# # This example Jython script shows how to # reslice an image in the GPU. # # # Author: Robert Haase, [email protected] # October 2019 ########################################## from net.haesleinhuepf.clij import CLIJ; from ij import IJ; IJ.run("Close All"); # init CLIJ and GPU clij = CLIJ.getInstance(); # get an example data set imp = IJ.openImage("http://imagej.nih.gov/ij/images/t1-head.zip"); imp.show(); imp.setRoi(86,3,100,250); imp = imp.crop("25-74"); imp.show(); # push it to the GPU src = clij.push(imp); # generate the output-image on the GPU with thee right size dst = clij.create([src.getWidth(), src.getDepth(), src.getHeight()], src.getNativeType()); # Reslice on GPU clij.op().resliceTop(src, dst);
return self.finished
def getCLIJ(self):
return self.clij2
#imp = IJ.openImage("C:/structure/data/2018-05-23-16-18-13-89-Florence_multisample/processed/tif/000116.raw.tif");
imp = IJ.openImage(
"https://bds.mpi-cbg.de/CLIJ_benchmarking_data/000461.raw.tif")
from net.haesleinhuepf.clij import CLIJ
from net.haesleinhuepf.clij2 import CLIJ2
# print out available OpenCL devices
print("Available devices:")
for name in CLIJ.getAvailableDeviceNames():
print(name)
# initialize a hand full of processors
processors = []
for i in range(0, len(CLIJ.getAvailableDeviceNames())):
processors.append(Processor(CLIJ2(CLIJ(i))))
from java.lang import System
startTime = System.currentTimeMillis()
# loop until a given number of images was processed
processed_images = 0
while (processed_images < 10):
# go trough all processors and see if one is doing nothing
# clinfo.py # =================== # # Output all information about found GPUs # (or rather: all found OpenCL devices) # # Author: Robert Haase, [email protected] # October 2019 ######################################### from ij import IJ from net.haesleinhuepf.clij import CLIJ IJ.log(CLIJ.clinfo())
# load single image
#imp = IJ.openImage("C:/structure/data/florence/000300.raw.tif");
#IJ.run(imp, "32-bit", "");
#imp.show();
# load sequence
IJ.run("Image Sequence...", "open=[" + data_folder + "] sort use")
IJ.run(
"Stack to Hyperstack...",
"order=xyczt(default) channels=1 slices=" + str(number_of_z_planes) +
" frames=" + str(number_of_images) + " display=Color")
imp = IJ.getImage()
# init GPU
clij = CLIJ.getInstance("1070")
# configure initial scaling step
calib = imp.getCalibration()
scaleX = calib.pixelWidth / calib.pixelDepth * zoom
scaleY = calib.pixelHeight / calib.pixelDepth * zoom
scaleZ = 1.0 * zoom
# initialize state
input = None
formerT = None
resultCylinderMaxProjection = None
resultMaxProjection = None
spots = None
circles = None
blobs = None
#@ OpService ops
#@ UIService ui
#@ Dataset data
#@ Dataset psf
from java.lang import System
# init CLIJ and GPU
from net.haesleinhuepf.clij import CLIJ
from net.haesleinhuepf.clij2 import CLIJ2
from net.haesleinhuepf.clijx.plugins import DeconvolveFFT
# show installed OpenCL devices
print CLIJ.getAvailableDeviceNames()
# initialize a device with a given name
clij2 = CLIJ2.getInstance("RTX")
clij2.clear()
print "Using GPU: " + clij2.getGPUName()
# transfer image to the GPU
gpuImg = clij2.push(data)
gpuPSF = clij2.push(psf)
# measure start time
start = System.currentTimeMillis()
# create memory for the output image first
gpuEstimate = clij2.create(gpuImg.getDimensions(), clij2.Float)
