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"
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
import skneuro from skneuro import workflows as wf optJsonFile = "opt.json" optFile = wf.loadJson(optJsonFile) wf.neuroproofWorkflow(optFile)