def Z1_metadata(sourcefile):
# Access header of Z1 lighsheet data to determine nb views
reader = ImageReader()
omeMeta = MetadataTools.createOMEXMLMetadata()
reader.setMetadataStore(omeMeta)
reader.setId(sourcefile)
seriesCount = reader.getSeriesCount()
reader.close()
return seriesCount
def meta_parser():
""" Iterates through .lif XML/OME metadata, returns selected values eg. timepoints, channels, series count, laser power.. """
# Get metadata.
reader = ImageReader()
omeMeta = MetadataTools.createOMEXMLMetadata()
reader.setMetadataStore(omeMeta)
reader.setId(str(Experiment))
# Extracts number of image series, channel number
seriesCount = reader.getSeriesCount()
channels = reader.getSizeC()
#reader.close()
# Number of images
imageCount = omeMeta.getImageCount()
# Image size in pixels AND microns (for scalebar).
Physical_x = omeMeta.getPixelsPhysicalSizeX(0)
Pixel_x = omeMeta.getPixelsSizeX(0)
Physical_x = Physical_x.value()
Pixel_x = Pixel_x.getNumberValue()
# Assumes square image (x=y).
org_size = (Physical_x*Pixel_x)*2
# Laser power of donor excitation laser.
if channels == 3:
LP = omeMeta.getChannelLightSourceSettingsAttenuation(0,0)
LP = 1 - LP.getNumberValue()
else:
LP = 0
timelist = []
for timepoint in range (imageCount):
times = omeMeta.getImageAcquisitionDate(timepoint)
timelist.append(times.toString())
# YY.MM... to minutes.
timelist =[ time.mktime(time.strptime(times, u'%Y-%m-%dT%H:%M:%S')) for times in timelist ]
timelist_unsorted =[ (times - timelist[0])/60 for times in timelist ]
timelist = sorted(timelist_unsorted)
# Prints to log.
IJ.log("Total # of image series (from BF reader): " + str(seriesCount))
IJ.log("Total # of image series (from OME metadata): " + str(imageCount))
IJ.log("Total # of channels (from OME metadata): " + str(channels))
IJ.log("Laserpower (from OME metadata): " + str(LP))
return channels, seriesCount, timelist, timelist_unsorted, LP, org_size
def get_metadata(imagefile, imageID=0):
metainfo = {}
# 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()
# read dimensions TZCXY from OME metadata
metainfo['SizeT'] = omeMeta.getPixelsSizeT(imageID).getValue()
metainfo['SizeZ'] = omeMeta.getPixelsSizeZ(imageID).getValue()
metainfo['SizeC'] = omeMeta.getPixelsSizeC(imageID).getValue()
metainfo['SizeX'] = omeMeta.getPixelsSizeX(imageID).getValue()
metainfo['SizeY'] = omeMeta.getPixelsSizeY(imageID).getValue()
# store info about stack
if metainfo['SizeZ'] == 1:
metainfo['is3d'] = False
elif metainfo['SizeZ'] > 1:
metainfo['is3d'] = True
# 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(physSizeY.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
# sort the dictionary
metainfo = OrderedDict(sorted(metainfo.items()))
return metainfo
def time_parser():
""" Iterates through timelapse, """
""" outputs timepoints with corresponding seriesnames. """
""" - S. Grødem 2017 """
# Get metadata.
reader = ImageReader()
omeMeta = MetadataTools.createOMEXMLMetadata()
reader.setMetadataStore(omeMeta)
reader.setId(str(Experiment))
# Extracts number of image series, channel number
seriesCount = reader.getSeriesCount()
reader.close()
# Gets timepoints, in minutes.
timelist = []
namelist = []
for timepoint in range (seriesCount):
times = omeMeta.getImageAcquisitionDate(timepoint)
timelist.append(times.toString())
namelist.append(omeMeta.getImageName(timepoint))
# YY.MM... to minutes.
timelist =[ time.mktime(time.strptime(times, u'%Y-%m-%dT%H:%M:%S')) for times in timelist ]
timelist_unsorted =[ (times - timelist[0])/60 for times in timelist ]
