Add files using upload-large-folder tool

evalFiloBass.py

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+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Mon Feb  5 14:02:31 2024
+@author: jacquema
+
+Evaluation of the score of the Fake Real Book dataset
+"""
+
+
+import sys
+import logging
+
+sys.path.append('/Users/xavriley/Projects/pse/lib')
+import pse
+
+import os
+from pathlib import Path, PosixPath
+from datetime import datetime
+import re
+from operator import itemgetter, attrgetter
+import pandas
+import music21 as m21
+import PSeval as ps
+
+
+########################
+##                    ##
+##  global variables  ##
+##                    ##
+########################
+
+# path to ASAP dataset
+_dataset_root = '/Users/xavriley/Dropbox/PhD/Datasets/FiloBass ISMIR Publication/musicxml/'
+
+ # default score file name
+_score_suffix = '.xml'
+
+# root of evaluation dir
+_eval_root = '../../PSeval'
+
+Path(_eval_root).mkdir(parents=True, exist_ok=True)
+
+# name of dir for evaluation output
+_output_dir = 'augASAP'
+
+timestamp = str(datetime.today().strftime('%Y%m%d-%H%M'))
+
+# MuseScore commandline executable
+_mscore = '/Applications/MuseScore 4.app/Contents/MacOS/mscore'
+
+
+#################################
+##                             ##
+## extraction of dataset files ##
+##                             ##
+#################################
+
+# corpus can be 'leads' or 'piano'
+def FiloBassCorpus(corpus):
+    """build a list of scores in a subdirectory of FiloBass"""
+    global _dataset_root
+    global _score_suffix
+    dataset_path = Path(_dataset_root)
+    assert isinstance(dataset_path, PosixPath)
+    if not os.path.exists(dataset_path):
+        print(dataset_path, 'not found')
+        return
+    # map: opus_name -> path
+    dataset = dict()
+    files = os.listdir(dataset_path)
+    for file in files:    
+        filepath = dataset_path/file
+        # skip directories
+        if os.path.isdir(filepath):
+            continue 
+        # check the extension in the file name
+        if (os.path.splitext(file)[1] == _score_suffix):
+            # map score name to file path
+            dataset[os.path.splitext(file)[0]] = filepath
+    # sort the list alphabetically
+    dataset = dict(sorted(dataset.items()))
+    return dataset
+
+def accids(ks, notes):
+    c = 0
+    for note in notes:
+        if note.pitch.accidental != ks.accidentalByStep(note.name):
+            c += 1            
+    return c
+    
+def FiloBass_table(corpus='leads'):
+    assert(corpus == 'leads' or corpus == 'piano')
+    table = []
+    dataset = FiloBassCorpus(corpus)
+    names = sorted(list(dataset)) # list of index in dataset   
+    for name in names:
+        if (dataset.get(name) == None):
+            print(name, "not found in dataset", corpus)
+            continue        
+        file = dataset[name]
+        score = m21.converter.parse(file.as_posix())
+        assert(len(score.parts) > 0)
+        part = score.parts[0]
+        fpart = part.flatten()
+        keys = fpart.getElementsByClass([m21.key.Key, m21.key.KeySignature])
+        notes = fpart.getElementsByClass(m21.note.Note)
+        row = []
+        row.append(name)
+        row.append(keys[0].sharps if len(keys) > 0 else None)            
+        row.append(len(part.getElementsByClass(m21.stream.Measure)))
+        row.append(len(notes))
+        row.append(accids(keys[0], notes) if len(keys) > 0 else None)
+        row.append(len(score.parts))
+        row.append(len(keys))
+        table.append(row)
+    df = pandas.DataFrame(table)
+    df.columns = ['name', 'KS','# bars', '# notes', '# accids', '# parts', '# keys']
+    df['KS'] = df['KS'].map('{:n}'.format)
+    return df
+
+# df.fillna('NaN').to_csv(file, header=True, index=False)
+        
+        
+###########################################
+##                                       ##
+## automatic evaluation of whole dataset ##
+##                                       ##
+###########################################
+
+# list of opus names with issues 
+skip = ['All-the-Things-You-Are',
+        'Alone-Together',
+        'Apple-Jump',]
+
+def eval_FiloBass(corpus='leads', algo=ps.pse.Algo_PSE, 
+             tons=104, kpre=33, kpost=23, 
+             output_dir='', filename='',             
+             debug=True, mark=True):
+    global _eval_root
+    assert(corpus == 'leads' or corpus == 'piano')
+    timestamp = datetime.today().strftime('%Y%m%d-%H%M')
+    # default output dir name
+    if output_dir == '':
+       output_dir = timestamp
+    output_path = Path(_eval_root)/'evalFiloBass'/output_dir
+    if not os.path.isdir(output_path):
+        if not os.path.isdir(Path(_eval_root)/'evalFiloBass'):
+            os.mkdir(Path(_eval_root)/'evalFiloBass')
+        os.mkdir(output_path)
+    else:
+        print('WARNING: dir', output_path, 'exists')
+    stat = ps.Stats()   
+    dataset = FiloBassCorpus(corpus)
+    names = sorted(list(dataset)) # list of index in dataset   
+    print('\n', 'starting evaluation of FiloBass dataset -', len(names), 'entries\n')
+    for name in names:
+        if (name in skip):
+            print('\n', name, 'SKIP\n')
+            continue
+        if (dataset.get(name) == None):
+            print(name, "not found in dataset", corpus)
+            continue
+        file = dataset[name]
+        print('\n', name, '\n')
+        s = m21.converter.parse(file.as_posix())
+        (ls, lld) = ps.eval_score(score=s, stat=stat, 
+                                  sid=0, title=name, composer='', 
+                                  algo=algo,
+                                  nbtons=tons,           # for PSE 
+                                  kpre=kpre, kpost=kpost,  # for PS13                                  
+                                  debug=debug, mark=mark)
+        if mark and not ps.empty_difflist(lld):
+            write_score(s, output_path, name)
+    # display and save evaluation table
+    # default table file name
+    if filename == '':
+       filename =  'FRWeval'+'_'+corpus+str(tons)+'_'+timestamp
+    stat.show()    
+    df = stat.get_dataframe() # create pands dataframe
+    df.pop('part') # del column part number (always 0)
+    df.to_csv(output_path/(filename+'.csv') , header=True, index=False)
+    stat.write_datasum(output_path/(filename+'_sum.csv'))    
+    
+    
+def eval_FiloBassitem(name, corpus='leads', algo=ps.pse.Algo_PSE, 
+                 tons=104, kpre=33, kpost=23, dflag=True, mflag=True):
+    assert(len(name) > 0)
+    assert(corpus == 'leads' or corpus == 'piano')
+    dataset = FiloBassCorpus(corpus)
+    if (dataset.get(name) == None):
+        print(name, "not found in dataset", corpus)
+        return
+    file = dataset[name]
+    score = m21.converter.parse(file.as_posix())
+    stat = ps.Stats()   
+    # ground truth ks, estimated ks, nnb of nontes and list of diff notes
+    #(k_gt, gt_est, nn, ld) = ps.eval_part(part=part, stat=stat, nbtons=tons, 
+    #                                      debug=dflag, mark=mflag)
+    (ls, lld) = ps.eval_score(score=score, stat=stat, 
+                              sid=0, title=name, composer='', 
+                              algo=algo,
+                              nbtons=tons,          # for PSE 
+                              kpre=kpre, kpost=kpost, # for PS13                                  
+                              debug=dflag, mark=mflag)
+    stat.show()   
+    assert(len(lld) == 1) # always 1 unique part in LG dataset
+    if mflag and len(lld[0]) > 0:
+        score.show()
+        write_score(score, Path(os.getcwd()), name)
+        
+def write_score(score, output_path, outname):
+    if not os.path.isdir(output_path):
+        os.mkdir(output_path)
+    xmlfile = output_path/(outname+'.musicxml')
+    score.write('musicxml', fp=xmlfile)
+
+def write_score2(score, output_path, outname):
+    assert(len(outname) > 0)
+    if not os.path.isdir(output_path):
+        os.mkdir(output_path)
+    output_path = output_path/outname
+    if not os.path.isdir(output_path):
+        os.mkdir(output_path)
+    xmlfile = output_path/(outname+'.musicxml')
+    score.write('musicxml', fp=xmlfile)
+    # pdffile = dirname+'/'+outname+'.pdf'
+    # os.system(_mscore + ' -o ' + pdffile + ' ' + xmlfile)
+
+
+def debug(name, corpus='leads'):    
+    assert(len(name) > 0)
+    dataset = FiloBassCorpus(corpus)
+    if (dataset.get(name) == None):
+        print(name, "not found in dataset", corpus)
+        return
+    file = dataset[name]
+    score = m21.converter.parse(file)
+    lp = score.getElementsByClass(m21.stream.Part)
