def mainFunction(self): # fix random seed from ilastik.core.randomSeed import RandomSeed RandomSeed.setRandomSeed(42) self.testThread = TestThread(self.testProject.unsupervisedMgr, self.testProject.listOfResultOverlays, self.testProject.listOfFilenames, self.testProject.tolerance) QtCore.QObject.connect(self.testThread, QtCore.SIGNAL('done()'), self.finalizeTest) self.testThread.start(self.testProject.inputOverlays) self.numOverlaysBefore = len(self.testProject.dataMgr[self.testProject.dataMgr._activeImageNumber].overlayMgr.keys())
def mainFunction(self): # fix random seed from ilastik.core.randomSeed import RandomSeed RandomSeed.setRandomSeed(42) self.testThread = TestThread(self.testProject.unsupervisedMgr, self.testProject.listOfResultOverlays, self.testProject.listOfFilenames, self.testProject.tolerance) QtCore.QObject.connect(self.testThread, QtCore.SIGNAL('done()'), self.finalizeTest) self.testThread.start(self.testProject.inputOverlays) self.numOverlaysBefore = len(self.testProject.dataMgr[ self.testProject.dataMgr._activeImageNumber].overlayMgr.keys())
def __init__(self, image_filename, borderOverlay_filename, groundtruth_filename): self.image_filename = image_filename self.borderOverlay_filename = borderOverlay_filename self.groundtruth_filename = groundtruth_filename self.testdir = ilastikpath[0] + "/testdata/automatic_segmentation/" # fix random seed from ilastik.core.randomSeed import RandomSeed RandomSeed.setRandomSeed(42) # create project self.project = Project('Project Name', 'Labeler', 'Description') self.dataMgr = self.project.dataMgr # create file list and load data path = str(self.testdir + self.image_filename) # the image is not really used since we load the threshold overlay from a file, however, we need it to set the correct dimensions fileList = [] fileList.append(path) self.project.addFile(fileList) # create automatic segmentation manager self.automaticSegmentationMgr = AutomaticSegmentationModuleMgr(self.dataMgr) # setup inputs self.inputOverlays = [] self.inputOverlays.append(self.dataMgr[self.dataMgr._activeImageNumber].overlayMgr["Raw Data"]) # calculate segmentation results # ...import border indicator self.border_indicator_ov = dataImpex.DataImpex.importOverlay(self.dataMgr[self.dataMgr._activeImageNumber], str(self.testdir + borderOverlay_filename), "") self.input = self.border_indicator_ov._data[0,:,:,:,0] # ...normalize it self.input = self.automaticSegmentationMgr.normalizePotential(self.input) # ...invert it twice, this should give us the original again :-) self.input = self.automaticSegmentationMgr.invertPotential(self.input) self.input = self.automaticSegmentationMgr.invertPotential(self.input) # overlay lists and filenames self.listOfResultOverlays = [] self.listOfFilenames = [] self.listOfResultOverlays.append("Auto Segmentation/Segmentation") self.listOfFilenames.append(self.testdir + self.groundtruth_filename)