def dialog(imp2, labelColorBarImp):
gd = GenericDialogPlus("ROI labeller")
categories=11
#placeholder slider variables so the class can be initiated
slider1=0
slider2=0
slider3=0
slider4=0
test=previewLabelerAndListeners(imp2, slider1,slider2,slider3,slider4, gd)
for i in range(1,categories):
gd.addButton("label "+str(i), test)
gd.addImage(labelColorBarImp)
#imp7.close() - causes an error as image needed for the dialog
gd.addButton("Set top",test)
gd.addButton("Whole stack",test)
gd.addButton("Set bottom", test)
gd.addSlider("Top",1, imp2.getStackSize(), 1)
gd.addSlider("Bottom",1, imp2.getStackSize(),imp2.getStackSize())
gd.addSlider("Minimum ROI size", 0, 9999, 0, 1)
gd.addSlider("Maximum ROI size", 1, 10000, 10000, 1)
slider1=gd.getSliders().get(0)
slider2=gd.getSliders().get(1)
test.slider1=slider1
test.slider2=slider2
slider3=gd.getSliders().get(2)
slider4=gd.getSliders().get(3)
test.slider3=slider3
test.slider4=slider4
slider1.addAdjustmentListener(test)
slider2.addAdjustmentListener(test)
slider3.addAdjustmentListener(test)
slider4.addAdjustmentListener(test)
gd.addChoice("Apply labeling to:", ["(Sub)stack", "Slice"], "(Sub)stack")
gd.setLayout(GridLayout(0,2))
gd.setModal(False)
buttons=gd.getButtons()
gd.showDialog()
while ((not gd.wasCanceled()) and not (gd.wasOKed())):
Thread.sleep(50)
return test
def previewDialog(imp):
gd = GenericDialogPlus("Nuclear segmentation and quantification v1.01")
#create a list of the channels in the provided imagePlus
types = []
for i in xrange(1, imp.getNChannels() + 1):
types.append(str(i))
#user can pick which channel to base the segmentation on
gd.addChoice("Channel number to use for segmentation", types, types[0])
gd.addChoice("Channel to quantify", types, types[0])
methods = [
"Otsu", "Default", "Huang", "Intermodes", "IsoData", "IJ_IsoData",
"Li", "MaxEntropy", "Mean", "MinError", "Minimum", "Moments",
"Percentile", "RenyiEntropy", "Shanbhag", "Triangle", "Yen"
]
gd.addChoice("Autosegmentation method", methods, methods[0])
intensities = ["254", "4094", "65534"]
gd.addChoice("Max Intensity", intensities, intensities[-1])
gd.addSlider("Small DoG sigma", 0.5, 10, 1, 0.1)
gd.addSlider("Large DoG sigma", 0.5, 20, 5, 0.1)
gd.addCheckbox("TopHat background subtraction? (Slower, but better) ",
True)
gd.addSlider("TopHat sigma", 5, 20, 8, 0.1)
gd.setModal(False)
gd.addCheckbox("Manually set threshold? ", False)
gd.addSlider("Manual threshold", 10, 65534, 2000, 1)
gd.hideCancelButton()
gd.showDialog()
cal = imp.getCalibration()
pixelAspect = (cal.pixelDepth / cal.pixelWidth)
originalTitle = imp1.getTitle()
choices = gd.getChoices()
print choices
sliders = gd.getSliders()
checkboxes = gd.getCheckboxes()
segmentChannel = int(choices.get(0).getSelectedItem())
quantChannel = int(choices.get(1).getSelectedItem())
thresholdMethod = choices.get(2).getSelectedItem()
maxIntensity = int(choices.get(3).getSelectedItem())
gaussianSigma = sliders.get(0).getValue() / 10.0
largeDoGSigma = gd.sliders.get(1).getValue() / 10.0
topHat = gd.checkboxes.get(0).getState()
topHatSigma = gd.sliders.get(2).getValue() / 10.0
manualSegment = gd.checkboxes.get(1).getState()
manualThreshold = gd.sliders.get(3).getValue()
segmentChannelOld = segmentChannel
thresholdMethodOld = thresholdMethod
maxIntensityOld = maxIntensity
gaussianSigmaOld = gaussianSigma
largeDoGSigmaOld = largeDoGSigma
topHatOld = topHat
topHatSigmaOld = topHatSigma
manualSegmentOld = manualSegment
manualThresholdOld = manualThreshold
clij2.clear()
segmentImp = extractChannel(imp1, segmentChannel, 0)
try:
gfx1 = clij2.push(segmentImp)
gfx2 = clij2.create(gfx1)
gfx3 = clij2.create(gfx1)
gfx4 = clij2.create(gfx1)
gfx5 = clij2.create(gfx1)
gfx7 = clij2.create([imp.getWidth(), imp.getHeight()])
except:
try:
Thread.sleep(500)
IJ.log(
"Succeeded to sending to graphics card on the second time...")
gfx1 = clij2.push(segmentImp)
gfx2 = clij2.create(gfx1)
gfx3 = clij2.create(gfx1)
gfx4 = clij2.create(gfx1)
gfx5 = clij2.create(gfx1)
gfx7 = clij2.create([imp.getWidth(), imp.getHeight()])
except:
errorDialog(
"""Could not send image to graphics card, it may be too large!
Easy solutions: Try processing as 8-bit, cropping or scaling the image, or
select a different CLIJ2 GPU.
This issue is often intermittent, so trying again may also work!
See the "Big Images on x graphics cards' notes at:
https://clij2.github.io/clij2-docs/troubleshooting for more solutions
""" + str(clij2.reportMemory()))
gfx1, gfx2, gfx3, gfx4, gfx5 = segment(gfx1, gfx2, gfx3, gfx4, gfx5,
gaussianSigma, thresholdMethod,
maxIntensity, largeDoGSigma,
pixelAspect, originalTitle, topHat,
topHatSigma, manualSegment,
manualThreshold)
clij2.maximumZProjection(gfx5, gfx7)
labelPrevImp = clij2.pull(gfx7)
IJ.setMinAndMax(labelPrevImp, 0, clij2.getMaximumOfAllPixels(gfx7))
labelPrevImp.setTitle("Preview segmentation")
labelPrevImp.show()
IJ.run("glasbey_inverted")
while ((not gd.wasCanceled()) and not (gd.wasOKed())):
segmentChannel = int(choices.get(0).getSelectedItem())
quantChannel = int(choices.get(1).getSelectedItem())
thresholdMethod = choices.get(2).getSelectedItem()
maxIntensity = int(choices.get(3).getSelectedItem())
gaussianSigma = sliders.get(0).getValue() / 10.0
largeDoGSigma = gd.sliders.get(1).getValue() / 10.0
topHat = gd.checkboxes.get(0).getState()
topHatSigma = gd.sliders.get(2).getValue() / 10.0
manualSegment = gd.checkboxes.get(1).getState()
manualThreshold = gd.sliders.get(3).getValue()
if (segmentChannelOld != segmentChannel
or thresholdMethodOld != thresholdMethod
or maxIntensityOld != maxIntensity
or gaussianSigmaOld != gaussianSigma
or largeDoGSigmaOld != largeDoGSigma or topHatOld != topHat
or topHatSigmaOld != topHatSigma
or manualSegmentOld != manualSegment
or manualThresholdOld != manualThreshold):
if segmentChannelOld != segmentChannel:
clij2.clear()
segmentImp = extractChannel(imp1, segmentChannel, 0)
gfx1 = clij2.push(segmentImp)
gfx2 = clij2.create(gfx1)
gfx3 = clij2.create(gfx1)
gfx4 = clij2.create(gfx1)
gfx5 = clij2.create(gfx1)
gfx7 = clij2.create([imp.getWidth(), imp.getHeight()])
gfx1, gfx2, gfx3, gfx4, gfx5 = segment(
gfx1, gfx2, gfx3, gfx4, gfx5, gaussianSigma, thresholdMethod,
maxIntensity, largeDoGSigma, pixelAspect, originalTitle,
topHat, topHatSigma, manualSegment, manualThreshold)
clij2.maximumZProjection(gfx5, gfx7)
labelPrevImp.close()
labelPrevImp = clij2.pull(gfx7)
IJ.setMinAndMax(labelPrevImp, 0, clij2.getMaximumOfAllPixels(gfx7))
labelPrevImp.setTitle("Preview segmentation")
labelPrevImp.show()
IJ.run("glasbey_inverted")
segmentChannelOld = segmentChannel
thresholdMethodOld = thresholdMethod
maxIntensityOld = maxIntensity
gaussianSigmaOld = gaussianSigma
largeDoGSigmaOld = largeDoGSigma
topHatOld = topHat
topHatSigmaOld = topHatSigma
manualSegmentOld = manualSegment
manualThresholdOld = manualThreshold
Thread.sleep(200)
labelPrevImp.close()
return segmentChannel, quantChannel, thresholdMethod, maxIntensity, gaussianSigma, largeDoGSigma, topHat, topHatSigma, manualSegment, manualThreshold
gdp.addMessage("Rigid transform");
gdp.addCheckbox("Do rigid transformation", formerDoRigidTransform);
gdp.addSlider("Translation X (in pixel)", -100, 100, formerTranslationX);
gdp.addSlider("Translation Y (in pixel)", -100, 100, formerTranslationY);
gdp.addSlider("Translation Z (in pixel)", -100, 100, formerTranslationZ);
gdp.addSlider("Rotation X (in degrees)", -180, 180, formerRotationX);
gdp.addSlider("Rotation Y (in degrees)", -180, 180, formerRotationY);
gdp.addSlider("Rotation Z (in degrees)", -180, 180, formerRotationZ);
gdp.addMessage("Spot detection")
gdp.addCheckbox("Do spot detection", formerDoSpotDetection);
gdp.addSlider("Tolerance", 0, 100, formerTolerance);
gdp.addSlider("Threshold", 0, 100, formerThreshold);
gdp.setModal(False);
gdp.showDialog();
doNoiseAndBackgroundRemovalCheckbox = gdp.getCheckboxes().get(0);
sigma1Slider = gdp.getSliders().get(0);
sigma2Slider = gdp.getSliders().get(1);
doRigidTransformCheckbox = gdp.getCheckboxes().get(1);
translationXSlider = gdp.getSliders().get(2);
translationYSlider = gdp.getSliders().get(3);
translationZSlider = gdp.getSliders().get(4);
rotationXSlider = gdp.getSliders().get(5);
rotationYSlider = gdp.getSliders().get(6);
rotationZSlider = gdp.getSliders().get(7);
doSpotDetectionCheckbox = gdp.getCheckboxes().get(2);
toleranceSlider = gdp.getSliders().get(8);
thresholdSlider = gdp.getSliders().get(9);
gdp.addCheckbox("Do rigid transformation", formerDoRigidTransform)
gdp.addSlider("Translation X (in pixel)", -100, 100, formerTranslationX)
gdp.addSlider("Translation Y (in pixel)", -100, 100, formerTranslationY)
gdp.addSlider("Translation Z (in pixel)", -100, 100, formerTranslationZ)
gdp.addSlider("Rotation X (in degrees)", -180, 180, formerRotationX)
gdp.addSlider("Rotation Y (in degrees)", -180, 180, formerRotationY)
gdp.addSlider("Rotation Z (in degrees)", -180, 180, formerRotationZ)
gdp.addMessage("Spot detection")
gdp.addCheckbox("Do spot detection", formerDoSpotDetection)
gdp.addSlider("Tolerance", 0, 100, formerTolerance)
