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 createDefaultColorTable(cls,
type,
levels=256,
transparentValues=set()):
typeCap = type.capitalize()
colorTab = []
if (typeCap == "GRAY"):
for i in range(levels):
if i in transparentValues:
colorTab.append(0L)
else:
colorTab.append(OverlayItem.qgray(
i, i, i)) # see qGray function in QtGui
else:
#RGB
import numpy
from ilastik.core.randomSeed import RandomSeed
seed = RandomSeed.getRandomSeed()
if seed is not None:
numpy.random.seed(seed)
for i in range(levels):
if i in transparentValues:
colorTab.append(0L)
else:
colorTab.append(
OverlayItem.qrgb(
numpy.random.randint(255),
numpy.random.randint(255), numpy.random.randint(
255))) # see gRGB function in QtGui
return colorTab
def createDefault16ColorColorTable(cls):
sublist = []
sublist.append(OverlayItem.qrgb(69, 69, 69)) # dark grey
sublist.append(OverlayItem.qrgb(255, 0, 0))
sublist.append(OverlayItem.qrgb(0, 255, 0))
sublist.append(OverlayItem.qrgb(0, 0, 255))
sublist.append(OverlayItem.qrgb(255, 255, 0))
sublist.append(OverlayItem.qrgb(0, 255, 255))
sublist.append(OverlayItem.qrgb(255, 0, 255))
sublist.append(OverlayItem.qrgb(255, 105, 180)) #hot pink!
sublist.append(OverlayItem.qrgb(102, 205, 170)) #dark aquamarine
sublist.append(OverlayItem.qrgb(165, 42, 42)) #brown
sublist.append(OverlayItem.qrgb(0, 0, 128)) #navy
sublist.append(OverlayItem.qrgb(255, 165, 0)) #orange
sublist.append(OverlayItem.qrgb(173, 255, 47)) #green-yellow
sublist.append(OverlayItem.qrgb(128,0, 128)) #purple
sublist.append(OverlayItem.qrgb(192, 192, 192)) #silver
sublist.append(OverlayItem.qrgb(240, 230, 140)) #khaki
colorlist = []
colorlist.append(long(0))
colorlist.extend(sublist)
import numpy
from ilastik.core.randomSeed import RandomSeed
seed = RandomSeed.getRandomSeed()
if seed is not None:
numpy.random.seed(seed)
for i in range(17, 256):
color = OverlayItem.qrgb(numpy.random.randint(255),numpy.random.randint(255),numpy.random.randint(255))
colorlist.append(color)
return colorlist
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)
def decompose(self,
features): # features are of dimension NUMVOXELSxNUMFEATURES
# sanity checks
self.numComponents = self.checkNumComponents(features.shape[1],
self.numComponents)
# random seed
from ilastik.core.randomSeed import RandomSeed
seed = RandomSeed.getRandomSeed()
if seed is not None:
numpy.random.seed(seed)
features = features.T
numFeatures, numVoxels = features.shape # this should be the shape of features!
# initialize result matrices
# features/hidden and hidden/pixels
FZ = self.normalizeColumn(
numpy.random.random((numFeatures, self.numComponents)))
ZV = self.normalizeColumn(
numpy.random.random((self.numComponents, numVoxels)))
# init vars
lastChange = 1 / numpy.finfo(float).eps
err = 0
iteration = 0
# expectation maximization (EM) algorithm
voxelSums = numpy.sum(features, 0)
FZV = numpy.dot(FZ, ZV) # pre-calculate
while (lastChange > self.minRelGain
and iteration < self.maxIterations):
if (numpy.mod(iteration, 25) == 0):
print "iteration %d" % iteration
print "last relative change %f" % lastChange
factor = features / (FZV + numpy.finfo(float).eps)
ZV = self.normalizeColumn(ZV * numpy.dot(FZ.T, factor))
FZ = self.normalizeColumn(FZ * numpy.dot(factor, ZV.T))
FZV = numpy.dot(FZ, ZV) # pre-calculate
# check relative change in least squares model fit
model = numpy.tile(voxelSums, (numFeatures, 1)) * FZV
error_old = err
err = numpy.sum((features - model)**2)
lastChange = numpy.abs(
(err - error_old) / (numpy.finfo(float).eps + err))
iteration = iteration + 1
return FZ, ZV
def createDefaultColorTable(cls, type, levels = 256, transparentValues = set()):
typeCap = type.capitalize()
colorTab = []
if(typeCap == "GRAY"):
for i in range(levels):
if i in transparentValues:
colorTab.append(0L)
else:
colorTab.append(OverlayItem.qgray(i, i, i)) # see qGray function in QtGui
else:
#RGB
import numpy
from ilastik.core.randomSeed import RandomSeed
seed = RandomSeed.getRandomSeed()
if seed is not None:
numpy.random.seed(seed)
for i in range(levels):
if i in transparentValues:
colorTab.append(0L)
else:
colorTab.append(OverlayItem.qrgb(numpy.random.randint(255),numpy.random.randint(255),numpy.random.randint(255))) # see gRGB function in QtGui
return colorTab
def decompose(self, features): # features are of dimension NUMVOXELSxNUMFEATURES
# sanity checks
self.numComponents = self.checkNumComponents(features.shape[1], self.numComponents)
# random seed
from ilastik.core.randomSeed import RandomSeed
seed = RandomSeed.getRandomSeed()
if seed is not None:
numpy.random.seed(seed)
features = features.T
numFeatures, numVoxels = features.shape # this should be the shape of features!
