def getTotal(imagefile,setflat=True):
options = DynamicMetadataOptions()
options.setBoolean("zeissczi.attachments", False)
czireader = ZeissCZIReader()
czireader.setFlattenedResolutions(setflat)
czireader.setId(imagefile)
seriesCount = czireader.getSeriesCount()
czireader.close()
return seriesCount
def setCZIReaderOptions(imagefile, czi_options, setflatres=True):
czireader = ZeissCZIReader()
czireader.setFlattenedResolutions(setflatres)
czireader.setMetadataOptions(czi_options)
czireader.setId(imagefile)
return czireader
def readczi(imagefile,
stitchtiles=True,
setflatres=False,
readpylevel=0,
setconcat=True,
openallseries=True,
showomexml=False,
attach=False,
autoscale=True):
log.info('Filename : ' + imagefile)
metainfo = {}
# checking for thr file Extension
metainfo['Extension'] = MiscTools.getextension(MiscTools.splitext_recurse(imagefile))
log.info('Detected File Extension : ' + metainfo['Extension'])
# initialize the reader and get the OME metadata
reader = ImageReader()
omeMeta = MetadataTools.createOMEXMLMetadata()
#metainfo['ImageCount_OME'] = omeMeta.getImageCount()
reader.setMetadataStore(omeMeta)
reader.setId(imagefile)
metainfo['SeriesCount_BF'] = reader.getSeriesCount()
reader.close()
# get the scaling for XYZ
physSizeX = omeMeta.getPixelsPhysicalSizeX(0)
physSizeY = omeMeta.getPixelsPhysicalSizeY(0)
physSizeZ = omeMeta.getPixelsPhysicalSizeZ(0)
if physSizeX is not None:
metainfo['ScaleX'] = round(physSizeX.value(), 3)
metainfo['ScaleY'] = round(physSizeX.value(), 3)
if physSizeX is None:
metainfo['ScaleX'] = None
metainfo['ScaleY'] = None
if physSizeZ is not None:
metainfo['ScaleZ'] = round(physSizeZ.value(), 3)
if physSizeZ is None:
metainfo['ScaleZ'] = None
options = DynamicMetadataOptions()
options.setBoolean("zeissczi.autostitch", stitchtiles)
options.setBoolean("zeissczi.attachments", attach)
czireader = ZeissCZIReader()
czireader.setFlattenedResolutions(setflatres)
czireader.setMetadataOptions(options)
czireader.setId(imagefile)
# Set the preferences in the ImageJ plugin
# Note although these preferences are applied, they are not refreshed in the UI
Prefs.set("bioformats.zeissczi.allow.autostitch", str(stitchtiles).lower())
Prefs.set("bioformats.zeissczi.include.attachments", str(attach).lower())
# metainfo = {}
metainfo['rescount'] = czireader.getResolutionCount()
metainfo['SeriesCount_CZI'] = czireader.getSeriesCount()
#metainfo['flatres'] = czireader.hasFlattenedResolutions()
#metainfo['getreslevel'] = czireader.getResolution()
# Dimensions
metainfo['SizeT'] = czireader.getSizeT()
metainfo['SizeZ'] = czireader.getSizeZ()
metainfo['SizeC'] = czireader.getSizeC()
metainfo['SizeX'] = czireader.getSizeX()
metainfo['SizeY'] = czireader.getSizeY()
# check for autostitching and possibility to read attachment
metainfo['AllowAutoStitching'] = czireader.allowAutostitching()
metainfo['CanReadAttachments'] = czireader.canReadAttachments()
# read in and display ImagePlus(es) with arguments
options = ImporterOptions()
options.setOpenAllSeries(openallseries)
options.setShowOMEXML(showomexml)
options.setConcatenate(setconcat)
options.setAutoscale(autoscale)
options.setId(imagefile)
# open the ImgPlus
imps = BF.openImagePlus(options)
metainfo['Pyramid Level Output'] = readpylevel + 1
try:
imp = imps[readpylevel]
pylevelout = metainfo['SeriesCount_CZI']
except:
# fallback option
log.info('PyLevel=' + str(readpylevel) + ' does not exist.')
log.info('Using Pyramid Level = 0 as fallback.')
