def _applyInternalPathToTempOps(self, index):
if index == -1:
return
newInternalPath = str( self.internalDatasetNameComboBox.currentText() )
# Save a copy of our settings
oldInfos = {}
for laneIndex, op in self.tempOps.items():
oldInfos[laneIndex] = copy.copy( op.Dataset.value )
# Attempt to apply to all temp operators
try:
for laneIndex, op in self.tempOps.items():
info = copy.copy( op.Dataset.value )
pathComponents = PathComponents(info.filePath)
if pathComponents.internalPath != newInternalPath:
pathComponents.internalPath = newInternalPath
info.filePath = pathComponents.totalPath()
op.Dataset.setValue( info )
self._error_fields.discard('Internal Dataset Name')
return True
except Exception as e:
# Revert everything back to the previous state
for laneIndex, op in self.tempOps.items():
op.Dataset.setValue( oldInfos[laneIndex] )
msg = "Could not set new internal path settings due to an exception:\n"
msg += "{}".format( e )
log_exception( logger, msg )
QMessageBox.warning(self, "Error", msg)
self._error_fields.add('Internal Dataset Name')
return False
def handleImportLabelsAction():
# Find the directory of the most recently opened image file
mostRecentImageFile = PreferencesManager().get(
'DataSelection', 'recent image')
if mostRecentImageFile is not None:
defaultDirectory = os.path.split(mostRecentImageFile)[0]
else:
defaultDirectory = os.path.expanduser('~')
fileNames = DataSelectionGui.getImageFileNamesToOpen(
self, defaultDirectory)
fileNames = map(str, fileNames)
# For now, we require a single hdf5 file
if len(fileNames) > 1:
QMessageBox.critical(
self, "Too many files",
"Labels must be contained in a single hdf5 volume.")
return
if len(fileNames) == 0:
# user cancelled
return
file_path = fileNames[0]
internal_paths = DataSelectionGui.getPossibleInternalPaths(
file_path)
if len(internal_paths) == 0:
QMessageBox.critical(
self, "No volumes in file",
"Couldn't find a suitable dataset in your hdf5 file.")
return
if len(internal_paths) == 1:
internal_path = internal_paths[0]
else:
dlg = H5VolumeSelectionDlg(internal_paths, self)
if dlg.exec_() == QDialog.Rejected:
return
selected_index = dlg.combo.currentIndex()
internal_path = str(internal_paths[selected_index])
path_components = PathComponents(file_path)
path_components.internalPath = str(internal_path)
try:
top_op = self.topLevelOperatorView
opReader = OpInputDataReader(parent=top_op.parent)
opReader.FilePath.setValue(path_components.totalPath())
# Reorder the axes
op5 = OpReorderAxes(parent=top_op.parent)
op5.AxisOrder.setValue(
top_op.LabelInputs.meta.getAxisKeys())
op5.Input.connect(opReader.Output)
# Finally, import the labels
top_op.importLabels(top_op.current_view_index(),
op5.Output)
finally:
op5.cleanUp()
opReader.cleanUp()
def handleImportLabelsAction():
# Find the directory of the most recently opened image file
mostRecentImageFile = PreferencesManager().get( 'DataSelection', 'recent image' )
if mostRecentImageFile is not None:
defaultDirectory = os.path.split(mostRecentImageFile)[0]
else:
defaultDirectory = os.path.expanduser('~')
fileNames = DataSelectionGui.getImageFileNamesToOpen(self, defaultDirectory)
fileNames = list(map(str, fileNames))
# For now, we require a single hdf5 file
if len(fileNames) > 1:
QMessageBox.critical(self, "Too many files",
"Labels must be contained in a single hdf5 volume.")
return
if len(fileNames) == 0:
# user cancelled
return
file_path = fileNames[0]
internal_paths = DataSelectionGui.getPossibleInternalPaths(file_path)
if len(internal_paths) == 0:
QMessageBox.critical(self, "No volumes in file",
"Couldn't find a suitable dataset in your hdf5 file.")
return
if len(internal_paths) == 1:
internal_path = internal_paths[0]
else:
dlg = H5VolumeSelectionDlg(internal_paths, self)
if dlg.exec_() == QDialog.Rejected:
return
selected_index = dlg.combo.currentIndex()
internal_path = str(internal_paths[selected_index])
path_components = PathComponents(file_path)
path_components.internalPath = str(internal_path)
try:
top_op = self.topLevelOperatorView
opReader = OpInputDataReader(parent=top_op.parent)
opReader.FilePath.setValue( path_components.totalPath() )
# Reorder the axes
op5 = OpReorderAxes(parent=top_op.parent)
op5.AxisOrder.setValue( top_op.LabelInputs.meta.getAxisKeys() )
op5.Input.connect( opReader.Output )
# Finally, import the labels
top_op.importLabels( top_op.current_view_index(), op5.Output )
finally:
op5.cleanUp()
opReader.cleanUp()
def handleImportLabelsAction():
fileNames = ImageFileDialog(
self,
preferences_group="DataSelection",
preferences_setting="recent image").getSelectedPaths()
fileNames = list(map(str, fileNames))
# For now, we require a single hdf5 file
if len(fileNames) > 1:
QMessageBox.critical(
self, "Too many files",
"Labels must be contained in a single hdf5 volume.")
