def extract_tempo():
project_name = utils._get_name_project_most_recent()
data, rate = librosa.load(
os.path.join(utils.get_dirname_audio(), project_name + '.wav'))
data_tempo = vamp.collect(data, rate, "qm-vamp-plugins:qm-tempotracker")
subprocess.run(
['mkdir', os.path.join(utils.get_project_dir(), 'tempo')],
stdout=subprocess.PIPE)
estimate_tempo = vamp_prep.to_tempo(data_tempo)
utils.to_pickle(estimate_tempo,
os.path.join(utils.get_dirname_audio(), project_name))
return estimate_tempo
def main(args):
use_warped = utils.b_use_warped()
data_melody = ir.extract_melody(
os.path.join(
utils.get_dirname_audio_warped()
if use_warped else utils.get_dirname_audio(),
utils._get_name_project_most_recent() + '.wav'))
df_melody = prep_vamp.melody_to_df(
(data_melody['vector'][0], data_melody['vector'][1]), index_type='s')
df_melody[df_melody['melody'] < 0] = 0
conv_max.to_coll(df_melody.rename(columns={'melody': 'signal'}),
conv_max.file_ts_coll)
messenger = mes.Messenger()
messenger.message(['done', 'bang'])
def main(args):
messenger = mes.Messenger()
(s_beat_start, s_beat_end, tempo, beat_start, beat_end, length_beats,
beatmap) = utils.get_tuple_beats()
messenger.message(['length_beats', str(length_beats)])
data_chords = ir.extract_chords(
os.path.join(
utils.get_dirname_audio_warped()
if utils.b_use_warped() else utils.get_dirname_audio(),
utils._get_name_project_most_recent() + '.wav'))
non_empty_chords = vamp_filter.filter_non_chords(data_chords)
# TODO: refactor, this is slow
events_chords: Dict[float,
music21.chord.Chord] = vamp_convert.vamp_chord_to_dict(
non_empty_chords)
df_chords = prep_vamp.chords_to_df(events_chords)
chord_tree = quantize.get_interval_tree(df_chords, diff=False)
data_quantized = quantize.quantize(beatmap,
s_beat_start,
s_beat_end,
trees={'chord': chord_tree})
data_quantized_chords = data_quantized['chord']
score = postp_mxl.df_grans_to_score(data_quantized_chords, parts=['chord'])
part_chord = postp_mxl.extract_part(score, 'chord')
part_chord = postp_mxl.force_texture(part_chord, num_voices=4)
utils.create_dir_score()
utils.create_dir_chord()
filename_pickle = os.path.join(
utils.get_dirname_score(), 'chord',
''.join([utils._get_name_project_most_recent(), '.pkl']))
utils_mxl.freeze_stream(part_chord, filename_pickle)
notes_live = convert_mxl.to_notes_live(part_chord,
beatmap=beatmap,
s_beat_start=s_beat_start,
s_beat_end=s_beat_end,
tempo=tempo)
exporter = io_exporter.Exporter()
exporter.set_part(notes_live, 'chord')
exporter.export(utils.get_file_json_comm())
messenger.message(['done', 'bang'])
def main(args):
messenger = mes.Messenger()
use_warped = utils.b_use_warped()
(s_beat_start, s_beat_end, tempo, beat_start, beat_end, length_beats,
beatmap) = utils.get_tuple_beats()
messenger.message(['length_beats', str(length_beats)])
representation = utils.parse_arg(args.representation)
if representation == 'symbolic':
filename_pickle = os.path.join(
utils.get_dirname_score(), 'melody',
''.join([utils._get_name_project_most_recent(), '.pkl']))
part_melody = utils_mxl.thaw_stream(filename_pickle)
stream_segment = analysis_mxl.get_segments(part_melody)
elif representation == 'numeric':
data_segments = ir.extract_segments(
os.path.join(
utils.get_dirname_audio_warped()
if use_warped else utils.get_dirname_audio(),
utils._get_name_project_most_recent() + '.wav'))
df_segments = prep_vamp.segments_to_df(data_segments)
segment_tree = quantize.get_interval_tree(df_segments, diff=False)
data_quantized = quantize.quantize(beatmap,
s_beat_start,
s_beat_end,
trees={'segment': segment_tree})
data_quantized_segments = data_quantized['segment']
score = postp_mxl.df_grans_to_score(data_quantized_segments,
parts=['segment'])
stream_segment = postp_mxl.extract_part(score, 'segment')
else:
raise ' '.join(['representation', representation, 'does not exist'])
utils.create_dir_score()
utils.create_dir_segment()
filename_pickle = os.path.join(
utils.get_dirname_score(), 'segment',
''.join([utils._get_name_project_most_recent(), '.pkl']))
utils_mxl.freeze_stream(stream_segment, filename_pickle)
notes_live = convert_mxl.to_notes_live(stream_segment, beatmap,
s_beat_start, s_beat_end, tempo)
exporter = io_exporter.Exporter()
exporter.set_part(notes_live, 'segment')
