def openMainDialogBox():
#od = OpenDialog("Selectionner un fichier")
#folder = od.getDirectory()
#IJ.log(folder);
#filename = od.getFileName() #intérêt de récupérer le nom du fichier -> récupérer l'extension
#extension = od.getFileName().split('.').pop() #Array.pop(). Pratique pour faire une fonction getExtension()
#IJ.log(folder+filename)
# Create an instance of GenericDialogPlus
mainDialogBox = GenericDialogPlus("Restack Tiff deconvolved images from Huygens")
mainDialogBox.addMessage("Ne fonctionnera correctement que si les noms des fichiers images de sortie de Huygens ont ete laisses intacts. Ne pas les modifier.")
#mainDialogBox.addButton("Ouvrir image", imageSelectionListener())
mainDialogBox.addMessage("------------------------------------------")
mainDialogBox.addDirectoryField("Choisir un repertoire-cible", "None")
mainDialogBox.addMessage("------------------------------------------")
mainDialogBox.addDirectoryField("Choisir un repertoire pour deposer les piles d'images", "None")
mainDialogBox.addMessage("------------------------------------------")
#Select File Type
choixType = ["1 fichier par canal (NOM_FICHIER_chXX.tif)", "1 fichier par canal + temps (NOM_FICHIER_tXX_chXX.tif)", "1 fichier par canal et par profondeur (NOM_FICHIER_zXX_chXX.tif)", "1 fichier par canal et par profondeur + temps (NOM_FICHIER_tXX_zXX_chXX.tif)"]
selectionType = choixType[0]
mainDialogBox.addChoice("Selectionner type de fichiers",choixType,selectionType)
mainDialogBox.addMessage("------------------------------------------")
choixDisplayMode = ["Color", "Greyscale", "Composite"]
selectionDisplayModeDefaut = choixDisplayMode[0]
mainDialogBox.addChoice("Color Display Mode",choixDisplayMode,selectionDisplayModeDefaut)
mainDialogBox.addMessage("------------------------------------------")
#Affichage de la boîte de dialogue
mainDialogBox.showDialog();
#Récupération choix
folder = mainDialogBox.getNextString()
save_folder = mainDialogBox.getNextString()
vecteurChoix=mainDialogBox.getChoices()
selectionTypeFichier = vecteurChoix[0]
valeurSelectionTypeFichier = str(selectionTypeFichier.getSelectedItem())
selectionDisplayMode = vecteurChoix[1]
valeurSelectionDisplayMode = str(selectionDisplayMode.getSelectedItem())
if mainDialogBox.wasCanceled() == True:
print("Canceled, Values set to None")
folder = None
save_folder = None
valeurSelectionTypeFichier = None
valeurSelectionDisplayMode = None
return folder, save_folder, valeurSelectionTypeFichier, valeurSelectionDisplayMode
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
gd.addDirectoryOrFileField("Input Image or Image Directory",None,dirFieldWidth)
imgdirf = gd.getStringFields().get(2)
gd.setInsets(10,gdMargin,10)
gd.addMessage("Output folders:")
outputf=gd.getMessage()
# what to do: affine/warp/reformat
gd.setInsets(10,200,10)
gd.addCheckboxGroup(3,2,["affine","01","warp","02","reformat","03"],[True,True,True,True,True,True],["Registration Actions","Reformat Channels"])
#gd.addCheckboxGroup(1,3,["01","02","03"],[True,True,True],["Reformat Channels"])
# Registration options
# Jefferis,Potter 2007, Cachero,Ostrovsky 2010, Manual
gd.addChoice("Registration Params",["Jefferis, Potter 2007","Cachero, Ostrovsky 2010"],"Jefferis, Potter 2007")
choicef=gd.getChoices().get(0)
print choicef.getSelectedItem()
# final Action (Test, Run, Write Script)
gd.addChoice("Action",["Test","Write Script","Run"],"Write Script")
font=Font("SansSerif",Font.BOLD,12)
# Advanced options
gd.setInsets(25,100,10)
gd.addMessage("Advanced Options:",font)
advancedoptionsf=gd.getMessage()
ncores=Runtime.getRuntime().availableProcessors()
defaultCores=1
if ncores >=8:
defaultCores=4
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
gd.addMessage("Output folders:")
outputf = gd.getMessage()
# what to do: affine/warp/reformat
gd.setInsets(10, 200, 10)
gd.addCheckboxGroup(3, 2, ["affine", "01", "warp", "02", "reformat", "03"],
[True, True, True, True, True, True],
["Registration Actions", "Reformat Channels"])
#gd.addCheckboxGroup(1,3,["01","02","03"],[True,True,True],["Reformat Channels"])
# Registration options
# Jefferis,Potter 2007, Cachero,Ostrovsky 2010, Manual
gd.addChoice("Registration Params",
["Jefferis, Potter 2007", "Cachero, Ostrovsky 2010"],
"Jefferis, Potter 2007")
choicef = gd.getChoices().get(0)
print choicef.getSelectedItem()
# final Action (Test, Run, Write Script)
gd.addChoice("Action", ["Test", "Write Script", "Run (Experimental)"],
"Write Script")
font = Font("SansSerif", Font.BOLD, 12)
# Advanced options
gd.setInsets(25, 100, 10)
gd.addMessage("Advanced Options:", font)
advancedoptionsf = gd.getMessage()
ncores = Runtime.getRuntime().availableProcessors()
defaultCores = 1
if ncores >= 8:
