def _get_modified_settings(self, name, has_timelapse=True):
settings = BaseProcessorFrame._get_modified_settings(self, name, has_timelapse)
settings.set_section('ObjectDetection')
prim_id = PrimaryChannel.NAME
settings.set_section('Processing')
settings.set2('tracking', True)
settings.set2('tracking_synchronize_trajectories', False)
settings.set_section('Tracking')
region_name = settings.get2('tracking_regionname')
settings.set_section('General')
settings.set2('rendering_class', {})
settings.set2('rendering', {})
settings.set_section('Classification')
settings.set2('collectsamples', False)
settings.set('Output', 'hdf5_create_file', False)
show_ids = settings.get('Output', 'rendering_contours_showids')
show_ids_class = settings.get('Output', 'rendering_class_showids')
if name == self.PROCESS_TRACKING:
# tracking only invokes the primary channel
settings.set_section('Processing')
settings.set2('primary_classification', False)
settings.set2('primary_featureextraction', True)
settings.set2('secondary_processChannel', False)
settings.set2('secondary_featureextraction', False)
settings.set2('secondary_classification', False)
settings.set2('tertiary_processChannel', False)
settings.set2('tertiary_featureextraction', False)
settings.set2('tertiary_classification', False)
settings.set2('merged_processChannel', False)
settings.set2('merged_classification', False)
settings.set('Output', 'events_export_gallery_images', False)
settings.set('General', 'rendering', {'primary_contours':
{PrimaryChannel.NAME: {'raw': ('#FFFFFF', 1.0),
'contours': {region_name: ('#FF0000', 1, show_ids)}}}})
else:
settings.set_section('Processing')
settings.set2('primary_featureextraction', True)
settings.set2('primary_classification', True)
settings.set2('tracking_synchronize_trajectories', True)
cl_rnd = {'primary_classification':
{PrimaryChannel.NAME: {'raw': ('#FFFFFF', 1.0),
'contours': [('primary', 'class_label', 1, False),
('primary', '#000000', 1, show_ids_class)]}}, }
settings.set('General', 'rendering_class', cl_rnd)
settings.set_section('Processing')
self._channel_render_settings(settings, SecondaryChannel.NAME, show_ids_class)
self._channel_render_settings(settings, TertiaryChannel.NAME, show_ids_class)
self._channel_render_settings(settings, MergedChannel.NAME, show_ids_class)
return settings
def _get_modified_settings(self, name, has_timelapse=True):
settings = BaseProcessorFrame._get_modified_settings( \
self, name, has_timelapse)
# turn on tracking and event seletion
settings.set('Processing', 'tracking', True)
settings.set('Processing', 'eventselection', True)
settings.set('General', 'rendering_class', {})
settings.set('General', 'rendering', {})
settings.set('Classification', 'collectsamples', False)
settings.set('Output', 'hdf5_create_file', False)
settings.set('Output', 'events_export_gallery_images', False)
# only primary channel for event selection
settings.set('Processing', 'secondary_featureextraction', False)
settings.set('Processing', 'secondary_classification', False)
settings.set('General', 'process_secondary', False)
settings.set('Processing', 'tertiary_featureextraction', False)
settings.set('Processing', 'tertiary_classification', False)
settings.set('General', 'process_tertiary', False)
settings.set('Processing', 'merged_classification', False)
settings.set('General', 'process_merged', False)
show_ids = settings.get('Output', 'rendering_contours_showids')
show_ids_class = settings.get('Output', 'rendering_class_showids')
render_contours = {
PrimaryChannel.NAME: {
'raw': ('#FFFFFF', 1.0),
'contours': {
'primary': ('#FF0000', 1, show_ids)
}
}
}
render_class = {
PrimaryChannel.NAME: {
'raw': ('#FFFFFF', 1.0),
'contours': [('primary', 'class_label', 1, False),
('primary', '#000000', 1, show_ids_class)]
}
}
# setting up primary channel and live rendering
if settings.get('EventSelection', 'unsupervised_event_selection'):
settings.set('Processing', 'primary_featureextraction', True)
settings.set('Processing', 'primary_classification', True)
settings.set('Processing', 'secondary_classification', False)
settings.set('Processing', 'tertiary_classification', False)
settings.set('Processing', 'merged_classification', False)
settings.set('General', 'rendering',
{'primary_contours': render_contours})
elif settings.get('EventSelection', 'supervised_event_selection'):
settings.set('Processing', 'primary_featureextraction', True)
settings.set('Processing', 'primary_classification', True)
settings.set('General', 'rendering_class',
{'primary_classification': render_class})
return settings
def _get_modified_settings(self, name, has_timelapse=True):
settings = BaseProcessorFrame._get_modified_settings(self, name, has_timelapse)
settings.set('Processing', 'tracking', True)
settings.set('Processing', 'eventselection', False)
settings.set('General', 'rendering_class', {})
settings.set('General', 'rendering', {})
settings.set('Classification', 'collectsamples', False)
settings.set('Output', 'hdf5_create_file', False)
# tracking only invokes the primary channel
settings.set('Processing', 'primary_classification', False)
settings.set('Processing', 'primary_featureextraction', True)
settings.set('General', 'process_secondary', False)
settings.set('Processing', 'secondary_featureextraction', False)
settings.set('Processing', 'secondary_classification', False)
settings.set('General', 'process_tertiary', False)
settings.set('Processing', 'tertiary_featureextraction', False)
settings.set('Processing', 'tertiary_classification', False)
settings.set('General', 'process_merged', False)
settings.set('Processing', 'merged_classification', False)
settings.set('Output', 'events_export_gallery_images', False)
region_name = settings.get('Tracking', 'region')
show_ids = settings.get('Output', 'rendering_contours_showids')
pct = {'primary_contours':
{CH_PRIMARY[0].title(): {'raw': ('#FFFFFF', 1.0),
'contours': {region_name: ('#FF0000', 1, show_ids)}}}}
settings.set('General', 'rendering', pct)
return settings
def _get_modified_settings(self, name, has_timelapse=True):
settings = BaseProcessorFrame._get_modified_settings(self, name, has_timelapse)
settings.set_section('ObjectDetection')
settings.set_section('Processing')
for prefix in ['primary', 'secondary', 'tertiary']:
settings.set2('%s_featureextraction' % prefix, False)
settings.set2('%s_classification' % prefix, False)
settings.set2('tracking', False)
settings.set_section('Classification')
settings.set2('collectsamples', False)
settings.set_section('General')
settings.set2('rendering_class', {})
settings.set('Output', 'events_export_gallery_images', False)
settings.set('Output', 'hdf5_create_file', False)
settings.set('Output', 'export_object_counts', False)
settings.set('Output', 'export_file_names', False)
settings.set('Output', 'export_object_details', False)
settings.set('Output', 'export_tracking_as_dot', False)
settings.set('Output', 'export_track_data', False)
show_ids = settings.get('Output', 'rendering_contours_showids')
current_tab = self._tab.current_index
# turn of merged channel
settings.set('General', 'process_merged', False)
if current_tab == 0:
settings.set('General', 'process_secondary', False)
settings.set('General', 'process_tertiary', False)
prefix = 'primary'
elif current_tab == 1:
settings.set('General', 'process_secondary', True)
settings.set('General', 'process_tertiary', False)
prefix = 'secondary'
else:
settings.set('General', 'process_secondary', True)
settings.set('General', 'process_tertiary', True)
prefix = 'tertiary'
region_info = self.plugin_mgr.region_info
colors = region_info.colors
rdn = dict([('%s_contours_%s' % (prefix, x),
{prefix.capitalize(): {'raw': ('#FFFFFF', 1.0),
'contours': [(x, colors[x] , 1, show_ids)]
}
}
) for x in region_info.names[prefix]])
settings.set('General', 'rendering', rdn)
return settings
def _get_modified_settings(self, name, has_timelapse=True):
settings = BaseProcessorFrame._get_modified_settings(
self, name, has_timelapse)
settings.set_section('ObjectDetection')
settings.set_section('Processing')
for prefix in ['primary', 'secondary', 'tertiary']:
settings.set2('%s_featureextraction' % prefix, False)
settings.set2('%s_classification' % prefix, False)
settings.set2('tracking', False)
settings.set_section('Classification')
settings.set2('collectsamples', False)
settings.set_section('General')
settings.set2('rendering_class', {})
settings.set('Output', 'events_export_gallery_images', False)
settings.set('Output', 'hdf5_create_file', False)
settings.set('Output', 'export_object_counts', False)
settings.set('Output', 'export_file_names', False)
settings.set('Output', 'export_object_details', False)
settings.set('Output', 'export_tracking_as_dot', False)
settings.set('Output', 'export_track_data', False)
show_ids = settings.get('Output', 'rendering_contours_showids')
current_tab = self._tab.current_index
# turn of merged channel
settings.set('General', 'process_merged', False)
if current_tab == 0:
settings.set('General', 'process_secondary', False)
settings.set('General', 'process_tertiary', False)
prefix = 'primary'
elif current_tab == 1:
settings.set('General', 'process_secondary', True)
settings.set('General', 'process_tertiary', False)
prefix = 'secondary'
else:
settings.set('General', 'process_secondary', True)
settings.set('General', 'process_tertiary', True)
prefix = 'tertiary'
region_info = self.plugin_mgr.region_info
colors = region_info.colors
rdn = dict([('%s_contours_%s' % (prefix, x), {
prefix.capitalize(): {
'raw': ('#FFFFFF', 1.0),
'contours': [(x, colors[x], 1, show_ids)]
}
}) for x in region_info.names[prefix]])
settings.set('General', 'rendering', rdn)
return settings
def _get_modified_settings(self, name, has_timelapse=True):
settings = BaseProcessorFrame._get_modified_settings(self, name, has_timelapse)
settings.set_section('Processing')
if settings.get2('primary_classification'):
settings.set2('primary_errorcorrection', True)
if not settings.get2('secondary_processchannel'):
settings.set2('secondary_classification', False)
settings.set2('secondary_errorcorrection', False)
elif settings.get2('secondary_classification'):
settings.set2('secondary_errorcorrection', True)
return settings
def _get_modified_settings(self, name, has_timelapse=True):
settings = BaseProcessorFrame._get_modified_settings(self, name, has_timelapse)
settings.set_section('Processing')
if settings.get2('primary_classification'):
settings.set2('primary_errorcorrection', True)
if not settings.get2('secondary_processchannel'):
settings.set2('secondary_classification', False)
settings.set2('secondary_errorcorrection', False)
elif settings.get2('secondary_classification'):
settings.set2('secondary_errorcorrection', True)
return settings
def _get_modified_settings(self, name, has_timelapse=True):
settings = BaseProcessorFrame._get_modified_settings( \
self, name, has_timelapse)
# turn on tracking and event seletion
settings.set('Processing', 'tracking', True)
settings.set('Processing', 'eventselection', True)
settings.set('General', 'rendering_class', {})
settings.set('General', 'rendering', {})
settings.set('Classification', 'collectsamples', False)
settings.set('Output', 'hdf5_create_file', False)
settings.set('Output', 'events_export_gallery_images', False)
# only primary channel for event selection
settings.set('Processing', 'secondary_featureextraction', False)
settings.set('Processing', 'secondary_classification', False)
settings.set('General', 'process_secondary', False)
settings.set('Processing', 'tertiary_featureextraction', False)
settings.set('Processing', 'tertiary_classification', False)
settings.set('General', 'process_tertiary', False)
settings.set('Processing', 'merged_classification', False)
settings.set('General', 'process_merged', False)
show_ids = settings.get('Output', 'rendering_contours_showids')
show_ids_class = settings.get('Output', 'rendering_class_showids')
render_contours = {PrimaryChannel.NAME:
{'raw': ('#FFFFFF', 1.0),
'contours': {'primary': ('#FF0000', 1, show_ids)}}}
render_class = {PrimaryChannel.NAME:
{'raw': ('#FFFFFF', 1.0),
'contours': [('primary', 'class_label', 1, False),
('primary', '#000000', 1,
show_ids_class)]}}
# setting up primary channel and live rendering
if settings.get('EventSelection', 'unsupervised_event_selection'):
settings.set('Processing', 'primary_featureextraction', True)
settings.set('Processing', 'primary_classification', True)
settings.set('Processing', 'secondary_classification', False)
settings.set('Processing', 'tertiary_classification', False)
settings.set('Processing', 'merged_classification', False)
settings.set('General', 'rendering',
{'primary_contours': render_contours})
elif settings.get('EventSelection', 'supervised_event_selection'):
settings.set('Processing', 'primary_featureextraction', True)
settings.set('Processing', 'primary_classification', True)
settings.set('General', 'rendering_class',
{'primary_classification': render_class})
return settings
def _get_modified_settings(self, name, has_timelapse=True):
settings = BaseProcessorFrame._get_modified_settings(self, name, has_timelapse)
settings.set_section('ObjectDetection')
prim_id = PrimaryChannel.NAME
sec_id = SecondaryChannel.NAME
sec_regions = [v for k,v in SECONDARY_REGIONS.iteritems()
if settings.get2(k)]
tert_id = TertiaryChannel.NAME
tert_regions = [v for k,v in TERTIARY_REGIONS.iteritems()
if settings.get2(k)]
settings.set_section('Processing')
for prefix in ['primary', 'secondary', 'tertiary']:
settings.set2('%s_featureextraction' % prefix, False)
settings.set2('%s_classification' % prefix, False)
settings.set2('tracking', False)
settings.set_section('Classification')
settings.set2('collectsamples', False)
settings.set_section('General')
settings.set2('rendering_class', {})
#settings.set2('rendering_discwrite', True)
#settings.set2('rendering_class_discwrite', True)
settings.set('Output', 'events_export_gallery_images', False)
show_ids = settings.get('Output', 'rendering_contours_showids')
#settings.set('Output', 'export_object_details', False)
#settings.set('Output', 'export_object_counts', False)
current_tab = self._tab.currentIndex()
print current_tab
if current_tab == 0:
settings.set('Processing', 'secondary_processchannel', False)
settings.set('Processing', 'tertiary_processchannel', False)
settings.set('General', 'rendering', {'primary_contours': {prim_id: {'raw': ('#FFFFFF', 1.0), 'contours': {'primary': ('#FF0000', 1, show_ids)}}}})
elif current_tab == 1:
settings.set('Processing', 'secondary_processchannel', True)
settings.set('Processing', 'tertiary_processchannel', False)
settings.set('General', 'rendering', dict([('secondary_contours_%s' % x, {sec_id: {'raw': ('#FFFFFF', 1.0),
'contours': [(x, SECONDARY_COLORS[x] , 1, show_ids)]
}})
for x in sec_regions]))
else:
settings.set('Processing', 'secondary_processChannel', True)
settings.set('Processing', 'tertiary_processchannel', True)
settings.set('General', 'rendering', dict([('tertiary_contours_%s' % x, {tert_id: {'raw': ('#FFFFFF', 1.0),
'contours': [(x, SECONDARY_COLORS[x] , 1, show_ids)]
}})
for x in tert_regions]))
return settings
def _process_image(self, ):
self.image_viewer.remove_objects()
settings = BaseProcessorFrame.get_special_settings(self._settings)
settings.set_section('General')
settings.set2('constrain_positions', True)
settings.set2('positions', self.coordinate.position)
settings.set2('skip_finished', False)
settings.set2('framerange', True)
settings.set2('framerange_begin', self.coordinate.time)
settings.set2('framerange_end', self.coordinate.time)
settings.set_section('Processing')
_classify_objects = self._show_objects_by == 'classification'
settings.set2('primary_classification', _classify_objects)
settings.set2('secondary_classification', _classify_objects)
settings.set2('tertiary_classification', _classify_objects)
settings.set2('merged_classification', _classify_objects)
settings.set2('primary_featureextraction', _classify_objects)
settings.set2('secondary_featureextraction', _classify_objects)
settings.set2('objectdetection', self._detect_objects)
settings.set2('tracking', False)
settings.set('Output', 'hdf5_create_file', False)
settings.set('General', 'rendering', {})
settings.set('General', 'rendering_class', {})
nchannels = len(self._imagecontainer.channels)
# XXX channel mapping unclear
# processing channel <--> color channel
# i.e problems if 2 processing channels have the same color
if nchannels == 2:
settings.set('General', 'process_secondary', True)
elif nchannels >= 3:
settings.set('General', 'process_secondary', True)
settings.set('General', 'process_tertiary', True)
settings.set('General', 'rendering', {})
analyzer = AnalyzerBrowser(self.coordinate.plate, settings,
self._imagecontainer)
res = None
try:
QApplication.setOverrideCursor(QCursor(Qt.WaitCursor))
res = analyzer()
self.render_browser(res)
except Exception, e:
import traceback
traceback.print_exc()
QMessageBox.critical(self, "Error", str(e))
raise
def _process_image(self, ):
self.image_viewer.remove_objects()
settings = BaseProcessorFrame.get_special_settings(self._settings)
settings.set_section('General')
settings.set2('constrain_positions', True)
settings.set2('positions', self.coordinate.position)
settings.set2('skip_finished', False)
settings.set2('framerange', True)
settings.set2('framerange_begin', self.coordinate.time)
settings.set2('framerange_end', self.coordinate.time)
settings.set_section('Processing')
_classify_objects = self._show_objects_by == 'classification'
settings.set2('primary_classification', _classify_objects )
settings.set2('secondary_classification', _classify_objects)
settings.set2('tertiary_classification', _classify_objects)
settings.set2('merged_classification', _classify_objects)
settings.set2('primary_featureextraction', _classify_objects)
settings.set2('secondary_featureextraction', _classify_objects)
settings.set2('objectdetection', self._detect_objects)
settings.set2('tracking', False)
settings.set('Output', 'hdf5_create_file', False)
settings.set('General', 'rendering', {})
settings.set('General', 'rendering_class', {})
nchannels = len(self._imagecontainer.channels)
# XXX channel mapping unclear
# processing channel <--> color channel
# i.e problems if 2 processing channels have the same color
if nchannels == 2:
settings.set('General', 'process_secondary', True)
elif nchannels >= 3:
settings.set('General', 'process_secondary', True)
settings.set('General', 'process_tertiary', True)
settings.set('General', 'rendering', {})
analyzer = AnalyzerBrowser(self.coordinate.plate, settings, self._imagecontainer)
res = None
try:
QApplication.setOverrideCursor(QCursor(Qt.WaitCursor))
res = analyzer()
self.render_browser(res)
except Exception, e:
import traceback
traceback.print_exc()
QMessageBox.critical(self, "Error", str(e))
raise
def _get_modified_settings(self, name, has_timelapse=True):
settings = BaseProcessorFrame._get_modified_settings(self, name, has_timelapse)
# turn on tracking and event seletion
settings.set("Processing", "tracking", True)
settings.set("Processing", "eventselection", True)
settings.set("General", "rendering_class", {})
settings.set("General", "rendering", {})
settings.set("Classification", "collectsamples", False)
settings.set("Output", "hdf5_create_file", False)
settings.set("Output", "events_export_gallery_images", False)
# only primary channel for event selection
settings.set("Processing", "secondary_featureextraction", False)
settings.set("Processing", "secondary_classification", False)
settings.set("General", "process_secondary", False)
settings.set("Processing", "tertiary_featureextraction", False)
settings.set("Processing", "tertiary_classification", False)
