def __NbFoci(self):
self.__boolFoci=True
self.__image.killRoi()
self.__image.setRoi(self.__contour)
self.__ip=self.__image.getProcessor()
rt=ResultsTable.getResultsTable()
rt.reset()
mf=MaximumFinder()
mf.findMaxima(self.__ip, self.__noise, 0, MaximumFinder.LIST, True, False)
self.__listMax[:]=[]
#feret=self.getFercoord()
#xc=feret[0]-((feret[0]-feret[2])/2.0)
#yc=feret[1]-((feret[1]-feret[3])/2.0)
#print xc, yc
xc=self.getXC()
yc=self.getYC()
#print xc, yc
for i in range(rt.getCounter()):
x=int(rt.getValue("X", i))
y=int(rt.getValue("Y", i))
size=self.__localwand(x, y, self.__ip, self.__seuilPeaks, self.__peaksMethod, self.__light)
coord=[(1, xc, x), (1, yc, y)]
d=self.distMorph(coord,"Euclidean distance")
d=( d / (self.getMaxF()/2) )*100
self.__listMax.append((x, y, size[0], size[1], size[2], size[3], size[4], d))
rt.reset()
def findCells(imp, rm, channel, noisetol, thresh):
'''
Function for finding cells as local maxima and creating an ROI showing them
imp: ImagePlus
rm: the current ROI manager
channel, int: the channel being processed (used for ROI name)
noisetol, thresh, ints: noise tolerance and pixel value threshold for findMaxima
returns the count
'''
# set the channel
imp.setC(channel)
# find maxima
ip = imp.getProcessor()
mf = MaximumFinder()
maxima = mf.findMaxima(ip, noisetol, thresh, MaximumFinder.SINGLE_POINTS,
False, False)
findmaximashow = ImagePlus("Found Maxima", maxima)
findmaximashow.show() # an image of all the points
maximaip = findmaximashow.getProcessor()
maximahist = maximaip.getHistogram()
cellCount = maximahist[255]
if cellCount != 0:
IJ.setRawThreshold(findmaximashow, 255, 255, "red")
IJ.run(findmaximashow, "Create Selection", "")
rm.addRoi(findmaximashow.getRoi()
) # a selection consisting of all the points
# close maxima image if present
if findmaximashow:
findmaximashow.close()
return cellCount
if output_type == 'Single_Points':
output_type_param = mf.SINGLE_POINTS
elif output_type == 'Maxima_Within_Tolerance':
output_type_param = mf.IN_TOLERANCE
elif output_type == 'Segmented_Particles':
output_type_param = mf.SEGMENTED
elif output_type == 'List':
output_type_param = mf.LIST
elif output_type == 'Count':
output_type_param = mf.COUNT
# Get a new byteProcessor with a normal (uninverted) LUT where
# the marked points are set to 255 (Background 0). Pixels outside
# of the roi of the input image_processor_copy are not set. No
# output image is created for output types POINT_SELECTION, LIST
# and COUNT. In these cases findMaxima returns null.
byte_processor = mf.findMaxima( image_processor_copy,
noise_tolerance,
ImageProcessor.NO_THRESHOLD,
output_type_param,
exclude_edge_maxima,
False )
# Invert the image or ROI.
byte_processor.invert()
if output_type == 'Segmented_Particles' and not light_background:
# Invert the values in this image's LUT (indexed color model).
byte_processor.invertLut()
image_plus = ImagePlus( "output", byte_processor )
IJ.saveAs( image_plus, output_datatype, tmp_output_path )
except Exception, e:
jython_utils.handle_error( error_log, str( e ) )
# by the tolerance.
mf = MaximumFinder()
if output_type == 'Single_Points':
output_type_param = mf.SINGLE_POINTS
elif output_type == 'Maxima_Within_Tolerance':
output_type_param = mf.IN_TOLERANCE
elif output_type == 'Segmented_Particles':
output_type_param = mf.SEGMENTED
elif output_type == 'List':
output_type_param = mf.LIST
elif output_type == 'Count':
output_type_param = mf.COUNT
# Get a new byteProcessor with a normal (uninverted) LUT where
# the marked points are set to 255 (Background 0). Pixels outside
# of the roi of the input image_processor_copy are not set. No
# output image is created for output types POINT_SELECTION, LIST
# and COUNT. In these cases findMaxima returns null.
byte_processor = mf.findMaxima(image_processor_copy, noise_tolerance,
ImageProcessor.NO_THRESHOLD,
output_type_param, exclude_edge_maxima,
False)
# Invert the image or ROI.
byte_processor.invert()
if output_type == 'Segmented_Particles' and not light_background:
# Invert the values in this image's LUT (indexed color model).
byte_processor.invertLut()
image_plus = ImagePlus("output", byte_processor)
IJ.saveAs(image_plus, output_datatype, tmp_output_path)
except Exception, e:
jython_utils.handle_error(error_log, str(e))
def __fmaxfinder(self) :
#stack = self.__impRes.getStack()
self.__impD.killRoi()
self.__impF.killRoi()
stack = self.__impF.getStack()
n_slices = stack.getSize()
#newstack=ImageStack(self.__impRes.getWidth(), self.__impRes.getHeight())
newstack=ImageStack(self.__impF.getWidth(), self.__impF.getHeight())
noise = self.__display3.text
for index in range(1,n_slices+1):
IJ.selectWindow(self.__impF.getTitle())
self.__impF.setSlice(index)
ip = self.__impF.getProcessor()
mf=MaximumFinder()
ipmax = mf.findMaxima(ip, int(noise), 0, 0, False, False)
newstack.addSlice("", ipmax)
newimage=ImagePlus("max points"+self.__name, newstack)
newimage.show()
newimage.updateAndDraw()
listip = []
maxh=self.__impRes.getHeight()
for roi in self.__cellsrois :
straightener = Straightener()
newimage.setSlice(roi[1])
newimage.setRoi(roi[0])
#listip.append(straightener.straighten(newimage, roi[0], int(self.__widthl)))
listip.append(straightener.straighten(newimage, roi[0], maxh))
ipw=[ ip.getWidth() for ip in listip ]
iph=[ ip.getHeight() for ip in listip ]
maxw=max(ipw)
maxh=max(iph)
if self.__enlarge : resizelist = [ ip.resize(maxw, maxh, True) for ip in listip ]
elif self.__alignC :
resizelist = []
for ip in listip :
tempip = ByteProcessor(maxw, maxh)
tempip.copyBits(ip, 0, 0, Blitter.COPY)
resizelist.append(tempip)
else :
resizelist = []
for ip in listip :
tempip = ByteProcessor(maxw, maxh)
tempip.copyBits(ip, 0, 0, Blitter.COPY)
resizelist.append(tempip)
ims = ImageStack(maxw, maxh)
#for ip in resizelist : ims.addSlice("", ip)
for i in range(len(resizelist)) :
ims.addSlice(self.__labels[i], resizelist[i])
self.__impMax = ImagePlus(self.__name+"-max", ims)
self.__impMax.show()
stack = self.__impMax.getStack() # get the stack within the ImagePlus
n_slices = stack.getSize()
for index in range(1, n_slices+1):
self.__impMax.killRoi()
self.__impMax.setSlice(index)
roi = self.__listrois[index-1]
if self.__sens[index-1]<0 :
self.__impMax.setRoi(roi)
ip1 = self.__impMax.getProcessor()
ip1.flipHorizontal()
self.__impMax.killRoi()
self.__impMax.updateAndDraw()
ip = self.__impMax.getProcessor()
for i in range(ip.getWidth()*ip.getHeight()) :
if ip.getf(i) > 0 : ip.setf(i, 255)
#else : ip.setf(i, 0)
IJ.run(self.__impMax, "8-bit", "")
IJ.run(self.__impMax, "Options...", "iterations=2 count=1 black edm=Overwrite do=Close stack")
IJ.run(self.__impMax, "Ultimate Points", "stack")
self.__impMax.updateAndDraw()
rt.reset() # supposed to reset the results table
postReset = rt.getCounter()
print "After resetting there are " + str(postReset) + " results"
IJ.run("Select None")
print "Using the IJ.run method with no threshold, I found " + str(
CountMethod1) + " maxima."
# ---- METHOD 2: API findMaxima WITH THRESHOLD AND SINGLE POINTS
# findMaxima(ImageProcessor ip, double tolerance, double threshold, int outputType, boolean excludeOnEdges, boolean isEDM)
# source: https://github.com/imagej/ImageJA/blob/8e283502055d25b9f0456f4aad95afa30a649d45/src/main/java/ij/plugin/filter/MaximumFinder.java
# note LIST produces list of coors, SINGLE POINTS produces a bunch of points that are shown by the code below.
# POINT_SELECTION is supposed to give just that but can't figure out how to get it in the manager
# https://stackoverflow.com/questions/26526269/image-analysis-finding-proteins-in-an-image
# https://github.com/bgruening/galaxytools/blob/18b441b263846cece9c5527cab0de66a54ecba3a/tools/image_processing/imagej2/imagej2_find_maxima/jython_script.py
maxima = mf.findMaxima(ip, 100.0, THRESH, MaximumFinder.SINGLE_POINTS, False,
False)
findmaximashow = ImagePlus("Found Maxima", maxima)
findmaximashow.show() # an image of all the points
maximaip = findmaximashow.getProcessor()
maximahist = maximaip.getHistogram()
CountMethod2 = maximahist[255]
print "Using the findMaxima method with a threshold of " + str(
THRESH) + ", I found " + str(CountMethod2) + " maxima."
IJ.setRawThreshold(findmaximashow, 255, 255, "red")
IJ.run(findmaximashow, "Create Selection", "")
rm.addRoi(findmaximashow.getRoi())
rm.rename(1, "Maxima with threshold")
# ---- METHOD 3-4: API getMaxima WITH THE POINTS COUNTED OR ADDED TO THE RESULTS TABLE
