def regBf(fn=None, imp=None, refId=None):
"""
Register a time series stack to a specified reference slice,
from a file (imported by BioFormat) or a stack ImagePlus.
Returns a registered ImagePlus.
The stack must have only 1 z layer.
refId is in the format of [int channel, int slice, int frame]
If no refId is supplied, will use the first slice [1,1,1]
Note: since TurboReg is used for registeration, there will be
temporary opened image windows.
"""
## Prepare the right ImagePlus
if imp is None:
if fn is None:
od = OpenDialog("Choose a file", None)
filename = od.getFileName()
if filename is None:
print "User canceled the dialog!"
return
else:
directory = od.getDirectory()
filepath = directory + filename
print "Selected file path:", filepath
else:
if os.path.exists(fn) and os.path.isfile(fn):
filepath = fn
else:
print "File does not exist!"
return
imps = BF.openImagePlus(filepath)
imp = imps[0]
if imp is None:
print "Cannot load file!"
return
else:
if fn is not None:
print "File or ImagePlus? Cannot load both."
return
width = imp.getWidth()
height = imp.getHeight()
# C
nChannels = imp.getNChannels()
# Z
nSlices = imp.getNSlices()
# T
nFrames = imp.getNFrames()
# pixel size
calibration = imp.getCalibration()
# Only supoort one z layer
if nSlices != 1:
print "Only support 1 slice at Z dimension."
return
# set registration reference slice
if refId is None:
refC = 1
refZ = 1
refT = 1
else:
refC = refId[0]
refZ = refId[1]
refT = refId[2]
if (refC not in range(1, nChannels + 1)
or refZ not in range(1, nSlices + 1)
or refT not in range(1, nFrames + 1)):
print "Invalid reference image!"
return
stack = imp.getImageStack()
registeredStack = ImageStack(width, height, nChannels * nFrames * nSlices)
# setup windows, these are needed by TurboReg
tmpip = FloatProcessor(width, height)
refWin = ImageWindow(ImagePlus("ref", tmpip))
bounds = refWin.getBounds()
# refWin.setVisible(False)
toRegWin = ImageWindow(ImagePlus("toReg", tmpip))
toRegWin.setLocation(bounds.width + bounds.x, bounds.y)
# toRegWin.setVisible(False)
toTransformWin = ImageWindow(ImagePlus("toTransform", tmpip))
toTransformWin.setLocation(2 * bounds.width + bounds.x, bounds.y)
# toTransformWin.setVisible(False)
# get reference image
refImp = ImagePlus("ref",
stack.getProcessor(imp.getStackIndex(refC, refZ, refT)))
refWin.setImage(refImp)
tr = TurboReg_()
for t in xrange(1, nFrames + 1):
IJ.showProgress(t - 1, nFrames)
# print "t ", t
# do TurboReg on reference channel
toRegId = imp.getStackIndex(refC, refZ, t)
toRegImp = ImagePlus("toReg", stack.getProcessor(toRegId))
toRegWin.setImage(toRegImp)
regArg = "-align " +\
"-window " + toRegImp.getTitle() + " " +\
"0 0 " + str(width - 1) + " " + str(height - 1) + " " +\
"-window " + refImp.getTitle() + " " +\
"0 0 " + str(width - 1) + " " + str(height - 1) + " " +\
"-rigidBody " +\
str(width / 2) + " " + str(height / 2) + " " +\
str(width / 2) + " " + str(height / 2) + " " +\
"0 " + str(height / 2) + " " +\
"0 " + str(height / 2) + " " +\
str(width - 1) + " " + str(height / 2) + " " +\
str(width - 1) + " " + str(height / 2) + " " +\
"-hideOutput"
tr = TurboReg_()
tr.run(regArg)
registeredImp = tr.getTransformedImage()
sourcePoints = tr.getSourcePoints()
targetPoints = tr.getTargetPoints()
registeredStack.setProcessor(registeredImp.getProcessor(), toRegId)
# toRegImp.flush()
# apply transformation on other channels
for c in xrange(1, nChannels + 1):
# print "c ", c
if c == refC:
continue
toTransformId = imp.getStackIndex(c, 1, t)
toTransformImp = ImagePlus("toTransform",
stack.getProcessor(toTransformId))
toTransformWin.setImage(toTransformImp)
transformArg = "-transform " +\
"-window " + toTransformImp.getTitle() + " " +\
str(width) + " " + str(height) + " " +\
"-rigidBody " +\
str(sourcePoints[0][0]) + " " +\
str(sourcePoints[0][1]) + " " +\
str(targetPoints[0][0]) + " " +\
str(targetPoints[0][1]) + " " +\
str(sourcePoints[1][0]) + " " +\
str(sourcePoints[1][1]) + " " +\
str(targetPoints[1][0]) + " " +\
str(targetPoints[1][1]) + " " +\
str(sourcePoints[2][0]) + " " +\
str(sourcePoints[2][1]) + " " +\
str(targetPoints[2][0]) + " " +\
str(targetPoints[2][1]) + " " +\
"-hideOutput"
tr = TurboReg_()
tr.run(transformArg)
registeredStack.setProcessor(
tr.getTransformedImage().getProcessor(), toTransformId)
# toTransformImp.flush()
sourcePoints = None
targetPoints = None
IJ.showProgress(t, nFrames)
IJ.showStatus("Frames registered: " + str(t) + "/" + str(nFrames))
refWin.close()
toRegWin.close()
toTransformWin.close()
imp2 = ImagePlus("reg_" + imp.getTitle(), registeredStack)
imp2.setCalibration(imp.getCalibration().copy())
imp2.setDimensions(nChannels, nSlices, nFrames)
# print "type ", imp.getType()
# print "type ", imp2.getType()
# print nChannels, " ", nSlices, " ", nFrames
# print registeredStack.getSize()
for key in imp.getProperties().stringPropertyNames():
imp2.setProperty(key, imp.getProperty(key))
# comp = CompositeImage(imp2, CompositeImage.COLOR)
# comp.show()
# imp2 = imp.clone()
# imp2.setStack(registeredStack)
# imp2.setTitle("reg"+imp.getTitle())
# imp2.show()
# imp.show()
return imp2
refpath = os.path.join(refdir, reffn)
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)
refpath = os.path.join(refdir, reffn)
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 main():
Interpreter.batchMode = True
if (lambda_flat == 0) ^ (lambda_dark == 0):
print ("ERROR: Both of lambda_flat and lambda_dark must be zero,"
" or both non-zero.")
return
lambda_estimate = "Automatic" if lambda_flat == 0 else "Manual"
#import pdb; pdb.set_trace()
print "Loading images..."
filenames = enumerate_filenames(pattern)
num_channels = len(filenames)
num_images = len(filenames[0])
image = Opener().openImage(filenames[0][0])
width = image.width
height = image.height
image.close()
# The internal initialization of the BaSiC code fails when we invoke it via
# scripting, unless we explicitly set a the private 'noOfSlices' field.
# Since it's private, we need to use Java reflection to access it.
Basic_noOfSlices = Basic.getDeclaredField('noOfSlices')
Basic_noOfSlices.setAccessible(True)
basic = Basic()
Basic_noOfSlices.setInt(basic, num_images)
# Pre-allocate the output profile images, since we have all the dimensions.
ff_image = IJ.createImage("Flat-field", width, height, num_channels, 32);
df_image = IJ.createImage("Dark-field", width, height, num_channels, 32);
print("\n\n")
# BaSiC works on one channel at a time, so we only read the images from one
# channel at a time to limit memory usage.
for channel in range(num_channels):
print "Processing channel %d/%d..." % (channel + 1, num_channels)
print "==========================="
stack = ImageStack(width, height, num_images)
opener = Opener()
for i, filename in enumerate(filenames[channel]):
print "Loading image %d/%d" % (i + 1, num_images)
image = opener.openImage(filename)
stack.setProcessor(image.getProcessor(), i + 1)
input_image = ImagePlus("input", stack)
