def logger(self): logger = logging.getLogger(__name__) if not logger.handlers: from dcase_util.utils import setup_logging setup_logging() return logger
def logger(self): """Logger instance""" logger = logging.getLogger(__name__) if not logger.handlers: setup_logging() return logger
def feature_extractor_factory(feature_extractor_label, **kwargs): """Function to get correct feature extractor class instance based on extractor label or class name. Parameters ---------- feature_extractor_label : str Class name or extractor label Raises ------ NameError Class does not exists Returns ------- Feature extractor class instance """ try: feature_extractor_class = None # Get all classes inherited from FeatureExtractor class_list = get_class_inheritors(FeatureExtractor) # Search correct feature extractor for item in class_list: if str(item.__name__) == feature_extractor_label: feature_extractor_class = getattr( importlib.import_module(str(item.__module__)), feature_extractor_label) break elif hasattr( item, 'label' ) and item.label == feature_extractor_label and item.__name__.endswith( 'Extractor'): feature_extractor_class = getattr( importlib.import_module(str(item.__module__)), item.__name__) break # Valid feature extractor class not found, raise error if not feature_extractor_class: raise AttributeError except AttributeError: message = 'Invalid FeatureExtractor class name or extractor label given [{label}].'.format( label=feature_extractor_label) logger = logging.getLogger(__name__) if not logger.handlers: setup_logging() logger.exception(message) raise AttributeError(message) return feature_extractor_class(**dict(kwargs))
def logger(self): logger = logging.getLogger(__name__) if not logger.handlers: setup_logging() return logger
def logger(): logger_instance = logging.getLogger(__name__) if not logger_instance.handlers: setup_logging() return logger_instance
class MyLogger(object): def debug(self, msg): pass def warning(self, msg): pass def error(self, msg): pass if __name__ == "__main__": from dcase_util.ui.ui import FancyLogger from dcase_util.utils import setup_logging setup_logging(logging_file='download_data.log') log = FancyLogger() log.title("Download_data") log.info( "Once database is downloaded, do not forget to check your missing_files" ) # Modify it with the number of process you want, but be careful, youtube can block you if you put too many. N_JOBS = 3 # Only useful when multiprocessing, # if chunk_size is high, download is faster. Be careful, progress bar only update after each chunk. CHUNK_SIZE = 10 log.line("Test data")
# -*- coding: utf-8 -*- ######################################################################### # Initial software # Copyright Nicolas Turpault, Romain Serizel, Hamid Eghbal-zadeh, Ankit Parag Shah, 2018, v1.0 # This software is distributed under the terms of the License MIT ######################################################################### import pandas as pd import glob import os import argparse from dcase_util.ui.ui import FancyLogger from dcase_util.utils import setup_logging setup_logging(logging_file='check_data.log') log = FancyLogger() # This function is not used in the baseline but can be used to check if your audio folders correspond to your metadata def check_audio_vs_meta(csv_file, audio_dir, write=False): """ Check AudioSet filenames contained in csv_file are all present in the resulting audio directory Parameters ---------- csv_file : str, filename of a csv file which contains a column "filename" listing AudioSet filenames downloaded audio_dir : str, audio directory which contains downloaded files write : bool, Write the missing files into a csv file or not.