def checkResult( self, tested_image, reference_image ):
""" Check if testVar and refVar are equal with the given precision and the given type
@param tested_image: variable computed by the test
@param reference_image: array variable containing the reference value(s), the precision and the type
-> reference value(s) to compare with the testVar
-> numerical precision to use to chekc if variables are equal
-> type of variables to check
@return: True is variables are equal, False otherwise
"""
print "Comparing {} and {}".format(reference_image, tested_image)
command = "otbcli_CompareImages -ref.in {} -meas.in {}".format(reference_image,
tested_image)
mse = -9999
mae = -9999
psnr = -9999
res = run_process(command)
lines = str(res).splitlines()
# for line in lines:
# # sensor_line = result_sensor[0]
# mse = re.search('mse: (\d*)$', line)
# if mse:
# # group 1 parce qu'on a demande qqchose de particulier a la regexpr a cause des ()
# mse = mse.group(1)
# continue
# print "suite", lines
# for line in lines:
# mae = re.search('mae: (\d*)$', line)
# if mae:
# # group 1 parce qu'on a demande qqchose de particulier a la regexpr a cause des ()
# mae = mae.group(1)
# print "MAE", mae
# continue
# for line in lines:
# psnr = re.search('mse: (\d*)$', line)
# if psnr:
# # group 1 parce qu'on a demande qqchose de particulier a la regexpr a cause des ()
# mse = psnr.group(1)
# continue
mse_line = lines[-4]
mae_line = lines[-3]
psnr_line = lines[-2]
mse = re.search('mse: (\d*)$', mse_line).group(1).replace(" ", "")
mae = re.search('mae: (\d*)$', mae_line).group(1).replace(" ", "")
psnr = re.search('psnr: (\d*)$', psnr_line).group(1).replace(" ", "")
if mse == mae == psnr == "0":
return True
else:
print '"{}"'.format(mse)
print "mse: {}, \n mae {}, \n psnr: {}".format(mse, mae, psnr)
return False
def checkResult(self, tested_image, reference_image):
""" Check if testVar and refVar are equal with the given precision and the given type
@param tested_image: variable computed by the test
@param reference_image: array variable containing the reference value(s), the precision and the type
-> reference value(s) to compare with the testVar
-> numerical precision to use to chekc if variables are equal
-> type of variables to check
@return: True is variables are equal, False otherwise
"""
print "Comparing {} and {}".format(reference_image, tested_image)
command = "otbcli_CompareImages -ref.in {} -meas.in {}".format(
reference_image, tested_image)
mse = -9999
mae = -9999
psnr = -9999
res = run_process(command)
lines = str(res).splitlines()
# for line in lines:
# # sensor_line = result_sensor[0]
# mse = re.search('mse: (\d*)$', line)
# if mse:
# # group 1 parce qu'on a demande qqchose de particulier a la regexpr a cause des ()
# mse = mse.group(1)
# continue
# print "suite", lines
# for line in lines:
# mae = re.search('mae: (\d*)$', line)
# if mae:
# # group 1 parce qu'on a demande qqchose de particulier a la regexpr a cause des ()
# mae = mae.group(1)
# print "MAE", mae
# continue
# for line in lines:
# psnr = re.search('mse: (\d*)$', line)
# if psnr:
# # group 1 parce qu'on a demande qqchose de particulier a la regexpr a cause des ()
# mse = psnr.group(1)
# continue
mse_line = lines[-4]
mae_line = lines[-3]
psnr_line = lines[-2]
mse = re.search('mse: (\d*)$', mse_line).group(1).replace(" ", "")
mae = re.search('mae: (\d*)$', mae_line).group(1).replace(" ", "")
psnr = re.search('psnr: (\d*)$', psnr_line).group(1).replace(" ", "")
if mse == mae == psnr == "0":
return True
else:
print '"{}"'.format(mse)
print "mse: {}, \n mae {}, \n psnr: {}".format(mse, mae, psnr)
return False
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