# BaSiC seems to require the input image is actually the ImageJ
# "current" image, otherwise it prints an error and aborts.
WindowManager.setTempCurrentImage(input_image)
basic.exec(
input_image, None, None,
"Estimate shading profiles", "Estimate both flat-field and dark-field",
lambda_estimate, lambda_flat, lambda_dark,
"Ignore", "Compute shading only"
)
input_image.close()
# Copy the pixels from the BaSiC-generated profile images to the
# corresponding channel of our output images.
ff_channel = WindowManager.getImage("Flat-field:%s" % input_image.title)
ff_image.slice = channel + 1
ff_image.getProcessor().insert(ff_channel.getProcessor(), 0, 0)
ff_channel.close()
df_channel = WindowManager.getImage("Dark-field:%s" % input_image.title)
df_image.slice = channel + 1
df_image.getProcessor().insert(df_channel.getProcessor(), 0, 0)
df_channel.close()
print("\n\n")
template = '%s/%s-%%s.tif' % (output_dir, experiment_name)
ff_filename = template % 'ffp'
IJ.saveAsTiff(ff_image, ff_filename)
ff_image.close()
df_filename = template % 'dfp'
IJ.saveAsTiff(df_image, df_filename)
df_image.close()
print "Done!"
def main():
Interpreter.batchMode = True
if (lambda_flat == 0) ^ (lambda_dark == 0):
print ("ERROR: Both of lambda_flat and lambda_dark must be zero,"
" or both non-zero.")
return
lambda_estimate = "Automatic" if lambda_flat == 0 else "Manual"
print "Loading images..."
filenames = enumerate_filenames(pattern)
if len(filenames) == 0:
return
# This is the number of channels inferred from the filenames. The number
# of channels in an individual image file will be determined below.
num_channels = len(filenames)
num_images = len(filenames[0])
image = Opener().openImage(filenames[0][0])
if image.getNDimensions() > 3:
print "ERROR: Can't handle images with more than 3 dimensions."
(width, height, channels, slices, frames) = image.getDimensions()
# The third dimension could be any of these three, but the other two are
# guaranteed to be equal to 1 since we know NDimensions is <= 3.
image_channels = max((channels, slices, frames))
image.close()
if num_channels > 1 and image_channels > 1:
print (
"ERROR: Can only handle single-channel images with {channel} in"
" the pattern, or multi-channel images without {channel}. The"
" filename patterns imply %d channels and the images themselves"
" have %d channels." % (num_channels, image_channels)
)
return
if image_channels == 1:
multi_channel = False
else:
print (
"Detected multi-channel image files with %d channels"
% image_channels
)
multi_channel = True
num_channels = image_channels
# Clone the filename list across all channels. We will handle reading
# the individual image planes for each channel below.
filenames = filenames * num_channels
# The internal initialization of the BaSiC code fails when we invoke it via
# scripting, unless we explicitly set a the private 'noOfSlices' field.
# Since it's private, we need to use Java reflection to access it.
Basic_noOfSlices = Basic.getDeclaredField('noOfSlices')
Basic_noOfSlices.setAccessible(True)
basic = Basic()
Basic_noOfSlices.setInt(basic, num_images)
# Pre-allocate the output profile images, since we have all the dimensions.
ff_image = IJ.createImage("Flat-field", width, height, num_channels, 32);
df_image = IJ.createImage("Dark-field", width, height, num_channels, 32);
print("\n\n")
# BaSiC works on one channel at a time, so we only read the images from one
# channel at a time to limit memory usage.
for channel in range(num_channels):
print "Processing channel %d/%d..." % (channel + 1, num_channels)
print "==========================="
stack = ImageStack(width, height, num_images)
opener = Opener()
for i, filename in enumerate(filenames[channel]):
print "Loading image %d/%d" % (i + 1, num_images)
# For multi-channel images the channel determines the plane to read.
args = [channel + 1] if multi_channel else []
image = opener.openImage(filename, *args)
stack.setProcessor(image.getProcessor(), i + 1)
input_image = ImagePlus("input", stack)
