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# -*- coding: utf-8 -*-
"""
Created on Mon Oct 12 14:24:34 2015
@author: marchand
"""
import sys
import csv
import os
import numpy as np
import lxml.etree as etree
try:
import jams
JAMS_LIB = True
except:
JAMS_LIB = False
print('You need jams lib to create jams files (https://github.com/marl/jams.git)')
raise Exception('You need jams lib to create jams files (https://github.com/marl/jams.git)')
def load_annotations(file_):
''' Read a musicdescription xml file.
Returns a 4-column matrix whose columns are time (in sec), is_beat (1
if the marker is a beat or a downbeat 0 in case of tatum), is_tatum
(1 if the marker is a tatum, a beat or a downbeat), and is_measure
(1 if the marker is a downbeat).
Args:
file_ (str): path of the xml file.
Returns:
np.array: a 4-column (time, is_beat, is_tatum, is_measure) matrix
with each row representing a marker.
'''
tree = etree.parse(file_)
data = []
for elem in tree.iter():
if elem.tag[-7:] == 'segment':
a = elem.getchildren()
if 'beat' in a[0].keys():
b = int(a[0].get('beat'))
tatum = int(a[0].get('tatum'))
t = float(elem.get('time'))
m = int(a[0].get('measure'))
data.append([t, b, tatum, m])
return np.asarray(data)
def swing_groundtruth_from_annot(file_):
''' Return a dic of groundtruth.
Args:
file_ (str): path of the xml file.
Returns:
dict: containing temporal information of markers::
{
'swing_median': swing ration median over the whole track,
'swing_iqr': idem with iqr (inter-quartile-range)
'swing_mean': idem with mean
'swing_std': idem with std (standard deviation)
'tempo_mean': tempo mean over the whole track
'tempo_std': idem with std
'beat_by_measure': a list containing the number of beat for each
measure in the track
'percentage_of_swing': the number of 8th-note markers over the
number of beat markers
}
'''
def iqr(x):
return np.subtract(*np.percentile(x, [75, 25]))
out = {}
data = load_annotations(file_)
# swing
idx_swing = np.argwhere(data[:, 1] == 0)
if len(idx_swing):
# patch due to annotation files that ends with a swing annotation
if idx_swing[-1] + 1 == data.shape[0]:
idx_swing = idx_swing[:-1]
# idem for files that begins with a swing annotation
if idx_swing[0] == 0:
idx_swing = idx_swing[1:]
short_eight = data[idx_swing + 1, 0] - data[idx_swing, 0]
long_eight = data[idx_swing, 0] - data[idx_swing - 1, 0]
swings = long_eight / short_eight
else:
swings = [1.]
out['swing_median'] = np.around(np.median(swings), decimals=3)
out['swing_iqr'] = iqr(swings)
out['swing_mean'] = np.around(np.mean(swings), decimals=3)
out['swing_std'] = np.std(swings)
# tempo
d = np.diff(data[data[:, 1] >= 1, 0]) # select all beats : data[data[:, 1] >= 1, 0]
out['tempo_mean'] = (60. / d).mean()
out['tempo_std'] = (60. / d).std()
# number of beat by measure
d = data[data[:, 1] == 1, 3]
a = np.argwhere(d == 1)
out['beat_by_measure'] = np.diff(a.reshape(a.size))
# percentage of swing
d = data[data[:, 2] == 1, 1]
out['percentage_of_swing'] = (d == 0).sum() / (d.sum() - 1)
return out
def import_metadata(file_='GTZANindex.txt'):
''' Import title and artist from Sturm's file
Args:
file_ (str): path to Sturm's file
Returns:
dict: {audio_filename: [artist, title]}
'''
import re
#test = "blues.00002.wav ::: John Lee Hooker ::: Think Twice Before You Go\n"
re_metadata = re.compile('^((?:blues|classical|country|disco|hiphop|jazz|metal|pop|reggae|rock)\.[\d]{5}\.wav) ::: (.*?) ?::: ?(.*?)\n?$')
metadata = {}
with open('GTZANindex.txt', 'r') as f:
for line in f.readlines():
if line.startswith('#'):
continue
m = re_metadata.match(line)
if m is not None:
filename, artist, title = m.groups()
metadata[filename] = [artist, title]
else:
raise Exception('Error parsing line: "{}"'.format(line))
return metadata
def generate_csv_jams(folder, version_tag=''):
'''Generates a .csv file_ containing high-level infos and jams files.
Generates a .csv file_ containing high-level informations, given the root
folder of annotations. This folder should contain 3 folders named 'swing',
'no_swing' and 'ternary'. Each folder should contain a bunch of .xml
files following the muscidescription format.
Writes stats.csv next to these 3 folders.
stats.csv contains a line for each .xml, and a number of columns described
here::
{
'filename': audio filename,
'tempo mean': tempo mean over the track,
'tempo std': tempo std over the track,
'swing ?': 'yes' if track has swing, 'no' instead,
'swing ratio median': swing ratio median over the track,
'swing ratio iqr': swing ratio iqr over the track,
'swing confidence': percentage of swinged 8th-note in the track,
'meter',
'ternary': 'yes' if track is ternary, 'no' if not,
'beat by measure': list of number of beat by measure,
}
Generates a jams file for each annotation file.
Writes them in folder/jams/.
Args:
folder (str): path of the root folder of annotations.
version_tag (str): optional, version tag to put in jams file
'''
try:
os.mkdir(os.path.join(folder, 'jams'))
except:
pass
metadata = import_metadata()
with open(os.path.join(folder,'stats.csv'), 'wb') as csvfile:
fieldnames = ['filename', 'artist', 'title', 'tempo mean', 'tempo std', 'swing ?', 'swing ratio median',
'swing ratio iqr', 'swing confidence', 'meter', 'ternary ?', 'beat by measure']
csvwriter = csv.writer(csvfile, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
csvwriter.writerow(fieldnames)
to_write = []
for path, subdirs, files in os.walk(folder):
for file_ in files:
if file_[-4:] != '.xml':
continue
file_path = os.path.join(path, file_)
filename = file_[:-4]
swing = 'no' if 'no_swing' in path else 'yes'
gt_dic = swing_groundtruth_from_annot(file_path)
tempo, tempo_var = gt_dic['tempo_mean'], gt_dic['tempo_std']
bbm = gt_dic['beat_by_measure']
if np.unique(bbm).size == 1:
if 'ternary' in path:
meter = '{}/8'.format(bbm[0] * 3)
else:
meter = '{}/4'.format(bbm[0])
else:
meter = ''
ternary = 'yes' if 'ternary' in path else 'no'
if swing == 'yes':
swing_ratio, swing_ratio_iqr = format(gt_dic['swing_median'], '.2f'), format(gt_dic['swing_iqr'], '.3f')
confidence = gt_dic['percentage_of_swing']
else:
swing_ratio, swing_ratio_iqr, confidence = '', '', ''
artist, title = metadata[filename]
# csv
to_write.append([filename, artist, title, format(tempo, '.2f'),
format(tempo_var, '.2f'), format(swing, 's'), swing_ratio,
swing_ratio_iqr, confidence, meter, ternary, bbm])
# jams
if JAMS_LIB:
data = load_annotations(file_path)
create_jams_file(filename, data, artist, title, format(tempo, '.2f'),
format(tempo_var, '.2f'), format(swing, 's'), swing_ratio,
swing_ratio_iqr, confidence, meter, ternary,
os.path.join(folder, 'jams', filename + '.jams'),
version_tag)
# sort by filenames
to_write.sort(key=lambda x: x[0])
csvwriter.writerows(to_write)
def create_jams_file(filename, data, artist, title, tempo, tempo_var, swing,
swing_ratio, swing_ratio_iqr, confidence, meter, ternary,
jams_file, version_tag):
jam = jams.JAMS()
# ---------------------------------------------------
# metadata
jam.file_metadata.duration = 30.0
jam.file_metadata.artist = artist
