def rescaleimp(file_inpath,file_outpath): imp = IJ.openImage(file_inpath) img = ImgLib.wrap(imp) img2 = Resample(img,0.25) imp = ImgLib.wrap(img2) output = "nrrd=["+file_outpath+"]" IJ.run(imp, "Nrrd ... ", output)
def rescaleimp(file_inpath, file_outpath):
"""Function to rescale a single 3D NRRD image """
imp = IJ.openImage(file_inpath)
img = ImgLib.wrap(imp)
img2 = Resample(img, 0.25)
imp = ImgLib.wrap(img2)
output = "nrrd=[" + file_outpath + "]"
IJ.run(imp, "Nrrd ... ", output)
def rescale(folder_in,folder_out):
for filename in os.listdir(folder_in):
imp =IJ.openImage(os.path.join(folder_in,filename))
img = ImgLib.wrap(imp)
img2 = Resample(img,0.25)
imp=ImgLib.wrap(img2)
output = "nrrd=["+folder_out+filename+"]"
IJ.run(imp, "Nrrd ... ", output)
IJ.run("Collect Garbage", "");
def rescale(folder_in, folder_out):
"""Function to rescale 3D NRRD image series"""
for filename in os.listdir(folder_in):
imp = IJ.openImage(os.path.join(folder_in, filename))
img = ImgLib.wrap(imp)
img2 = Resample(img, 0.25)
imp = ImgLib.wrap(img2)
output = "nrrd=[" + folder_out + filename + "]"
IJ.run(imp, "Nrrd ... ", output)
imp = None
img = None
img2 = None
gc.collect()
time.sleep(15)
gc.collect()
IJ.run("Collect Garbage", "")
IJ.run("Collect Garbage", "")
from script.imglib.math import Compute, Divide, Multiply, Subtract
from script.imglib.algorithm import Gauss, Scale2D, Resample
from script.imglib import ImgLib
from ij import IJ, WindowManager
# Start Clean
IJ.run("Close All")
# 1. Open an image
imp = IJ.openImage("https://imagej.nih.gov/ij/images/bridge.gif")
ti = imp.getShortTitle()
img = ImgLib.wrap(imp)
# 2. Simulate a brighfield from a Gauss with a large radius
# (First scale down by 4x, then gauss of radius=20, then scale up)
brightfield = Resample(Gauss(Scale2D(img, 0.25), 20), img.getDimensions())
# 3. Simulate a perfect darkfield
darkfield = 0
# 4. Compute the mean pixel intensity value of the image
mean = reduce(lambda s, t: s + t.get(), img, 0) / img.size()
# 5. Correct the illumination
corrected = Compute.inFloats(Multiply(Divide(Subtract(img, brightfield),
Subtract(brightfield, darkfield)), mean))
# 6. ... and show it in ImageJ - it needs to be scaled. This is a 32 bit image
ImgLib.wrap(corrected).show()
# 7. JRM get the displayed image