# BaSiC seems to require the input image is actually the ImageJ
# "current" image, otherwise it prints an error and aborts.
WindowManager.setTempCurrentImage(input_image)
basic.exec(
input_image, None, None,
"Estimate shading profiles", "Estimate both flat-field and dark-field",
lambda_estimate, lambda_flat, lambda_dark,
"Ignore", "Compute shading only"
)
input_image.close()
# Copy the pixels from the BaSiC-generated profile images to the
# corresponding channel of our output images.
ff_channel = WindowManager.getImage("Flat-field:%s" % input_image.title)
ff_image.slice = channel + 1
ff_image.getProcessor().insert(ff_channel.getProcessor(), 0, 0)
ff_channel.close()
df_channel = WindowManager.getImage("Dark-field:%s" % input_image.title)
df_image.slice = channel + 1
df_image.getProcessor().insert(df_channel.getProcessor(), 0, 0)
df_channel.close()
print("\n\n")
template = '%s/%s-%%s.tif' % (output_dir, experiment_name)
ff_filename = template % 'ffp'
IJ.saveAsTiff(ff_image, ff_filename)
ff_image.close()
df_filename = template % 'dfp'
IJ.saveAsTiff(df_image, df_filename)
df_image.close()
print "Done!"
def regBf(fn=None, imp=None, refId=None):
"""
Register a time series stack to a specified reference slice,
from a file (imported by BioFormat) or a stack ImagePlus.
Returns a registered ImagePlus.
The stack must have only 1 z layer.
refId is in the format of [int channel, int slice, int frame]
If no refId is supplied, will use the first slice [1,1,1]
Note: since TurboReg is used for registeration, there will be
temporary opened image windows.
"""
## Prepare the right ImagePlus
if imp is None:
if fn is None:
od = OpenDialog("Choose a file", None)
filename = od.getFileName()
if filename is None:
print "User canceled the dialog!"
return
else:
directory = od.getDirectory()
filepath = directory + filename
print "Selected file path:", filepath
else:
if os.path.exists(fn) and os.path.isfile(fn):
filepath = fn
else:
print "File does not exist!"
return
imps = BF.openImagePlus(filepath)
imp = imps[0]
if imp is None:
print "Cannot load file!"
return
else:
if fn is not None:
print "File or ImagePlus? Cannot load both."
return
width = imp.getWidth()
height = imp.getHeight()
# C
nChannels = imp.getNChannels()
# Z
nSlices = imp.getNSlices()
# T
nFrames = imp.getNFrames()
# pixel size
calibration = imp.getCalibration()
# Only supoort one z layer
if nSlices != 1:
print "Only support 1 slice at Z dimension."
return
# set registration reference slice
if refId is None:
refC = 1
refZ = 1
refT = 1
else:
refC = refId[0]
refZ = refId[1]
refT = refId[2]
if (refC not in range(1, nChannels+1) or
refZ not in range(1, nSlices+1) or
refT not in range(1, nFrames+1) ):
print "Invalid reference image!"