# Sort timepoints.
timelist, namelist = zip(*sorted(zip(timelist_unsorted, namelist)))
timelist = [round(float(i), 3) for i in timelist]
# Output to IJ log
images = zip(timelist, namelist)
IJ.log("Series number: " + str(seriesCount))
IJ.log("*"*15)
for i in range(len(images)):
IJ.log("Name: " + str(images[i][1]))
IJ.log("Time: " + str(images[i][0]))
IJ.log("-"*15)
def choose_series(filepath, params):
"""if input file contains more than one image series (xy position), prompt user to choose which one to use"""
# todo: if necessary (e.g. if lots of series), can improve thumbnail visuals based loosely on https://github.com/ome/bio-formats-imagej/blob/master/src/main/java/loci/plugins/in/SeriesDialog.java
import_opts = ImporterOptions();
import_opts.setId(filepath);
reader = ImageReader();
ome_meta = MetadataTools.createOMEXMLMetadata();
reader.setMetadataStore(ome_meta);
reader.setId(filepath);
no_series = reader.getSeriesCount();
if no_series == 1:
return import_opts, params;
else:
series_names = [ome_meta.getImageName(idx) for idx in range(no_series)];
dialog = GenericDialog("Select series to load...");
dialog.addMessage("There are multiple series in this file! \n" +
"This is probably because there are multiple XY stage positions. \n " +
"Please choose which series to load: ");
thumbreader = BufferedImageReader(reader);
cbg = CheckboxGroup();
for idx in range(no_series):
p = Panel();
p.add(Box.createRigidArea(Dimension(thumbreader.getThumbSizeX(), thumbreader.getThumbSizeY())));
ThumbLoader.loadThumb(thumbreader, idx, p, True);
dialog.addPanel(p);
cb = Checkbox(series_names[idx], cbg, idx==0);
p.add(cb);
dialog.showDialog();
if dialog.wasCanceled():
raise KeyboardInterrupt("Run canceled");
if dialog.wasOKed():
selected_item = cbg.getSelectedCheckbox().getLabel();
selected_index = series_names.index(selected_item);
params.setSelectedSeriesIndex(selected_index);
for idx in range(0, no_series):
import_opts.setSeriesOn(idx, True) if (idx==selected_index) else import_opts.setSeriesOn(idx, False);
reader.close();
return import_opts, params
import net.imglib2.type.logic.BitType import net.imglib2.algorithm.neighborhood.HyperSphereShape from net.imglib2.type.numeric.real import FloatType,DoubleType from ij.measure import ResultsTable from net.imagej.ops import Ops from loci.plugins.in import ImporterOptions options = ImporterOptions() options.setId(Input_File.getAbsolutePath()) from loci.formats import ImageReader from loci.formats import MetadataTools #get import ready and import reader = ImageReader() omeMeta = MetadataTools.createOMEXMLMetadata() reader.setMetadataStore(omeMeta) reader.setId(Input_File.getAbsolutePath()) seriesCount = reader.getSeriesCount() reader.close() #open image imp, = BF.openImagePlus(options) #get output path variable outdir=Output_File.getAbsolutePath() #get input path variable inpu=Input_File.getAbsolutePath() #convert to RGB IC(imp).convertToRGB() #show image imp.show() #Define ROI of whole image (basically) imp.setRoi(1,1,478,479)
def processFile(filename, inDir, outDir, dichroics, mergeList):
if mergeList is None:
merge = False
else:
merge = True
filenameExExt = os.path.splitext(filename)[0]
filepath = inDir + filename
# parse metadata
reader = ImageReader()
omeMeta = MetadataTools.createOMEXMLMetadata()
reader.setMetadataStore(omeMeta)
reader.setId(filepath)
numChannels = reader.getSizeC()
numSlices = reader.getSizeZ()
numFrames = reader.getSizeT()
seriesCount = reader.getSeriesCount()
globalMetadata = reader.getGlobalMetadata()
seriesMetadata = reader.getSeriesMetadata()
objLensName = globalMetadata['- Objective Lens name #1']
areaRotation = float(seriesMetadata['area rotation #1'])
