def compute(audio, pool, options):
# analysis parameters
sampleRate = options['sampleRate']
frameSize = options['frameSize']
hopSize = options['hopSize']
windowType = options['windowType']
# temporal descriptors
lpc = essentia.LPC(order=10, type='warped', sampleRate=sampleRate)
zerocrossingrate = essentia.ZeroCrossingRate()
# frame algorithms
frames = essentia.FrameGenerator(audio=audio,
frameSize=frameSize,
hopSize=hopSize)
window = essentia.Windowing(size=frameSize, zeroPadding=0, type=windowType)
spectrum = essentia.Spectrum(size=frameSize)
# spectral algorithms
barkbands = essentia.BarkBands(sampleRate=sampleRate)
centralmoments = essentia.SpectralCentralMoments()
crest = essentia.Crest()
centroid = essentia.SpectralCentroid()
decrease = essentia.SpectralDecrease()
spectral_contrast = essentia.SpectralContrast(frameSize=frameSize,
sampleRate=sampleRate,
numberBands=6,
lowFrequencyBound=20,
highFrequencyBound=11000,
neighbourRatio=0.4,
staticDistribution=0.15)
distributionshape = essentia.DistributionShape()
energy = essentia.Energy()
# energyband_bass, energyband_middle and energyband_high parameters come from "standard" hi-fi equalizers
energyband_bass = essentia.EnergyBand(startCutoffFrequency=20.0,
stopCutoffFrequency=150.0,
sampleRate=sampleRate)
energyband_middle_low = essentia.EnergyBand(startCutoffFrequency=150.0,
stopCutoffFrequency=800.0,
sampleRate=sampleRate)
energyband_middle_high = essentia.EnergyBand(startCutoffFrequency=800.0,
stopCutoffFrequency=4000.0,
sampleRate=sampleRate)
energyband_high = essentia.EnergyBand(startCutoffFrequency=4000.0,
stopCutoffFrequency=20000.0,
sampleRate=sampleRate)
flatnessdb = essentia.FlatnessDB()
flux = essentia.Flux()
harmonic_peaks = essentia.HarmonicPeaks()
hfc = essentia.HFC()
mfcc = essentia.MFCC()
rolloff = essentia.RollOff()
rms = essentia.RMS()
strongpeak = essentia.StrongPeak()
# pitch algorithms
pitch_detection = essentia.PitchDetection(frameSize=frameSize,
sampleRate=sampleRate)
pitch_salience = essentia.PitchSalience()
# dissonance
spectral_peaks = essentia.SpectralPeaks(sampleRate=sampleRate,
orderBy='frequency')
dissonance = essentia.Dissonance()
# spectral complexity
# magnitudeThreshold = 0.005 is hardcoded for a "blackmanharris62" frame
spectral_complexity = essentia.SpectralComplexity(magnitudeThreshold=0.005)
INFO('Computing Low-Level descriptors...')
# used for a nice progress display
total_frames = frames.num_frames()
n_frames = 0
start_of_frame = -frameSize * 0.5
pitches, pitch_confidences = [], []
progress = Progress(total=total_frames)
scPool = essentia.Pool() # pool for spectral contrast
for frame in frames:
frameScope = [
start_of_frame / sampleRate,
(start_of_frame + frameSize) / sampleRate
]
#pool.setCurrentScope(frameScope)
# silence rate
pool.add(namespace + '.' + 'silence_rate_60dB',
essentia.isSilent(frame))
pool.add(namespace + '.' + 'silence_rate_30dB',
is_silent_threshold(frame, -30))
pool.add(namespace + '.' + 'silence_rate_20dB',
is_silent_threshold(frame, -20))
if options['skipSilence'] and essentia.isSilent(frame):
total_frames -= 1
start_of_frame += hopSize
continue
# temporal descriptors
pool.add(namespace + '.' + 'zerocrossingrate', zerocrossingrate(frame))
(frame_lpc, frame_lpc_reflection) = lpc(frame)
pool.add(namespace + '.' + 'temporal_lpc', frame_lpc)
frame_windowed = window(frame)
frame_spectrum = spectrum(frame_windowed)