gdp.addSlider("Threshold", 0, 100, formerThreshold)
gdp.setModal(False)
gdp.showDialog()
doNoiseAndBackgroundRemovalCheckbox = gdp.getCheckboxes().get(0)
sigma1Slider = gdp.getSliders().get(0)
sigma2Slider = gdp.getSliders().get(1)
doRigidTransformCheckbox = gdp.getCheckboxes().get(1)
translationXSlider = gdp.getSliders().get(2)
translationYSlider = gdp.getSliders().get(3)
translationZSlider = gdp.getSliders().get(4)
rotationXSlider = gdp.getSliders().get(5)
rotationYSlider = gdp.getSliders().get(6)
rotationZSlider = gdp.getSliders().get(7)
doSpotDetectionCheckbox = gdp.getCheckboxes().get(2)
toleranceSlider = gdp.getSliders().get(8)
thresholdSlider = gdp.getSliders().get(9)
def previewDialog(imp):
gd = GenericDialogPlus("FRETENATOR")
#create a list of the channels in the provided imagePlus
types = []
for i in xrange(1, imp.getNChannels()+1):
types.append(str(i))
gd.addMessage("""Rowe, J. H, Rizza, A., Jones A. M. (2022) Quantifying phytohormones
in vivo with FRET biosensors and the FRETENATOR analysis toolset
Methods in Molecular Biology
Rowe, JH., Grangé-Guermente, M., Exposito-Rodriguez, M.,Wimalasekera, R., Lenz, M.,
Shetty, K., Cutler, S., Jones, AM., Next-generation ABACUS biosensors reveal cellular
ABA dynamics driving root growth at low aerial humidity
""")
#user can pick which channel to base the segmentation on
if len(types)>2:
gd.addChoice("Channel number to use for segmentation", types, types[2])
gd.addChoice("Channel number to use for donor", types, types[0])
gd.addChoice("Channel number to use for acceptor (FRET)", types, types[1])
gd.addChoice("Channel number to use for acceptor", types, types[2])
#print('YAY')
else:
gd.addChoice("Channel number to use for segmentation", types, types[-1])
gd.addChoice("Channel number to use for donor", types, types[0])
gd.addChoice("Channel number to use for acceptor (FRET)", types, types[-2])
gd.addChoice("Channel number to use for acceptor", types, types[-1])
methods=["Otsu","Default", "Huang", "Intermodes", "IsoData", "IJ_IsoData", "Li", "MaxEntropy", "Mean", "MinError", "Minimum", "Moments", "Percentile", "RenyiEntropy", "Shanbhag", "Triangle", "Yen"]
gd.addChoice("Autosegmentation method", methods, methods[0])
intensities=["254", "4094", "65534"]
gd.addChoice("Max Intensity", intensities, intensities[-1])
gd.addSlider("Small DoG sigma", 0.5, 10, 0.8, 0.1)
gd.addSlider("Large DoG sigma", 0.5, 20, 4 ,0.1)
gd.addCheckbox("TopHat background subtraction? (Slower, but better) ", False)
gd.addSlider("TopHat sigma", 5, 20, 8 ,0.1)
gd.setModal(False)
gd.addCheckbox("Manually set threshold? ", False)
gd.addSlider("Manual threshold", 10, 65534, 2000, 1)
