c3683a34715651da553fda70ab50c1c0c2c63e41,ilastik/workflows/pixelClassification/pixelClassificationWorkflow.py,PixelClassificationWorkflow,onProjectLoaded,#PixelClassificationWorkflow#Any#,397

Before Change

            self.pcApplet.topLevelOperator.FreezePredictions.setValue(False)
        
            // Now run the batch export and report progress....
            opBatchDataExport = self.batchResultsApplet.topLevelOperator
            for i, opExportDataLaneView in enumerate(opBatchDataExport):
                logger.info( "Exporting result {} to {}".format(i, opExportDataLaneView.ExportPath.value) )
    
                sys.stdout.write( "Result {}/{} Progress: ".format( i, len( opBatchDataExport ) ) )
                sys.stdout.flush()
                def print_progress( progress ):
                    sys.stdout.write( "{} ".format( progress ) )
                    sys.stdout.flush()
    
                // If the operator provides a progress signal, use it.
                slotProgressSignal = opExportDataLaneView.progressSignal
                slotProgressSignal.subscribe( print_progress )
                opExportDataLaneView.run_export()
                
                // Finished.
                sys.stdout.write("\n")


    def _print_labels_by_slice(self, search_value):
        
        Iterate over each label image in the project and print the number of labels present on each Z-slice of the image.
        (This is a special feature requested by the FlyEM proofreaders.)

After Change

            logger.warn("Your project file has no classifier.  A new classifier will be trained for this run.")

        if self._headless and self._batch_input_args and self._batch_export_args:
            logger.info("Beginning Batch Processing")
            self.batchProcessingApplet.run_export(self._batch_input_args)
            logger.info("Completed Batch Processing")

    def _print_labels_by_slice(self, search_value):

Instances