acquisitionValueRotation = float(seriesMetadata['acquisitionValue rotation #1'])
if 'regionInfo rotation #1' in seriesMetadata:
regionInfoRotation = float(seriesMetadata['regionInfo rotation #1'])
else:
regionInfoRotation = float(0)
totalRotation = areaRotation + regionInfoRotation
physSizeX = omeMeta.getPixelsPhysicalSizeX(0)
physSizeY = omeMeta.getPixelsPhysicalSizeY(0)
pxSizeX = physSizeX.value(UNITS.MICROM)
pxSizeY = physSizeY.value(UNITS.MICROM)
# log metadata
IJ.log("\nMETADATA")
#IJ.log("Filename: " + filepath)
IJ.log("Number of series: " + str(seriesCount))
IJ.log("Number of channels: " + str(numChannels))
IJ.log("Number of frames: " + str(numFrames))
IJ.log("Number of slices: " + str(numSlices))
IJ.log("Objective lens: " + objLensName)
IJ.log("FOV rotation: " + str(areaRotation))
IJ.log("ROI rotation: " + str(regionInfoRotation))
IJ.log("Total rotation: " + str(totalRotation))
IJ.log("Pixel size:")
IJ.log("\t\tX = " + str(physSizeX.value()) + " " + physSizeX.unit().getSymbol())
IJ.log("\t\tY = " + str(physSizeY.value()) + " " + physSizeY.unit().getSymbol())
if merge:
tifDir = outDir + "." + str(datetime.now()).replace(" ", "").replace(":", "") + "/"
if not os.path.exists(tifDir):
os.makedirs(tifDir)
IJ.log("\nCreated temporary folder: " + tifDir + "\n")
else:
IJ.log("Unable to create temporary folder!\n")
else:
tifDir = outDir + filenameExExt + "/"
if not os.path.exists(tifDir):
os.makedirs(tifDir)
IJ.log("\nCreated subfolder: " + tifDir + "\n")
else:
IJ.log("\nSubfolder " + tifDir + " already exists.\n")
# correct images
tifFilePaths = []
for i in range(numChannels):
ip = extractChannel(oirFile=filepath, ch=i)
if dichroics[i] == "DM1":
IJ.log("Channel " + str(i+1) + " was imaged using DM1, so no correction required.")
else:
offsets = getOffset(obj=objLensName,dm=dichroicDict[dichroics[i]])
xom = offsets['x']
yom = offsets['y']
if abs(totalRotation) > 0.1:
rotOff = rotateOffset(x=xom, y=yom, angle=-totalRotation)
xom = rotOff['x']
yom = rotOff['y']
xop = int(round(xom/pxSizeX))
yop = int(round(yom/pxSizeY))
IJ.log("Channel " + str(i+1) + " offsets")
IJ.log("\t\tMicrometres")
IJ.log("\t\t\t\tx = " + str(xom))
IJ.log("\t\t\t\ty = " + str(yom))
IJ.log("\t\tPixels")
IJ.log("\t\t\t\tx = " + str(xop))
IJ.log("\t\t\t\ty = " + str(yop))
IJ.run(ip, "Translate...", "x=" + str(-xop) + " y=" + str(-yop) + " interpolation=None stack")
tifFilePath = tifDir + filenameExExt + "_ch_"+str(i+1)+".tif"
tifFilePaths.append(tifFilePath)
if os.path.exists(tifFilePath):
IJ.log("\nOutput file exists: " + tifFilePath)
IJ.log("Rerun plugin choosing a different output folder")
IJ.log("or delete file and then rerun plugin.")
IJ.log("Image processing terminated!\n")
return
FileSaver(ip).saveAsTiff(tifFilePath)
if merge:
max_list = []
for i in range(len(mergeList)):
if mergeList[i] != None:
mergeList[i] = readSingleChannelImg(tifFilePaths[mergeList[i]])
channel = mergeList[i]#https://python.hotexamples.com/examples/ij.plugin/RGBStackMerge/mergeChannels/python-rgbstackmerge-mergechannels-method-examples.html
projector = ZProjector(channel)
projector.setMethod(ZProjector.MAX_METHOD)
projector.doProjection()
max_list.append(projector.getProjection())
merged = RGBStackMerge.mergeChannels(mergeList, False)
merged_max = RGBStackMerge.mergeChannels(max_list, False)
mergedChannelFilepath = outDir + filenameExExt + ".tif"
maxMergedChannelFilepath = outDir + filenameExExt + "_max.tif"
if os.path.exists(mergedChannelFilepath):
IJ.log("\nOutput file exists: " + mergedChannelFilepath)
IJ.log("Rerun plugin choosing a different output folder")
IJ.log("or delete file and then rerun plugin.")