+    ln = ps.extract_part(lp[0]) # first and unique part
+    for (n, b, s) in ln:   
+        a = 'sp.add('
+        a += str(n.pitch.midi)
+        a += ', '
+        a += str(b)
+        a += ', '
+        a += 'true' if s else 'false'
+        a += ');'
+        print(a)        
+    #sp = ps.Speller()
+    #sp.debug(True)
+    #ps.add_tons(0, sp)
+    #sp.add_notes(ln1[:61], sp)
+    #sp.spell()
+    
+if __name__=="__main__":
+    eval_FiloBass()
+

notebooks_and_scripts/Compile_Backing.py

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+import numpy as np
+import soundfile as sf
+import csv
+from pathlib import Path
+import librosa
+import hashlib
+import argparse
+import warnings
+# Silence librosa MP3 warning
+warnings.filterwarnings("ignore", category=Warning)
+
+INPUT_FOLDER = "Aebersold"
+OUTPUT_FOLDER = "Backing"
+SCRIPTS_FOLDER = "Scripts"
+CSV_FILENAME = "Edit_Data.csv"
+CSV_CHECKSUM = "799806dbc9756b3baf0c7df8027dea95"
+CROSS_FADE_SAMPLES = 4410
+SR = 44100
+NORMALISE_TARGET = 0.95
+VERSION_OPTIONS = ['full', 'lite']
+INPUT_OPTIONS = ['-version', '-overwrite']
+
+def md5(fname):
+    hash_md5 = hashlib.md5()
+    with open(fname, "rb") as f:
+        for chunk in iter(lambda: f.read(4096), b""):
+            hash_md5.update(chunk)
+    return hash_md5.hexdigest()
+
+def check_files():
+    # Check if backing folder exists
+    backing_path = Path.cwd() / OUTPUT_FOLDER
+    if not backing_path.exists():
+        raise OSError("Error: folder structure incomplete. Run this script inside the Filosax folder, which should contain a 'Backing' folder.")
+
+    # Check if Aebersold folder exists
+    aebersold_path = Path.cwd() / INPUT_FOLDER
+    if not aebersold_path.exists():
+        raise OSError("Error: folder structure incomplete. Run this script inside the Filosax folder, which should contain an 'Aebersold' folder.")
+
+    # Check if CSV file exists and matches checksum
+    csv_path = Path.cwd() / SCRIPTS_FOLDER / CSV_FILENAME
+    if not csv_path.exists():
+        raise OSError("Error: %s file missing." % CSV_FILENAME)
+    if md5(csv_path) != CSV_CHECKSUM:
+        raise OSError("Error: %s wrong file version." % CSV_FILENAME)
+    
+def load_data():
+    # Load data from CSV file
+    csv_path = Path.cwd() / SCRIPTS_FOLDER / CSV_FILENAME
+    csv_data = []
+    with open(csv_path) as csv_file:
+        csv_reader = csv.reader(csv_file, delimiter=',')
+        line_count = 0
+        for row in csv_reader:
+            if line_count == 0:
+                line_count += 1
+            else:
+                csv_data.append(row)
+    return csv_data
+
+def crossfade_ramps(sample_count, fade_type='equal_power'):
+    if fade_type == 'equal_power':
+        in_ramp = np.zeros(sample_count)
+        for i in np.arange(sample_count):
+            in_ramp[i] = np.sqrt(i/sample_count)
+        out_ramp = np.flip(in_ramp)
+    else:
+        # Linear ramps
+        in_ramp = np.linspace(0, 1, sample_count)
+        out_ramp = np.flip(in_ramp)
+    return in_ramp, out_ramp
+
+def perform_edits(filosax_version='full', overwrite_files=False):
+
+    num_files = 0
+    if filosax_version == 'full':
+        num_files = 48
+    if filosax_version == 'lite':
+        num_files = 5
+
+    csv_data = load_data()
+    in_ramp, out_ramp = crossfade_ramps(CROSS_FADE_SAMPLES)
+    num_files_processed = 0
+
+    # Iterate over tracks
+    for track_num in np.arange(0, num_files):
+        track_data = csv_data[track_num]
+        track_id = track_data[0]
+        track_name = track_data[1]
+        print("Processing Track", track_id, ": '%s'... " % track_name, end = '')
+        
+        # Does folder exist?
+        this_folder = Path.cwd() / OUTPUT_FOLDER / track_id
+        if not this_folder.exists():
+            print("Backing folder does not exist.")
+            continue
+        
+        # Does Aebersold track exist? Does it match the checksum?
+        file_name = track_data[3]
+        file_ext = track_data[4]
+        aebersold_path = Path.cwd() / INPUT_FOLDER / (file_name + file_ext)
+        if not aebersold_path.exists():
+            print("Aebersold file does not exist.")
+            continue
+        if (md5(aebersold_path) != track_data[5]):
+            print("Aebersold file wrong version.")
+            continue
+
+        # Do the files already exist?
