import vigra
import vigra.graphs as graphs
import skneuro
#import skneuro.oversegmentation as oseg
import skneuro.blockwise_filters as blockF
import numpy
import gc
import sys
from skneuro import workflows as wf

optJsonFile = "opt.json"
opt = wf.loadJson(optJsonFile)






dset = "exported_data"


print "read raw data"
raw = vigra.impex.readHDF5(opt['rawData'], opt['rawDatasetName']).view(numpy.ndarray)
grayData = [(raw, "raw")]
segData  = []




#if False:
#    print "compute eigenvalues of hessian of gaussian"
Example #2
0
import vigra
import vigra.graphs as graphs
import skneuro
#import skneuro.oversegmentation as oseg
import skneuro.blockwise_filters as blockF
import numpy
import gc
import sys
from skneuro import workflows as wf

optJsonFile = "opt.json"
opt = wf.loadJson(optJsonFile)

dset = "exported_data"

print "read raw data"
raw = vigra.impex.readHDF5(opt['rawData'],
                           opt['rawDatasetName']).view(numpy.ndarray)
grayData = [(raw, "raw")]
segData = []

#if False:
#    print "compute eigenvalues of hessian of gaussian"
#    ew = blockF.blockwiseHessianOfGaussianLargestEigenvalues(raw, 2.0, nThreads=20)
#    ew -= ew.min()
#    ew /= ew.max()
#    grayData.append([ew,"hessian ew"])
#    skneuro.addHocViewer(grayData, segData)
#    vigra.impex.writeHDF5(ew, hessianPath, "data")

# make thinned map
Example #3
0
import skneuro
from skneuro import workflows as wf



optJsonFile = "opt.json"
optFile = wf.loadJson(optJsonFile)


wf.neuroproofWorkflow(optFile)