def getC1Projection(imp, norm):
stack = imp.getStack()
projStack = ImageStack(W,H)
for t in range(1,T+1):
proj = FloatProcessor(W,H)
for z in range(1,Z+1): #max intensity projection
ip = stack.getProcessor(imp.getStackIndex(1,z,t)).convertToFloatProcessor()
proj.copyBits(ip, 0,0, Blitter.MAX)
projStack.addSlice(proj)
if norm: #Z normalise
stats = StackStatistics(ImagePlus("wrapper",projStack))
for t in range(1,T+1):
ip = projStack.getProcessor(t)
ip.subtract(stats.mean)
ip.multiply( 1.0/(stats.stdDev) )
return projStack
def run():
""" Loads an image stack which contains both reference and target images for the registration
Scales the images to have their largest side equal to longSide
Registration is performed:
- translation (brute force optimization)
- rotation (brute force optimization)
- sift registration
- bunwarpj registration
Calculation of the errors by different methods """
# load the input stack as an ImagePlus
imp = IJ.openImage(filePath.getAbsolutePath())
stack = imp.getStack()
sizeZ = imp.getStackSize()
LAND_MARKS = 0
# Copy the reference and target slice
refId = 1
ref = stack.getProcessor(refId).duplicate()
if (Scale == 1):
[ref, s] = scaleLongSide(ref, longSide)
sizeZ = min(sizeZ, maxSlice)
stackReg = ImageStack(ref.getWidth(), ref.getHeight())
stackReg.addSlice(ref)
# = stack.duplicate()
for i in range(2, sizeZ+1):
targetId = i
target = stack.getProcessor(targetId).duplicate()
# Scale the slices: scale the reference slice using the longSide parameter, and use the same scale for the target slice.
if (Scale == 1):
target = scale(target, s)
#ImagePlus('Ref',ref).show()
#ImagePlus('Target',target).show()
if (Reg == 1):
if (translationReg == 1):
target = translation(ref, target)
if (rotationReg == 1):
[rot, target] = rotationSingle(ref,target,rotationStep)
if (siftReg == 1):
[roiRef, roiTarget] = siftSingle(ref, target)
impTarget = ImagePlus('Target',target)
impTarget.setRoi(roiTarget)
#impTarget.show()
impRef = ImagePlus('Ref',ref)
impRef.setRoi(roiRef)
#impRef.show()
LAND_MARKS = 1
if (bunwarpjReg == 1):
target = bunwarpjSingle(impRef, impTarget, LAND_MARKS, 'direct_transfo_' + str(i) + '.txt', 'inverse_transfo_' + str(i) + '.txt')
impTarget = ImagePlus('unwarpj_target', target)
#impTarget.show()
fileName = 'target_id' + str(targetId) + '.tif'
IJ.saveAs(impTarget, "Tiff", os.path.join(saveDir.getAbsolutePath(), fileName))
#stackReg.setProcessor(target.convertToShortProcessor(), i)
stackReg.addSlice(target)
if (calculateError == 1):
eCorrelation = zeros(sizeZ, 'f')
eMSE = zeros(sizeZ, 'f')
eMSE_ROI = zeros(sizeZ, 'f')
eRMSE = zeros(sizeZ, 'f')
eNRMSE = zeros(sizeZ, 'f')
eCVRMSE = zeros(sizeZ, 'f')
for i in range(1, sizeZ+1):
ip = stackReg.getProcessor(i).duplicate()
#ImagePlus('test',ip).show()
eCorrelation[i-1], eMSE[i-1], eMSE_ROI[i-1], eRMSE[i-1], eNRMSE[i-1], eCVRMSE[i-1] = measureError(ref,ip)
errorFileName = 'error.txt'
errorFilePath = os.path.join(saveDir.getAbsolutePath(), errorFileName)
writeCSV( errorFilePath, [eCorrelation,eMSE, eMSE_ROI, eRMSE,eNRMSE,eCVRMSE], ["Correlation","MSE","MSE_ROI","RMSE","N_RMSE","CV_RMSE"] )
def run():
""" Loads an image stack which contains both reference and target images for the registration
Scales the images to have their largest side equal to longSide
Registration is performed:
- translation (brute force optimization)
- rotation (brute force optimization)
- sift registration
- bunwarpj registration
Calculation of the errors by different methods """
# load the input stack as an ImagePlus
imp = IJ.openImage(filePath.getAbsolutePath())
stack = imp.getStack()
sizeZ = imp.getStackSize()
LAND_MARKS = 0
# Copy the reference and target slice
refId = 1
ref = stack.getProcessor(refId).duplicate()
if (Scale == 1):
[ref, s] = scaleLongSide(ref, longSide)
sizeZ = min(sizeZ, maxSlice)
stackReg = ImageStack(ref.getWidth(), ref.getHeight())
stackReg.addSlice(ref)
# = stack.duplicate()
for i in range(2, sizeZ + 1):
targetId = i
target = stack.getProcessor(targetId).duplicate()