imp = imps[0]
pylevelout = 0
metainfo['Pyramid Level Output'] = pylevelout
# get the stack and some info
imgstack = imp.getImageStack()
metainfo['Output Slices'] = imgstack.getSize()
metainfo['Output SizeX'] = imgstack.getWidth()
metainfo['Output SizeY'] = imgstack.getHeight()
# calc scaling in case of pyramid
scale = float(metainfo['SizeX']) / float(metainfo['Output SizeX'])
metainfo['Pyramid Scale Factor'] = scale
metainfo['ScaleX Output'] = metainfo['ScaleX'] * scale
metainfo['ScaleY Output'] = metainfo['ScaleY'] * scale
# set the correct scaling
imp = MiscTools.setscale(imp, scaleX=metainfo['ScaleX Output'],
scaleY=metainfo['ScaleX Output'],
scaleZ=metainfo['ScaleZ'],
unit="micron")
# close czireader
czireader.close()
return imp, metainfo
def readCZI(imagefile,
metainfo,
stitchtiles=False,
setflatres=False,
readpylevel=0,
setconcat=False,
openallseries=True,
showomexml=False,
attach=False,
autoscale=True):
options = DynamicMetadataOptions()
options.setBoolean("zeissczi.autostitch", stitchtiles)
options.setBoolean("zeissczi.attachments", attach)
czireader = ZeissCZIReader()
czireader.setFlattenedResolutions(setflatres)
czireader.setMetadataOptions(options)
czireader.setId(imagefile)
# Set the preferences in the ImageJ plugin
# Note although these preferences are applied, they are not refreshed in the UI
Prefs.set("bioformats.zeissczi.allow.autostitch", str(stitchtiles).lower())
Prefs.set("bioformats.zeissczi.include.attachments", str(attach).lower())
# metainfo = {}
metainfo['rescount'] = czireader.getResolutionCount()
metainfo['SeriesCount_CZI'] = czireader.getSeriesCount()
metainfo['flatres'] = czireader.hasFlattenedResolutions()
# metainfo['getreslevel'] = czireader.getResolution()
# Dimensions
metainfo['SizeT'] = czireader.getSizeT()
metainfo['SizeZ'] = czireader.getSizeZ()
metainfo['SizeC'] = czireader.getSizeC()
metainfo['SizeX'] = czireader.getSizeX()
metainfo['SizeY'] = czireader.getSizeY()
# check for autostitching and possibility to read attachment
metainfo['AllowAutoStitching'] = czireader.allowAutostitching()
metainfo['CanReadAttachments'] = czireader.canReadAttachments()
# read in and display ImagePlus(es) with arguments
options = ImporterOptions()
options.setOpenAllSeries(openallseries)
options.setShowOMEXML(showomexml)
options.setConcatenate(setconcat)
options.setAutoscale(autoscale)
options.setId(imagefile)
# open the ImgPlus
imps = BF.openImagePlus(options)
metainfo['Pyramid Level Output'] = readpylevel
# read image data using the specified pyramid level
imp, slices, width, height, pylevel = ImageTools.getImageSeries(imps, series=readpylevel)
metainfo['Pyramid Level Output'] = pylevel
metainfo['Output Slices'] = slices
metainfo['Output SizeX'] = width
metainfo['Output SizeY'] = height
# calc scaling in case of pyramid
# scale = float(metainfo['Output SizeX']) / float(metainfo['SizeX'])
scale = float(metainfo['SizeX']) / float(metainfo['Output SizeX'])
metainfo['Pyramid Scale Factor'] = scale
metainfo['ScaleX Output'] = metainfo['ScaleX'] * scale
metainfo['ScaleY Output'] = metainfo['ScaleY'] * scale
"""
imp = MiscTools.setproperties(imp, scaleX=metainfo['ScaleX Output'],
scaleY=metainfo['ScaleX Output'],
scaleZ=metainfo['ScaleZ'],
unit="micron",
sizeC=metainfo['SizeC'],
sizeZ=metainfo['SizeZ'],
sizeT=metainfo['SizeT'])
"""
imp = MiscTools.setscale(imp, scaleX=metainfo['ScaleX Output'],
scaleY=metainfo['ScaleX Output'],
scaleZ=metainfo['ScaleZ'],
unit="micron")
# close czireader
czireader.close()
return imp, metainfo
def check_fusion_settings(czi_path):
"""Check for fusion settings and asks confirmation to user if H5/XML fusion
Parameters
----------
czi_path : str
Path to the CZI file
Returns
-------
bool
Bool for fusion
str
Method of RAM handling
bool
Bool for TIFF or H5/XML fusion
"""
# Default values
do_fusion = True
fuse_tiff = True
reader = ZeissCZIReader()
m = DynamicMetadataOptions()
m.setBoolean(ZeissCZIReader.ALLOW_AUTOSTITCHING_KEY, False)
m.setBoolean(ZeissCZIReader.RELATIVE_POSITIONS_KEY, True)
reader.setMetadataOptions(m)
omeMeta = MetadataTools.createOMEXMLMetadata()
reader.setMetadataStore(omeMeta)
reader.setId(str(czi_path))
nbr_tp = omeMeta.getTimestampAnnotationCount() + 1
nbr_chnl = omeMeta.getChannelCount(0)
# check the file size of the file to be fused and compare to the available RAM
# h5_filesize = os.path.getsize(export_path_temp + ".h5")
h5_filesize = os.path.getsize(czi_path) / 2
free_memory = get_free_memory()
print("h5 filesize " + convert_bytes(h5_filesize))
print("free memory in ij " + convert_bytes(free_memory))
