return options, args
if __name__ == '__main__':
opts, args = parse_args()
if len(args) != 2:
cmd = './' + os.path.basename(sys.argv[0]) + ' -h'
os.system(cmd)
sys.exit(1)
if opts.generate_dot:
essentia.translate(PitchExtractor,
'streaming_extractorpitch',
dot_graph=True)
elif opts.generate_cpp:
essentia.translate(PitchExtractor,
'streaming_extractorpitch',
dot_graph=False)
# find out replay gain
loader = EqloudLoader(filename=args[0],
sampleRate=analysisSampleRate,
downmix='mix')
rgain = ReplayGain(applyEqloud=False)
pool = essentia.Pool()
loader.audio >> rgain.signal
return options, args
if __name__ == '__main__':
opts, args = parse_args()
if len(args) != 2:
cmd = './'+os.path.basename(sys.argv[0])+ ' -h'
os.system(cmd)
sys.exit(1)
if opts.generate_dot:
essentia.translate(RhythmDescriptorsExtractor, "streaming_extractorrhythmdescriptors", dot_graph=True)
elif opts.generate_cpp:
essentia.translate(RhythmDescriptorsExtractor, "streaming_extractorrhythmdescriptors", dot_graph=False)
pool = essentia.Pool()
loader = essentia.streaming.MonoLoader(filename=args[0])
rhythm = RhythmDescriptorsExtractor()
loader.audio >> rhythm.signal
for desc, output in rhythm.outputs.items():
output >> (pool, desc)
essentia.run(loader)
stats = ['mean', 'var', 'min', 'max', 'dmean', 'dmean2', 'dvar', 'dvar2']
poolStats = essentia.standard.PoolAggregator(defaultStats=stats)(pool)
essentia.standard.YamlOutput(filename=args[1])(poolStats)
return options, args
if __name__ == '__main__':
opts, args = parse_args()
if len(args) != 2:
cmd = './'+os.path.basename(sys.argv[0])+ ' -h'
os.system(cmd)
sys.exit(1)
if opts.generate_dot:
essentia.translate(PanningExtractor, 'streaming_extractorpanning', dot_graph=True)
elif opts.generate_cpp:
essentia.translate(PanningExtractor, 'streaming_extractorpanning', dot_graph=False)
pool = essentia.Pool()
loader = AudioLoader(filename=args[0])
panExtractor = PanningExtractor()
loader.audio >> panExtractor.signal
loader.numberChannels >> None
loader.sampleRate >> None
panExtractor.panning_coefficients >> (pool, namespace + '.panning_coefficients')
essentia.run(loader)
essentia.standard.YamlOutput(filename=args[1])(pool)
return options, args
if __name__ == '__main__':
opts, args = parse_args()
if len(args) != 2:
cmd = './' + os.path.basename(sys.argv[0]) + ' -h'
os.system(cmd)
sys.exit(1)
if opts.generate_dot:
essentia.translate(SfxExtractor,
'streaming_extractorsfx',
dot_graph=True)
elif opts.generate_cpp:
essentia.translate(SfxExtractor,
'streaming_extractorsfx',
dot_graph=False)
pool = essentia.Pool()
loader = MonoLoader(filename=args[0])
sfx = SfxExtractor()
loader.audio >> sfx.signal
for desc, output in sfx.outputs.items():
output >> (pool, namespace + '.' + desc)
essentia.run(loader)
(options, args) = parser.parse_args()
return options, args
if __name__ == '__main__':
opts, args = parse_args()
if len(args) != 2:
cmd = './'+os.path.basename(sys.argv[0])+ ' -h'
os.system(cmd)
sys.exit(1)
if opts.generate_dot:
essentia.translate(TuningFrequencyExtractor, 'streaming_extractortuningfrequency', dot_graph=True)
elif opts.generate_cpp:
essentia.translate(TuningFrequencyExtractor, 'streaming_extractortuningfrequency', dot_graph=False)
pool = essentia.Pool()
loader = essentia.streaming.MonoLoader(filename=args[0])
tuning = TuningFrequencyExtractor()
loader.audio >> tuning.signal
tuning.tuningFrequency >> (pool, 'tuning_frequency')
essentia.run(loader)
stats = ['mean', 'var', 'min', 'max', 'dmean', 'dmean2', 'dvar', 'dvar2']
poolStats = essentia.standard.PoolAggregator(defaultStats=stats)(pool)
essentia.standard.YamlOutput(filename=args[1])(poolStats)
self.outputs['mfcc'] = mfcc.mfcc
if __name__ == '__main__':
# Make sure the command was well-formed.
if len(sys.argv) < 3:
print 'Usage: extractor_mfcc.py <input audio filename> <output yaml filename>'
sys.exit(1)
# Loaders must be specified outside your composite algorithm.
loader = essentia.streaming.MonoLoader(filename=sys.argv[1])
# We are using the default values of our parameters so we don't specify any keyword arguments.
mfccex = ExtractorMfcc()
p = essentia.Pool()
# When connecting to/from your composite algorithm, use the names you declared in the
# self.inputs and self.outputs dictionaries, respectively.
loader.audio >> mfccex.audio
mfccex.mfcc >> (p, 'mfcc')
essentia.run(loader)
# CompoxiteBase algorithms can be translated into c++ code and dot graphs
# can also be generated:
essentia.translate(ExtractorMfcc, # algorithm to be translated
'myExtractorMfcc', # output name for the c++ and dot generated files
dot_graph=True) # whether dot file should be generated
essentia.standard.YamlOutput(filename=sys.argv[2])(p)
(options, args) = parser.parse_args()
return options, args
if __name__ == '__main__':
opts, args = parse_args()
if len(args) != 2:
cmd = './'+os.path.basename(sys.argv[0])+ ' -h'
os.system(cmd)
sys.exit(1)
if opts.generate_dot:
essentia.translate(LowLevelSpectralEqloudExtractor, 'streaming_extractorlowlevelspectraleqloud', dot_graph=True)
elif opts.generate_cpp:
essentia.translate(LowLevelSpectralEqloudExtractor, 'streaming_extractorlowlevelspectraleqloud', dot_graph=False)
loader = EqloudLoader(filename=args[0], replayGain=-6)
lowlevelExtractor = LowLevelSpectralEqloudExtractor()
pool = essentia.Pool()
loader.audio >> lowlevelExtractor.signal
for desc, output in lowlevelExtractor.outputs.items():
output >> (pool, namespace + '.' + desc)
essentia.run(loader)
# compute aggregation on values:
return options, args
if __name__ == '__main__':
opts, args = parse_args()
if len(args) != 2:
cmd = './' + os.path.basename(sys.argv[0]) + ' -h'
os.system(cmd)
sys.exit(1)
if opts.generate_dot:
essentia.translate(LevelExtractor,
'streaming_extractorlevel',
dot_graph=True)
elif opts.generate_cpp:
essentia.translate(LevelExtractor,
'streaming_extractorlevel',
dot_graph=False)
# find out replay gain:
loader = EqloudLoader(filename=args[0],
sampleRate=analysisSampleRate,
downmix='mix')
rgain = ReplayGain(applyEqloud=False)
pool = essentia.Pool()
loader.audio >> rgain.signal
return options, args
if __name__ == '__main__':
opts, args = parse_args()
if len(args) != 2:
cmd = './' + os.path.basename(sys.argv[0]) + ' -h'
os.system(cmd)
sys.exit(1)
if opts.generate_dot:
essentia.translate(LowLevelSpectralExtractor,
'streaming_extractorlowlevelspectral',
dot_graph=True)
elif opts.generate_cpp:
essentia.translate(LowLevelSpectralExtractor,
'streaming_extractorlowlevelspectral',
dot_graph=False)
loader = MonoLoader(filename=args[0])
lowlevelExtractor = LowLevelSpectralExtractor()
pool = essentia.Pool()
loader.audio >> lowlevelExtractor.signal
for desc, output in lowlevelExtractor.outputs.items():
output >> (pool, namespace + '.' + desc)
(options, args) = parser.parse_args()
return options, args
if __name__ == '__main__':
opts, args = parse_args()
if len(args) != 2:
cmd = './'+os.path.basename(sys.argv[0])+ ' -h'
os.system(cmd)
sys.exit(1)
if opts.generate_dot:
essentia.translate(TuningFrequencyExtractor, 'streaming_extractortuningfrequency', dot_graph=True)
elif opts.generate_cpp:
essentia.translate(TuningFrequencyExtractor, 'streaming_extractortuningfrequency', dot_graph=False)
pool = essentia.Pool()
loader = essentia.streaming.MonoLoader(filename=args[0])
tuning = TuningFrequencyExtractor()
loader.audio >> tuning.signal
tuning.tuningFrequency >> (pool, 'tuning_frequency')
essentia.run(loader)
stats = ['mean', 'var', 'min', 'max', 'dmean', 'dmean2', 'dvar', 'dvar2']
poolStats = essentia.standard.PoolAggregator(defaultStats=stats)(pool)
essentia.standard.YamlOutput(filename=args[1])(poolStats)
return options, args
if __name__ == '__main__':
opts, args = parse_args()
if len(args) != 2:
cmd = './'+os.path.basename(sys.argv[0])+ ' -h'
os.system(cmd)
sys.exit(1)
if opts.generate_dot:
essentia.translate(LevelExtractor, 'streaming_extractorlevel', dot_graph=True)
elif opts.generate_cpp:
essentia.translate(LevelExtractor, 'streaming_extractorlevel', dot_graph=False)
# find out replay gain:
loader = EqloudLoader(filename=args[0],
sampleRate=analysisSampleRate,
downmix='mix')
rgain = ReplayGain(applyEqloud=False)
pool = essentia.Pool()
loader.audio >> rgain.signal
rgain.replayGain >> (pool, 'replay_gain')
essentia.run(loader)
return options, args
if __name__ == '__main__':
opts, args = parse_args()
if len(args) != 2:
cmd = './'+os.path.basename(sys.argv[0])+ ' -h'
os.system(cmd)
sys.exit(1)
if opts.generate_dot:
essentia.translate(TonalDescriptorsExtractor, 'streaming_extractortonaldescriptors', dot_graph=True)
elif opts.generate_cpp:
essentia.translate(TonalDescriptorsExtractor, 'streaming_extractortonaldescriptors', dot_graph=False)
pool = essentia.Pool()
loader = essentia.streaming.MonoLoader(filename=args[0])
tonalExtractor = TonalDescriptorsExtractor()
loader.audio >> tonalExtractor.signal
for desc, output in tonalExtractor.outputs.items():
output >> (pool, desc)
essentia.run(loader)
stats = ['mean', 'var', 'min', 'max', 'dmean', 'dmean2', 'dvar', 'dvar2']
poolStats = essentia.standard.PoolAggregator(defaultStats=stats)(pool)
essentia.standard.YamlOutput(filename=args[1])(poolStats)
return options, args
if __name__ == '__main__':
opts, args = parse_args()
if len(args) != 2:
cmd = './'+os.path.basename(sys.argv[0])+ ' -h'
os.system(cmd)
sys.exit(1)
if opts.generate_dot:
essentia.translate(SfxExtractor, 'streaming_extractorsfx', dot_graph=True)
elif opts.generate_cpp:
essentia.translate(SfxExtractor, 'streaming_extractorsfx', dot_graph=False)
pool = essentia.Pool()
loader = MonoLoader(filename=args[0])
sfx = SfxExtractor()
loader.audio >> sfx.signal
for desc, output in sfx.outputs.items():
output >> (pool, namespace + '.' + desc)
essentia.run(loader)
# compute aggregation on values:
stats = ['mean', 'var', 'min', 'max', 'dmean', 'dmean2', 'dvar', 'dvar2']
exceptions = {'lowlevel.mfcc' : ['mean', 'cov', 'icov']}
return options, args
if __name__ == '__main__':
opts, args = parse_args()
if len(args) != 2:
cmd = './' + os.path.basename(sys.argv[0]) + ' -h'
os.system(cmd)
sys.exit(1)
if opts.generate_dot:
essentia.translate(PanningExtractor,
'streaming_extractorpanning',
dot_graph=True)
elif opts.generate_cpp:
essentia.translate(PanningExtractor,
'streaming_extractorpanning',
dot_graph=False)
pool = essentia.Pool()
loader = AudioLoader(filename=args[0])
panExtractor = PanningExtractor()
loader.audio >> panExtractor.signal
loader.numberChannels >> None
loader.sampleRate >> None
panExtractor.panning_coefficients >> (pool,
namespace + '.panning_coefficients')
if __name__ == '__main__':