settings.set("General", "process_tertiary", False)
settings.set("Processing", "merged_classification", False)
settings.set("General", "process_merged", False)
show_ids = settings.get("Output", "rendering_contours_showids")
show_ids_class = settings.get("Output", "rendering_class_showids")
render_contours = {
PrimaryChannel.NAME: {"raw": ("#FFFFFF", 1.0), "contours": {"primary": ("#FF0000", 1, show_ids)}}
}
render_class = {
PrimaryChannel.NAME: {
"raw": ("#FFFFFF", 1.0),
"contours": [("primary", "class_label", 1, False), ("primary", "#000000", 1, show_ids_class)],
}
}
# setting up primary channel and live rendering
if settings.get("EventSelection", "unsupervised_event_selection"):
settings.set("Processing", "primary_featureextraction", True)
settings.set("Processing", "primary_classification", True)
settings.set("Processing", "secondary_classification", False)
settings.set("Processing", "tertiary_classification", False)
settings.set("Processing", "merged_classification", False)
settings.set("General", "rendering", {"primary_contours": render_contours})
elif settings.get("EventSelection", "supervised_event_selection"):
settings.set("Processing", "primary_featureextraction", True)
settings.set("Processing", "primary_classification", True)
settings.set("General", "rendering_class", {"primary_classification": render_class})
return settings
def get_export_settings(cls, settings, has_timelapse=True):
settings = BaseProcessorFrame.get_special_settings(
settings, has_timelapse)
settings.set('General', 'version', VERSION)
settings.set('General', 'rendering', {})
settings.set('General', 'rendering_class', {})
show_ids = settings.get('Output', 'rendering_contours_showids')
show_ids_class = settings.get('Output', 'rendering_class_showids')
# set propertys of merged channel to the same as for Primary
# unfortunately REGION_INFO is like a global variable
d = {}
for prefix in CH_PRIMARY + CH_OTHER:
if prefix == CH_PRIMARY[0] \
or settings.get('Processing', '%s_processchannel' % prefix):
for x in reginfo.names[prefix]:
d = {
'%s_contours_%s' % (prefix, x): {
prefix.capitalize(): {
'raw': ('#FFFFFF', 1.0),
'contours':
[(x, reginfo.colors[x], 1, show_ids)]
}
}
}
settings.get('General', 'rendering').update(d)
if settings.get('Processing', '%s_classification' % prefix):
for x in reginfo.names[prefix]:
if x == settings.get('Classification', '%s_classification_regionname' % prefix) or \
prefix == CH_VIRTUAL[0]:
d = {
'%s_classification_%s' % (prefix, x): {
prefix.capitalize(): {
'raw': ('#FFFFFF', 1.0),
'contours':
[(x, 'class_label', 1, False),
(x, '#000000', 1, show_ids_class)]
}
}
}
settings.get('General', 'rendering_class').update(d)
# setup rendering properties for merged channel
# want the same rendering properties as for the primary channel!
if settings.get('Processing', 'merged_processchannel'):
regions = cls._merged_regions(settings)
d = {
'merged_contours_%s' % '-'.join(regions): {
"Merged": {
'raw': ('#FFFFFF', 1.0),
'contours':
[(regions, reginfo.colors["primary"], 1, show_ids)]
}
}
}
settings.get("General", "rendering").update(d)
if settings.get('Processing', 'merged_classification'):
d = {
'merged_classification_%s' % '-'.join(regions): {
"Merged": {
'raw': ('#FFFFFF', 1.0),
'contours':
[(regions, 'class_label', 1, False),
(regions, '#000000', 1, show_ids_class)]
}
}
}
settings.get("General", "rendering_class").update(d)
if has_timelapse:
# generate raw images of selected channels (later used for gallery images)
if settings.get('Output', 'events_export_gallery_images'):
for prefix in CHANNEL_PREFIX:
if prefix == 'primary' or settings.get(
'Processing', '%s_processchannel' % prefix):
settings.get('General', 'rendering').update({
prefix: {
prefix.capitalize(): {
'raw': ('#FFFFFF', 1.0)
}
}
})
return settings
def _process_image(self, ):
self.image_viewer.remove_objects()
settings = BaseProcessorFrame.get_special_settings(self._settings)
settings.set_section('General')
settings.set2('constrain_positions', True)
settings.set2('positions', self.coordinate.position)
settings.set2('redofailedonly', False)
settings.set2('framerange', True)
settings.set2('framerange_begin', self.coordinate.time)
settings.set2('framerange_end', self.coordinate.time)
settings.set_section('Processing')
_classify_objects = self._show_objects_by == 'classification'
settings.set2('primary_classification', _classify_objects )
settings.set2('secondary_classification', _classify_objects)
settings.set2('tertiary_classification', _classify_objects)
settings.set2('merged_classification', _classify_objects)
settings.set2('primary_featureextraction', _classify_objects)
settings.set2('secondary_featureextraction', _classify_objects)
settings.set2('objectdetection', self._detect_objects)
settings.set2('tracking', False)
settings.set_section('Output')
settings.set2('rendering_contours_discwrite', False)
settings.set2('rendering_class_discwrite', False)
settings.set2('export_object_counts', False)
settings.set2('export_object_details', False)
settings.set2('export_track_data', False)
settings.set2('hdf5_create_file', False)
settings.set_section('Classification')
settings.set2('collectsamples', False)
settings.set('General', 'rendering', {})
settings.set('General', 'rendering_class', {})
settings.set('Output', 'events_export_gallery_images', False)
# turn of output:
settings.set('Output', 'export_object_counts', False)
settings.set('Output', 'export_object_details', False)
settings.set('Output', 'export_file_names', False)
settings.set('Output', 'events_export_gallery_images', False)
settings.set('Output', 'export_track_data', False)
settings.set('Output', 'export_tracking_as_dot', False)
nchannels = len(self._imagecontainer.channels)
# XXX channel mapping unclear
# processing channel <--> color channel
# i.e problems if 2 processing channels have the same color
if nchannels == 2:
settings.set('General', 'process_secondary', True)
elif nchannels >= 3:
settings.set('General', 'process_secondary', True)
settings.set('General', 'process_tertiary', True)
settings.set('General', 'rendering', {})
analyzer = AnalyzerBrowser(self.coordinate.plate,
settings,
self._imagecontainer)
res = None
try:
QApplication.setOverrideCursor(QCursor(Qt.WaitCursor))
res = analyzer.processPositions()
self.render_browser(res)
except Exception, e:
import traceback
from cecog.gui.util import exception
traceback.print_exc()
exception(self, str(e))
raise
def _get_modified_settings(self, name, has_timelapse=True):
settings = BaseProcessorFrame._get_modified_settings( \
self, name, has_timelapse)
settings.set('Processing', 'primary_classification', False)