jam.file_metadata.title = title
jam.file_metadata.identifiers = {'filename': filename}
# ---------------------------------------------------
# annotations: beat
ann = jams.Annotation(namespace='beat')
for b in data[data[:, 1] >= 1, 0]:
ann.append(time=b, duration=0.0, confidence=1, value=1)
ann.annotation_metadata = jams.AnnotationMetadata(data_source='Manual annotations.',
annotator=jams.Curator('Ugo Marchand & Quentin Fresnel'),
corpus='GTZAN',
annotation_tools='Audioscuplt 3.3.9',
version=version_tag,
)
ann.annotation_metadata.curator = jams.Curator('Ugo Marchand', '[email protected]')
ann.sandbox = {'annotation_type': 'beat'}
jam.annotations.append(ann)
# ---------------------------------------------------
# annotations: downbeat
ann = jams.Annotation(namespace='beat')
for b in data[data[:, 3] == 1, 0]:
ann.append(time=b, duration=0.0, confidence=1, value=1)
ann.annotation_metadata = jams.AnnotationMetadata(data_source='Manual annotations.',
annotator=jams.Curator('Ugo Marchand & Quentin Fresnel'),
corpus='GTZAN',
annotation_tools='Audioscuplt 3.3.9',
version=version_tag,
)
ann.annotation_metadata.curator = jams.Curator('Ugo Marchand', '[email protected]')
ann.sandbox = {'annotation_type': 'downbeat'}
jam.annotations.append(ann)
# ---------------------------------------------------
# annotations: 8th-note
if swing == 'yes':
ann = jams.Annotation(namespace='beat')
for b in data[data[:, 1] == 0, 0]:
ann.append(time=b, duration=0.0, confidence=1, value=1)
ann.annotation_metadata = jams.AnnotationMetadata(data_source='Manual annotations.',
annotator=jams.Curator('Ugo Marchand'),
corpus='GTZAN',
annotation_tools='Audioscuplt 3.3.9',
version=version_tag,
)
ann.annotation_metadata.curator = jams.Curator('Ugo Marchand', '[email protected]')
ann.sandbox = {'annotation_type': '8th-note'}
jam.annotations.append(ann)
# ---------------------------------------------------
# tags manual
tag = jams.Annotation(namespace='tag_open')
tag.annotation_metadata = jams.AnnotationMetadata(data_source='Manual annotations.',
annotator=jams.Curator('Ugo Marchand'),
corpus='GTZAN',
annotation_tools='Audioscuplt 3.3.9',
version=version_tag,
)
tag.annotation_metadata.curator = jams.Curator('Ugo Marchand', '[email protected]')
tag.sandbox = {'swing': swing, 'ternary': ternary}
jam.annotations.append(tag)
# ---------------------------------------------------
# tags automatic
tag = jams.Annotation(namespace='tag_open')
tag.annotation_metadata = jams.AnnotationMetadata(data_source='Automatic values.',
corpus='GTZAN',
annotation_tools='generate.py',
version=version_tag,
)
tag.annotation_metadata.curator = jams.Curator('Ugo Marchand', '[email protected]')
tag.sandbox = {
'tempo mean': tempo,
'tempo std': tempo_var,
'swing ratio': swing_ratio,
'swing ratio iqr': swing_ratio_iqr,
'swing ratio confidence': confidence,
'meter': meter,
}
jam.annotations.append(tag)
jam.save(jams_file)
# %%
if __name__ == '__main__':
print('generating {} and jams files (might take a long time...)'.format(os.path.join(sys.argv[1], 'stats.csv')))
folder, version_tag = sys.argv[1]
generate_csv_jams(folder, version_tag)
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