# spectrum-based descriptors
power_spectrum = frame_spectrum**2
pool.add(namespace + '.' + 'spectral_centroid',
centroid(power_spectrum))
pool.add(namespace + '.' + 'spectral_decrease',
decrease(power_spectrum))
pool.add(namespace + '.' + 'spectral_energy', energy(frame_spectrum))
pool.add(namespace + '.' + 'spectral_energyband_low',
energyband_bass(frame_spectrum))
pool.add(namespace + '.' + 'spectral_energyband_middle_low',
energyband_middle_low(frame_spectrum))
pool.add(namespace + '.' + 'spectral_energyband_middle_high',
energyband_middle_high(frame_spectrum))
pool.add(namespace + '.' + 'spectral_energyband_high',
energyband_high(frame_spectrum))
pool.add(namespace + '.' + 'hfc', hfc(frame_spectrum))
pool.add(namespace + '.' + 'spectral_rms', rms(frame_spectrum))
pool.add(namespace + '.' + 'spectral_flux', flux(frame_spectrum))
pool.add(namespace + '.' + 'spectral_rolloff', rolloff(frame_spectrum))
pool.add(namespace + '.' + 'spectral_strongpeak',
strongpeak(frame_spectrum))
# central moments descriptors
frame_centralmoments = centralmoments(power_spectrum)
(frame_spread, frame_skewness,
frame_kurtosis) = distributionshape(frame_centralmoments)
pool.add(namespace + '.' + 'spectral_kurtosis', frame_kurtosis)
pool.add(namespace + '.' + 'spectral_spread', frame_spread)
pool.add(namespace + '.' + 'spectral_skewness', frame_skewness)
# dissonance
(frame_frequencies, frame_magnitudes) = spectral_peaks(frame_spectrum)
frame_dissonance = dissonance(frame_frequencies, frame_magnitudes)
pool.add(namespace + '.' + 'dissonance', frame_dissonance)
# mfcc
(frame_melbands, frame_mfcc) = mfcc(frame_spectrum)
pool.add(namespace + '.' + 'mfcc', frame_mfcc)
# spectral contrast
(sc_coeffs, sc_valleys) = spectral_contrast(frame_spectrum)
scPool.add(namespace + '.' + 'sccoeffs', sc_coeffs)
scPool.add(namespace + '.' + 'scvalleys', sc_valleys)
# barkbands-based descriptors
frame_barkbands = barkbands(frame_spectrum)
pool.add(namespace + '.' + 'barkbands', frame_barkbands)
pool.add(namespace + '.' + 'spectral_crest', crest(frame_barkbands))
pool.add(namespace + '.' + 'spectral_flatness_db',
flatnessdb(frame_barkbands))
barkbands_centralmoments = essentia.CentralMoments(
range=len(frame_barkbands) - 1)
(barkbands_spread, barkbands_skewness,
barkbands_kurtosis) = distributionshape(
barkbands_centralmoments(frame_barkbands))
pool.add(namespace + '.' + 'barkbands_spread', barkbands_spread)
pool.add(namespace + '.' + 'barkbands_skewness', barkbands_skewness)
pool.add(namespace + '.' + 'barkbands_kurtosis', barkbands_kurtosis)
# pitch descriptors
frame_pitch, frame_pitch_confidence = pitch_detection(frame_spectrum)
if frame_pitch > 0 and frame_pitch <= 20000.:
pool.add(namespace + '.' + 'pitch', frame_pitch)
pitches.append(frame_pitch)
pitch_confidences.append(frame_pitch_confidence)
pool.add(namespace + '.' + 'pitch_instantaneous_confidence',
frame_pitch_confidence)
frame_pitch_salience = pitch_salience(frame_spectrum[:-1])
pool.add(namespace + '.' + 'pitch_salience', frame_pitch_salience)
# spectral complexity
pool.add(namespace + '.' + 'spectral_complexity',
spectral_complexity(frame_spectrum))
# display of progress report
progress.update(n_frames)
n_frames += 1
start_of_frame += hopSize
# if no 'temporal_zerocrossingrate' it means that this is a silent file
if 'zerocrossingrate' not in descriptorNames(pool.descriptorNames(),
namespace):
raise essentia.EssentiaError('This is a silent file!')