# Scale the slices: scale the reference slice using the longSide parameter, and use the same scale for the target slice.
if (Scale == 1):
target = scale(target, s)
#ImagePlus('Ref',ref).show()
#ImagePlus('Target',target).show()
if (Reg == 1):
if (translationReg == 1):
target = translation(ref, target)
if (rotationReg == 1):
[rot, target] = rotationSingle(ref, target, rotationStep)
if (siftReg == 1):
[roiRef, roiTarget] = siftSingle(ref, target)
impTarget = ImagePlus('Target', target)
impTarget.setRoi(roiTarget)
#impTarget.show()
impRef = ImagePlus('Ref', ref)
impRef.setRoi(roiRef)
#impRef.show()
LAND_MARKS = 1
if (bunwarpjReg == 1):
target = bunwarpjSingle(impRef, impTarget, LAND_MARKS,
'direct_transfo_' + str(i) + '.txt',
'inverse_transfo_' + str(i) + '.txt')
impTarget = ImagePlus('unwarpj_target', target)
#impTarget.show()
fileName = 'target_id' + str(targetId) + '.tif'
IJ.saveAs(impTarget, "Tiff",
os.path.join(saveDir.getAbsolutePath(), fileName))
#stackReg.setProcessor(target.convertToShortProcessor(), i)
stackReg.addSlice(target)
if (calculateError == 1):
eCorrelation = zeros(sizeZ, 'f')
eMSE = zeros(sizeZ, 'f')
eMSE_ROI = zeros(sizeZ, 'f')
eRMSE = zeros(sizeZ, 'f')
eNRMSE = zeros(sizeZ, 'f')
eCVRMSE = zeros(sizeZ, 'f')
for i in range(1, sizeZ + 1):
ip = stackReg.getProcessor(i).duplicate()
#ImagePlus('test',ip).show()
eCorrelation[i - 1], eMSE[i - 1], eMSE_ROI[i - 1], eRMSE[
i - 1], eNRMSE[i - 1], eCVRMSE[i - 1] = measureError(ref, ip)
errorFileName = 'error.txt'
errorFilePath = os.path.join(saveDir.getAbsolutePath(), errorFileName)
writeCSV(
errorFilePath,
[eCorrelation, eMSE, eMSE_ROI, eRMSE, eNRMSE, eCVRMSE],
["Correlation", "MSE", "MSE_ROI", "RMSE", "N_RMSE", "CV_RMSE"])
refImp = IJ.openImage(refpath)
width = refImp.width
height = refImp.height
roim = RoiManager()
roim.runCommand("open", roipath)
roiArray = roim.getRoisAsArray()
nRoi = len(roiArray)
roim.close()
bwStack = ImageStack(width, height, nRoi)
for i in xrange(1, nRoi+1):
bwStack.setProcessor(FloatProcessor(width, height, zeros('f', width * height), None), i)
for i in xrange(1, nRoi+1):
roi = roiArray[i-1]
fp = bwStack.getProcessor(i)
fp.setValue(1.0)
fp.fill(roi)
roiImp = ImagePlus("roi", bwStack)
outfn = "roi_" + os.path.splitext(roifn)[0] + ".tif"
outpath = os.path.join(roidir, outfn)
if os.path.exists(outpath):
print "Skipped, already exists: ", outfn
else:
IJ.saveAsTiff(roiImp, outpath)
refImp = IJ.openImage(refpath)
width = refImp.width
height = refImp.height
roim = RoiManager()
roim.runCommand("open", roipath)
roiArray = roim.getRoisAsArray()
nRoi = len(roiArray)
roim.close()
bwStack = ImageStack(width, height, nRoi)
for i in xrange(1, nRoi + 1):
bwStack.setProcessor(
FloatProcessor(width, height, zeros('f', width * height), None), i)
for i in xrange(1, nRoi + 1):
roi = roiArray[i - 1]
fp = bwStack.getProcessor(i)
fp.setValue(1.0)
fp.fill(roi)
roiImp = ImagePlus("roi", bwStack)
outfn = "roi_" + os.path.splitext(roifn)[0] + ".tif"
outpath = os.path.join(roidir, outfn)
if os.path.exists(outpath):
print "Skipped, already exists: ", outfn
else:
IJ.saveAsTiff(roiImp, outpath)
def decon(seriesNumber, imgP, psfP):
nChannels = imgP.getNChannels()
if nChannels>1:
imgPc = ChannelSplitter.split(imgP)
else:
imgPc = [imgP]
if psfP.getNChannels()>1:
psfPc = ChannelSplitter.split(psfP)
if len(psfPc)<nChannels:
log("PSF image has fewer channels! Skipping image's trailing channels {} to {}".format(psfP.getNChannels()+1,nChannels))
imgPc = imgPc[:psfP.getNChannels()]
else:
psfPc = [psfP]*nChannels
nChannels = len(imgPc)
if combinedChannels:
deconChannels = None
for channelNumber in range(nChannels):
