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import copy
import librosa
import essentia
import essentia.standard
import numpy as np
import scipy.interpolate as interp
import note_seq
SAMPLERATE = 44100
def nearest_onset_offset_digitize(on, off, bins):
intermediate = (bins[1:] + bins[:-1]) / 2
on_idx = np.digitize(on, intermediate)
off_idx = np.digitize(off, intermediate)
off_idx[on_idx == off_idx] += 1
# off_idx = np.clip(off_idx, a_min=0, a_max=len(bins) - 1)
return on_idx, off_idx
def apply_sustain_pedal(pm):
ns = note_seq.midi_to_note_sequence(pm)
susns = note_seq.apply_sustain_control_changes(ns)
suspm = note_seq.note_sequence_to_pretty_midi(susns)
return suspm
def interpolate_beat_times(beat_times, steps_per_beat, extend=False):
beat_times_function = interp.interp1d(
np.arange(beat_times.size),
beat_times,
bounds_error=False,
fill_value="extrapolate",
)
if extend:
beat_steps_8th = beat_times_function(
np.linspace(0, beat_times.size, beat_times.size * steps_per_beat + 1)
)
else:
beat_steps_8th = beat_times_function(
np.linspace(0, beat_times.size - 1, beat_times.size * steps_per_beat - 1)
)
return beat_steps_8th
def midi_quantize_by_beats(
sample, beat_times, steps_per_beat, ignore_sustain_pedal=False
):
ns = note_seq.midi_file_to_note_sequence(sample.midi)
if ignore_sustain_pedal:
susns = ns
else:
susns = note_seq.apply_sustain_control_changes(ns)
qns = copy.deepcopy(susns)
notes = np.array([[n.start_time, n.end_time] for n in susns.notes])
note_attributes = np.array([[n.pitch, n.velocity] for n in susns.notes])
note_ons = np.array(notes[:, 0])
note_offs = np.array(notes[:, 1])
beat_steps_8th = interpolate_beat_times(beat_times, steps_per_beat, extend=False)
on_idx, off_idx = nearest_onset_offset_digitize(note_ons, note_offs, beat_steps_8th)
beat_steps_8th = interpolate_beat_times(beat_times, steps_per_beat, extend=True)
discrete_notes = np.concatenate(
(np.stack((on_idx, off_idx), axis=1), note_attributes), axis=1
)
def delete_duplicate_notes(dnotes):
note_order = dnotes[:, 0] * 128 + dnotes[:, 2]
dnotes = dnotes[note_order.argsort()]
indices = []
for i in range(1, len(dnotes)):
if dnotes[i, 0] == dnotes[i - 1, 0] and dnotes[i, 2] == dnotes[i - 1, 2]:
indices.append(i)
dnotes = np.delete(dnotes, indices, axis=0)
note_order = dnotes[:, 0] * 128 + dnotes[:, 1]
dnotes = dnotes[note_order.argsort()]
return dnotes
discrete_notes = delete_duplicate_notes(discrete_notes)
digitized_note_ons, digitized_note_offs = (
beat_steps_8th[on_idx],
beat_steps_8th[off_idx],
)
for i, note in enumerate(qns.notes):
note.start_time = digitized_note_ons[i]
note.end_time = digitized_note_offs[i]
return qns, discrete_notes, beat_steps_8th
def extract_rhythm(song, y=None):
if y is None:
y, sr = librosa.load(song, sr=SAMPLERATE)
essentia_tracker = essentia.standard.RhythmExtractor2013(method="multifeature")
(
bpm,
beat_times,
confidence,
estimates,
essentia_beat_intervals,
) = essentia_tracker(y)
return bpm, beat_times, confidence, estimates, essentia_beat_intervals
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