def analyze_cells(imp, size, i, zmin): test = [] cdf = [] #ip = imp.getProcessor() #print "grabbing image..." #test = ip.getHistogram() #test = StackStatistics(imp).getHistogram() #print "calculating stack statistics..." #total = sum(test) #print "calculate threshold" #cdf = map(lambda x: x/float(total), acc(test)) #thresh = min(filter(lambda x: cdf[x] >= quantile, xrange(1,len(cdf)) )) max_int = StackStatistics(imp).max cal= imp.getCalibration() scale2D = cal.pixelWidth / cal.pixelDepth sigma = (size / cal.pixelWidth) * scale2D iso = Compute.inFloats(Scale2D(ImgLib.wrap(imp),scale2D)) peaks = DoGPeaks(iso, sigma, sigma * 0.5, thresh, 1) print "FOund", len(peaks), "peaks" ps = [] file = open(folder+str(i).zfill(4)+'_test_out.csv','w') exporter = csv.writer(file) for peak in peaks: if peak[2]>=zmin: print "raw",peak p = Point3f(peak) p.scale(cal.pixelWidth * 1/scale2D) print "sf", cal.pixelWidth * 1/scale2D print "scaled", p ps.append(p) t = () exporter.writerow([p.x, p.y, p.z]) file.close() if vis: iso = Compute.inFloats(Scale2D(Red(ImgLib.wrap(imp)),scale2D)) univ = Image3DUniverse(512,512) univ.addIcospheres(ps,Color3f(1,0,0), 2, size/2, "Cells").setLocked(True) univ.addOrthoslice(imp).setLocked(True) univ.show()
from net.imglib2.img.display.imagej import ImageJFunctions
from net.imglib2.view import Views
from itertools import imap
from java.lang import System
from net.imglib2.roi import EllipseRegionOfInterest
from net.imglib2 import Point, RealPoint
cell_diameter = 5 # in microns
minPeak = 40 # The minimum intensity for a peak to be considered so.
imp = IJ.getImage(
) #IJ.openImage("http://pacific.mpi-cbg.de/samples/first-instar-brain.zip")
# Scale the X,Y axis down to isotropy with the Z axis
cal = imp.getCalibration()
scale2D = cal.pixelWidth / cal.pixelDepth
iso = Compute.inFloats(Scale2D(Red(ImgLib.wrap(imp)), scale2D))
#ImgLib.wrap(iso).show()
# Find peaks by difference of Gaussian
sigma = (cell_diameter / cal.pixelWidth) * scale2D
peaks = DoGPeaks(iso, sigma, sigma * 0.5, minPeak, 1)
print "Found", len(peaks), "peaks"
# Copy ImgLib1 iso image into ImgLib2 copy image
copy = ArrayImgFactory().create(
[iso.getDimension(0),
iso.getDimension(1),
iso.getDimension(2)], FloatType())
c1 = iso.createCursor()
c2 = copy.cursor()
while c1.hasNext():
from script.imglib.math import Compute, Subtract
from script.imglib.color import Red, Green, Blue, RGBA
from script.imglib import ImgLib
from ij import IJ
# RGB image stack 열기
imp = IJ.openImage("https://imagej.nih.gov/ij/images/flybrain.zip")
# Wrap it as an Imglib image
img = ImgLib.wrap(imp)
# Example 1: subtract red from green channel
sub = Compute.inFloats(Subtract(Green(img), Red(img)))
ImgLib.wrap(sub).show()
# Example 2: subtract red from green channel, and compose a new RGBA image
rgb = RGBA(Red(img), Subtract(Green(img), Red(img)), Blue(img)).asImage()
ImgLib.wrap(rgb).show()
from script.imglib.math import Compute, Subtract, Multiply
from script.imglib.color import Red, Blue, RGBA
from script.imglib.algorithm import Gauss, Dither
from script.imglib import ImgLib
from ij import IJ
# Obtain a color image from the ImageJ samples
clown = ImgLib.wrap(IJ.openImage("https://imagej.nih.gov/ij/images/clown.jpg"))
# Example 1: compose a new image manipulating the color channels of the clown image:
img = RGBA(Gauss(Red(clown), 10), 40, Multiply(255,
Dither(Blue(clown)))).asImage()
print type(img)
ImgLib.wrap(img).show()
# Correct gamma
from script.imglib.math import Min, Max, Exp, Multiply, Divide, Log
from script.imglib.color import RGBA, Red, Green, Blue
from ij import IJ
from script.imglib import ImgLib
gamma = 0.5
# img = ImgLib.wrap(IJ.getImage())
img = ImgLib.wrap(IJ.openImage("https://imagej.nih.gov/ij/images/clown.jpg"))
ImgLib.wrap(img).show()
def g(channel, gamma):
""" Return a function that, when evaluated, computes the gamma
of the given color channel.
If 'i' was the pixel value, then this function would do:
double v = Math.exp(Math.log(i/255.0) * gamma) * 255.0);
if (v < 0) v = 0;
if (v >255) v = 255;
"""
return Min(255, Max(0, Multiply(Exp(Multiply(gamma, Log(Divide(channel, 255)))), 255)))
corrected = RGBA(g(Red(img), gamma), g(Green(img), gamma), g(Blue(img), gamma)).asImage()
ImgLib.wrap(corrected).show()