE,
# stdin=subprocess.PIPE,
# stderr=subprocess.STDOUT,
# universal_newlines=False)
#
# loglines = []
# with open(outputlog, "w") as logfile:
# for line in iter(proc.stdout.readline, ""):
# loglines.append(line)
# logfile.writelines(line)
# logfile.flush()
# os.fsync(logfile.fileno())
#
# proc.wait()
# if proc.returncode != 0:
# raise OSError
#
# except OSError:
# errorDuringClassif = True
#
# mbox = QtGui.QMessageBox()
# mbox.setWindowTitle(u"Erreur")
# mbox.setText(u"Une erreur a été rencontrée lors de la classification")
#
# # has no effect...
# #mbox.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Expanding)
# #mbox.setSizeGripEnabled(True)
#
# detailedtext = (u"Code de retour : %s%s"
# "Commande : %s%s"
# "Sortie standard :%s%s"
# % ( proc.returncode, 2*os.linesep,
# classifcommand, 2*os.linesep,
# os.linesep, u''.join([u'%s%s' % (unicode(c, 'mbcs'), os.linesep) for c in loglines]) ) )
#
# mbox.setDetailedText(detailedtext)
# mbox.setIcon(QtGui.QMessageBox.Critical)
# mbox.setStandardButtons(QtGui.QMessageBox.Ok | QtGui.QMessageBox.Cancel)
# ret = mbox.exec_()
#
# saferemovefile(outputlog)
# saferemovefile(outputclassification)
# saferemovefile(outputresults)
if (not simulation and not errorDuringClassif):
QGisLayers.loadLabelImage(outputclassification, labeldescriptor)
notificationDialog = ConfusionMatrixViewer(selectedvectorlayers, outputresults)
self.clearStatus()
QtGui.QApplication.restoreOverrideCursor()
notificationDialog.setModal(True)
notificationDialog.show()
pixmap = QtGui.QPixmap(notificationDialog.size())
notificationDialog.render(pixmap)
pixmap.save(os.path.join(outputdir, 'resultats.png'))
notificationDialog.exec_()
# except:
# raise
finally:
self.clearStatus()
QtGui.QApplication.restoreOverrideCursor()
return # this discards exception
def classify(self):
dirDest = QtGui.QFileDialog.getExistingDirectory(
None,
u"Répertoire de destination des fichiers de la classification",
self.output_dir)
if dirDest:
self.output_dir = dirDest
logger.debug("classify")
simulation = False
try:
# Get rasters
selectedrasterlayers = self.rasterlayerselector.getSelectedOptions(
)
logger.debug(
"selectedrasterlayers {}".format(selectedrasterlayers))
if len(selectedrasterlayers) < 1:
QtGui.QMessageBox.critical( self, \
u"Erreur", \
u"Aucune couche raster sélectionnée" )
return
# Get vectors
selectedvectorlayers = self.vectorlayerselector.getSelectedOptions(
)
if len(selectedvectorlayers) < 2:
QtGui.QMessageBox.critical( self, \
u"Erreur", \
u"Au minimum deux couches vecteur doivent être sélectionnées" )
return
errorDuringClassif = False
outputdir = self.getOutputDir()
# Build list of input vector files
vectorlist = []
labeldescriptor = {}
label = 0
logger.info("Crop and reproject vector data")
for i in range(len(selectedvectorlayers)):
v = selectedvectorlayers[i]
inputshpfilepath = v[0].source()
classcolor = v[1]
classlabel = v[2]
labeldescriptor[label] = (classcolor, classlabel)
logger.debug("labeldescriptor {}".format(labeldescriptor))
label += 1
# Reprocess input shp file to crop it to firstraster extent
vectordir = os.path.join(outputdir, 'class%s' % (str(i)))
ensure_clean_dir(vectordir)
preprocessedshpfile = cropVectorDataToImage(
selectedrasterlayers[0].source(), inputshpfilepath,
vectordir)
vectorlist.append(preprocessedshpfile)
logger.info("Merge vector data")
union = mergeVectorData.unionPolygonsWithOGR(vectorlist, outputdir)
logger.info("Run classification")
# Build classifcommand
outputlog = os.path.join(outputdir, 'output.log')
