def save_sample_outputs(sample_outputs, prefix):
'''
Writes the resulting output volumes to disk according to the
output_prefix
'''
for sample_num, output in sample_outputs.iteritems():
for dataset_name, dataset in output.output_volumes.iteritems():
num_volumes = dataset.data.shape[0]
#Consolidated 4d volume
# hdf5 output for watershed
h5name = "{}_sample{}_{}.h5".format(prefix, sample_num,
dataset_name)
print "save output to ", h5name
import os
if os.path.exists(h5name):
os.remove(h5name)
emio.imsave(dataset.data, h5name)
#Constitutent 3d volumes
# tif file for easy visualization
for i in range(num_volumes):
emio.imsave(dataset.data[i,:,:,:],\
"{}_sample{}_{}_{}.tif".format(prefix, sample_num, dataset_name, i))
def _save_dataset(self):
from emirt.emio import imsave
for sample in self.samples:
# save sample images
raw, lbl = sample.get_dataset()
fname = '../testsuit/sample_{}_raw.h5'.format(sample.sid)
if os.path.exists( fname ):
os.remove( fname )
imsave(raw, fname)
fname = '../testsuit/sample_{}_lbl.h5'.format(sample.sid)
if os.path.exists( fname ):
os.remove( fname )
imsave(lbl, fname )
def _save_dataset(self):
from emirt.emio import imsave
for sample in self.samples:
# save sample images
raw, lbl = sample.get_dataset()
fname = '../testsuit/sample_{}_raw.h5'.format(sample.sid)
if os.path.exists(fname):
os.remove(fname)
imsave(raw, fname)
fname = '../testsuit/sample_{}_lbl.h5'.format(sample.sid)
if os.path.exists(fname):
os.remove(fname)
imsave(lbl, fname)
def save_sample_outputs(sample_outputs, prefix):
"""
Writes the resulting output volumes to disk according to the
output_prefix
"""
for sample_num, output in sample_outputs.iteritems():
for dataset_name, dataset in output.output_volumes.iteritems():
num_volumes = dataset.data.shape[0]
# Consolidated 4d volume
emio.imsave(dataset.data, "{}_sample{}_{}.tif".format(prefix, sample_num, dataset_name))
# Constitutent 3d volumes
for i in range(num_volumes):
emio.imsave(
dataset.data[i, :, :, :], "{}_sample{}_{}_{}.tif".format(prefix, sample_num, dataset_name, i)
)
def save_sample_outputs(sample_outputs, prefix):
'''
Writes the resulting output volumes to disk according to the
output_prefix
'''
for sample_num, output in sample_outputs.iteritems():
for dataset_name, dataset in output.output_volumes.iteritems():
num_volumes = dataset.data.shape[0]
#Consolidated 4d volume
emio.imsave(dataset.data,
"{}_sample{}_{}.tif".format(prefix, sample_num,
dataset_name))
#Constitutent 3d volumes
for i in range( num_volumes ):
emio.imsave(dataset.data[i,:,:,:],
"{}_sample{}_{}_{}.tif".format(prefix, sample_num,
dataset_name, i))
def save_sample_outputs(sample_outputs, prefix):
'''
Writes the resulting output volumes to disk according to the
output_prefix
'''
for sample_num, output in sample_outputs.iteritems():
for dataset_name, dataset in output.output_volumes.iteritems():
num_volumes = dataset.data.shape[0]
#Consolidated 4d volume
# hdf5 output for watershed
h5name = "{}_sample{}_{}.h5".format(prefix, sample_num, dataset_name)
import os
if os.path.exists( h5name ):
os.remove( h5name )
emio.imsave(dataset.data, h5name)
#Constitutent 3d volumes
# tif file for easy visualization
for i in range( num_volumes ):
emio.imsave(dataset.data[i,:,:,:],\
"{}_sample{}_{}_{}.tif".format(prefix, sample_num, dataset_name, i))