dilationOptions=["0", "1", "2","3", "4", "5", "6"]
gd.addChoice("Dilation?", dilationOptions, "0")
gd.addCheckbox("Size exclusion of ROI? ", False)
gd.addSlider("Minimum ROI size", 0, 9999, 20, 1)
gd.addSlider("Maximum ROI size", 1, 10000, 10000, 1)
gd.addCheckbox("Create nearest point projection with outlines (SLOW)? ", True)
gd.addCheckbox("Watershed object splitting? ", True)
gd.showDialog()
cal = imp.getCalibration()
pixelAspect=(cal.pixelDepth/cal.pixelWidth)
originalTitle=imp1.getTitle()
choices=gd.getChoices()
sliders=gd.getSliders()
checkboxes=gd.getCheckboxes()
segmentChannel=int(choices.get(0).getSelectedItem())
donorChannel=int(choices.get(1).getSelectedItem())
acceptorChannel=int(choices.get(2).getSelectedItem())
acceptorChannel2=int(choices.get(3).getSelectedItem())
thresholdMethod=choices.get(4).getSelectedItem()
maxIntensity=int(choices.get(5).getSelectedItem())
gaussianSigma=sliders.get(0).getValue()/10.0
largeDoGSigma = gd.sliders.get(1).getValue()/10.0
topHat=gd.checkboxes.get(0).getState()
topHatSigma=gd.sliders.get(2).getValue()/10.0
manualSegment = gd.checkboxes.get(1).getState()
manualThreshold=gd.sliders.get(3).getValue()
dilation=int(choices.get(6).getSelectedItem())
sizeExclude=gd.checkboxes.get(2).getState()
minSize = gd.sliders.get(4).getValue()
maxSize = gd.sliders.get(5).getValue()
watershed = gd.checkboxes.get(4).getState()
#print dir(gd.sliders.get(5))
#print maxSize
segmentChannelOld=segmentChannel
thresholdMethodOld=thresholdMethod
maxIntensityOld=maxIntensity
gaussianSigmaOld=gaussianSigma
largeDoGSigmaOld= largeDoGSigma
topHatOld=topHat
topHatSigmaOld=topHatSigma
manualSegmentOld= manualSegment
manualThresholdOld=manualThreshold
dilationOld=dilation
sizeExcludeOld=sizeExclude
minSizeOld=minSize
maxSizeOld=maxSize
watershedOld=watershed
clij2.clear()
segmentImp=extractChannel(imp1, segmentChannel, 0)
try:
gfx1=clij2.push(segmentImp)
gfx2=clij2.create(gfx1)
gfx3=clij2.create(gfx1)
gfx4=clij2.create(gfx1)
gfx5=clij2.create(gfx1)
gfx7=clij2.create([imp.getWidth(), imp.getHeight()])
except:
try:
Thread.sleep(500)
print("Succeeded to sending to graphics card on the second time...")
gfx1=clij2.push(segmentImp)
gfx2=clij2.create(gfx1)
gfx3=clij2.create(gfx1)
gfx4=clij2.create(gfx1)
gfx5=clij2.create(gfx1)
gfx7=clij2.create([imp.getWidth(), imp.getHeight()])
except:
errorDialog("""Could not send image to graphics card, it may be too large!
Easy solutions: Try processing as 8-bit, cropping or scaling the image, or
select a different CLIJ2 GPU.
This issue is often intermittent, so trying again may also work!