# initialize result matrices
# features/hidden and hidden/pixels
FZ = self.normalizeColumn(numpy.random.random((numFeatures, self.numComponents)))
ZV = self.normalizeColumn(numpy.random.random((self.numComponents, numVoxels)))
# init vars
lastChange = 1/numpy.finfo(float).eps
err = 0;
iteration = 0;
# expectation maximization (EM) algorithm
voxelSums = numpy.sum(features, 0)
FZV = numpy.dot(FZ, ZV) # pre-calculate
while(lastChange > self.minRelGain and iteration < self.maxIterations):
if(numpy.mod(iteration, 25)==0):
print "iteration %d" % iteration
print "last relative change %f" % lastChange
factor = features / (FZV + numpy.finfo(float).eps)
ZV = self.normalizeColumn(ZV * numpy.dot(FZ.T, factor))
FZ = self.normalizeColumn(FZ * numpy.dot(factor, ZV.T))
FZV = numpy.dot(FZ, ZV) # pre-calculate
# check relative change in least squares model fit
model = numpy.tile(voxelSums, (numFeatures, 1)) * FZV
error_old = err;
err = numpy.sum((features - model)**2)
lastChange = numpy.abs((err - error_old)/(numpy.finfo(float).eps+err))
iteration = iteration + 1;
return FZ, ZV
def createDefault16ColorColorTable(cls):
sublist = []
sublist.append(OverlayItem.qrgb(69, 69, 69)) # dark grey
sublist.append(OverlayItem.qrgb(255, 0, 0))
sublist.append(OverlayItem.qrgb(0, 255, 0))
sublist.append(OverlayItem.qrgb(0, 0, 255))
sublist.append(OverlayItem.qrgb(255, 255, 0))
sublist.append(OverlayItem.qrgb(0, 255, 255))
sublist.append(OverlayItem.qrgb(255, 0, 255))
sublist.append(OverlayItem.qrgb(255, 105, 180)) #hot pink!
sublist.append(OverlayItem.qrgb(102, 205, 170)) #dark aquamarine
sublist.append(OverlayItem.qrgb(165, 42, 42)) #brown
sublist.append(OverlayItem.qrgb(0, 0, 128)) #navy
sublist.append(OverlayItem.qrgb(255, 165, 0)) #orange
sublist.append(OverlayItem.qrgb(173, 255, 47)) #green-yellow
sublist.append(OverlayItem.qrgb(128, 0, 128)) #purple
sublist.append(OverlayItem.qrgb(192, 192, 192)) #silver
sublist.append(OverlayItem.qrgb(240, 230, 140)) #khaki
colorlist = []
colorlist.append(long(0))
colorlist.extend(sublist)
import numpy
from ilastik.core.randomSeed import RandomSeed
seed = RandomSeed.getRandomSeed()
if seed is not None:
numpy.random.seed(seed)
for i in range(17, 256):
color = OverlayItem.qrgb(numpy.random.randint(255),
numpy.random.randint(255),
numpy.random.randint(255))
colorlist.append(color)
return colorlist
painter.begin(splashImage)
painter.drawText(QtCore.QPointF(270, 110), ilastik.core.readInBuildInfo())
painter.end()
splashScreen = QtGui.QSplashScreen(splashImage)
splashScreen.show()
app.processEvents()
ilastik.modules.loadModuleGuis()
mainwindow = MainWindow(sys.argv)
mainwindow.setStyleSheet("QSplitter::handle { background-color: #CCCCCC;}")
mainwindow.show()
#On OS X, the window has to be raised in order to be visible directly after starting
#the app
mainwindow.raise_()
splashScreen.finish(mainwindow)
randomseed = RandomSeed()
app.exec_()
print "cleaning up..."
if mainwindow.labelWidget is not None:
del mainwindow.labelWidget
del mainwindow
del randomseed
del ilastik.core.jobMachine.GLOBAL_WM