# TODO: include in below calculation t_end, since only one t is fused at a time.
if free_memory > (6 * h5_filesize / downsampling):
ram_handling = "[Precompute Image]"
else:
ram_handling = "Virtual"
print("fusion mode used " + str(ram_handling))
# if autoselect_illuminations and nbr_ill > 1:
# ill_value = 2
# else:
# ill_value = 1
ram_requirement = 2 * h5_filesize / (nbr_tp * nbr_chnl * downsampling)
print(ram_requirement)
sufficient_ram = ram_requirement < free_memory / 10
if not sufficient_ram:
try:
yn = YesNoCancelDialog(
IJ.getInstance(),
"Warning!",
(
"File size is too big to use TIFF for fusion\n"
"Fusion will happen using H5/XML which might take weeks. Are you "
"sure you want to do fusion ?\n"
"All steps prior to fusion would still happen, allowing for manual "
"fusion and tile selection."
),
)
if yn.yesPressed():
fuse_tiff = False
else:
do_fusion = False
except Exception:
# when running headless the above will raise a java.awt.HeadlessException,
# so we simply fall back to the same behavior as if "No" was clicked:
do_fusion = False
return do_fusion, ram_handling, fuse_tiff
def getCZIinfo(imagefile, showimage=False, setreslevel=0, setflat2=False, openallseries=True, showomexml=False,setconcat=False,filepath1="./"):
options = DynamicMetadataOptions()
options.setBoolean("zeissczi.attachments", False)
czireader = ZeissCZIReader()
czireader.setFlattenedResolutions(setflat2)
czireader.setMetadataOptions(options)
czireader.setId(imagefile)
lc = czireader.getSeriesCount()
#get the first occurence of each pyramid stack
location=list()
for i in range(0, int(seriesCount)-2):
location.append(czireader.coreIndexToSeries(i))
c=0
#log.info(location)
loc2=list()
for i,v in enumerate(location):
if i==0:
loc2.append(i)
elif i>0 and v!=c:
loc2.append(i)
c=v
log.info(str(loc2))
# get OME data
omeMeta = MetadataTools.createOMEXMLMetadata()
# Set the preferences in the ImageJ plugin
Prefs.set("bioformats.zeissczi.include.attachments", str(True).lower())
if showimage:
# read in and display ImagePlus(es) with arguments
options = ImporterOptions()
options.setOpenAllSeries(openallseries)
options.setShowOMEXML(showomexml)
options.setConcatenate(setconcat)
options.setId(imagefile)
# open the ImgPlus
imps = BF.openImagePlus(options)
name_list=imagefile.split('/')
name=name_list[len(name_list)-1]
out_path=filepath1 + "/"+name+"_Preview.tif"
log.info(name)
imp=getImageSeries(imps, seriesCount-1)
imp.show()
IJ.run("RGB Color")
imp.close()
IJ.saveAs("tiff", out_path)
IJ.run("Close")
out_path=filepath1 + "/"+name+"_Label.tif"
imp=getImageSeries(imps, (seriesCount-2))
imp.show()
IJ.run("RGB Color")
imp.close()
IJ.saveAs("tiff", out_path)
IJ.run("Close")
c=1
for series in loc2:
out_path=filepath1 + "/"+name+"Scene_" + str(c) + ".tif"
imp=getImageSeries(imps, series)
imp.show()
IJ.run("RGB Color")
imp.close()
IJ.saveAs("tiff", out_path)
IJ.run("Close")
c+=1
czireader.close()