# 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")
from ij.process import ImageProcessor, FloatProcessor, ShortProcessor, ByteProcessor, ColorProcessor, LUT
from net.haesleinhuepf.clij.clearcl import ClearCLBuffer
from net.haesleinhuepf.clij.coremem.enums import NativeTypeEnum
from net.haesleinhuepf.clij2 import CLIJ2
IJ.log('\\Clear') #efface le contenu de la console
grayLevelImagePlus = IJ.openImage()
grayLevelImagePlus.show()
totalCoefficient = float(1.5)
grayLevelImagePlusProcessor = grayLevelImagePlus.getProcessor()
grayLevelImagePlusMatrix = grayLevelImagePlusProcessor.getPixels()
#testGrayLevelImageMatrixBuffer = clij2_instance.pushMatXYZ(grayLevelImagePlusMatrix)
# init GPU
clij2_instance = CLIJ2.getInstance()
#Conversion 32bit to 8bit
testGrayLevelImageMatrixBuffer = clij2_instance.push(grayLevelImagePlus)
print("testGrayLevelImageMatrixBuffer dimensions: " +
str(clij2_instance.getDimensions(testGrayLevelImageMatrixBuffer)) +
", " + str(testGrayLevelImageMatrixBuffer.getDimension()))
#clij2_instance.print(testGrayLevelImageMatrixBuffer) #java.util.UnknownFormatConversionException: java.util.UnknownFormatConversionException: Conversion = 'Cannot convert image of type UnsignedInt'
test8bitUnsignedMatrixBuffer = clij2_instance.create(
clij2_instance.getDimensions(testGrayLevelImageMatrixBuffer),
NativeTypeEnum.UnsignedByte)
#https://github.com/clij/clij-coremem/blob/master/src/main/java/net/haesleinhuepf/clij/coremem/enums/NativeTypeEnum.java
clij2_instance.copy(testGrayLevelImageMatrixBuffer,
test8bitUnsignedMatrixBuffer)
clij2_instance.print(test8bitUnsignedMatrixBuffer)
#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
for j in range(0, len(processors)):
processor = processors[j]
if (not processor.isWorking()):
# found a sleeping processor!
# was he done with something?
# 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
clij2 = CLIJ2.getInstance("630")
# 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
# December 2019
#########################################
from __future__ import with_statement
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")
IJ.run(imp, "32-bit", "")
imp.show()
# init GPU
with CLIJ2.getInstance() as clij2:
# push image to GPU
input = clij2.push(imp)
# reserve memory for output, same size and type as input
blurred = clij2.create(input)
# blur, threshold and label the image
clij2.blur(input, blurred, 5, 5, 0)
# show result
clij2.show(blurred, "blurred")
#
# By the end of this block, clijx will
# clean up memory automatically
#@ 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)
# submit deconvolution task
# load/create example images
# imp = IJ.openImage("C:/structure/data/Nantes_000646.tif");
# imp = IJ.openImage("C:/structure/data/Riga_000512.tif");
# imp = IJ.openImage("C:/structure/data/Pau_001130.tif");
# imp = IJ.openImage("C:/structure/data/Finsterwalde_001250.tif");
imp = IJ.openImage(
"C:/structure/data/2018-05-23-16-18-13-89-Florence_multisample/processed/tif/000450.raw.tif"
)
IJ.run(imp, "32-bit", "")
IJ.run(imp, "Rotate 90 Degrees Right", "")
imp.show()
# Init GPU
clij2 = CLIJ2.getInstance("2060")
clijx.stopWatch("")
# push data to GPU
inputImage = clij2.push(imp)
# blur a bit and detect maxima
blurred = clij2.create(inputImage)
thresholded = clij2.create(inputImage)
detected_spots = clij2.create(inputImage)
masked = clij2.create(inputImage)
clijx.stopWatch("alloc")
# background / noise removal
clij2.differenceOfGaussian(inputImage, blurred, 3, 3, 0, 15, 15, 0)
# clijx.op().blur(inputImage, blurred, 3, 3, 0);
# 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.clij2 import CLIJ2 IJ.log(CLIJ2.clinfo())