# -*- 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', 'ugo.marchand@ircam.fr') 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', 'ugo.marchand@ircam.fr') 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', 'ugo.marchand@ircam.fr') 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', 'ugo.marchand@ircam.fr') 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', 'ugo.marchand@ircam.fr') 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)