def compute(audio, pool, options):
INFO('Computing Tonal descriptors...')
sampleRate = options['sampleRate']
frameSize = options['frameSize']
hopSize = options['hopSize']
zeroPadding = options['zeroPadding']
windowType = options['windowType']
frames = essentia.FrameGenerator(audio=audio,
frameSize=frameSize,
hopSize=hopSize)
window = essentia.Windowing(size=frameSize,
zeroPadding=zeroPadding,
type=windowType)
spectrum = essentia.Spectrum(size=(frameSize + zeroPadding) / 2)
spectral_peaks = essentia.SpectralPeaks(maxPeaks=10000,
magnitudeThreshold=0.00001,
minFrequency=40,
maxFrequency=5000,
orderBy="frequency")
tuning = essentia.TuningFrequency()
# computing the tuning frequency
tuning_frequency = 440.0
for frame in frames:
frame_windowed = window(frame)
frame_spectrum = spectrum(frame_windowed)
(frame_frequencies, frame_magnitudes) = spectral_peaks(frame_spectrum)
#if len(frame_frequencies) > 0:
(tuning_frequency, tuning_cents) = tuning(frame_frequencies,
frame_magnitudes)
pool.add(namespace + '.' + 'tuning_frequency',
tuning_frequency) #, pool.GlobalScope)
# computing the HPCPs
spectral_whitening = essentia.SpectralWhitening()
hpcp_key_size = 36
hpcp_chord_size = 36
hpcp_tuning_size = 120
hpcp_key = essentia.HPCP(size=hpcp_key_size,
referenceFrequency=tuning_frequency,
bandPreset=False,
minFrequency=40.0,
maxFrequency=5000.0,
weightType='squaredCosine',
nonLinear=False,
windowSize=4.0 / 3.0,
sampleRate=sampleRate)
hpcp_chord = essentia.HPCP(size=hpcp_chord_size,
referenceFrequency=tuning_frequency,
harmonics=8,
bandPreset=True,
minFrequency=40.0,
maxFrequency=5000.0,
splitFrequency=500.0,
weightType='cosine',
nonLinear=True,
windowSize=0.5,
sampleRate=sampleRate)
hpcp_tuning = essentia.HPCP(size=hpcp_tuning_size,
referenceFrequency=tuning_frequency,
harmonics=8,
bandPreset=True,
minFrequency=40.0,
maxFrequency=5000.0,
splitFrequency=500.0,
weightType='cosine',
nonLinear=True,
windowSize=0.5,
sampleRate=sampleRate)
# intializing the HPCP arrays
hpcps_key = []
hpcps_chord = []
hpcps_tuning = []
# computing HPCP loop
frames = essentia.FrameGenerator(audio=audio,
frameSize=frameSize,
hopSize=hopSize)
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)
# spectral peaks
(frame_frequencies, frame_magnitudes) = spectral_peaks(frame_spectrum)
if (len(frame_frequencies) > 0):
# spectral_whitening
frame_magnitudes_white = spectral_whitening(
frame_spectrum, frame_frequencies, frame_magnitudes)
frame_hpcp_key = hpcp_key(frame_frequencies,
frame_magnitudes_white)
frame_hpcp_chord = hpcp_chord(frame_frequencies,
frame_magnitudes_white)
frame_hpcp_tuning = hpcp_tuning(frame_frequencies,
frame_magnitudes_white)
else:
frame_hpcp_key = essentia.array([0] * hpcp_key_size)
frame_hpcp_chord = essentia.array([0] * hpcp_chord_size)
frame_hpcp_tuning = essentia.array([0] * hpcp_tuning_size)
# key HPCP
hpcps_key.append(frame_hpcp_key)
# add HPCP to the pool
pool.add(namespace + '.' + 'hpcp', frame_hpcp_key)
# chords HPCP
hpcps_chord.append(frame_hpcp_chord)
# tuning system HPCP
hpcps_tuning.append(frame_hpcp_tuning)
# display of progress report
progress.update(n_frames)
n_frames += 1
start_of_frame += hopSize
progress.finish()
# check if silent file
if len(hpcps_key) == 0:
raise EssentiaError('This is a silent file!')
# key detection
key_detector = essentia.Key(profileType='temperley')
average_hpcps_key = numpy.average(essentia.array(hpcps_key), axis=0)
average_hpcps_key = normalize(average_hpcps_key)
# thpcps
max_arg = numpy.argmax(average_hpcps_key)
thpcp = []
for i in range(max_arg, len(average_hpcps_key)):
thpcp.append(float(average_hpcps_key[i]))
for i in range(max_arg):
thpcp.append(float(average_hpcps_key[i]))
pool.add(namespace + '.' + 'thpcp', thpcp) #, pool.GlobalScope )
(key, scale, key_strength,
first_to_second_relative_strength) = key_detector(
essentia.array(average_hpcps_key))
pool.add(namespace + '.' + 'key_key', key) #, pool.GlobalScope)
pool.add(namespace + '.' + 'key_scale', scale) #, pool.GlobalScope)
pool.add(namespace + '.' + 'key_strength',
key_strength) #, pool.GlobalScope)
# chord detection
chord_detector = essentia.Key(profileType='tonictriad', usePolyphony=False)
hpcp_frameSize = 2.0 # 2 seconds
hpcp_number = int(hpcp_frameSize * (sampleRate / hopSize - 1))
for hpcp_index in range(len(hpcps_chord)):
hpcp_index_begin = max(0, hpcp_index - hpcp_number)
hpcp_index_end = min(hpcp_index + hpcp_number, len(hpcps_chord))
average_hpcps_chord = numpy.average(essentia.array(
hpcps_chord[hpcp_index_begin:hpcp_index_end]),
axis=0)
average_hpcps_chord = normalize(average_hpcps_chord)
(key, scale, strength,
first_to_second_relative_strength) = chord_detector(
essentia.array(average_hpcps_chord))
if scale == 'minor':
chord = key + 'm'
else:
chord = key
frame_second_scope = [
hpcp_index_begin * hopSize / sampleRate,
hpcp_index_end * hopSize / sampleRate
]
pool.add(namespace + '.' + 'chords_progression',
chord) #, frame_second_scope)
pool.add(namespace + '.' + 'chords_strength',
strength) #, frame_second_scope)
# tuning system features
keydetector = essentia.Key(profileType='diatonic')
average_hpcps_tuning = numpy.average(essentia.array(hpcps_tuning), axis=0)
average_hpcps_tuning = normalize(average_hpcps_tuning)
(key, scale, diatonic_strength,
first_to_second_relative_strength) = keydetector(
essentia.array(average_hpcps_tuning))
pool.add(namespace + '.' + 'tuning_diatonic_strength',
diatonic_strength) #, pool.GlobalScope)
(equal_tempered_deviation, nontempered_energy_ratio,
nontempered_peaks_energy_ratio
) = essentia.HighResolutionFeatures()(average_hpcps_tuning)
pool.add(namespace + '.' + 'tuning_equal_tempered_deviation',
equal_tempered_deviation) #, pool.GlobalScope)
pool.add(namespace + '.' + 'tuning_nontempered_energy_ratio',
nontempered_energy_ratio) #, pool.GlobalScope)
pool.add(namespace + '.' + 'tuning_nontempered_peaks_energy_ratio',
nontempered_peaks_energy_ratio) #, pool.GlobalScope)
frameSize=frame_size,
hopSize=hop_size)
window = essentia.Windowing(windowSize=frame_size,
zeroPadding=zero_padding,
type="blackmanharris62")
spectrum = essentia.Spectrum(size=frame_size + zero_padding)
spectralpeaks = essentia.SpectralPeaks(maxPeaks=100,
magnitudeThreshold=-100,
minFrequency=130,
maxFrequency=8000,
highestPeaks=True)
lin2db = essentia.UnaryOperator(type="lin2db")
db2lin = essentia.UnaryOperator(type="db2lin")
hpcp = essentia.HPCP(size=12,
referenceFrequency=440,
useWeight=True,
windowSize=4.0 / 3.0,
sampleRate=sample_rate,
normalize=True)
patterndetection = essentia.PatternDetection(frameRate=frame_rate,
lengthMin=10.0,
lengthMax=15.0)
total_frames = frames.num_frames()
n_frames = 0
for frame in frames:
frame_windowed = window(frame)
frame_spectrum = spectrum(frame_windowed)
(frame_peaks_freq,
frame_peaks_mag) = spectralpeaks(lin2db(frame_spectrum))
# FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
# details.
#
# You should have received a copy of the Affero GNU General Public License
# version 3 along with this program. If not, see http://www.gnu.org/licenses/
import numpy
import essentia
import sys
hpcp = essentia.HPCP(size=36,
referenceFrequency=440.0,
bandPreset=False,
minFrequency=40.0,
maxFrequency=5000.0,
midLowFrequency=500.0,
midHighFrequency=1000.0,
useWeight=True,
squareWeight=True,
nonLinear=False,
windowSize=4.0 / 3.0,
sampleRate=44100.0)
frequencies = [
947.3032226562, 1399.7023925781, 1216.341796875, 762.8428344727,
654.5443115234, 520.2301635742, 4575.2436523438, 409.2276306152,
4791.2998046875, 2573.521484375, 827.6868286133, 3270.7573242188,
1922.7291259766, 3627.2180175781, 3452.2028808594, 1671.4516601562,
1588.4647216797, 4390.6713867188, 3758.7380371094, 3160.9790039062,
3866.9069824219, 2903.2268066406, 3974.7385253906, 2157.0363769531,
4211.8017578125, 4906.0146484375, 4107.1103515625, 188.6952819824,
115.285446167, 2071.6237792969, 2310.9438476562, 3019.662109375, 4281.8125,