IJ.log("Image processing terminated!\n")
FileSaver(merged).saveAsTiff(mergedChannelFilepath)
FileSaver(merged_max).saveAsTiff(maxMergedChannelFilepath)
for tf in tifFilePaths:
os.remove(tf)
os.rmdir(tifDir)
IJ.log("\nFinished processing file:\n" + filepath + "\n")
if merge:
IJ.log("Image file with channels aligned:\n" + outDir + filenameExExt + ".tif\n")
else:
IJ.log("Aligned images (one tiff file for each channel) can be found in:\n" + tifDir + "\n")
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 openfile(imagefile,
stitchtiles=True,
setflatres=False,
readpylevel=0,
setconcat=True,
openallseries=True,
showomexml=False,
attach=False,
autoscale=True,
imageID=0):
# stitchtiles = option of CZIReader to return the raw tiles as
# individual series rather than the auto-stitched images
metainfo = {}
# checking for thr file Extension
metainfo['Extension'] = MiscTools.getextension(MiscTools.splitext_recurse(imagefile))
# initialite 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()
# read dimensions TZCXY from OME metadata
metainfo['SizeT'] = omeMeta.getPixelsSizeT(imageID).getValue()
metainfo['SizeZ'] = omeMeta.getPixelsSizeZ(imageID).getValue()
metainfo['SizeC'] = omeMeta.getPixelsSizeC(imageID).getValue()
metainfo['SizeX'] = omeMeta.getPixelsSizeX(imageID).getValue()
metainfo['SizeY'] = omeMeta.getPixelsSizeY(imageID).getValue()
# store info about stack
if metainfo['SizeZ'] == 1:
metainfo['is3d'] = False
elif metainfo['SizeZ'] > 1:
metainfo['is3d'] = True
# 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
# if image file is Carl Zeiss Image - CZI
if metainfo['Extension'] == '.czi':
# read the CZI file using the CZIReader
# pylevel = 0 - read the full resolution image
imp, metainfo = ImportTools.readCZI(imagefile, metainfo,
stitchtiles=stitchtiles,
setflatres=setflatres,
readpylevel=readpylevel,
setconcat=setconcat,
openallseries=openallseries,
showomexml=showomexml,
attach=attach,
autoscale=autoscale)
# if image file is not Carl Zeiss Image - CZI
if metainfo['Extension'] != '.czi':
# read the imagefile using the correct method
if metainfo['Extension'].lower() == ('.jpg' or '.jpeg'):
# use dedicated method for jpg
imp, metainfo = ImageTools.openjpg(imagefile, method='IJ')
else:
# if not jpg - use BioFormats
imp, metainfo = ImportTools.readbf(imagefile, metainfo,
setflatres=setflatres,
readpylevel=readpylevel,
setconcat=setconcat,
openallseries=openallseries,
showomexml=showomexml,
autoscale=autoscale)
return imp, metainfo
def processFile():
# start logging
IJ.log("\n______________________________\n\n\t\tOlympus DM correction\n\t\tVersion " + pluginVersion +"\n______________________________\n")
# ask user for file
ofd = OpenDialog("Choose a file", None)
filename = ofd.getFileName()
if filename is None:
IJ.log("User canceled the dialog!\nImage processing canceled!\n")
return
directory = ofd.getDirectory()
filepath = directory + filename
IJ.log("File path: " + filepath)
if not filename.endswith(".oir"):
IJ.log("Not an Olympus (.oir) file.\nNo image to process.\n")
return
filenameExExt = os.path.splitext(filename)[0]
# parse metadata
reader = ImageReader()
omeMeta = MetadataTools.createOMEXMLMetadata()
reader.setMetadataStore(omeMeta)
reader.setId(filepath)
numChannels = reader.getSizeC()
numSlices = reader.getSizeZ()
numFrames = reader.getSizeT()
seriesCount = reader.getSeriesCount()
globalMetadata = reader.getGlobalMetadata()
seriesMetadata = reader.getSeriesMetadata()