return
stack = imp.getImageStack()
registeredStack = ImageStack(width, height, nChannels*nFrames*nSlices)
# setup windows, these are needed by TurboReg
tmpip = FloatProcessor(width, height)
refWin = ImageWindow(ImagePlus("ref", tmpip))
bounds = refWin.getBounds()
# refWin.setVisible(False)
toRegWin = ImageWindow(ImagePlus("toReg", tmpip))
toRegWin.setLocation(bounds.width + bounds.x, bounds.y)
# toRegWin.setVisible(False)
toTransformWin = ImageWindow(ImagePlus("toTransform", tmpip))
toTransformWin.setLocation(2 * bounds.width + bounds.x, bounds.y)
# toTransformWin.setVisible(False)
# get reference image
refImp = ImagePlus("ref", stack.getProcessor(imp.getStackIndex(refC, refZ, refT)))
refWin.setImage(refImp)
tr = TurboReg_()
for t in xrange(1, nFrames+1):
IJ.showProgress(t-1, nFrames)
# print "t ", t
# do TurboReg on reference channel
toRegId = imp.getStackIndex(refC, refZ, t)
toRegImp = ImagePlus("toReg", stack.getProcessor(toRegId))
toRegWin.setImage(toRegImp)
regArg = "-align " +\
"-window " + toRegImp.getTitle() + " " +\
"0 0 " + str(width - 1) + " " + str(height - 1) + " " +\
"-window " + refImp.getTitle() + " " +\
"0 0 " + str(width - 1) + " " + str(height - 1) + " " +\
"-rigidBody " +\
str(width / 2) + " " + str(height / 2) + " " +\
str(width / 2) + " " + str(height / 2) + " " +\
"0 " + str(height / 2) + " " +\
"0 " + str(height / 2) + " " +\
str(width - 1) + " " + str(height / 2) + " " +\
str(width - 1) + " " + str(height / 2) + " " +\
"-hideOutput"
tr = TurboReg_()
tr.run(regArg)
registeredImp = tr.getTransformedImage()
sourcePoints = tr.getSourcePoints()
targetPoints = tr.getTargetPoints()
registeredStack.setProcessor(registeredImp.getProcessor(), toRegId)
# toRegImp.flush()
# apply transformation on other channels
for c in xrange(1, nChannels+1):
# print "c ", c
if c == refC:
continue
toTransformId = imp.getStackIndex(c, 1, t)
toTransformImp = ImagePlus("toTransform", stack.getProcessor(toTransformId))
toTransformWin.setImage(toTransformImp)
transformArg = "-transform " +\
"-window " + toTransformImp.getTitle() + " " +\
str(width) + " " + str(height) + " " +\
"-rigidBody " +\
str(sourcePoints[0][0]) + " " +\
str(sourcePoints[0][1]) + " " +\
str(targetPoints[0][0]) + " " +\
str(targetPoints[0][1]) + " " +\
str(sourcePoints[1][0]) + " " +\
str(sourcePoints[1][1]) + " " +\
str(targetPoints[1][0]) + " " +\
str(targetPoints[1][1]) + " " +\
str(sourcePoints[2][0]) + " " +\
str(sourcePoints[2][1]) + " " +\
str(targetPoints[2][0]) + " " +\
str(targetPoints[2][1]) + " " +\
"-hideOutput"
tr = TurboReg_()
tr.run(transformArg)
registeredStack.setProcessor(tr.getTransformedImage().getProcessor(), toTransformId)
# toTransformImp.flush()
sourcePoints = None
targetPoints = None
IJ.showProgress(t, nFrames)
IJ.showStatus("Frames registered: " + str(t) + "/" + str(nFrames))
refWin.close()
toRegWin.close()
toTransformWin.close()
imp2 = ImagePlus("reg_"+imp.getTitle(), registeredStack)
imp2.setCalibration(imp.getCalibration().copy())
imp2.setDimensions(nChannels, nSlices, nFrames)
# print "type ", imp.getType()
# print "type ", imp2.getType()
# print nChannels, " ", nSlices, " ", nFrames
# print registeredStack.getSize()
for key in imp.getProperties().stringPropertyNames():
imp2.setProperty(key, imp.getProperty(key))
# comp = CompositeImage(imp2, CompositeImage.COLOR)
# comp.show()
# imp2 = imp.clone()
# imp2.setStack(registeredStack)
# imp2.setTitle("reg"+imp.getTitle())
# imp2.show()
# imp.show()
return imp2