settings.set('Processing', 'secondary_classification', False)
settings.set('Processing', 'tracking', False)
settings.set('Classification', 'collectsamples', False)
settings.set('General', 'rendering', {})
settings.set('General', 'rendering_class', {})
settings.set('Output', 'events_export_gallery_images', False)
settings.set('Output', 'hdf5_create_file', False)
settings.set('Output', 'rendering_channel_gallery', False)
current_tab = self._tab.current_index
if current_tab == 0:
prefix = 'primary'
settings.set('Processing', 'primary_featureextraction', True)
settings.set('Processing', 'secondary_featureextraction', False)
settings.set('Processing', 'tertiary_featureextraction', False)
settings.set('General', 'process_secondary', False)
settings.set('General', 'process_tertiary', False)
settings.set('General', 'process_merged', False)
rdn = {"%s_%s" %(prefix, settings.get("Classification",
"%s_classification_regionname" %prefix)): {}}
elif current_tab == 1:
prefix = 'secondary'
settings.set('Processing', 'primary_featureextraction', False)
settings.set('Processing', 'secondary_featureextraction', True)
settings.set('General', 'process_secondary', True)
settings.set('Processing', 'tertiary_featureextraction', False)
settings.set('General', 'process_tertiary', False)
settings.set('General', 'process_merged', False)
# to setup the rending of the image currently processed
rdn = {"%s_%s" %(prefix, settings.get("Classification",
"%s_classification_regionname" %prefix)): {}}
elif current_tab == 2:
prefix = 'tertiary'
seg_region = settings.get('Classification',
'tertiary_classification_regionname')
settings.set('Processing', 'primary_featureextraction', False)
settings.set('Processing', 'secondary_featureextraction', False)
settings.set('General', 'process_secondary', True)
settings.set('Processing', 'tertiary_featureextraction', True)
settings.set('General', 'process_tertiary', True)
settings.set('General', 'process_merged', False)
rdn = {"%s_%s" %(prefix, settings.get("Classification",
"%s_classification_regionname" %prefix)): {}}
else:
# checkboxes in merged channel tab
pch = settings.get('Classification', 'merge_primary')
sch = settings.get('Classification', 'merge_secondary')
tch = settings.get('Classification', 'merge_tertiary')
settings.set('Processing', 'primary_featureextraction', pch)
settings.set('Processing', 'secondary_featureextraction', sch)
settings.set('General', 'process_secondary', sch)
settings.set('Processing', 'tertiary_featureextraction', tch)
settings.set('General', 'process_tertiary', tch)
settings.set('General', 'process_merged', True)
prefix = 'merged'
rdn = {}
for pfx in (CH_PRIMARY+CH_OTHER):
if settings.get("Classification", "merge_%s" %pfx):
rdn["%s_%s" %(pfx, settings.get("Classification","merged_%s_region" %pfx))] = {}
settings.set('Classification', 'collectsamples_prefix', prefix)
if name == self.TESTING:
rdn = dict()
settings.set('Processing', '%s_classification' % prefix, True)
settings.set('General', 'rendering_class',
self._class_rendering_params(prefix, settings))
else:
settings.set('Classification', 'collectsamples', True)
settings.set('General', 'positions', '')
settings.set('General', 'rendering', rdn)
return settings
def _get_modified_settings(self, name, has_timelapse=True):
settings = BaseProcessorFrame._get_modified_settings( \
self, name, has_timelapse)
settings.set('Processing', 'primary_classification', False)
settings.set('Processing', 'secondary_classification', False)
settings.set('Processing', 'tracking', False)
settings.set('Classification', 'collectsamples', False)
settings.set('General', 'rendering', {})
settings.set('General', 'rendering_class', {})
settings.set('Output', 'events_export_gallery_images', False)
settings.set('Output', 'hdf5_create_file', False)
settings.set('Output', 'rendering_channel_gallery', False)
current_tab = self._tab.current_index
if current_tab == 0:
prefix = 'primary'
settings.set('Processing', 'primary_featureextraction', True)
settings.set('Processing', 'secondary_featureextraction', False)
settings.set('Processing', 'tertiary_featureextraction', False)
settings.set('General', 'process_secondary', False)
settings.set('General', 'process_tertiary', False)
settings.set('General', 'process_merged', False)
rdn = {
"%s_%s" % (prefix,
settings.get(
"Classification", "%s_classification_regionname" % prefix)):
{}
}
elif current_tab == 1:
prefix = 'secondary'
settings.set('Processing', 'primary_featureextraction', False)
settings.set('Processing', 'secondary_featureextraction', True)
settings.set('General', 'process_secondary', True)
settings.set('Processing', 'tertiary_featureextraction', False)
settings.set('General', 'process_tertiary', False)
settings.set('General', 'process_merged', False)
# to setup the rending of the image currently processed
rdn = {
"%s_%s" % (prefix,
settings.get(
"Classification", "%s_classification_regionname" % prefix)):
{}
}
elif current_tab == 2:
prefix = 'tertiary'
seg_region = settings.get('Classification',
'tertiary_classification_regionname')
settings.set('Processing', 'primary_featureextraction', False)
settings.set('Processing', 'secondary_featureextraction', False)
settings.set('General', 'process_secondary', True)
settings.set('Processing', 'tertiary_featureextraction', True)
settings.set('General', 'process_tertiary', True)
settings.set('General', 'process_merged', False)
rdn = {
"%s_%s" % (prefix,
settings.get(
"Classification", "%s_classification_regionname" % prefix)):
{}
}
else:
# checkboxes in merged channel tab
pch = settings.get('Classification', 'merge_primary')
sch = settings.get('Classification', 'merge_secondary')
tch = settings.get('Classification', 'merge_tertiary')
settings.set('Processing', 'primary_featureextraction', pch)
settings.set('Processing', 'secondary_featureextraction', sch)
settings.set('General', 'process_secondary', sch)
settings.set('Processing', 'tertiary_featureextraction', tch)
settings.set('General', 'process_tertiary', tch)
settings.set('General', 'process_merged', True)
prefix = 'merged'
rdn = {}
for pfx in (CH_PRIMARY + CH_OTHER):
if settings.get("Classification", "merge_%s" % pfx):
rdn["%s_%s" %
(pfx,
settings.get("Classification",
"merged_%s_region" % pfx))] = {}
settings.set('Classification', 'collectsamples_prefix', prefix)
if name == self.PROCESS_TESTING:
rdn = dict()
settings.set('Processing', '%s_classification' % prefix, True)
settings.set('General', 'rendering_class',
self._class_rendering_params(prefix, settings))
else:
settings.set('Classification', 'collectsamples', True)