spectralContrastPCA(scPool, pool)
# build pitch value histogram
from math import log
from numpy import bincount
# convert from Hz to midi notes
midipitches = []
unknown = 0
for freq in pitches:
if freq > 0. and freq <= 12600:
midipitches.append(12 * (log(freq / 6.875) / 0.69314718055995) -
3.)
else:
unknown += 1
if len(midipitches) > 0:
# compute histogram
midipitchhist = bincount(midipitches)
# set 0 midi pitch to be the number of pruned value
midipitchhist[0] = unknown
# normalise
midipitchhist = [
val / float(sum(midipitchhist)) for val in midipitchhist
]
# zero pad
for i in range(128 - len(midipitchhist)):
midipitchhist.append(0.0)
else:
midipitchhist = [0.] * 128
midipitchhist[0] = 1.
# pitchhist = essentia.array(zip(range(len(midipitchhist)), midipitchhist))
pool.add(namespace + '.' + 'spectral_pitch_histogram',
midipitchhist) #, pool.GlobalScope)
# the code below is the same as the one above:
#for note in midipitchhist:
# pool.add(namespace + '.' + 'spectral_pitch_histogram_values', note)
# print "midi note:", note
pitch_centralmoments = essentia.CentralMoments(range=len(midipitchhist) -
1)
(pitch_histogram_spread, pitch_histogram_skewness,
pitch_histogram_kurtosis) = distributionshape(
pitch_centralmoments(midipitchhist))
pool.add(namespace + '.' + 'spectral_pitch_histogram_spread',
pitch_histogram_spread) #, pool.GlobalScope)
progress.finish()
def compute(audio, pool, options):
INFO('Computing SFX descriptors...')
# analysis parameters
sampleRate = options['sampleRate']
frameSize = options['frameSize']
hopSize = options['hopSize']
windowType = options['windowType']
# frame algorithms
frames = essentia.FrameGenerator(audio=audio,
frameSize=frameSize,
hopSize=hopSize)
window = essentia.Windowing(size=frameSize, zeroPadding=0, type=windowType)
spectrum = essentia.Spectrum(size=frameSize)
# pitch algorithm
pitch_detection = essentia.PitchDetection(frameSize=2048,
sampleRate=sampleRate)
# sfx descriptors
spectral_peaks = essentia.SpectralPeaks(sampleRate=sampleRate,
orderBy='frequency')
harmonic_peaks = essentia.HarmonicPeaks()
inharmonicity = essentia.Inharmonicity()
odd2evenharmonicenergyratio = essentia.OddToEvenHarmonicEnergyRatio()
tristimulus = essentia.Tristimulus()
# used for a nice progress display
total_frames = frames.num_frames()
n_frames = 0
start_of_frame = -frameSize * 0.5
progress = Progress(total=total_frames)
for frame in frames:
frameScope = [
start_of_frame / sampleRate,
(start_of_frame + frameSize) / sampleRate
]
#pool.setCurrentScope(frameScope)
if options['skipSilence'] and essentia.isSilent(frame):
total_frames -= 1
start_of_frame += hopSize
continue
frame_windowed = window(frame)
frame_spectrum = spectrum(frame_windowed)
# pitch descriptors
frame_pitch, frame_pitch_confidence = pitch_detection(frame_spectrum)
# spectral peaks based descriptors
(frame_frequencies, frame_magnitudes) = spectral_peaks(frame_spectrum)
(frame_harmonic_frequencies,
frame_harmonic_magnitudes) = harmonic_peaks(frame_frequencies,
frame_magnitudes,
frame_pitch)
if len(frame_harmonic_frequencies) > 1:
frame_inharmonicity = inharmonicity(frame_harmonic_frequencies,
frame_harmonic_magnitudes)
pool.add(namespace + '.' + 'inharmonicity', frame_inharmonicity)
frame_tristimulus = tristimulus(frame_harmonic_frequencies,
frame_harmonic_magnitudes)
pool.add(namespace + '.' + 'tristimulus', frame_tristimulus)
frame_odd2evenharmonicenergyratio = odd2evenharmonicenergyratio(
frame_harmonic_frequencies, frame_harmonic_magnitudes)
