def translate_single_stack_using_imglib2(imp, dx, dy, dz):
# wrap into a float imglib2 and translate
# conversion into float is necessary due to "overflow of n-linear interpolation due to accuracy limits of unsigned bytes"
# see: https://github.com/fiji/fiji/issues/136#issuecomment-173831951
img = ImagePlusImgs.from(imp.duplicate())
extended = Views.extendBorder(img)
converted = Converters.convert(extended, RealFloatSamplerConverter())
interpolant = Views.interpolate(converted, NLinearInterpolatorFactory())
# translate
if imp.getNDimensions()==3:
transformed = RealViews.affine(interpolant, Translation3D(dx, dy, dz))
elif imp.getNDimensions()==2:
transformed = RealViews.affine(interpolant, Translation2D(dx, dy))
else:
IJ.log("Can only work on 2D or 3D stacks")
return None
cropped = Views.interval(transformed, img)
# wrap back into bit depth of input image and return
bd = imp.getBitDepth()
if bd==8:
return(ImageJFunctions.wrapUnsignedByte(cropped,"imglib2"))
elif bd == 16:
return(ImageJFunctions.wrapUnsignedShort(cropped,"imglib2"))
elif bd == 32:
return(ImageJFunctions.wrapFloat(cropped,"imglib2"))
else:
return None
def translate_single_stack_using_imglib2(imp, dx, dy, dz):
# wrap into a float imglib2 and translate
# conversion into float is necessary due to "overflow of n-linear interpolation due to accuracy limits of unsigned bytes"
# see: https://github.com/fiji/fiji/issues/136#issuecomment-173831951
img = ImagePlusImgs.from(imp.duplicate())
extended = Views.extendBorder(img)
converted = Converters.convert(extended, RealFloatSamplerConverter())
interpolant = Views.interpolate(converted, NLinearInterpolatorFactory())
# translate
if imp.getNDimensions()==3:
transformed = RealViews.affine(interpolant, Translation3D(dx, dy, dz))
elif imp.getNDimensions()==2:
transformed = RealViews.affine(interpolant, Translation2D(dx, dy))
else:
IJ.log("Can only work on 2D or 3D stacks")
return None
cropped = Views.interval(transformed, img)
# wrap back into bit depth of input image and return
bd = imp.getBitDepth()
if bd==8:
return(ImageJFunctions.wrapUnsignedByte(cropped,"imglib2"))
elif bd == 16:
return(ImageJFunctions.wrapUnsignedShort(cropped,"imglib2"))
elif bd == 32:
return(ImageJFunctions.wrapFloat(cropped,"imglib2"))
else:
return None
def translate_using_imglib2(imp, dx, dy, dz):
print "imp channels",imp.getNChannels()
# todo:
# if multiple channels use Duplicator to translate each channel individually
## wrap
# http://javadoc.imagej.net/ImgLib2/net/imglib2/img/imageplus/ImagePlusImg.html
img = ImagePlusImgs.from(imp.duplicate())
print "dimensions:",img.numDimensions()
print img.getChannels()
## prepare image
print "img",img
ddd
extended = Views.extendBorder(img)
#print "extended",extended
#print "extended",extended.dimension(1)
dims = zeros(4, 'l')
img.dimensions(dims)
print "dims",dims
converted = Converters.convert(extended, RealFloatSamplerConverter())
composite = Views.collapseReal(converted, imp.getNChannels())
print "composite",composite
interpolant = Views.interpolate(composite, NLinearInterpolatorFactory())
#print "interpolant",interpolant
transformed = RealViews.affine(interpolant, Translation3D(dx, dy, dz))
print "transformed", transformed
cropped = Views.interval(transformed, img)
print "cropped.numDimensions()", cropped.numDimensions()
print "cropped",cropped
## wrap back and return
bd = imp.getBitDepth()
# maybe simply wrap works?
if bd==8:
return(ImageJFunctions.wrapUnsignedByte(cropped,"imglib2"))
elif bd == 16:
return(ImageJFunctions.wrapUnsignedShort(cropped,"imglib2"))
elif bd == 32:
return(ImageJFunctions.wrapFloat(cropped,"imglib2"))
else:
return None
redgreen= ops.add(red32,green32)
display.createDisplay("redgreen", data.create(redgreen))
# make a copy of the red + green image
copy=redgreen.copy()
# wrap as ImagePlus
imp=ImageJFunctions.wrap(copy, "wrapped")
# create and call background subtractor
bgs=BackgroundSubtracter()
bgs.rollingBallBackground(imp.getProcessor(), 50.0, False, False, True, True, True)
# wrap as Img and display
iplus=ImagePlus("bgs", imp.getProcessor())
print type(imp)
imgBgs=ImageJFunctions.wrapFloat(iplus)
display.createDisplay("back_sub", data.create(ImgPlus(imgBgs)))
kernel = DetectionUtils.createLoGKernel( 3.0, 2, array([1.0, 1.0], 'd' ) )
print type(kernel)
print type(imgBgs)
print type(red32.getImg())
log = ops.convolve(ops.create( dimensions2D, FloatType()), imgBgs, kernel)
display.createDisplay("log", data.create(ImgPlus(log)))
otsu=ops.run("threshold", ops.create( dimensions2D, BitType()), log, Otsu())
display.createDisplay("thresholded", data.create(ImgPlus(otsu)))
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()))
display.createDisplay("redgreen", data.create(redgreen))
# make a copy of the red + green image
copy = redgreen.copy()
# wrap as ImagePlus
imp = ImageJFunctions.wrap(copy, "wrapped")
# create and call background subtractor
bgs = BackgroundSubtracter()
bgs.rollingBallBackground(imp.getProcessor(), 50.0, False, False, True, True,
True)
# wrap as Img and display
iplus = ImagePlus("bgs", imp.getProcessor())
print type(imp)
imgBgs = ImageJFunctions.wrapFloat(iplus)
display.createDisplay("back_sub", data.create(ImgPlus(imgBgs)))
kernel = DetectionUtils.createLoGKernel(3.0, 2, array([1.0, 1.0], 'd'))
print type(kernel)
print type(imgBgs)
print type(red32.getImg())
log = ops.convolve(ops.create(dimensions2D, FloatType()), imgBgs, kernel)
display.createDisplay("log", data.create(ImgPlus(log)))
otsu = ops.run("threshold", ops.create(dimensions2D, BitType()), log, Otsu())
display.createDisplay("thresholded", data.create(ImgPlus(otsu)))