Skip to content

Instantly share code, notes, and snippets.

@Alan-Liang

Alan-Liang/music.py

Created March 18, 2020 23:41
Show Gist options
  • Save Alan-Liang/6b190aad5879795488e2b85b400c858b to your computer and use it in GitHub Desktop.
Save Alan-Liang/6b190aad5879795488e2b85b400c858b to your computer and use it in GitHub Desktop.
Download ZIP
Music preprocessing
Raw
music.py
# TODO
import librosa
import json
import time
__version__ = 1
__authors__ = ['Alan-Liang']
def maybe_array_from_maybe_ndarray(ndarray):
if ndarray is not None:
return ndarray.tolist()
return ndarray
class Music:
def __init__(self, filename):
start = time.time()
self.filename = filename
self.y, self.sr = librosa.load(filename)
self.mfcc = self.onset_envelope = self.onset_frames = self.tempo = self.beats = self.recurrence_matrix = None
self.chroma = None # PEP 8: line too long
print(f'File {filename} loaded in {time.time() - start} seconds.')
def dump(self, filename):
start = time.time()
with open(filename, 'w') as f:
json.dump({
'filename': self.filename,
# 'y': maybe_array_from_maybe_ndarray(self.y),
'sr': self.sr,
# 'mfcc': maybe_array_from_maybe_ndarray(self.mfcc),
'onsetEnvelope': maybe_array_from_maybe_ndarray(self.onset_envelope),
'onsetFrames': maybe_array_from_maybe_ndarray(self.onset_frames),
'tempo': self.tempo,
'beats': maybe_array_from_maybe_ndarray(self.beats),
# 'recurrence_matrix': maybe_array_from_maybe_ndarray(self.recurrence_matrix),
'chroma': maybe_array_from_maybe_ndarray(self.chroma),
}, f)
print(f'File {self.filename} saved to {filename} in {time.time() - start} seconds.')
def do_mfcc(self):
start = time.time()
self.mfcc = librosa.feature.mfcc(y=self.y, sr=self.sr)
print(f'MFCC done for {self.filename} in {time.time() - start} seconds.')
def do_onset_detection(self):
start = time.time()
self.onset_envelope = librosa.onset.onset_strength(y=self.y, sr=self.sr)
self.onset_frames = librosa.onset.onset_detect(onset_envelope=self.onset_envelope, sr=self.sr)
print(f'Onset detection done for {self.filename} in {time.time() - start} seconds.')
def do_beat_track(self):
start = time.time()
if self.onset_envelope is None:
print('Beat track requires onset envelope which is not present, calling do_onset_detection.')
self.do_onset_detection()
self.tempo, self.beats = librosa.beat.beat_track(onset_envelope=self.onset_envelope, sr=self.sr)
print(f'Beat track done for {self.filename} in {time.time() - start} seconds.')
def do_recurrence_matrix(self):
start = time.time()
if self.mfcc is None:
print('Recurrence matrix requires MFCC which is not present, calling do_mfcc.')
self.do_mfcc()
self.recurrence_matrix = librosa.segment.recurrence_matrix(self.mfcc)
print(f'Recurrence matrix done for {self.filename} in {time.time() - start} seconds.')
def do_chroma(self):
start = time.time()
self.chroma = librosa.feature.chroma_stft(y=self.y, sr=self.sr)
print(f'Chroma done for {self.filename} in {time.time() - start} seconds.')
if __name__ == '__main__':
music = Music(input('infile = '))
music.do_mfcc()
music.do_onset_detection()
music.do_beat_track()
music.do_chroma()
# music.do_recurrence_matrix()
music.dump(input('outfile = '))
Raw
test.py
from music import Music
import time
music_names = []
last_input = input()
while last_input != '$':
music_names.append(last_input)
last_input = input()
for f in music_names:
start = time.time()
music = Music(f'../dataAll/{f}')
music.do_onset_detection()
music.do_beat_track()
music.do_chroma()
music.dump(f'data/{f}.json')
print(f'File {f} processed in {time.time() - start} seconds.')
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment