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.