pool.add(namespace + '.' + 'odd2evenharmonicenergyratio',
frame_odd2evenharmonicenergyratio)
# display of progress report
progress.update(n_frames)
n_frames += 1
start_of_frame += hopSize
envelope = essentia.Envelope()
file_envelope = envelope(audio)
# temporal statistics
decrease = essentia.AudioDecrease(blockSize=len(audio))
pool.add(namespace + '.' + 'temporal_decrease',
decrease(file_envelope)) #, pool.GlobalScope)
centralmoments = essentia.AudioCentralMoments(blockSize=len(audio))
file_centralmoments = centralmoments(file_envelope)
distributionshape = essentia.DistributionShape()
(file_spread, file_skewness,
file_kurtosis) = distributionshape(file_centralmoments)
pool.add(namespace + '.' + 'temporal_spread',
file_spread) #, pool.GlobalScope)
pool.add(namespace + '.' + 'temporal_skewness',
file_skewness) #, pool.GlobalScope)
pool.add(namespace + '.' + 'temporal_kurtosis',
file_kurtosis) #, pool.GlobalScope)
centroid = essentia.AudioCentroid(blockSize=len(audio))
pool.add(namespace + '.' + 'temporal_centroid',
centroid(file_envelope)) #, pool.GlobalScope)
# effective duration
effectiveduration = essentia.EffectiveDuration()
pool.add(namespace + '.' + 'effective_duration',
effectiveduration(file_envelope)) #, pool.GlobalScope)
# log attack time
logattacktime = essentia.LogAttackTime()
pool.add(namespace + '.' + 'logattacktime',
logattacktime(audio)) #, pool.GlobalScope)
# strong decay
strongdecay = essentia.StrongDecay()
pool.add(namespace + '.' + 'strongdecay',
strongdecay(file_envelope)) #, pool.GlobalScope)
# dynamic profile
flatness = essentia.FlatnessSFX()
pool.add(namespace + '.' + 'flatness',
flatness(file_envelope)) #, pool.GlobalScope)
# onsets number
onsets_number = len(pool.value('rhythm.onset_times')[0])
pool.add(namespace + '.' + 'onsets_number',
onsets_number) #, pool.GlobalScope)
# morphological descriptors
max_to_total = essentia.MaxToTotal()
pool.add(namespace + '.' + 'max_to_total',
max_to_total(file_envelope)) #, pool.GlobalScope)
tc_to_total = essentia.TCToTotal(sampleRate=sampleRate)
pool.add(namespace + '.' + 'tc_to_total',
tc_to_total(file_envelope)) #, pool.GlobalScope)
derivativeSFX = essentia.DerivativeSFX(sampleRate=sampleRate)
(der_av_after_max, max_der_before_max) = derivativeSFX(file_envelope)
pool.add(namespace + '.' + 'der_av_after_max',
der_av_after_max) #, pool.GlobalScope)
pool.add(namespace + '.' + 'max_der_before_max',
max_der_before_max) #, pool.GlobalScope)
# pitch profile
pitch = pool.value('lowlevel.pitch')
if len(pitch) > 1:
pool.add(namespace + '.' + 'pitch_max_to_total',
max_to_total(pitch)) #, pool.GlobalScope)
min_to_total = essentia.MinToTotal()
pool.add(namespace + '.' + 'pitch_min_to_total',
min_to_total(pitch)) #, pool.GlobalScope)
pitch_centroid = essentia.Centroid(range=len(pitch) - 1)
pool.add(namespace + '.' + 'pitch_centroid',
pitch_centroid(pitch)) #, pool.GlobalScope)
pitch_after_max_to_before_max_energy_ratio = essentia.AfterMaxToBeforeMaxEnergyRatio(
)
pool.add(namespace + '.' +
'pitch_after_max_to_before_max_energy_ratio',
pitch_after_max_to_before_max_energy_ratio(
pitch)) #, pool.GlobalScope)
else:
pool.add(namespace + '.' + 'pitch_max_to_total',
0.0) #, pool.GlobalScope)
pool.add(namespace + '.' + 'pitch_min_to_total',
0.0) #, pool.GlobalScope)
pool.add(namespace + '.' + 'pitch_centroid', 0.0) #, pool.GlobalScope)
pool.add(namespace + '.' +
'pitch_after_max_to_before_max_energy_ratio',
0.0) #, pool.GlobalScope)
progress.finish()