+        if not(overwrite_files):
+            bass_drums_file = this_folder / "Bass_Drums.wav"
+            piano_drums_file = this_folder / "Piano_Drums.wav"
+            if bass_drums_file.exists() or piano_drums_file.exists():
+                print("One or both backing tracks already exists.")
+                continue
+            
+        # If all this works, proceed
+        track_length = int(track_data[7])
+        bass_drums = np.zeros(track_length)
+        piano_drums = np.zeros(track_length)
+        file_adjust = int(track_data[6])
+        num_edits = int(track_data[9])
+        fade_dur = int(track_data[8])
+        
+        audio_data, sr = librosa.load(aebersold_path, sr=SR, mono=False)
+        audio_data_l = audio_data[0]
+        audio_data_r = audio_data[1]
+        
+        # Normalise audio data
+        audio_data_l = librosa.util.normalize(audio_data_l) * NORMALISE_TARGET
+        audio_data_r = librosa.util.normalize(audio_data_r) * NORMALISE_TARGET
+        
+        # Iterate over edits
+        for n in np.arange(num_edits):
+            file_ref = int(track_data[10+(n*3)])
+            edit_start = int(track_data[11+(n*3)])
+            edit_dur = int(track_data[12+(n*3)])
+            if (n > 0):
+                edit_start -= CROSS_FADE_SAMPLES
+                edit_dur += CROSS_FADE_SAMPLES
+                
+            #print(file_adjust, file_ref, edit_start, edit_dur)
+                
+            start_sample = edit_start - file_ref - file_adjust
+            end_sample = start_sample + edit_dur
+            edit_end = edit_start + edit_dur
+            if edit_end > track_length:
+                edit_end = track_length
+                end_sample = start_sample + (edit_end - edit_start)
+            
+            #print(start_sample, end_sample, edit_start, edit_end)
+            
+            l_splice = audio_data_l[start_sample:end_sample].copy()
+            r_splice = audio_data_r[start_sample:end_sample].copy()
+            
+            # Cross fade in
+            #if (n > 0):
+            l_splice[:CROSS_FADE_SAMPLES] = l_splice[:CROSS_FADE_SAMPLES] * in_ramp
+            r_splice[:CROSS_FADE_SAMPLES] = r_splice[:CROSS_FADE_SAMPLES] * in_ramp
+            
+            if (n == num_edits-1) and (fade_dur > 0) and (fade_dur <= len(l_splice)):
+                # Longer fade out for final edit if required
+                fade_ramp = np.flip(np.linspace(0, 1, fade_dur+1, endpoint=False))[:-1]
+                l_splice[-fade_dur:] = l_splice[-fade_dur:] * fade_ramp
+                r_splice[-fade_dur:] = r_splice[-fade_dur:] * fade_ramp
+            else:
+                # Cross fade out
+                l_splice[-CROSS_FADE_SAMPLES:] = l_splice[-CROSS_FADE_SAMPLES:] * out_ramp
+                r_splice[-CROSS_FADE_SAMPLES:] = r_splice[-CROSS_FADE_SAMPLES:] * out_ramp
+                
+            bass_drums[edit_start:edit_end] += l_splice
+            piano_drums[edit_start:edit_end] += r_splice
+            
+        # Export audio files
+        bass_drums_file = this_folder / "Bass_Drums.wav"
+        piano_drums_file = this_folder / "Piano_Drums.wav"
+        sf.write(bass_drums_file, bass_drums, sr, subtype="PCM_24")
+        sf.write(piano_drums_file, piano_drums, sr, subtype="PCM_24")
+        print("Edited backing tracks created.")
+        num_files_processed += 1
+
+    print("***")
+    print("%d of %d files processed." % (num_files_processed, num_files))
+    print("***")
+    
+def main(args):
+    check_files()
+    perform_edits(args.version, args.overwrite)
+    
+if __name__ == "__main__":
+    PARSER = argparse.ArgumentParser(description="Make Filosax backing edits")
+    PARSER.add_argument("-version", choices=VERSION_OPTIONS, default='full', help="which Filosax version?")
+    PARSER.add_argument("-overwrite", action="store_true", help="overwrite existing?")
