def subprocessFeatureExtractionFrame(path_root, path_folder, fn):
"""
subprocess for essentia freesound feature extractor
:param path_root: input audio root path
:param path_folder: input audio subfolder path
:param fn: audio file name
:return:
"""
extractor = es.FreesoundExtractor(lowlevelFrameSize=2048,
lowlevelHopSize=1024,
tonalFrameSize=2048,
tonalHopSize=1024,
gfccStats=["mean"],
mfccStats=["mean"],
lowlevelStats=["mean", "stdev"],
tonalStats=["mean", "stdev"],
rhythmStats=["mean"])
feature_aggregated, _ = extractor(os.path.join(path_root, path_folder, fn))
feature_array, list_desc = convert_essentia_pool_2_feature_array(
feature_aggregated)
ensure_dir(os.path.join(path_root, path_folder + "_feature"))
pickle.dump([feature_array, list_desc],
open(
os.path.join(path_root, path_folder + "_feature",
fn + ".pkl"), 'w'))
def subprocessFeatureExtractionFrame(path_audio,
path_feature_freesound_statistics, fn):
"""
Run this in process to avoid memory leak
:param path_audio:
:param path_feature_freesound_statistics:
:param fn:
:return:
"""
extractor = es.FreesoundExtractor(lowlevelFrameSize=4096,
lowlevelHopSize=2048)
_, feature_frame_pool = extractor(os.path.join(path_audio, fn))
feature_pd_DataFrame = frame_pool_aggregation(feature_frame_pool, fn)
feature_pd_DataFrame.to_csv(
os.path.join(path_feature_freesound_statistics,
fn.split('.')[0] + '.csv'))
def batchFeatureExtractionFrame(path_audio, path_feature_freesound_statistics,
channel_string):
filenames_audio = [
f for f in os.listdir(path_audio)
if os.path.isfile(os.path.join(path_audio, f))
]
for ii, fn in enumerate(filenames_audio):
if ii < 21840:
continue
print('calculating', ii, fn, 'audio feature for', channel_string,
'in total', len(filenames_audio))
# try:
extractor = es.FreesoundExtractor(lowlevelFrameSize=4096,
lowlevelHopSize=2048)
_, feature_frame_pool = extractor(os.path.join(path_audio, fn))
feature_pd_DataFrame = frame_pool_aggregation(feature_frame_pool, fn)
feature_pd_DataFrame.to_csv(
os.path.join(path_feature_freesound_statistics,
fn.split('.')[0] + '.csv'))
'lowlevelHopSize': 1024,
'lowlevelWindowType': 'blackmanharris62',
'lowlevelSilentFrames': 'noise',
'lowlevelStats': stats,
'rhythmMethod': 'degara',
'rhythmMinTempo': 40,
'rhythmMaxTempo': 208,
'rhythmStats': stats,
'tonalFrameSize': 4096,
'tonalHopSize': 2048,
'tonalWindowType': 'blackmanharris62',
'tonalSilentFrames': 'noise',
'tonalStats': stats
}
features, features_frames = es.FreesoundExtractor(
**profile)(audio_in)
file_json = output + ".json"
es.YamlOutput(filename=file_json, format='json')(features)
tab_header = []
tab_value = []
features_name = sorted(features.descriptorNames())
for feat in range(0, len(features_name)):
name_feature = features_name[feat]
# print(name)
kind_of_feature = name_feature.split(".")
# print(type)
# ALL FEATURES
# if(kind_of_feature[0] != 'metadata' and