settings.set('General', 'positions', '')
settings.set('General', 'rendering', rdn)
return settings
def _process_image(self, ):
self.image_viewer.remove_objects()
settings = BaseProcessorFrame.get_special_settings(self._settings)
settings.set_section('General')
settings.set2('constrain_positions', True)
settings.set2('positions', self.coordinate.position)
settings.set2('redofailedonly', False)
settings.set2('framerange', True)
settings.set2('framerange_begin', self.coordinate.time)
settings.set2('framerange_end', self.coordinate.time)
settings.set_section('Processing')
_classify_objects = self._show_objects_by == 'classification'
settings.set2('primary_classification', _classify_objects)
settings.set2('secondary_classification', _classify_objects)
settings.set2('tertiary_classification', _classify_objects)
settings.set2('merged_classification', _classify_objects)
settings.set2('primary_featureextraction', _classify_objects)
settings.set2('secondary_featureextraction', _classify_objects)
settings.set2('objectdetection', self._detect_objects)
settings.set2('tracking', False)
settings.set_section('Output')
settings.set2('rendering_contours_discwrite', False)
settings.set2('rendering_class_discwrite', False)
settings.set2('export_object_counts', False)
settings.set2('export_object_details', False)
settings.set2('export_track_data', False)
settings.set2('hdf5_create_file', False)
settings.set_section('Classification')
settings.set2('collectsamples', False)
settings.set('General', 'rendering', {})
settings.set('General', 'rendering_class', {})
settings.set('Output', 'events_export_gallery_images', False)
# turn of output:
settings.set('Output', 'export_object_counts', False)
settings.set('Output', 'export_object_details', False)
settings.set('Output', 'export_file_names', False)
settings.set('Output', 'events_export_gallery_images', False)
settings.set('Output', 'export_track_data', False)
settings.set('Output', 'export_tracking_as_dot', False)
nchannels = len(self._imagecontainer.channels)
# XXX channel mapping unclear
# processing channel <--> color channel
# i.e problems if 2 processing channels have the same color
if nchannels == 2:
settings.set('General', 'process_secondary', True)
elif nchannels >= 3:
settings.set('General', 'process_secondary', True)
settings.set('General', 'process_tertiary', True)
settings.set('General', 'rendering', {})
analyzer = AnalyzerBrowser(self.coordinate.plate, settings,
self._imagecontainer)
res = None
try:
QApplication.setOverrideCursor(QCursor(Qt.WaitCursor))
res = analyzer.processPositions()
self.render_browser(res)
except Exception, e:
import traceback
from cecog.gui.util import exception
traceback.print_exc()
exception(self, str(e))
raise
def _get_modified_settings(self, name, has_timelapse=True):
settings = BaseProcessorFrame._get_modified_settings(
self, name, has_timelapse)
settings.set_section('ObjectDetection')
prim_id = PrimaryChannel.NAME
settings.set_section('Processing')
settings.set2('tracking', True)
settings.set2('tracking_synchronize_trajectories', False)
settings.set_section('Tracking')
region_name = settings.get2('tracking_regionname')
settings.set_section('General')
settings.set2('rendering_class', {})
settings.set2('rendering', {})
settings.set_section('Classification')
settings.set2('collectsamples', False)
settings.set('Output', 'hdf5_create_file', False)
show_ids = settings.get('Output', 'rendering_contours_showids')
show_ids_class = settings.get('Output', 'rendering_class_showids')
if name == self.PROCESS_TRACKING:
# tracking only invokes the primary channel
settings.set_section('Processing')
settings.set2('primary_classification', False)
settings.set2('primary_featureextraction', True)
settings.set2('secondary_processChannel', False)
settings.set2('secondary_featureextraction', False)
settings.set2('secondary_classification', False)
settings.set2('tertiary_processChannel', False)
settings.set2('tertiary_featureextraction', False)
settings.set2('tertiary_classification', False)
settings.set2('merged_processChannel', False)
settings.set2('merged_classification', False)
settings.set('Output', 'events_export_gallery_images', False)
settings.set(
'General', 'rendering', {
'primary_contours': {
PrimaryChannel.NAME: {
'raw': ('#FFFFFF', 1.0),
'contours': {
region_name: ('#FF0000', 1, show_ids)
}
}
}
})
else:
settings.set_section('Processing')
settings.set2('primary_featureextraction', True)
settings.set2('primary_classification', True)
settings.set2('tracking_synchronize_trajectories', True)
cl_rnd = {
'primary_classification': {
PrimaryChannel.NAME: {
'raw': ('#FFFFFF', 1.0),
'contours': [('primary', 'class_label', 1, False),
('primary', '#000000', 1, show_ids_class)]
}
},
}
settings.set('General', 'rendering_class', cl_rnd)
settings.set_section('Processing')
self._channel_render_settings(settings, SecondaryChannel.NAME,
show_ids_class)
self._channel_render_settings(settings, TertiaryChannel.NAME,
show_ids_class)
self._channel_render_settings(settings, MergedChannel.NAME,
show_ids_class)
return settings
def get_export_settings(self, settings, has_timelapse=True):
settings = BaseProcessorFrame.get_special_settings(settings, has_timelapse)
settings.set('General', 'version', version)
settings.set('General', 'rendering', {})
settings.set('General', 'rendering_class', {})
show_ids = settings.get('Output', 'rendering_contours_showids')
show_ids_class = settings.get('Output', 'rendering_class_showids')
# set properties of merged channel to the same as for Primary
for prefix in CH_PRIMARY+CH_OTHER:
if prefix == CH_PRIMARY[0] \
or settings.get('General', 'process_%s' %prefix):
d = {} # render settings for contours
for x in self.plugin_mgr.region_info.names[prefix]:
d = {'%s_contours_%s' % (prefix, x):
{prefix.capitalize(): {'raw': ('#FFFFFF', 1.0),
'contours': [(x, self.plugin_mgr.region_info.colors[x], 1, show_ids)]
}
}
}
settings.get('General', 'rendering').update(d)
# render settings for classifications
d = {}
if (settings.get('General', 'process_%s' %prefix) and \
settings.get('Processing', '%s_classification' % prefix)):
for x in self.plugin_mgr.region_info.names[prefix]:
if x == settings.get('Classification', '%s_classification_regionname' % prefix) or \
prefix == CH_VIRTUAL[0]:
d = {'%s_classification_%s' % (prefix, x):
{prefix.capitalize(): {'raw': ('#FFFFFF', 1.0),
'contours': [(x, 'class_label', 1, False),
(x, '#000000' , 1, show_ids_class)]
}
}
}
if settings('EventSelection', 'supervised_event_selection'):
settings.get('General', 'rendering_class').update(d)