objLensName = globalMetadata['- Objective Lens name #1']
areaRotation = float(seriesMetadata['area rotation #1'])
acquisitionValueRotation = float(seriesMetadata['acquisitionValue rotation #1'])
if 'regionInfo rotation #1' in seriesMetadata:
regionInfoRotation = float(seriesMetadata['regionInfo rotation #1'])
else:
regionInfoRotation = float(0)
totalRotation = areaRotation + regionInfoRotation
physSizeX = omeMeta.getPixelsPhysicalSizeX(0)
physSizeY = omeMeta.getPixelsPhysicalSizeY(0)
pxSizeX = physSizeX.value(UNITS.MICROM)
pxSizeY = physSizeY.value(UNITS.MICROM)
# log metadata
IJ.log("\nMETADATA")
#IJ.log("Filename: " + filepath)
IJ.log("Number of series: " + str(seriesCount))
IJ.log("Number of channels: " + str(numChannels))
IJ.log("Number of frames: " + str(numFrames))
IJ.log("Number of slices: " + str(numSlices))
IJ.log("Objective lens: " + objLensName)
IJ.log("FOV rotation: " + str(areaRotation))
IJ.log("ROI rotation: " + str(regionInfoRotation))
IJ.log("Total rotation: " + str(totalRotation))
IJ.log("Pixel size:")
IJ.log("\t\tX = " + str(physSizeX.value()) + " " + physSizeX.unit().getSymbol())
IJ.log("\t\tY = " + str(physSizeY.value()) + " " + physSizeY.unit().getSymbol())
# ask user to identify dichroic mirror used for each channel
gdDM = GenericDialog("Dichroic mirrors")
DMs = ["DM1", "DM2", "DM3", "DM4", "DM5"]
for i in range(numChannels):
gdDM.addChoice("Channel " + str(i+1), DMs, DMs[0])
gdDM.addCheckbox("Merge channels", False)
gdDM.showDialog()
if gdDM.wasCanceled():
IJ.log("User canceled the dialog!\nImage processing canceled!\n")
return
dichroics = []
for i in range(numChannels):
dichroics.append(gdDM.getNextChoice())
merge = gdDM.getNextBoolean()
IJ.log("\nUser selected dichroic mirrors")
for i in range(numChannels):
IJ.log("\t\tChannel " + str(i+1) + ": " + dichroics[i])
if merge:
channels = []
chDict = {}
for i in range(numChannels):
chName = "Channel"+str(i+1)
channels.append(chName)
chDict[chName] = i
channels.append("NONE")
colourChoices = ["red", "green", "blue", "gray", "cyan", "magenta", "yellow"]
gdMerge = GenericDialog("Merge channels")
for c in colourChoices:
gdMerge.addChoice(c + ":", channels, channels[numChannels])
gdMerge.showDialog()
if gdMerge.wasCanceled():
IJ.log("User canceled the dialog!\nImage processing canceled!\n")
return
IJ.log("\nUser selected channel colours")
mergeList = []
for i in range(len(colourChoices)):
ch = gdMerge.getNextChoice()
if ch == "NONE":
mergeList.append(None)
else:
mergeList.append(chDict[ch])
IJ.log("\t\t" + colourChoices[i] + ": " + ch)
# ask user for an output directory
dc = DirectoryChooser("Choose folder for output")
od = dc.getDirectory()
if od is None:
IJ.log("User canceled the dialog!\nImage processing canceled!\n")
return
if merge:
tifDir = od + "." + str(datetime.now()).replace(" ", "").replace(":", "") + "/"
if not os.path.exists(tifDir):
os.makedirs(tifDir)
IJ.log("\nCreated temporary folder: " + tifDir + "\n")
else:
IJ.log("Unable to create temporary folder!\n")
else:
tifDir = od + filenameExExt + "/"
if not os.path.exists(tifDir):
os.makedirs(tifDir)
IJ.log("\nCreated subfolder: " + tifDir + "\n")
else:
IJ.log("\nSubfolder " + tifDir + " already exists")
# correct images
tifFilePaths = []
for i in range(numChannels):
ip = extractChannel(oirFile=filepath, ch=i)
if dichroics[i] == "DM1":
IJ.log("Channel " + str(i+1) + " was imaged using DM1, so no correction required.")
