Watershed methods using Jython scripting and the ImageJ/ImgLib2/MorphoLibJ APIs. http://javadoc.scijava.org

create_gradient_image_for_watershed.py

"""Calculating the gradient image that needs to go into Watershed."""
from ij import IJ

# operates on ImagePlus object: imp
IJ.run(imp, "Gradient (3D)", "use")
# modifies imp, returns None.
# YOU MUST MAKE A COPY OF IMP BEFORE YOU RUN THIS! 
# This method also automatically displays the modified gradient image (unless you suppress it). 
# Output image name is always "Rebinned" - change it to something better afterwards.

watershed_snippet_morpholibj.py

# @OpService ops
from ij import IJ, ImagePlus
from net.imglib2.img import ImagePlusAdapter
from inra.ijpb.watershed import Watershed
from net.imglib2.roi.labeling import LabelRegions, LabelRegion, BoundingBox
from net.imglib2.algorithm.labeling.ConnectedComponents import StructuringElement

edges = IJ.openImage()  # opens file picker
seeds = IJ.openImage()  # opens file picker
output_watershed = Watershed().computeWatershed(edges.getStack(), seeds.getStack(), 26) # pixel connectivity = 26
output_ImagePlus = ImagePlus("Watershed result", output_watershed)  # to ImagePlus (from stack type)
output_ImagePlus.show()
output_ImgPlus = ImagePlusAdapter.wrapImgPlus(output_ImagePlus)  # to ImgPlus
# MUST convert watershed output into binary image, or else len(labelSet) = 0 !
watershed_binary_image = ops.run("convert.bit", output_ImgPlus)  # to binary type ImgPlus
labels = ops.labeling().cca(watershed_binary_image, StructuringElement.EIGHT_CONNECTED) # returns ImgLabeling object
regions = LabelRegions(labels)  # returns regions found from labels of connected components analysis