def preprocess_slices_giv_im(image_num,file_inpath,file_outpath):
imp = IJ.openImage(file_inpath)
file_names,rows = getLabels()
stack = imp.getImageStack()
stack2 = ImageStack(imp.width,imp.height)
for j in range(imp.getNSlices()):
if rows[j][image_num]== '0':
ip = stack.getProcessor(j+1)
NormalizeLocalContrast.run(ip, 341, 326, 4, True, True)
imagep = ImagePlus("imp",ip)
IJ.run(imagep, "Non-local Means Denoising", "sigma=15 smoothing_factor=1 slice")
imagep.setRoi(2,0,336,320);
IJ.run(imagep, "Level Sets", "method=[Active Contours] use_level_sets grey_value_threshold=50 distance_threshold=0.50 advection=2.20 propagation=1 curvature=1 grayscale=30 convergence=0.0025 region=inside")
fimp = IJ.getImage()
#fip = fimp.getProcessor()
fimp = removeSmallCCs(fimp)
fip = fimp.getProcessor()
stack2.addSlice(fip)
print("process")
else:
ip = stack.getProcessor(j+1)
stack2.addSlice(ip)
final_imp = ImagePlus("image",stack2)
output = "nrrd=["+file_outpath+"]"
IJ.run(final_imp, "Nrrd ... ", output)
def executeFilter(ip):
""" Given an ImageProcessor ip and a dictionary of parameters, filter the ip,
and return the same or a new ImageProcessor of the same dimensions and type. """
blockRadiusX = params["blockRadiusX"]
blockRadiusY = params["blockRadiusY"]
stds = params["stds"]
center = params["center"]
stretch = params["stretch"]
NormalizeLocalContrast.run(ip, blockRadiusX, blockRadiusY, stds, center,
stretch)
return ip
def getProcessor(self, n):
# Load the image at index n
filepath = os.path.join(self.getDirectory(), self.getFileName(n))
imp = IJ.openImage(filepath)
# Filter it:
ip = imp.getProcessor()
blockRadiusX = self.params["blockRadiusX"]
blockRadiusY = self.params["blockRadiusY"]
stds = self.params["stds"]
center = self.params["center"]
stretch = self.params["stretch"]
NormalizeLocalContrast.run(ip, blockRadiusX, blockRadiusY, stds, center, stretch)
return ip
def asNormalizedUnsignedByteArrayImg(blockRadius, stds, center, stretch, imp):
sp = imp.getProcessor() # ShortProcessor
NormalizeLocalContrast().run(sp, blockRadius, blockRadius, stds, center,
stretch)
return ArrayImgs.unsignedBytes(
sp.convertToByte(True).getPixels(),
[sp.getWidth(), sp.getHeight()])
def normalizeContrast(imp): # The width and height of the box centered at every pixel: blockRadiusX = 200 # in pixels blockRadiusY = 200 # The number of standard deviations to expand to stds = 2 # Whether to expand from the median value of the box or the pixel's value center = True # Whether to stretch the expanded values to the pixel depth of the image # e.g. between 0 and 255 for 8-bit images, or e.g. between 0 and 65536, etc. stretch = True # Duplicate the ImageProcessor copy_ip = imp.getProcessor().duplicate() # Apply contrast normalization to the copy NormalizeLocalContrast().run(copy_ip, 200, 200, stds, center, stretch) # Return as new image return ImagePlus(imp.getTitle(), copy_ip)
def normalizeContrast(imp):
# slide box 크기
blockRadiusX = 200 # pixel 단위
blockRadiusY = 200
# The number of standard deviations to expand to
stds = 2
# Whether to expand from the median value of the box or the pixel's value
center = True
# Whether to stretch the expanded values to the pixel depth of the image
# e.g. between 0 and 255 for 8-bit images, or e.g. between 0 and 65536, etc.
stretch = True
# Duplicate the ImageProcessor
copy_ip = imp.getProcessor().duplicate()
# Contrast Normalization을 copy에 적용
NormalizeLocalContrast().run(copy_ip, blockRadiusX, blockRadiusY, stds, center, stretch)
# Return as new image
return ImagePlus(imp.getTitle(), copy_ip)
# Read the dimensions from the first image
first_path = os.path.join(sourceDir, tiffImageFilenames(sourceDir).next())
width, height = dimensionsOf(first_path)
# Create the VirtualStack without a specific ColorModel
# (which will be set much later upon loading any slice)
vstack = VirtualStack(width, height, None, sourceDir)
# Add all TIFF images in sourceDir as slices in vstack
for filename in tiffImageFilenames(sourceDir):
vstack.addSlice(filename)
# Visualize the VirtualStack
imp = ImagePlus("virtual stack of images in " + os.path.basename(sourceDir), vstack)
# imp.show()
from mpicbg.ij.plugin import NormalizeLocalContrast
from ij.io import FileSaver
# slice마다 process 후 targetDir에 save
for i in xrange(0, vstack.size()):
ip = vstack.getProcessor(i+1) # slice list는 1부터 시작 (1-based listing)
# NormalizeLocalContrast plugin을 ImageProcessor에 적용
NormalizeLocalContrast.run(ip, 200, 200, 3, True, True)
# 결과 저장
name = vstack.getFileName(i+1)
if not name.lower().endswith(".tif"):
name += ".tif"
FileSaver(ImagePlus(name, ip)).saveAsTiff(os.path.join(targetDir, name))
def normLocalContrast(im, x, y, stdev, center, stretch): NormalizeLocalContrast().run(im.getProcessor(), x, y, stdev, center, stretch) # something like repaint needed ? return im