# Make sure the command was well-formed.
if len(sys.argv) < 3:
print 'Usage: extractor_mfcc.py <input audio filename> <output yaml filename>'
sys.exit(1)
# Loaders must be specified outside your composite algorithm.
loader = essentia.streaming.MonoLoader(filename=sys.argv[1])
# We are using the default values of our parameters so we don't specify any keyword arguments.
mfccex = ExtractorMfcc()
p = essentia.Pool()
# When connecting to/from your composite algorithm, use the names you declared in the
# self.inputs and self.outputs dictionaries, respectively.
loader.audio >> mfccex.audio
mfccex.mfcc >> (p, 'mfcc')
essentia.run(loader)
# CompoxiteBase algorithms can be translated into c++ code and dot graphs
# can also be generated:
essentia.translate(
ExtractorMfcc, # algorithm to be translated
'myExtractorMfcc', # output name for the c++ and dot generated files
dot_graph=True) # whether dot file should be generated
essentia.standard.YamlOutput(filename=sys.argv[2])(p)
return options, args
if __name__ == '__main__':
opts, args = parse_args()
if len(args) != 2:
cmd = './' + os.path.basename(sys.argv[0]) + ' -h'
os.system(cmd)
sys.exit(1)
if opts.generate_dot:
essentia.translate(RhythmDescriptorsExtractor,
"streaming_extractorrhythmdescriptors",
dot_graph=True)
elif opts.generate_cpp:
essentia.translate(RhythmDescriptorsExtractor,
"streaming_extractorrhythmdescriptors",
dot_graph=False)
pool = essentia.Pool()
loader = essentia.streaming.MonoLoader(filename=args[0])
rhythm = RhythmDescriptorsExtractor()
loader.audio >> rhythm.signal
for desc, output in rhythm.outputs.items():
output >> (pool, desc)
essentia.run(loader)
stats = ['mean', 'var', 'min', 'max', 'dmean', 'dmean2', 'dvar', 'dvar2']
return options, args
if __name__ == '__main__':
opts, args = parse_args()
if len(args) != 2:
cmd = './' + os.path.basename(sys.argv[0]) + ' -h'
os.system(cmd)
sys.exit(1)
if opts.generate_dot:
essentia.translate(TonalDescriptorsExtractor,
'streaming_extractortonaldescriptors',
dot_graph=True)
elif opts.generate_cpp:
essentia.translate(TonalDescriptorsExtractor,
'streaming_extractortonaldescriptors',
dot_graph=False)
pool = essentia.Pool()
loader = essentia.streaming.MonoLoader(filename=args[0])
tonalExtractor = TonalDescriptorsExtractor()
loader.audio >> tonalExtractor.signal
for desc, output in tonalExtractor.outputs.items():
output >> (pool, desc)
essentia.run(loader)
stats = ['mean', 'var', 'min', 'max', 'dmean', 'dmean2', 'dvar', 'dvar2']
return options, args
if __name__ == '__main__':
opts, args = parse_args()
if len(args) != 2:
cmd = './'+os.path.basename(sys.argv[0])+ ' -h'
os.system(cmd)
sys.exit(1)
if opts.generate_dot:
essentia.translate(PitchExtractor, 'streaming_extractorpitch', dot_graph=True)
elif opts.generate_cpp:
essentia.translate(PitchExtractor, 'streaming_extractorpitch', dot_graph=False)
# find out replay gain
loader = EqloudLoader(filename=args[0],
sampleRate=analysisSampleRate,
downmix='mix')
rgain = ReplayGain(applyEqloud=False)
pool = essentia.Pool()
loader.audio >> rgain.signal
rgain.replayGain >> (pool, 'replay_gain')
essentia.run(loader)
