def setup_classifiers(self):
sttg = self.settings
# processing channel, color channel
for p_channel, c_channel in self.ch_mapping.iteritems():
self.settings.set_section('Processing')
if sttg.get2(self._resolve_name(p_channel, 'classification')):
sttg.set_section('Classification')
clf = CommonClassPredictor(
clf_dir=sttg.get2(self._resolve_name(p_channel,
'classification_envpath')),
name=p_channel,
channels=self._channel_regions(p_channel),
color_channel=c_channel)
clf.importFromArff()
clf.loadClassifier()
self.classifiers[p_channel] = clf
def setup_classifiers(self):
sttg = self.settings
# processing channel, color channel
for p_channel, c_channel in self.ch_mapping.iteritems():
self.settings.set_section('Processing')
if sttg.get2(self._resolve_name(p_channel, 'classification')):
sttg.set_section('Classification')
clf = CommonClassPredictor(
clf_dir=sttg.get2(
self._resolve_name(p_channel,
'classification_envpath')),
name=p_channel,
channels=self._channel_regions(p_channel),
color_channel=c_channel)
clf.importFromArff()
clf.loadClassifier()
self.classifiers[p_channel] = clf
def setup_classifiers(self):
sttg = self.settings
# processing channel, color channel
for p_channel, c_channel in self.ch_mapping.iteritems():
self.settings.set_section('Processing')
if sttg.get2(self._resolve_name(p_channel, 'classification')):
chreg = self._channel_regions(p_channel)
if sttg("EventSelection", "unsupervised_event_selection"):
nclusters = sttg("EventSelection", "num_clusters")
self.classifiers[p_channel] = ClassDefinitionUnsup( \
nclusters, chreg)
else:
sttg.set_section('Classification')
clf = CommonClassPredictor(
clf_dir=sttg.get2(self._resolve_name(p_channel,
'classification_envpath')),
name=p_channel,
channels=chreg,
color_channel=c_channel)
clf.importFromArff()
clf.loadClassifier()
self.classifiers[p_channel] = clf
def setup_classifiers(self):
sttg = self.settings
# processing channel, color channel
for p_channel, c_channel in self.ch_mapping.iteritems():
self.settings.set_section('Processing')
if sttg.get2(self._resolve_name(p_channel, 'classification')):
chreg = self._channel_regions(p_channel)
if sttg("EventSelection", "unsupervised_event_selection"):
nclusters = sttg("EventSelection", "num_clusters")
self.classifiers[p_channel] = ClassDefinitionUnsup( \
nclusters, chreg)
else:
sttg.set_section('Classification')
clf = CommonClassPredictor(
clf_dir=sttg.get2(self._resolve_name(p_channel,
'classification_envpath')),
name=p_channel,
channels=chreg,
color_channel=c_channel)
clf.importFromArff()
clf.loadClassifier()
self.classifiers[p_channel] = clf