return
if len(fileNames) == 0:
# user cancelled
return
file_path = fileNames[0]
internal_paths = DatasetInfo.getPossibleInternalPathsFor(file_path)
if len(internal_paths) == 0:
QMessageBox.critical(
self, "No volumes in file",
"Couldn't find a suitable dataset in your hdf5 file.")
return
if len(internal_paths) == 1:
internal_path = internal_paths[0]
else:
dlg = SubvolumeSelectionDlg(internal_paths, self)
if dlg.exec_() == QDialog.Rejected:
return
selected_index = dlg.combo.currentIndex()
internal_path = str(internal_paths[selected_index])
path_components = PathComponents(file_path)
path_components.internalPath = str(internal_path)
try:
top_op = self.topLevelOperatorView
opReader = OpInputDataReader(parent=top_op.parent)
opReader.FilePath.setValue(path_components.totalPath())
# Reorder the axes
op5 = OpReorderAxes(parent=top_op.parent)
op5.AxisOrder.setValue(top_op.LabelInputs.meta.getAxisKeys())
op5.Input.connect(opReader.Output)
# Finally, import the labels
top_op.importLabels(top_op.current_view_index(), op5.Output)
finally:
op5.cleanUp()
opReader.cleanUp()
help="Path(s) to your exported predictions.")
parsed_args = parser.parse_args()
parsed_args, unused_args = DataExportApplet.parse_known_cmdline_args(
sys.argv[1:], parsed_args)
# As a convenience, auto-determine the internal dataset path if possible.
for index, input_path in enumerate(parsed_args.prediction_image_paths):
path_comp = PathComponents(input_path, os.getcwd())
if not parsed_args.output_internal_path:
parsed_args.output_internal_path = "segmentation"
if path_comp.extension in PathComponents.HDF5_EXTS and path_comp.internalDatasetName == "":
with h5py.File(path_comp.externalPath, "r") as f:
all_internal_paths = all_dataset_internal_paths(f)
if len(all_internal_paths) == 1:
path_comp.internalPath = all_internal_paths[0]
parsed_args.prediction_image_paths[
index] = path_comp.totalPath()
elif len(all_internal_paths) == 0:
sys.stderr.write(
"Could not find any datasets in your input file:\n{}\n".
format(input_path))
sys.exit(1)
else:
sys.stderr.write(
"Found more than one dataset in your input file:\n"
"{}\n".format(input_path) +
"Please specify the dataset name, e.g. /path/to/myfile.h5/internal/dataset_name\n"
)
sys.exit(1)
import argparse
# Construct a parser with all the 'normal' export options, and add arg for input_path.
parser = DataExportApplet.make_cmdline_parser( argparse.ArgumentParser() )
parser.add_argument("input_path", help="Path to your exported predictions.")
parsed_args = parser.parse_args()
# As a convenience, auto-determine the internal dataset path if possible.
path_comp = PathComponents(parsed_args.input_path, os.getcwd())
if path_comp.extension in PathComponents.HDF5_EXTS and path_comp.internalDatasetName == "":
with h5py.File(path_comp.externalPath, 'r') as f:
all_internal_paths = all_dataset_internal_paths(f)
if len(all_internal_paths) == 1:
path_comp.internalPath = all_internal_paths[0]
parsed_args.input_path = path_comp.totalPath()
elif len(all_internal_paths) == 0:
sys.stderr.write("Could not find any datasets in your input file.")
sys.exit(1)
else:
sys.stderr.write("Found more than one dataset in your input file.\n"
"Please specify the dataset name, e.g. /path/to/myfile.h5/internal/dataset_name")
sys.exit(1)
# As a convenience, if the user didn't explicitly specify an output file name, provide one for him.
if not parsed_args.output_filename_format:
output_path_comp = copy.copy(path_comp)
output_path_comp.filenameBase += "_Uncertainties"
parsed_args.output_filename_format = output_path_comp.externalPath
if path_comp.extension in PathComponents.HDF5_EXTS and not parsed_args.output_internal_path:
