def main_extractor(args):
"""main_extractor
Compute the comprehensive extractor feature set over the input
waveform and dump the pickled result into a file
"""
audio = loadaudio(args)
frame = audio
extr = estd.Extractor(
lowLevelFrameSize = args.frame_size_low_level,
lowLevelHopSize = int(args.frame_size_low_level/2),
)
# # compute the centroid for all frames in our audio and add it to the pool
# for frame in estd.FrameGenerator(audio, frameSize = 10 * args.samplerate, hopSize = 5 * args.samplerate):
# dreal, ddfa = danceability(w(frame))
# print "d", dreal # , "frame", frame
# pool.add('rhythm.danceability', dreal)
# compute feature of frame and put them into dict p
p = extr(frame)
pdict = {}
# print "type(p)", type(p)
for desc in p.descriptorNames():
print((desc, type(p[desc])))
# print "{0: >20}: {1}".format(desc, p[desc])
pdict[desc] = p[desc]
pickle.dump(pdict, open("data/music_features_%s.pkl" % (util_filename_clean(args.file), ), "wb"))
def featureExtraction(soundfiles):
#extractor = esst.LowLevelSpectralExtractor()
extractor = esst.Extractor(dynamics=True,
dynamicsFrameSize=88200,
dynamicsHopSize=44100,
highLevel=True,
lowLevel=True,
lowLevelFrameSize=2048,
lowLevelHopSize=1024,
midLevel=True,
namespace="",
relativeIoi=False,
rhythm=True,
sampleRate=44100,
tonalFrameSize=4096,
tonalHopSize=2048,
tuning=True)
#soundfiles = listdir(inputPath)
for file, outPath in soundfiles:
audioLoader = esst.MonoLoader(filename=file)
audio = audioLoader()
pool = essentia.Pool()
pool = extractor(audio)
aggPool = esst.PoolAggregator()(pool)
esst.YamlOutput(filename=outPath + 'features.json',
format='json')(aggPool)
print(file + ' exported')
def extractDefaultFeatures(audio, outputDir):
# compute all features for all sounds
extractor = ess.Extractor(dynamics=True,
dynamicsFrameSize=88200,
dynamicsHopSize=44100,
highLevel=True,
lowLevel=True,
lowLevelFrameSize=2048,
lowLevelHopSize=1024,
midLevel=True,
namespace="",
relativeIoi=False,
rhythm=True,
sampleRate=44100,
tonalFrameSize=4096,
tonalHopSize=2048,
tuning=True)
pool = essentia.Pool()
pool = extractor(audio)
aggPool = ess.PoolAggregator()(pool)
if not path.exists(outputDir):
makedirs(outputDir)
ess.YamlOutput(filename=outputDir + "features.json",
format="json",
doubleCheck=True)(aggPool)
def featureExtraction(soundfiles):
# extractor = esst.LowLevelSpectralExtractor()
extractor = esst.Extractor(dynamics = False,
dynamicsFrameSize = 88200,
dynamicsHopSize = 44100,
highLevel = False,
lowLevel = True,
lowLevelFrameSize = 2048,
lowLevelHopSize = 1024,
midLevel = True,
namespace = "",
relativeIoi = False,
rhythm = False,
sampleRate = 44100,
tonalFrameSize = 4096,
tonalHopSize = 2048,
tuning = True)
#soundfiles = listdir(inputPath)
for file in soundfiles:
path1= '/Users/helena/Desktop/SMC/ASP/sms-tools/workspace/A10/code/downloaded/'
name=file[70:-4] + '_features.json'
outPath = path1 + 'features/' + name
print file
audioLoader = esst.MonoLoader(filename=file)
audio = audioLoader()
pool = essentia.Pool()
pool = extractor(audio)
aggPool = esst.PoolAggregator()(pool)
output = esst.YamlOutput(filename = outPath, format='json')
output(aggPool)
print (outPath + ' exported')