def get_imageFile_from_microscope(winReg_location, winReg_separator, winReg_waitIntervall):
txt_out("waiting for microscope...")
wr = WindowsRegistry()
#reg = wr.writeRegistry(winReg_location,"Code","0")
#reg = wr.writeRegistry(winReg_location,"filepath",test_filename)
#txt_out("write: "+reg)
while True:
# check microscope status
time.sleep(winReg_waitIntervall)
output = wr.readRegistry(winReg_location,"Code")
#txt_out("microscope status: " + str(output))
#winReg_address, winReg_name, winReg_type, winReg_value = output.split(winReg_separator)
winReg_rest, winReg_value = output.split(winReg_separator)
code = winReg_value.strip()
if (code==LSM510_CODE_READIMAGE) or (code==LSM510_CODE_READIMAGE_HIGHRES) :
txt_out("microscope requesting action! obtaining image file name...")
output = wr.readRegistry(winReg_location,"filepath")
#winReg_address, winReg_name, winReg_type, winReg_value = output.split(winReg_separator)
winReg_rest, winReg_value = output.split(winReg_separator)
image_file = winReg_value.strip() # get rid of the line feed and stuff like this
txt_out("image file name: " + image_file)
txt_out("code: " + code)
# tell all programs to wait
reg = wr.writeRegistry(winReg_location,"Code",LSM510_CODE_ALLWAIT)
break
return code, image_file
def get_realvnc_key():
reg = None
for k in [
'vncserver',
'WinVNC4',
]:
try:
reg = wreg.WindowsRegistry('RealVNC', k)
break
except WindowsError as e:
if 'The system cannot find the file specified' in str(e):
pass
else:
raise e
return reg
def main():
parser = argparse.ArgumentParser(
description='Encrypt or Decrypt a VNC password')
parser.add_argument("-d", "--decrypt", dest="decrypt", action="store_true", default=False, \
help="Decrypt an obfuscated password.")
parser.add_argument("-e", "--encrypt", dest="decrypt", action="store_false", default=False, \
help="Encrypt a plaintext password. (default mode)")
parser.add_argument("-H", "--hex", dest="hex", action="store_true", default=False, \
help="Assume input is in hex.")
parser.add_argument("-R", "--registry", dest="registry", action="store_true", default=False, \
help="Input or Output to the windows registry.")
parser.add_argument("-f", "--file", dest="filename", \
help="Input or Output to a specified file.")
parser.add_argument("passwd", nargs='?', \
help="A password to encrypt")
parser.add_argument("-t", "--test", dest="test", action="store_true", default=False, \
help="Run the unit tests for this program.")
args = parser.parse_args()
if (args.test):
run_tests()
if (args.filename == None and args.passwd == None
and (args.registry == False
or not platform.system().startswith('Windows'))):
parser.error('Error: No password file or password passed\n')
if (args.registry and args.decrypt
and platform.system().startswith('Windows')):
reg = wreg.WindowsRegistry("RealVNC", "WinVNC4")
(args.passwd, key_type) = reg.getval("Password")
elif not platform.system().startswith('Windows'):
print 'Cannot read from Windows Registry on a %s system' % platform.system(
)
if (args.passwd != None and args.hex):
args.passwd = unhex(args.passwd)
if (args.filename != None and args.decrypt):
args.passwd = do_file_in(args.filename, args.hex)
# If the hex encoded passwd length is longer than 16 hex chars and divisible
# by 16, then we chop the passwd into blocks of 64 bits (16 hex chars)
# (1 hex char = 4 binary bits = 1 nibble)
hexpasswd = args.passwd.encode('hex')
if (len(hexpasswd) > 16 and (len(hexpasswd) % 16) == 0):
print 'INFO: Detected ciphertext > 64 bits... breaking into blocks to decrypt...'
splitstr = split_len(args.passwd.encode('hex'), 16)
print 'INFO: Split blocks = %s' % splitstr
cryptedblocks = []
for sblock in splitstr:
cryptedblocks.append(do_crypt(sblock.decode('hex'), args.decrypt))
#print '%016s\t%s' % ( sblock, cryptedblocks )
crypted = ''.join(cryptedblocks)
elif (len(hexpasswd) <= 16):
crypted = do_crypt(args.passwd, args.decrypt)
else:
if (args.decrypt):
print 'WARN: Ciphertext length was not divisible by 8 (hex/16).'
print 'Length: %d' % len(args.passwd)
print 'Hex Length: %d' % len(hexpasswd)
crypted = do_crypt(args.passwd, args.decrypt)
if (args.filename != None and not args.decrypt):
do_file_out(args.filename, crypted, args.hex)
if (args.registry and not args.decrypt
and platform.system().startswith('Windows')):
reg = wreg.WindowsRegistry("RealVNC", "WinVNC4")
reg.setval('Password', crypted, wreg.WindowsRegistry.REG_BINARY)
elif not platform.system().startswith('Windows'):
print 'Cannot write to Windows Registry on a %s system' % platform.system(
)
prefix = ('En', 'De')[args.decrypt == True]
print "%scrypted Bin Pass= '******'" % (prefix, crypted)
print "%scrypted Hex Pass= '******'" % (prefix, crypted.encode('hex'))
def run():
# project = "andrea_boni_ellenberg"
project = "julia_roberti_ellenberg"
# running modalities
max_images_to_analyse = 10000 #10000
communicateWithMicroscope = True
#winReg_separator = " "
winReg_separator = "REG_SZ"
winReg_waitIntervall = 1
microscope = LSM780 # LSM510
#winReg_location = "HKLM\SOFTWARE\Test"
winReg_location = "HKCU\SOFTWARE\VB and VBA Program Settings\OnlineImageAnalysis\macro"
if project == "andrea_boni_ellenberg":
particles_area_min = 3750 # divide by 4 for 512x512
particles_area_max = 12500 # divide by 4 for 512x512
particles_minCirc = 0.5
particles_maxCirc = 1.0
particles_threshold_method = "globalOtsuThreshold"
particle_selectionMode = "nuclear_rim_intensity"
iSlice_particles = 2
iSlice_measurement = 1
meanIntensThreshold = 30
nPixShrink = 2
nPixDilate = 10
minCellsPerImage = 1 # required cells per image
minCellsPerWell = 4 # required cells per well
drawRings = False # True or False !!needs to be False for the real measurement !!
elif project == "julia_roberti_ellenberg":# !!!!!!!!!!!CHANGE PARAMETERS HERE!!!!!!!!!!!!!!!!!
particles_area_min = 1001 # depends whether you use 512x512 or something else
particles_area_max = 5000
particles_minCirc = 0.0 # reject non-round particles
particles_maxCirc = 1.0
particles_threshold_method = "globalOtsuThreshold"
particle_selectionMode = "nuclear_intensity"
iSlice_particles = 2 # channel containing the particle marker
iSlice_measurement = 1 # channel to be measured
intensityThreshold = 300 # if depends on microscope settings
criterium = "mean_intensity" # !!! intensityThreshold is the mean
# criterium = "total_intensity" # !!! intensityThreshold is the total
else:
particles_area_min = 15000
particles_area_max = 50000
particles_area_min = 50
particles_minCirc = 0.0
particles_maxCirc = 1.0
particles_threshold_method = "autoLocalThreshold"
particle_selectionMode = "classification"
if particle_selectionMode == "classification":
# select classifier file
classifier_file = "/Users/tischi/Documents/40x_widefield_cherry_bg_interphase_mitosis.model.model"
classifier_file = "Z:/software/micropilot/Tischi-FIJI/testimages/3metaphase.model"
#classifier_file = "D:/data/iliana/training_06_liveh2bcherry_tubgfp/classifier.model"
ws = WekaSegmentation() # create an instance
ws.loadClassifier(classifier_file) # load classifier
for iImageAnalyzed in range(max_images_to_analyse):
# txt_out(str(iImageAnalyzed))
if communicateWithMicroscope:
code, image_file = get_imageFile_from_microscope(winReg_location, winReg_separator, winReg_waitIntervall)
else:
code = LSM510_CODE_READIMAGE
image_file = test_filename
# prepare output
sX = "0"
sY = "0"
sOrientation = "0"
if project == "andrea_boni_ellenberg":
pass # parameters have been set above
elif code == LSM510_CODE_READIMAGE:
particles_radius = 50 # ask the user
particles_threshold = 2 # ask the user (pixels > mean + threshold*sd)
elif code == LSM510_CODE_READIMAGE_HIGHRES:
particles_radius = 4*50 # ask the user
particles_threshold = 2 # ask the user (pixels > mean + threshold*sd)
# clean up for new stuff **********************
# close all open windows
if WindowManager.getIDList() != None:
#print "WindowManager.getIDList :"
#print WindowManager.getIDList()
for iImage in WindowManager.getIDList():
imp = WindowManager.getImage(iImage)
imp.changes = False
#imp.close()
imp.getWindow().close()
# clean up old ROIs
if RoiManager.getInstance() != None:
RoiManager.getInstance().runCommand("reset")
# end of clean up *****************************
# run("Bio-Formats Importer", " open=D:\\data\\tischi\\_R1.lsm color_mode=Default view=Hyperstack stack_order=XYCZT");
#imp_image_tmp = ImagePlus(image_file)
#imp_image_tmp.show()
# OPEN THE IMAGE
ImagePlus(image_file).show() # todo: check for errors while opening!!
imp_image = IJ.getImage()
IJ.run(imp_image, "Properties...", "unit=pix pixel_width=1 pixel_height=1 voxel_depth=1 origin=0,0")
# find particles
txt_out("finding particles...")
# get/generate/extract the image containing the particles
if project == "andrea_boni_ellenberg":
imp_image.setSlice(iSlice_particles)
#imp_particles = imp_image.duplicate()
# todo; how to only duplicate the current slice??
IJ.run(imp_image, "Duplicate...", "title=im_particles");
imp_particles = IJ.getImage()
elif project == "julia_roberti_ellenberg":
IJ.run(imp_image, "Z Project...", "projection=[Max Intensity]");
imp_zMax = IJ.getImage()
imp_zMax.setSlice(iSlice_particles)
IJ.run(imp_zMax, "Duplicate...", "title=im_particles");
imp_particles = IJ.getImage()
else:
imp_particles = None
# smooth
IJ.run(imp_particles, "Median...", "radius=5 slice");
# threshold
txt_out("thresholding...")
imp_mask = imp_particles.duplicate()
IJ.run(imp_mask, "8-bit", "")
if particles_threshold_method == "globalFixedThreshold":
ip = imp_mask.getProcessor()
ip.setThreshold(particles_threshold, 255, ImageProcessor.NO_LUT_UPDATE)
IJ.run(imp_mask, "Convert to Mask", "")
if particles_threshold_method == "globalOtsuThreshold":
IJ.run(imp_mask, "Auto Threshold", "method=Otsu white")
elif particles_threshold_method == "autoLocalThreshold":
alt = Auto_Local_Threshold()
alt.exec(imp_mask,"Niblack",particles_radius,particles_threshold,0.0,True)
# post-processing of the binary image (e.g. watershed touching objects)
imp_mask.show()
# Create a ParticleAnalyzer, with arguments:
# 1. options (could be SHOW_ROI_MASKS, SHOW_OUTLINES, SHOW_MASKS, SHOW_NONE, ADD_TO_MANAGER, and others; combined with bitwise-or)
# 2. measurement options (see [http://rsb.info.nih.gov/ij/developer/api/ij/measure/Measurements.html Measurements])
# 3. a ResultsTable to store the measurements
# 4. The minimum size of a particle to consider for measurement
# 5. The maximum size (idem)
# 6. The minimum circularity of a particle
# 7. The maximum circularity
table = ResultsTable()
pa = ParticleAnalyzer(ParticleAnalyzer.ADD_TO_MANAGER | ParticleAnalyzer.EXCLUDE_EDGE_PARTICLES, Measurements.CENTROID | Measurements.CENTER_OF_MASS | Measurements.ELLIPSE | Measurements.AREA, table, particles_area_min, Double.POSITIVE_INFINITY, particles_minCirc, particles_maxCirc)
pa.setHideOutputImage(False)
if pa.analyze(imp_mask):
pass
else:
print "There was a problem in analyzing the particles"
return()
# initialise
nGoodParticles = 0
iBestParticle = 0
if (RoiManager.getInstance() != None): # found a particle
if (len(RoiManager.getInstance().getRoisAsArray()) > 0): # found a particle
# todo: show the outlines on the original grayscale image
#imp = pa.getOutputImage()
#table.show("")
# find "the best" particle
if particle_selectionMode == "classification":
ws.setTrainingImage(imp_image)
#ws.loadClassifier(classifier_file)
myClassNumber = 0 # ask the user
#/** * Apply current classifier to a given image. *
#* @param imp image (2D single image or stack)
#* @param numThreads The number of threads to use. Set to zero for
#* auto-detection.
#* @param probabilityMaps create probability maps for each class instead of
#* a classification
#* @return result image
#*/ public ImagePlus applyClassifier(final ImagePlus imp, int numThreads, final boolean probabilityMaps)
IJ.log("Searching for class "+str(ws.getClassLabel(myClassNumber)))
imp_probabilities = ws.applyClassifier(imp_image,0,True)
# show the classification results and rename the images in the stack to show the class names
stack = imp_probabilities.getStack()
for iClass in range(0,imp_probabilities.getImageStackSize()):
stack.setSliceLabel(ws.getClassLabel(iClass), iClass+1)
imp_probabilities.setStack(stack)
imp_probabilities.setSlice(myClassNumber+1)
imp_probabilities.show()
# Create a new list to store the mean intensity values of each class:
means = []
classification_max = 0
imp_myClass = ImagePlus("myClass",imp_probabilities.getProcessor().duplicate())
for i, roi in enumerate(RoiManager.getInstance().getRoisAsArray()):
imp_myClass.setRoi(roi)
stats = imp_myClass.getStatistics(Measurements.MEAN)
if stats.mean > classification_max:
classification_max = stats.mean
iBestParticle = i
table.setValue("classification", i, stats.mean)
elif particle_selectionMode == "nuclear_rim_intensity":
if project == "julia_roberti_ellenberg":
pass
else:
imp= imp_image
imp.setSlice(iSlice_measurement)
IJ.run(imp, "Duplicate...", "title=signal");
imp_measure = IJ.getImage()
# loop through the particles
for i, roi in enumerate(RoiManager.getInstance().getRoisAsArray()):
imp_measure.setRoi(roi)
IJ.run(imp_measure, "Enlarge...", "enlarge=-"+str(nPixShrink));
if drawRings:
IJ.run(imp_measure, "Draw", "");
stats = imp_measure.getStatistics(Measurements.MEAN + Measurements.AREA)
areaSmall = stats.area
meanIntensSmall = stats.mean
IJ.run(imp_measure, "Enlarge...", "enlarge="+str(nPixDilate+nPixShrink));
if drawRings:
IJ.run(imp_measure, "Draw", "");
stats = imp_measure.getStatistics(Measurements.MEAN + Measurements.AREA)
areaLarge = stats.area
meanIntensLarge = stats.mean
meanIntensRing = (meanIntensLarge*areaLarge - meanIntensSmall*areaSmall ) / (areaLarge - areaSmall)
txt_out("mean intens ring: " + str(int(meanIntensRing)) + "/" +str(meanIntensThreshold) )
# only count valid cells
if (meanIntensRing > meanIntensThreshold) & (areaSmall < particles_area_max):
nGoodParticles = nGoodParticles + 1
elif particle_selectionMode == "nuclear_intensity":
if project == "julia_roberti_ellenberg":
imp = imp_zMax
else:
imp = imp_image
imp.setSlice(iSlice_measurement)
IJ.run(imp, "Duplicate...", "title=signal");
imp_measure = IJ.getImage()
# loop through the cells
intens_current_max = -1
for i, roi in enumerate(RoiManager.getInstance().getRoisAsArray()):
imp_measure.setRoi(roi)
stats = imp_measure.getStatistics(Measurements.MEAN + Measurements.AREA)
txt_out("particle " + str(i) + " mean: " + str(int(stats.mean)) + " area: " + str(int(stats.area)))
# only count valid cells
if (criterium == "mean_intensity"):
intensity_measure = stats.mean
elif (criterium == "total_intensity"):
intensity_measure = stats.mean*stats.area
if (intensity_measure > intensityThreshold) & (stats.area < particles_area_max):
nGoodParticles = nGoodParticles + 1 # count valid
if (intensity_measure > intens_current_max):
iBestParticle = i
intens_current_max = intensity_measure
# get location and orientation of the best particle
x = table.getColumn(table.getColumnIndex("X"))
y = table.getColumn(table.getColumnIndex("Y"))
angle = table.getColumn(table.getColumnIndex("Angle"))
dx = int(x[iBestParticle]-imp_image.getWidth()/2)
dy = int(y[iBestParticle]-imp_image.getWidth()/2)
angle = int(angle[iBestParticle])
txt_out("number of good particles: " + str(nGoodParticles))
if project == "andrea_boni_ellenberg":
code = "validCells_"+str(int(nGoodParticles))+"_"+str(int(minCellsPerImage))+"_"+str(int(minCellsPerWell))
txt_out(code)
elif project == "julia_roberti_ellenberg":
if nGoodParticles >= 1:
sX = str(-dx) #.replace(".",",")
sY = str(-dy) #.replace(".",",")
sOrientation = str(angle) #.replace(".",",")
code = LSM780_CODE_OBJECT_FOUND_AND_START_IMAGING
txt_out("index of best good particle: " + str(iBestParticle))
else:
sX = "0"
sY = "0"
sOrientation = "0"
code = LSM780_CODE_NO_OBJECT_FOUND
elif microscope == LSM510:
sX = str(dx) #.replace(".",",")
sY = str(dy) #.replace(".",",")
sOrientation = str(angle) #.replace(".",",")
code = LSM510_CODE_OBJECT_FOUND
elif microscope == LSM780:
sX = str(-dx) #.replace(".",",")
sY = str(-dy) #.replace(".",",")
sOrientation = str(angle) #.replace(".",",")
code = LSM780_CODE_OBJECT_FOUND_AND_START_IMAGING
#table.show("")
# write results to windows registry
txt_out("sX "+ sX)
txt_out("sY "+ sY)
txt_out("sOrientation "+ sOrientation)
wr = WindowsRegistry()
reg = wr.writeRegistry(winReg_location,"offsetx",sX)
reg = wr.writeRegistry(winReg_location,"offsety",sY)
reg = wr.writeRegistry(winReg_location,"orientation",sOrientation)
reg = wr.writeRegistry(winReg_location,"Code",code)
# clean up to save memory
wr = None
pa = None
ws = None
return()
