def __cleanup(self) -> None:
MediaObserver.__LOG.debug("Detaching event handlers")
self.__event_handler.shutdown()
MediaObserver.__LOG.debug("Shutting down observers")
try:
self.__observer.unschedule_all()
self.__observer.stop()
self.__observer.join()
MediaObserver.__LOG.debug(
f"Stop observing {self.__converter_config.media_in_folder}")
except RuntimeError as e:
MediaObserver.__LOG.debug(f"{e}", exc_info=True)
MediaObserver.__LOG.debug("Shutting down logging service")
LogManager.get_instance().shutdown()
def __init__(self,
rules: List[Rule],
max_threads: int = DEFAULT_MAX_THREADS):
super().__init__()
FileEventHandler.__LOG = LogManager.get_instance().get(
LogManager.Logger.OBSERVER)
self.__dispatcher = FileDispatcher(rules)
self.__executor = ThreadPoolExecutor(max_workers=max_threads)
def __cleanup(self) -> None:
FileObserver.__LOG.debug("Detaching event handlers")
self.__event_handler.shutdown()
FileObserver.__LOG.debug("Shutting down observers")
try:
for directory in self.__dir_obs_dict:
self.__dir_obs_dict[directory].unschedule_all()
# stop observer if interrupted
self.__dir_obs_dict[directory].stop()
# Wait until the thread terminates before exit
self.__dir_obs_dict[directory].join()
FileObserver.__LOG.debug(f"Stop observing {directory}")
except RuntimeError as e:
FileObserver.__LOG.debug(f"{e}", exc_info=True)
FileObserver.__LOG.debug("Shutting down logging service")
LogManager.get_instance().shutdown()
def __init__(self, ffmpeg: str = FFMPEG_BIN, ffprobe: str = FFPROBE_BIN):
super().__init__()
Validation.is_installed(ffmpeg, f"Wrong path for {FFmpeg.FFMPEG_BIN}")
Validation.is_installed(ffprobe,
f"Wrong path for {FFmpeg.FFPROBE_BIN}")
FFmpeg.__LOG = LogManager.get_instance().get(
LogManager.Logger.CONVERTER)
self.__converter = Converter(ffmpeg, ffprobe)
def __init__(self, rules: List[Rule]):
super().__init__()
FileDispatcher.__LOG = LogManager.get_instance().get(
LogManager.Logger.DISPATCHER)
self.__rules = rules
if len(rules) == 0:
FileDispatcher.__LOG.warning(
"No rule specified. All files will be skipped.")
def __init__(self, conf: Conf):
super().__init__()
# validate python version
Validation.python_version(
Evaluator.REQUIRED_PYTHON, f"Unsupported Python version.\n"
f"Required Python {Evaluator.REQUIRED_PYTHON[0]}.{Evaluator.REQUIRED_PYTHON[1]} or higher."
)
Validation.can_read(
conf.dataset_train,
f"Training set file *must* exists and be readable. "
f"Current file: '{conf.dataset_train}'.\n"
f"Training set path (fully qualified) can be specified in conf.ini file or using Conf object."
)
Validation.can_read(
conf.dataset_test, f"Test set file *must* exists and be readable. "
f"Current file: '{conf.dataset_test}'.\n"
f"Test set path (fully qualified) can be specified in conf.ini file or using Conf object."
)
self.__LOG = LogManager.get_instance().logger(LogManager.Logger.EVAL)
self.__conf = conf
# using full dataset as training set
self.__training = Set(pd.read_csv(self.conf.dataset_train))
# load test set if it has same format as training_set.csv provided
# as example file see ./res/dataset/test_set_no_index.csv
self.__test = Set(pd.read_csv(self.conf.dataset_test))
# load test set if it has header (F1-20 and CLASS row) and index, so a test test saved using
# command pd.to_csv('/path', index=True)
# as example file see ./res/dataset/test_set_index.csv
# self.__test = Set(pd.read_csv(self.conf.dataset_test, index_col=0))
# load test set if it does not have header row (does not have F1-20 and CLASS row) and
# it is was not saved using command pd.to_csv('/path', index=True), so it has not index
# as example file see ./res/dataset/test_set_no_index_features.csv
# self.__test = Set(pd.read_csv(self.conf.dataset_test, header=None,
# names=[f"F{i}" for i in range(1, 21)] + ["CLASS"]))
# current classifiers used
self.__classifiers = {
Evaluator._MULTILAYER_PERCEPTRON:
None,
Evaluator._SUPPORT_VECTOR_MACHINE:
None,
# Evaluator._DECISION_TREE: None,
Evaluator._RANDOM_FOREST:
None,
# Evaluator._KNEAREST_NEIGHBORS: None,
# Evaluator._STOCHASTIC_GRADIENT_DESCENT: None,
Evaluator._ADA_BOOST:
None,
# Evaluator._NAIVE_BAYES: None,
# Evaluator._KMEANS: None
}
def __init__(self,
max_processes: int = DEFAULT_MAX_PROCESSES,
converter: ConverterFactory.Converters = DEFAULT_CONVERTER):
super().__init__()
MediaEventHandler.__LOG = LogManager.get_instance().get(
LogManager.Logger.OBSERVER)
self.__converter = ConverterFactory.get_type(converter)
self.__executor = ProcessPoolExecutor(
max_workers=max_processes,
initializer=MediaEventHandler.__init_worker)
def __init_loggers(cls, log_filename: str) -> None:
log_manager = LogManager.get_instance()
log_manager.load(log_filename)
MediaObserver.__LOG = log_manager.get(LogManager.Logger.OBSERVER)
def __init_logging(self):
self.__LOG_MANAGER = LogManager.get_instance()
# get root logger
self.__LOG = self.__LOG_MANAGER.logger(LogManager.Logger.ROOT)