# setup rendering properties for merged channel
# want the same rendering properties as for the primary channel!
if settings.get('General', 'process_merged'):
# color are defined for regions (not for channels)
# therefore, we first retrieve the regions for the primary channel
# and (in the case there are some) we assign the color of the first
# ROI of the primary channel to the merged contour.
regions_primary = self.plugin_mgr.region_info.names[CH_PRIMARY[0]]
if len(regions_primary) == 0:
default_color = '#FF00FF'
else:
default_color = self.plugin_mgr.region_info.colors[regions_primary[0]]
regions = self._merged_regions(settings)
d = {'merged_contours_%s' %str(regions):
{"Merged": {'raw': ('#FFFFFF', 1.0),
'contours': [(regions, default_color, 1, show_ids)]}}}
settings.get("General", "rendering").update(d)
if settings.get('Processing', 'merged_classification'):
d = {'merged_classification_%s' %str(regions):
{"Merged": {'raw': ('#FFFFFF', 1.0),
'contours': [(regions, 'class_label', 1, False),
(regions, '#000000' , 1, show_ids_class)]}}}
settings.get("General", "rendering_class").update(d)
if has_timelapse:
# generate raw images of selected channels (later used for gallery images)
if settings.get('Output', 'events_export_gallery_images'):
for prefix in CHANNEL_PREFIX:
if prefix == 'primary' or settings.get('General', 'process_%s' % prefix):
settings.get('General', 'rendering').update({prefix : {prefix.capitalize() :
{'raw': ('#FFFFFF', 1.0)}}})
return settings
def get_export_settings(self, settings, has_timelapse=True):
settings = BaseProcessorFrame.get_special_settings(
settings, has_timelapse)
settings.set('General', 'version', version)
settings.set('General', 'rendering', {})
settings.set('General', 'rendering_class', {})
# set properties of merged channel to the same as for Primary
for prefix in CH_PRIMARY + CH_OTHER:
if prefix == CH_PRIMARY[0] \
or settings.get('General', 'process_%s' %prefix):
d = {} # render settings for contours
for x in self.plugin_mgr.region_info.names[prefix]:
d = {
'%s_contours_%s' % (prefix, x): {
prefix.capitalize(): {
'raw': ('#FFFFFF', 1.0),
'contours':
[(x, self.plugin_mgr.region_info.colors[x], 1,
False)]
}
}
}
settings.get('General', 'rendering').update(d)
# render settings for classifications
d = {}
if (settings.get('General', 'process_%s' %prefix) and \
settings.get('Processing', '%s_classification' % prefix)):
for x in self.plugin_mgr.region_info.names[prefix]:
if x == settings.get('Classification', '%s_classification_regionname' % prefix) or \
prefix == CH_VIRTUAL[0]:
d = {
'%s_classification_%s' % (prefix, x): {
prefix.capitalize(): {
'raw': ('#FFFFFF', 1.0),
'contours': [(x, 'class_label', 1, False),
(x, '#000000', 1, False)]
}
}
}
if settings('EventSelection', 'supervised_event_selection'):
settings.get('General', 'rendering_class').update(d)
# setup rendering properties for merged channel
# want the same rendering properties as for the primary channel!
if settings.get('General', 'process_merged'):
# color are defined for regions (not for channels)
# therefore, we first retrieve the regions for the primary channel
# and (in the case there are some) we assign the color of the first
# ROI of the primary channel to the merged contour.
regions_primary = self.plugin_mgr.region_info.names[CH_PRIMARY[0]]
if len(regions_primary) == 0:
default_color = '#FF00FF'
else:
default_color = self.plugin_mgr.region_info.colors[
regions_primary[0]]
regions = self._merged_regions(settings)
d = {
'merged_contours_%s' % str(regions): {
"Merged": {
'raw': ('#FFFFFF', 1.0),
'contours': [(regions, default_color, 1, False)]
}
}
}
settings.get("General", "rendering").update(d)
if settings.get('Processing', 'merged_classification'):
d = {
'merged_classification_%s' % str(regions): {
"Merged": {
'raw': ('#FFFFFF', 1.0),
'contours': [(regions, 'class_label', 1, False),
(regions, '#000000', 1, False)]
}
}
}
settings.get("General", "rendering_class").update(d)
return settings
def get_export_settings(cls, settings, has_timelapse=True):
settings = BaseProcessorFrame.get_special_settings(settings, has_timelapse)
settings.set('General', 'rendering', {})
settings.set('General', 'rendering_class', {})
additional_prefixes = [SecondaryChannel.PREFIX, TertiaryChannel.PREFIX]
settings.set_section('Classification')
sec_class_regions = dict([(prefix,
settings.get2('%s_classification_regionname' % prefix))
for prefix in additional_prefixes])
settings.set_section('ObjectDetection')
prim_id = PrimaryChannel.NAME
sec_ids = dict([(x.PREFIX, x.NAME) for x in [SecondaryChannel, TertiaryChannel]])
sec_regions = dict([(prefix, [v for k,v in regions.iteritems() if settings.get2(k)])
for prefix, regions in [(SecondaryChannel.PREFIX, SECONDARY_REGIONS),
(TertiaryChannel.PREFIX, TERTIARY_REGIONS),
]
])
show_ids = settings.get('Output', 'rendering_contours_showids')
show_ids_class = settings.get('Output', 'rendering_class_showids')
settings.get('General', 'rendering').update({'primary_contours': {prim_id: {'raw': ('#FFFFFF', 1.0),
'contours': {'primary': ('#FF0000', 1, show_ids)}}}})
settings.set_section('Processing')
if settings.get2('primary_classification'):
settings.get('General', 'rendering_class').update({'primary_classification': {prim_id: {'raw': ('#FFFFFF', 1.0),
'contours': [('primary', 'class_label', 1, False),
('primary', '#000000', 1, show_ids_class),
]}}})
for prefix in additional_prefixes:
if settings.get2('%s_processchannel' % prefix):
sec_id = sec_ids[prefix]
settings.get('General', 'rendering').update(dict([('%s_contours_%s' % (prefix, x), {sec_id: {'raw': ('#FFFFFF', 1.0),
'contours': [(x, SECONDARY_COLORS[x] , 1, show_ids)]
}})
for x in sec_regions[prefix]]))
if settings.get2('%s_classification' % prefix):
sec_id = sec_ids[prefix]
sec_region = sec_class_regions[prefix]
settings.get('General', 'rendering_class').update({'%s_classification_%s' % (prefix, sec_region):
{sec_id: {'raw': ('#FFFFFF', 1.0),
'contours': [(sec_region, 'class_label', 1, False),
(sec_region, '#000000', 1, show_ids_class),
]}}})
if has_timelapse:
# generate raw images of selected channels (later used for gallery images)
if settings.get('Output', 'events_export_gallery_images'):
settings.get('General', 'rendering').update({'primary' : {prim_id : {'raw': ('#FFFFFF', 1.0)}}})
for prefix in additional_prefixes:
if settings.get2('%s_processchannel' % prefix):
sec_id = sec_ids[prefix]
settings.get('General', 'rendering').update({prefix : {sec_id : {'raw': ('#FFFFFF', 1.0)}}})
return settings
def get_export_settings(cls, settings, has_timelapse=True):
settings = BaseProcessorFrame.get_special_settings(settings, has_timelapse)
settings.set('General', 'version', VERSION)
settings.set('General', 'rendering', {})
settings.set('General', 'rendering_class', {})
show_ids = settings.get('Output', 'rendering_contours_showids')
show_ids_class = settings.get('Output', 'rendering_class_showids')
# set propertys of merged channel to the same as for Primary
# unfortunately REGION_INFO is like a global variable
d = {}
for prefix in CH_PRIMARY+CH_OTHER:
if prefix == CH_PRIMARY[0] \
or settings.get('Processing', '%s_processchannel' % prefix):
for x in reginfo.names[prefix]:
d = {'%s_contours_%s' % (prefix, x):
{prefix.capitalize(): {'raw': ('#FFFFFF', 1.0),
'contours': [(x, reginfo.colors[x], 1, show_ids)]
}
}
}
settings.get('General', 'rendering').update(d)
if settings.get('Processing', '%s_classification' % prefix):
for x in reginfo.names[prefix]:
if x == settings.get('Classification', '%s_classification_regionname' % prefix) or \
prefix == CH_VIRTUAL[0]:
d = {'%s_classification_%s' % (prefix, x):
{prefix.capitalize(): {'raw': ('#FFFFFF', 1.0),
'contours': [(x, 'class_label', 1, False),
(x, '#000000' , 1, show_ids_class)]
}
}
}
settings.get('General', 'rendering_class').update(d)
# setup rendering properties for merged channel
# want the same rendering properties as for the primary channel!
if settings.get('Processing', 'merged_processchannel'):
regions = cls._merged_regions(settings)
d = {'merged_contours_%s' %'-'.join(regions):
{"Merged": {'raw': ('#FFFFFF', 1.0),
'contours': [(regions, reginfo.colors["primary"], 1, show_ids)]}}}
settings.get("General", "rendering").update(d)
if settings.get('Processing', 'merged_classification'):
d = {'merged_classification_%s' %'-'.join(regions):
{"Merged": {'raw': ('#FFFFFF', 1.0),
'contours': [(regions, 'class_label', 1, False),
(regions, '#000000' , 1, show_ids_class)]}}}
settings.get("General", "rendering_class").update(d)
if has_timelapse:
# generate raw images of selected channels (later used for gallery images)
if settings.get('Output', 'events_export_gallery_images'):
for prefix in CHANNEL_PREFIX:
if prefix == 'primary' or settings.get('Processing', '%s_processchannel' % prefix):
settings.get('General', 'rendering').update({prefix : {prefix.capitalize() :
{'raw': ('#FFFFFF', 1.0)}}})
return settings
def _get_modified_settings(self, name, has_timelapse=True):
settings = BaseProcessorFrame._get_modified_settings(self, name, has_timelapse)
settings.set_section('ObjectDetection')
prim_id = PrimaryChannel.NAME
sec_id = SecondaryChannel.NAME
#sec_regions = settings.get2('secondary_regions')
settings.set_section('Processing')
settings.set2('primary_classification', False)
settings.set2('secondary_classification', False)
settings.set2('tracking', False)
settings.set_section('Classification')
settings.set2('collectsamples', False)
settings.set('General', 'rendering', {})
settings.set('General', 'rendering_class', {})
settings.set('Output', 'events_export_gallery_images', False)
show_ids_class = settings.get('Output', 'rendering_class_showids')
current_tab = self._tab.currentIndex()
if current_tab == 0:
settings.set('Processing', 'primary_featureextraction', True)
settings.set('Processing', 'secondary_featureextraction', False)
settings.set_section('Classification')
settings.set2('collectsamples_prefix', 'primary')
settings.set('Processing', 'secondary_processChannel', False)
if name == self.PROCESS_TESTING:
settings.set('Processing', 'primary_classification', True)
settings.set('General', 'rendering_class', {'primary_classification': {prim_id: {'raw': ('#FFFFFF', 1.0),
'contours': [('primary', 'class_label', 1, False),
('primary', '#000000', 1, show_ids_class),
]}}})
else:
settings.set2('collectsamples', True)
settings.set('General', 'positions', '')
settings.set('General', 'framerange_begin', 0)
settings.set('General', 'framerange_end', 0)
else:
settings.set('Processing', 'primary_featureextraction', False)
settings.set('Processing', 'secondary_featureextraction', True)
settings.set_section('Classification')
sec_region = settings.get2('secondary_classification_regionname')
settings.set2('collectsamples_prefix', 'secondary')
for k,v in SECONDARY_REGIONS.iteritems():
settings.set('ObjectDetection', k, v == sec_region)
settings.set('Processing', 'secondary_processchannel', True)
if name == self.PROCESS_TESTING:
settings.set('Processing', 'secondary_classification', True)
settings.set('General', 'rendering_class', {'secondary_classification_%s' % sec_region: {sec_id: {'raw': ('#FFFFFF', 1.0),
'contours': [(sec_region, 'class_label', 1, False),
(sec_region, '#000000', 1, show_ids_class),
]}}})
else:
settings.set2('collectsamples', True)
settings.set('General', 'positions', '')
settings.set('General', 'framerange_begin', 0)
settings.set('General', 'framerange_end', 0)
return settings
