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)
