def runPoreDetection(inputImp, data, ops, display): name=inputImp.getTitle() inputDataset=Utility.getDatasetByName(data, name) detectionParameters=DetectionParams() roi=inputImp.getRoi() if (roi is None): message=name+": "+Messages.NoRoi IJ.write(message) return roi=inputImp.getRoi().clone(); header, statslist=poreDetectionTrueColor(inputImp, inputDataset, roi, ops, data, display, detectionParameters) directory, overlayname, roiname=Utility.createImageNames(inputImp) statsname=directory+'truecolor_stats.csv' IJ.save(inputImp, overlayname); IJ.saveAs(inputImp, "Selection", roiname); header.insert(0,Messages.FileName) statslist.insert(0,name) print header print statslist ExportDataFunction.exportSummaryStats(statsname, header, statslist)
def runPoreDetection(inputImp, data, ops, display):
name = inputImp.getTitle()
inputDataset = Utility.getDatasetByName(data, name)
detectionParameters = DetectionParams()
roi = inputImp.getRoi()
if (roi is None):
message = name + ": " + Messages.NoRoi
IJ.write(message)
return
roi = inputImp.getRoi().clone()
header, statslist = poreDetectionTrueColor(inputImp, inputDataset, roi,
ops, data, display,
detectionParameters)
directory, overlayname, roiname = Utility.createImageNames(inputImp)
statsname = directory + 'truecolor_stats.csv'
IJ.save(inputImp, overlayname)
IJ.saveAs(inputImp, "Selection", roiname)
header.insert(0, Messages.FileName)
statslist.insert(0, name)
print header
print statslist
ExportDataFunction.exportSummaryStats(statsname, header, statslist)
def runPoreDetection(inputImp, data, ops, display): # in this step get the image in the "imagej2" dataset format # this way we can take advantage of some of the new imagej2 functionality name=inputImp.getTitle() inputDataset=Utility.getDatasetByName(data, name) # this structure keeps track of detection parameters detectionParameters=DetectionParams() roi=inputImp.getRoi() # check if there is an roi on the image. If not return an error if (roi is None): message=name+": "+Messages.NoRoi IJ.write(message) return # clone the roi roi=inputImp.getRoi().clone(); # call the function that processes the UV image roilist, statslist, statsheader=poreDetectionUV(inputImp, inputDataset, roi, ops, data, display, detectionParameters) # get the names for the images that will be saved directory, overlayname, roiname=Utility.createImageNames(inputImp) # name of file to save summary stats statsname=os.path.join(directory, 'stats.csv') # save the image with overlay IJ.save(inputImp, overlayname); # save the roi IJ.saveAs(inputImp, "Selection", roiname); statsheader.insert(0,Messages.FileName) statslist.insert(0,name) ExportDataFunction.exportSummaryStats(statsname, statsheader, statslist) print statsname print statsheader print statslist
def runPoreDetection(inputImp, data, ops, display):
# in this step get the image in the "imagej2" dataset format
# this way we can take advantage of some of the new imagej2 functionality
name = inputImp.getTitle()
inputDataset = Utility.getDatasetByName(data, name)
# this structure keeps track of detection parameters
detectionParameters = DetectionParams()
roi = inputImp.getRoi()
# check if there is an roi on the image. If not return an error
if (roi is None):
message = name + ": " + Messages.NoRoi
IJ.write(message)
return
# clone the roi
roi = inputImp.getRoi().clone()
# call the function that processes the UV image
roilist, statslist, statsheader = poreDetectionUV(inputImp, inputDataset,
roi, ops, data, display,
detectionParameters)
# get the names for the images that will be saved
directory, overlayname, roiname = Utility.createImageNames(inputImp)
# name of file to save summary stats
statsname = os.path.join(directory, 'stats.csv')
# save the image with overlay
IJ.save(inputImp, overlayname)
# save the roi
IJ.saveAs(inputImp, "Selection", roiname)
statsheader.insert(0, Messages.FileName)
statslist.insert(0, name)
ExportDataFunction.exportSummaryStats(statsname, statsheader, statslist)
print statsname
print statsheader
print statslist
