# statistics.py

# =============

#

# Derive pixel statistics of an image on the GPU

#

# Author: Robert Haase, [email protected]

# October 2019

#########################################

from ij import IJ;

from net.haesleinhuepf.clij2 import CLIJ2;

IJ.run("Close All");

# load example image

imp = IJ.openImage("http://wsr.imagej.net/images/blobs.gif");

# imp = IJ.openImage("c:/structure/data/blobs.tif");

imp.show();

# init GPU

clij2 = CLIJ2.getInstance();

# push image to GPU

input = clij2.push(imp);

meanIntensity = clij2.sumOfAllPixels(input) / input.getWidth() / input.getHeight();

IJ.log("Mean intensity of all pixels: " + str(meanIntensity));

# reserve memory for a mask and masked image, same size and type as input

mask = clij2.create(input);

masked = clij2.create(input);

# apply threshold method on GPU

clij2.automaticThreshold(input, mask, "Otsu");

# mask the image

clij2.mask(input, mask, masked);

# determine mean intensity of masked area:

meanIntensity = clij2.sumOfAllPixels(masked) / input.getWidth() / input.getHeight();

IJ.log("Mean intensity of masked pixels: " + str(meanIntensity));

# clean up

clij2.clear();