log("Processing image {} series {} channel {}..".format(inputFile.getAbsolutePath(),seriesNumber,channelNumber))
imgP = imgPc[channelNumber]
psfP = psfPc[channelNumber]
img = ImageJFunctions.wrap(imgP)
psf = ImageJFunctions.wrap(psfP)
# convert to float (TODO: make sure deconvolution op works on other types)
imgF=ops.convert().float32(img)
psfF=ops.convert().float32(psf)
# make psf same size as image
psfSize=FinalDimensions([img.dimension(0), img.dimension(1), img.dimension(2)]);
# add border in z direction
#borderSize=[0,0,psfSize.dimension(2)/2];
borderSize=[0,0,0];
deconvolved = ops.deconvolve().richardsonLucy(imgF, psfF, numIterations);
# Create the ImagePlus, copy scale and dimensions
deconvolvedImp = ImageJFunctions.wrapFloat(deconvolved,inputFile.getName()+'-series{}-channel{}-deconvolvedWith-{}-{}iterations.tiff'.format(seriesNumber,channelNumber,psfFile.getName(),numIterations))
deconvolvedImp.copyScale(imgP)
width, height, nChannelz, nSlices, nFrames = imgP.getDimensions()
deconvolvedImp.setDimensions(nChannelz, nSlices, nFrames)
if combinedChannels:
if deconChannels is None:
deconChannels = ImageStack(width,height)
for z in range(nSlices):
deconChannels.addSlice(deconvolvedImp.getStack().getProcessor(z))
else:
IJ.saveAsTiff(deconvolvedImp,os.path.join(outputDirectory.getAbsolutePath(),deconvolvedImp.getTitle()))
if combinedChannels:
final = ImageStack(width,height)
for z in range(nSlices):
for c in range(nChannels):
i = c*nSlices+z
final.addSlice(deconChannels.getProcessor(i+1))
hyperstack = ImagePlus(inputFile.getName()+'-series{}-deconvolvedWith-{}-{}iterations.tiff'.format(seriesNumber,psfFile.getName(),numIterations),final)
hyperstack = HyperStackConverter.toHyperStack(hyperstack,nChannels,nSlices,1)
hyperstack.copyScale(imgP)
IJ.saveAsTiff(hyperstack,os.path.join(outputDirectory.getAbsolutePath(),hyperstack.getTitle()))
#ipMIP = newMIPImp.getProcessor() #EDM().toEDM( ipMIP.convertToByte(True) ) #imgMIP = IP( "MIP", ipMIP ) #imgMIP.show() #break print 'Converting to 8 bit...' stack = newImp.getStack() for s in range( 0, slices ): ip = stack.getProcessor(s+1) label = stack.getSliceLabel(s+1) ip.resetMinAndMax() newStack.addSlice( label, ip.convertToByte(True) ) IJ.showProgress(s+1, slices) print 'Applying ultimate erosion...' EDMStack = IMGS( imp.getWidth(), imp.getHeight() ) for s in range( 0, slices ): ip = newStack.getProcessor(s+1) EDM().toEDM( ip ) #EDM().run( ip ) EDMStack.addSlice( label, ip ) IJ.showProgress(s+1, slices) imp.setStack( EDMStack ) imp.show() #fs = FileSaver( imp ) #print "Saving to", outputPath #fs.saveAsTiff( outputPath )
# ACTUAL SCRIPT
imp1 = IJ.openImage(sys.argv[1])
imp2 = IJ.openImage(sys.argv[2])
# stabilize
stack = ImageStack(imp1.width, imp1.height)
stack.addSlice('', imp1.getProcessor())
stack.addSlice('', imp2.getProcessor())
stackimp = ImagePlus('stack', stack)
WindowManager.setTempCurrentImage(stackimp)
IJ.run(
stackimp, "Image Stabilizer",
"transformation=Affine maximum_pyramid_levels=4 template_update_coefficient=0.90 maximum_iterations=20000 error_tolerance=0.0000001"
)
stack = stackimp.getImageStack()
stabilized1 = ImagePlus('stabilized1', stack.getProcessor(1))
stabilized2 = ImagePlus('stabilized2', stack.getProcessor(2))
# subtract
ic = ImageCalculator()
diff = ic.run('Subtract create', stabilized1, stabilized2)
# smudge
diff.getProcessor().blurGaussian(2)
# enhance ;)
hysteresis = ImagePlus('hysteresis', hyst(diff.getProcessor(), HYST_HI,
HYST_LO))
# invert
hysteresis.getProcessor().invert()
# count worms
rt = ResultsTable()
pa = ParticleAnalyzer(SHOW_NONE, 0, rt, MIN_SIZE, MAX_SIZE, MIN_CIRC, MAX_CIRC)
pa.analyze(hysteresis)