outputclassification = os.path.join(outputdir,
'classification.tif')
out_pop = os.path.join(outputdir, 'classification.resultats.txt')
confmat, kappa = full_classification(
[r.source() for r in selectedrasterlayers], union,
outputclassification, out_pop, outputdir)
logger.info("Run confusion matrix viewer")
if (not simulation and not errorDuringClassif):
QGisLayers.loadLabelImage(outputclassification,
labeldescriptor)
notificationDialog = ConfusionMatrixViewer(
selectedvectorlayers, confmat, kappa, out_pop)
self.clearStatus()
QtGui.QApplication.restoreOverrideCursor()
notificationDialog.setModal(True)
notificationDialog.show()
pixmap = QtGui.QPixmap(notificationDialog.size())
notificationDialog.render(pixmap)
pixmap.save(os.path.join(outputdir, 'resultats.png'))
notificationDialog.exec_()
# except:
# raise
finally:
self.clearStatus()
QtGui.QApplication.restoreOverrideCursor()
def classify(self):
dirDest = QtGui.QFileDialog.getExistingDirectory( None, u"Répertoire de destination des fichiers de la classification", self.output_dir )
if dirDest :
self.output_dir = dirDest
logger.debug( "classify" )
simulation = False
try:
# Get rasters
selectedrasterlayers = self.rasterlayerselector.getSelectedOptions()
logger.debug( "selectedrasterlayers {}".format(selectedrasterlayers) )
if len(selectedrasterlayers) < 1:
QtGui.QMessageBox.critical( self, \
u"Erreur", \
u"Aucune couche raster sélectionnée" )
return
# Get vectors
selectedvectorlayers = self.vectorlayerselector.getSelectedOptions()
if len(selectedvectorlayers) < 2:
QtGui.QMessageBox.critical( self, \
u"Erreur", \
u"Au minimum deux couches vecteur doivent être sélectionnées" )
return
errorDuringClassif = False
outputdir = self.getOutputDir()
# Build list of input vector files
vectorlist = []
labeldescriptor = {}
label = 0
logger.info("Crop and reproject vector data")
for i in range(len(selectedvectorlayers)):
v = selectedvectorlayers[i]
inputshpfilepath = v[0].source()
classcolor = v[1]
classlabel = v[2]
labeldescriptor[label] = (classcolor, classlabel)
logger.debug( "labeldescriptor {}".format(labeldescriptor) )
label += 1
# Reprocess input shp file to crop it to firstraster extent
vectordir = os.path.join(outputdir, 'class%s' % (str(i)))
ensure_clean_dir(vectordir)
preprocessedshpfile = cropVectorDataToImage(selectedrasterlayers[0].source(), inputshpfilepath, vectordir)
vectorlist.append(preprocessedshpfile)
logger.info("Merge vector data")
union = mergeVectorData.unionPolygonsWithOGR(vectorlist, outputdir)
logger.info("Run classification")
# Build classifcommand
outputlog = os.path.join(outputdir, 'output.log')
outputclassification = os.path.join(outputdir, 'classification.tif')
out_pop = os.path.join(outputdir, 'classification.resultats.txt')
confmat, kappa = full_classification([r.source() for r in selectedrasterlayers],
union, outputclassification, out_pop, outputdir)
logger.info("Run confusion matrix viewer")
if (not simulation and not errorDuringClassif):
QGisLayers.loadLabelImage(outputclassification, labeldescriptor)
notificationDialog = ConfusionMatrixViewer(selectedvectorlayers, confmat, kappa, out_pop)
self.clearStatus()
QtGui.QApplication.restoreOverrideCursor()
notificationDialog.setModal(True)
notificationDialog.show()
pixmap = QtGui.QPixmap(notificationDialog.size())
notificationDialog.render(pixmap)
pixmap.save(os.path.join(outputdir, 'resultats.png'))
notificationDialog.exec_()
# except:
# raise
finally:
self.clearStatus()
QtGui.QApplication.restoreOverrideCursor()