exporter.export(utils.get_file_json_comm())
messenger.message(['done', 'bang'])
def main(args):
use_warped = utils.b_use_warped()
name_part = utils.parse_arg(args.name_part)
beat_multiple_quantization = utils.parse_arg(args.beat_multiple)
quarter_length_divisor = 1/float(beat_multiple_quantization)
importer = io_importer.Importer(
utils.get_file_json_comm()
)
importer.load([name_part])
notes_live = importer.get_part(name_part)
mode = 'polyphonic' if name_part == 'chord' else 'monophonic'
(
s_beat_start,
s_beat_end,
tempo,
beat_start,
beat_end,
length_beats,
beatmap
) = utils.get_tuple_beats()
messenger = mes.Messenger()
messenger.message(['length_beats', str(length_beats)])
stream = convert_mxl.live_to_stream(
notes_live,
beatmap=beatmap,
s_beat_start=s_beat_start,
s_beat_end=s_beat_end,
tempo=tempo,
mode=mode
)
# TODO: replace with logic in "granularize.py"
if name_part == 'melody':
data_melody = conv_vamp.to_data_melody(
notes_live,
offset_s_audio=0,
duration_s_audio=utils.get_duration_s_audio(
filename=os.path.join(
utils.get_dirname_audio_warped() if use_warped else utils.get_dirname_audio(),
utils._get_name_project_most_recent() + '.wav'
)
)
)
df_melody = prep_vamp.melody_to_df(
(data_melody['vector'][0], data_melody['vector'][1]),
index_type='s'
)
df_melody[df_melody['melody'] < 0] = 0
melody_tree = quantize.get_interval_tree(
df_melody
)
data_quantized = quantize.quantize(
beatmap,
s_beat_start,
s_beat_end,
trees={
'melody': melody_tree
}
)
data_quantized_melody = data_quantized['melody']
score = postp_mxl.df_grans_to_score(
data_quantized_melody,
parts=['melody']
)
stream = postp_mxl.extract_part(
score,
'melody'
)
else:
stream.quantize(
(quarter_length_divisor, ),
inPlace=True
)
notes_live = convert_mxl.to_notes_live(
stream,
beatmap=beatmap,
s_beat_start=s_beat_start,
s_beat_end=s_beat_end,
tempo=tempo,
bypass_seconds=True
)
exporter = io_exporter.Exporter()
exporter.set_part(notes_live, name_part)
exporter.export(utils.get_file_json_comm())
messenger.message(['done', 'bang'])
def main(args):
use_warped = args.m
messenger = mes.Messenger()
s_beat_start = float(utils.parse_arg(args.s_beat_start)) if utils.parse_arg(args.s_beat_start) else None
s_beat_end = float(utils.parse_arg(args.s_beat_end)) if utils.parse_arg(args.s_beat_end) else None
tempo = float(utils.parse_arg(args.tempo)) if utils.parse_arg(args.tempo) else None
beat_start = float(utils.parse_arg(args.beat_start)) if utils.parse_arg(args.beat_start) else None
beat_end = float(utils.parse_arg(args.beat_end)) if utils.parse_arg(args.beat_end) else None
length_beats = float(utils.parse_arg(args.length_beats)) if utils.parse_arg(args.length_beats) else None
filename_wav = os.path.join(
utils.get_dirname_audio_warped() if use_warped else utils.get_dirname_audio(),
utils._get_name_project_most_recent() + '.wav'
)
if args.a:
s_beat_start = 0
s_beat_end = utils.get_duration_s_audio(filename=filename_wav)
# NB: to look up beat in beatmap, given a beat in Live
# subtract one from measure, multply by 4, then subtract one beat
# e.g., 74.1.1 => beatmap_manual[73*4 + 0]
if use_warped:
s_beat_start = 0
s_beat_end = utils.get_duration_s_audio(
filename=filename_wav
)
beatmap = np.linspace(
0,
s_beat_end,
int(beat_end) - int(beat_start) + 1
)
else:
beatmap = [val.to_float() for val in ir.extract_beats(filename_wav)]
length_beats = utils.get_num_beats(beatmap, s_beat_start, s_beat_end)
if args.double:
beatmap = utils.double_beatmap(beatmap)
length_beats = length_beats*2
elif args.halve:
beatmap = utils.halve_beatmap(beatmap)
length_beats = length_beats/2
# TODO: does this mean that all unwarped audio is assumed to be cropped?
beat_start = 0
beat_end = beat_start + length_beats - 1
utils.create_dir_beat(
)
filepath_beatmap = os.path.join(
utils.get_dirname_beat(),
utils._get_name_project_most_recent() + '.pkl'
)
data_beats = {
's_beat_start': s_beat_start,
's_beat_end': s_beat_end,
'tempo': tempo,
'beat_start': float(beat_start),
'beat_end': float(beat_end),
'length_beats': float(length_beats),
'beatmap': beatmap
}
if args.dump_estimates:
for beat in beatmap:
messenger.message(['beat_relative', str(beat/s_beat_end)])
utils.to_pickle(
data_beats,
filepath_beatmap
)
messenger.message(['done', 'bang'])