def __init__(self):
self.path_manager = ds.PathManager()
self.dset_store = ds.DetectionSetStore()
self.hypothesis_manager = ds.HypothesisManager()
self.claim_manager = ds.ClaimManager()
self.graph = ds.Graph(self.dset_store, future_depth=3)
def __init__(self, app, parent=None):
super(MainWindow, self).__init__(parent)
self.resize(1000, 600)
self.setWindowTitle('BeesBook Filtering Editor')
self.central_widget = QtGui.QStackedWidget(self)
self.setCentralWidget(self.central_widget)
self.dset_store = ds.DetectionSetStore()
self.path_manager = ds.PathManager()
self.loader_tab = LoaderTab(self, app)
self.editor_tab = EditorTab(self, app)
self.central_widget.addWidget(self.loader_tab)
self.central_widget.addWidget(self.editor_tab)
self.central_widget.setCurrentWidget(self.loader_tab)
def __init__(self):
self.path_manager = ds.PathManager()
self.dset_store = ds.DetectionSetStore()
self.claim_manager = ds.ClaimManager()
def load_tracks(self):
if self.dset_store is None:
print 'Error: no data folder loaded'
return
self.block_inputs(True)
self.dset_store.delete_path_associations()
self.path_manager = ds.PathManager(config.PATHS_FILE)
if os.path.isfile(config.PATHS_FILE):
try:
with open(config.PATHS_FILE, 'rb') as paths_file:
input = pickle.load(paths_file)
if self.dset_store.source != input['source']:
print 'Warning: data source for detections and paths do not match'
paths_input = input['paths']
self.paths_load_progress.setMaximum(len(paths_input))
self.app.processEvents()
for i, tag_id in enumerate(paths_input.keys()):
self.path_manager.paths[tag_id] = {}
for path_id in paths_input[tag_id].keys():
path = ds.Path(tag_id)
self.path_manager.paths[tag_id][path_id] = path
for frame, detection_data in paths_input[tag_id][
path_id].items():
timestamp = self.dset_store.get_timestamp(frame)
if timestamp is not None:
detection_id, pos_x, pos_y, readability = detection_data
# data point is associated with a detection from the pipeline output
if detection_id is not None:
dset = self.dset_store.get(timestamp)
if detection_id in dset.detections:
detection = dset.detections[
detection_id]
else:
print 'Warning: detection_id not found, your truth file does not match your pipeline data. Please rematch!'
continue
# if two paths claim the same detection only the first one gets it
if detection.path is None:
detection.readability = readability
path.add_detection(detection)
# insert empty detection for every following path
else:
detection = ds.EmptyDetection(
timestamp)
detection.position = np.array(
[pos_x, pos_y])
detection.readability = readability
path.add_detection(detection)
# data point is an empty detection
else:
detection = ds.EmptyDetection(timestamp)
detection.position = np.array(
[pos_x, pos_y])
detection.readability = readability
path.add_detection(detection)
self.paths_load_progress.setValue(i + 1)
self.app.processEvents()
self.paths_load_label.setText(
str(len(paths_input)) + ' paths loaded')
self.app.processEvents()
except:
pass
else:
self.paths_load_progress.setMaximum(1)
self.paths_load_progress.setValue(1)
self.paths_load_label.setText('will write to new file')
self.app.processEvents()
self.block_inputs(False)