def load_training_settings(training_name):
file_path = get_training_settings_file_path(training_name)
logging.info(f'Loading annotator settings from "{file_path}"...')
text = file_path.read_text()
dict_ = yaml_utils.load(text)
return Settings.create_from_dict(dict_)
def _load_settings(self):
path = classifier_utils.get_settings_file_path(self.clip_type)
logging.info('Loading classifier settings from "{}"...'.format(path))
text = path.read_text()
d = yaml_utils.load(text)
return Settings.create_from_dict(d)
def create_settings_from_dict(self, d):
settings = Settings.create_from_dict(d)
return Settings(self.defaults, settings)
def _load_settings(self):
path = classifier_utils.get_settings_file_path(self._clip_type)
text = path.read_text()
d = yaml_utils.load(text)
return Settings.create_from_dict(d)
def test_create_from_dict(self):
contents = os_utils.read_file(_SETTINGS_FILE_PATH)
d = yaml_utils.load(contents)
settings = Settings.create_from_dict(d)
self._check_settings(settings)
def _load_settings(self):
path = classifier_utils.get_settings_file_path(self.clip_type)
logging.info('Loading classifier settings from "{}"...'.format(path))
text = path.read_text()
d = yaml_utils.load(text)
return Settings.create_from_dict(d)