See the "Big Images on x graphics cards' notes at:
https://clij2.github.io/clij2-docs/troubleshooting for more solutions
""" + str(clij2.reportMemory()) )
gfx1,gfx2,gfx3,gfx4,gfx5 = segment(gfx1,gfx2,gfx3,gfx4,gfx5, gaussianSigma, thresholdMethod,maxIntensity, largeDoGSigma, pixelAspect, originalTitle, topHat, topHatSigma , manualSegment, manualThreshold, dilation,sizeExclude, minSize, maxSize, watershed)
clij2.maximumZProjection(gfx5, gfx7)
labelPrevImp= clij2.pull(gfx7)
IJ.setMinAndMax(labelPrevImp, 0,clij2.getMaximumOfAllPixels(gfx7))
labelPrevImp.setTitle("Preview segmentation")
labelPrevImp.show()
IJ.run("glasbey_inverted")
while ((not gd.wasCanceled()) and not (gd.wasOKed())):
segmentChannel=int(choices.get(0).getSelectedItem())
donorChannel=int(choices.get(1).getSelectedItem())
acceptorChannel=int(choices.get(2).getSelectedItem())
acceptorChannel2=int(choices.get(3).getSelectedItem())
thresholdMethod=choices.get(4).getSelectedItem()
maxIntensity=int(choices.get(5).getSelectedItem())
gaussianSigma=sliders.get(0).getValue()/10.0
largeDoGSigma = gd.sliders.get(1).getValue()/10.0
topHat=gd.checkboxes.get(0).getState()
topHatSigma=gd.sliders.get(2).getValue()/10.0
manualSegment = gd.checkboxes.get(1).getState()
manualThreshold = gd.sliders.get(3).getValue()
dilation=int(choices.get(6).getSelectedItem())
sizeExclude=gd.checkboxes.get(2).getState()
minSize = gd.sliders.get(4).getValue()
maxSize = gd.sliders.get(5).getValue()
watershed = gd.checkboxes.get(4).getState()
if (segmentChannelOld !=segmentChannel or
thresholdMethodOld !=thresholdMethod or
maxIntensityOld !=maxIntensity or
gaussianSigmaOld !=gaussianSigma or
largeDoGSigmaOld != largeDoGSigma or
topHatOld !=topHat or
topHatSigmaOld !=topHatSigma or
manualSegmentOld != manualSegment or
manualThresholdOld !=manualThreshold or
dilation != dilationOld or
sizeExcludeOld!=sizeExclude or
minSizeOld!=minSize or
maxSizeOld!=maxSize or
watershedOld!=watershed
):
if minSizeOld!=minSize:
if minSize>=maxSize:
maxSize=minSize+1
gd.sliders.get(5).setValue(maxSize)
if maxSizeOld!=maxSize:
if minSize>=maxSize:
minSize=maxSize-1
gd.sliders.get(4).setValue(minSize)
if segmentChannelOld!=segmentChannel:
clij2.clear()
segmentImp=extractChannel(imp1, segmentChannel, 0)
gfx1=clij2.push(segmentImp)
gfx2=clij2.create(gfx1)
gfx3=clij2.create(gfx1)
gfx4=clij2.create(gfx1)
gfx5=clij2.create(gfx1)
gfx7=clij2.create([imp.getWidth(), imp.getHeight()])
gfx1,gfx2,gfx3,gfx4,gfx5 = segment(gfx1,gfx2,gfx3,gfx4,gfx5, gaussianSigma, thresholdMethod,maxIntensity, largeDoGSigma, pixelAspect, originalTitle, topHat,topHatSigma, manualSegment, manualThreshold, dilation,sizeExclude, minSize, maxSize, watershed)
clij2.maximumZProjection(gfx5, gfx7)
labelPrevImp.close()
labelPrevImp= clij2.pull(gfx7)
IJ.setMinAndMax(labelPrevImp, 0,clij2.getMaximumOfAllPixels(gfx7))
labelPrevImp.setTitle("Preview segmentation")
labelPrevImp.show()
IJ.run("glasbey_inverted")
segmentChannelOld=segmentChannel
thresholdMethodOld=thresholdMethod
maxIntensityOld=maxIntensity
gaussianSigmaOld=gaussianSigma
largeDoGSigmaOld = largeDoGSigma
topHatOld=topHat
topHatSigmaOld=topHatSigma
manualSegmentOld= manualSegment
manualThresholdOld=manualThreshold
dilationOld=dilation
sizeExcludeOld=sizeExclude
minSizeOld=minSize
maxSizeOld=maxSize
watershedOld=watershed
Thread.sleep(200)
labelPrevImp.close()
makeNearProj = gd.checkboxes.get(3).getState()
return segmentChannel, donorChannel, acceptorChannel, acceptorChannel2, thresholdMethod, maxIntensity, gaussianSigma, largeDoGSigma, topHat, topHatSigma, manualSegment, manualThreshold, makeNearProj, dilation, sizeExclude, minSize, maxSize, watershed