else:
offsets = getOffset(obj=objLensName,dm=dichroicDict[dichroics[i]])
xom = offsets['x']
yom = offsets['y']
if abs(totalRotation) > 0.1:
rotOff = rotateOffset(x=xom, y=yom, angle=-totalRotation)
xom = rotOff['x']
yom = rotOff['y']
xop = int(round(xom/pxSizeX))
yop = int(round(yom/pxSizeY))
IJ.log("Channel " + str(i+1) + " offsets")
IJ.log("\t\tMicrometres")
IJ.log("\t\t\t\tx = " + str(xom))
IJ.log("\t\t\t\ty = " + str(yom))
IJ.log("\t\tPixels")
IJ.log("\t\t\t\tx = " + str(xop))
IJ.log("\t\t\t\ty = " + str(yop))
IJ.run(ip, "Translate...", "x=" + str(-xop) + " y=" + str(-yop) + " interpolation=None stack")
tifFilePath = tifDir + filenameExExt + "_ch_"+str(i+1)+".tif"
tifFilePaths.append(tifFilePath)
if os.path.exists(tifFilePath):
IJ.log("\nOutput file exists: " + tifFilePath)
IJ.log("Rerun plugin choosing a different output folder")
IJ.log("or delete file and then rerun plugin.")
IJ.log("Image processing terminated!\n")
return
FileSaver(ip).saveAsTiff(tifFilePath)
if merge:
for i in range(len(mergeList)):
if mergeList[i] != None:
mergeList[i] = readSingleChannelImg(tifFilePaths[mergeList[i]])
merged = RGBStackMerge.mergeChannels(mergeList, False)
mergedChannelFilepath = od + filenameExExt + ".tif"
if os.path.exists(mergedChannelFilepath):
IJ.log("\nOutput file exists: " + mergedChannelFilepath)
IJ.log("Rerun plugin choosing a different output folder")
IJ.log("or delete file and then rerun plugin.")
IJ.log("Image processing terminated!\n")
FileSaver(merged).saveAsTiff(mergedChannelFilepath)
for tf in tifFilePaths:
os.remove(tf)
os.rmdir(tifDir)
IJ.log("\nFinished processing file:\n" + filepath + "\n")
if merge:
IJ.log("Image file with channels aligned:\n" + od + filenameExExt + ".tif\n")
else:
IJ.log("Aligned images (one tiff file for each channel) can be found in:\n" + tifDir + "\n")
from ij import IJ
from ij.io import OpenDialog
from loci.formats import ImageReader
from loci.formats import MetadataTools
# open file
od = OpenDialog("Choose a file");
filepath = od.getPath()
print("Image path: " + filepath);
# use bio-formats to extract information
reader = ImageReader()
omeMeta = MetadataTools.createOMEXMLMetadata()
reader.setMetadataStore(omeMeta)
reader.setId(filepath)
seriesCount = reader.getSeriesCount()
print "Series count:",seriesCount
reader.close()
def get_lif_series_length(fpath): reader = ImageReader() reader.setId(fpath) return reader.getSeriesCount();
omeMeta.setResolutionSizeX(PositiveInteger(int(reader.getSizeX() / divScale)), 0, i + 1)
omeMeta.setResolutionSizeY(PositiveInteger(int(reader.getSizeY() / divScale)), 0, i + 1)
# setup writer with tiling
writer = PyramidOMETiffWriter()
writer.setMetadataRetrieve(omeMeta)
tileSizeX = writer.setTileSizeX(tileSizeX)
tileSizeY = writer.setTileSizeY(tileSizeY)
writer.setId(outFile)
type = reader.getPixelType()
# create image scaler for downsampling
scaler = SimpleImageScaler()
# convert to Pyramidal OME-TIFF using tiling
for series in range(reader.getSeriesCount()):
reader.setSeries(series)
writer.setSeries(series)
# convert each image in the current series
for image in range(reader.getImageCount()):
width = reader.getSizeX()
height = reader.getSizeY()
# Determined the number of tiles to read and write
nXTiles = int(math.floor(width / tileSizeX))
nYTiles = int(math.floor(height / tileSizeY))
if nXTiles * tileSizeX != width:
nXTiles = nXTiles + 1
if nYTiles * tileSizeY != height:
nYTiles = nYTiles + 1;
