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: