Python DatasetInfo.nickname方法代码示例

# 需要导入模块: from ilastik.applets.dataSelection.opDataSelection import DatasetInfo [as 别名]
# 或者: from ilastik.applets.dataSelection.opDataSelection.DatasetInfo import nickname [as 别名]
    def _run_export_with_empty_batch_lane(self, role_input_paths, batch_lane_index, template_infos, progress_callback):
        """
        Configure the fresh batch lane with the given input files, and export the results.
        """
        assert role_input_paths[0], "At least one file must be provided for each dataset (the first role)."
        opDataSelectionBatchLaneView = self.dataSelectionApplet.topLevelOperator.getLane( batch_lane_index )

        # Apply new settings for each role
        for role_index, path_for_role in enumerate(role_input_paths):
            if not path_for_role:
                continue

            if template_infos[role_index]:
                info = copy.copy(template_infos[role_index])
            else:
                info = DatasetInfo()

            # Override the template settings with the current filepath.
            default_info = DataSelectionApplet.create_default_headless_dataset_info(path_for_role)
            info.filePath = default_info.filePath
            info.location = default_info.location
            info.nickname = default_info.nickname

            # Apply to the data selection operator
            opDataSelectionBatchLaneView.DatasetGroup[role_index].setValue(info)

        # Make sure nothing went wrong
        opDataExportBatchlaneView = self.dataExportApplet.topLevelOperator.getLane( batch_lane_index )
        assert opDataExportBatchlaneView.ImageToExport.ready()
        assert opDataExportBatchlaneView.ExportPath.ready()
        
        # New lanes were added.
        # Give the workflow a chance to restore anything that was unecessarily invalidated (e.g. classifiers)
        self.workflow.handleNewLanesAdded()
        
        # Call customization hook
        self.dataExportApplet.prepare_lane_for_export(batch_lane_index)

        # Finally, run the export
        logger.info("Exporting to {}".format( opDataExportBatchlaneView.ExportPath.value ))
        opDataExportBatchlaneView.progressSignal.subscribe(progress_callback)
        opDataExportBatchlaneView.run_export()

        # Call customization hook
        self.dataExportApplet.post_process_lane_export(batch_lane_index)

# 需要导入模块: from ilastik.applets.dataSelection.opDataSelection import DatasetInfo [as 别名]
# 或者: from ilastik.applets.dataSelection.opDataSelection.DatasetInfo import nickname [as 别名]
def append_lane(workflow, input_filepath, axisorder=None):
    # Sanity checks
    assert isinstance(workflow, PixelClassificationWorkflow)
    opPixelClassification = workflow.pcApplet.topLevelOperator
    assert opPixelClassification.Classifier.ready()

    # If the filepath is a globstring, convert the stack to h5
    input_filepath = DataSelectionApplet.convertStacksToH5( [input_filepath], TMP_DIR )[0]

    info = DatasetInfo()
    info.location = DatasetInfo.Location.FileSystem
    info.filePath = input_filepath

    comp = PathComponents(input_filepath)

    # Convert all (non-url) paths to absolute 
    # (otherwise they are relative to the project file, which probably isn't what the user meant)        
    if not isUrl(input_filepath):
        comp.externalPath = os.path.abspath(comp.externalPath)
        info.filePath = comp.totalPath()
    info.nickname = comp.filenameBase
    if axisorder:
        info.axistags = vigra.defaultAxistags(axisorder)

    logger.debug( "adding lane: {}".format( info ) )

    opDataSelection = workflow.dataSelectionApplet.topLevelOperator

    # Add a lane
    num_lanes = len( opDataSelection.DatasetGroup )+1
    logger.debug( "num_lanes: {}".format( num_lanes ) )
    opDataSelection.DatasetGroup.resize( num_lanes )
    
    # Configure it.
    role_index = 0 # raw data
    opDataSelection.DatasetGroup[-1][role_index].setValue( info )

    # Sanity check
    assert len(opPixelClassification.InputImages) == num_lanes
    
    return opPixelClassification

# 需要导入模块: from ilastik.applets.dataSelection.opDataSelection import DatasetInfo [as 别名]
# 或者: from ilastik.applets.dataSelection.opDataSelection.DatasetInfo import nickname [as 别名]
        def impl():
            projFilePath = self.project_file
            shell = self.shell

            # New project
            shell.createAndLoadNewProject(projFilePath, self.workflowClass())
            workflow = shell.projectManager.workflow

            # Add our input files:
            opDataSelection = workflow.dataSelectionApplet.topLevelOperator
            opDataSelection.DatasetGroup.resize(1)
            info_raw = DatasetInfo()
            info_raw.filePath = self.sample_data_raw
            opDataSelection.DatasetGroup[0][0].setValue(info_raw)
            info_prob = DatasetInfo()
            info_prob.filePath = self.sample_data_prob
            info_raw.nickname = 'test_data'
            opDataSelection.DatasetGroup[0][1].setValue(info_prob)

            # Save
            shell.projectManager.saveProject()

# 需要导入模块: from ilastik.applets.dataSelection.opDataSelection import DatasetInfo [as 别名]
# 或者: from ilastik.applets.dataSelection.opDataSelection.DatasetInfo import nickname [as 别名]
def append_lane(workflow, input_filepath, axisorder=None):
    """
    Add a lane to the project file for the given input file.

    If axisorder is given, override the default axisorder for
    the file and force the project to use the given one.
    
    Globstrings are supported, in which case the files are converted to HDF5 first.
    """
    # If the filepath is a globstring, convert the stack to h5
    input_filepath = DataSelectionApplet.convertStacksToH5( [input_filepath], tempfile.mkdtemp() )[0]

    info = DatasetInfo()
    info.location = DatasetInfo.Location.FileSystem
    info.filePath = input_filepath

    comp = PathComponents(input_filepath)

    # Convert all (non-url) paths to absolute 
    # (otherwise they are relative to the project file, which probably isn't what the user meant)        
    if not isUrl(input_filepath):
        comp.externalPath = os.path.abspath(comp.externalPath)
        info.filePath = comp.totalPath()
    info.nickname = comp.filenameBase
    if axisorder:
        info.axistags = vigra.defaultAxistags(axisorder)

    logger.debug( "adding lane: {}".format( info ) )

    opDataSelection = workflow.dataSelectionApplet.topLevelOperator

    # Add a lane
    num_lanes = len( opDataSelection.DatasetGroup )+1
    logger.debug( "num_lanes: {}".format( num_lanes ) )
    opDataSelection.DatasetGroup.resize( num_lanes )
    
    # Configure it.
    role_index = 0 # raw data
    opDataSelection.DatasetGroup[-1][role_index].setValue( info )