+    main(PARSER.parse_args())

notebooks_and_scripts/Edit_Data.csv

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+Track ID,Track Name,Soloist,File Name,Extension,Checksum,Adjust Samples,Duration,Fade Out Duration,Num Edits,Edit 1 Ref,Edit 1 Start,Edit 1 Duration,Edit 2 Ref,Edit 2 Start,Edit 2 Duration,Edit 3 Ref,Edit 3 Start,Edit 3 Duration,Edit 4 Ref,Edit 4 Start,Edit 4 Duration,Edit 5 Ref,Edit 5 Start,Edit 5 Duration,Edit 6 Ref,Edit 6 Start,Edit 6 Duration,Edit 7 Ref,Edit 7 Start,Edit 7 Duration,Edit 8 Ref,Edit 8 Start,Edit 8 Duration
+1,All The Things You Are,Getz,V36_03 Prince Albert,.mp3,1d88ea5493a53fddcaf299e8a4f6109e,3369,14878364,0,1,-90843,33075,14844387,,,,,,,,,,,,,,,,,,,,,
+2,Alone Together,Hayes,V41_1-02 Alone Together,.mp3,f27708fcca211ca20dbec4bbce8f2f69,-7795,15915335,0,6,-70095,126590,6161685,-70095,6288275,1379395,-70095,7667670,2401351,3710651,10069021,1379395,3710651,11448416,2401351,3710651,13849767,2061356,,,,,,
+3,Apple Jump,Gordon,V82_04 Apple Jump,.mp3,f47fb41fff47477f3761c4d9919a856d,-34,16250448,0,6,-118718,38587,6136414,-118718,6174995,1961906,-118718,8136891,1949344,3792482,10086235,1961906,3792472,12048131,1949344,3792472,13997475,2252947,,,,,,
+4,Autumn Leaves,Webster,V54_14 Autmn Leaves,.mp3,18e1e0e1791c91948625422308fe4e61,-1359,15344691,0,4,-80188,78066,5891057,-80188,5969123,2852507,2772319,8821630,2852507,2772319,11674137,3664729,,,,,,,,,,,,
+5,Blues By Five,Hayes,V54_10 F Blues,.mp3,94af1d573f74ede36e435a4ae35e8063,-1349,13903307,0,4,-77409,132118,5754363,-77409,5886481,2220286,2142876,8106766,2220286,2142875,10327051,3576254,,,,,,,,,,,,
+6,Bye Bye Blackbird,Rollins,V39_06 Bye Bye Blackbird,.mp3,1d45807fa24d9c3849375d5c1cf720bc,3,17036628,0,2,-117304,39413,15940278,-420111,15979792,1056936,,,,,,,,,,,,,,,,,,
+7,C Jam Blues,Webster,V48_06 C Jam Blues,.mp3,1b67279417388e1f641515513109ba55,774,13360868,0,4,-135429,42261,7389921,-135428,7432183,918765,783337,8350948,918765,783337,9269713,4091155,,,,,,,,,,,,
+8,Come Rain Or Shine,Gordon,04 - Come Rain Or Shine,.mp3,ed1de7de075765e232553bc834773d9a,4,15793109,0,4,-131234,40424,4388278,-131221,4428715,2027246,1896025,6455961,2027246,1896025,8483207,7309419,,,,,,,,,,,,
+9,Cottontail,Henderson,14 Serpent's Tooth Fast,.mp3,754ec3666da8116d6488cc23775994f1,-1062,16951467,0,4,-81959,41342,1547565,-81958,1588908,1524888,1442930,3113796,1524888,1442930,4638684,12312783,,,,,,,,,,,,
+10,Dear Old Stockholm,Getz,Vol. 91_05 Dear Old Stockholm,.mp3,2a05c5ae761c597fb97419ad782726ed,-717,15897180,0,1,-132631,44100,15786533,,,,,,,,,,,,,,,,,,,,,
+11,Dolphin Dance,Hayes,V11_07 Dolphin Dance,.mp3,eac33b5542e3cad136cd674c268ff2c8,-4264,14959333,0,5,-134976,43959,6047492,-134975,6091452,2871188,2736213,8962640,2871188,2736213,11833828,2518216,-783475,14352044,607290,,,,,,,,,
+12,Doxy,Rollins,V08_02 Doxy,.mp3,754ba20fa73ca89e6373d5d7431b6965,-1371,17300036,0,4,-63835,122306,7518777,-63834,7641084,3752772,3688938,11393856,3752772,3688938,15146628,1235376,3688938,16382004,848029,,,,,,,,,
+13,For Regulars Only,Gordon,V82_07 For Regulars Only,.mp3,6971ab4cd5810961be31dc5d975e8f64,-43,16051748,0,4,-47073,97506,6657274,-47073,6754780,3617832,3570759,10372612,3617832,3570759,13990444,2060495,,,,,,,,,,,,
+14,Four,Rollins,02-Four,.mp3,87167844495e4b3e1342bd4a095e80b8,4,16498147,0,8,-18371,77010,425277,-19452,502294,1132636,-19377,1635005,1593216,-19377,3228221,1508705,-19377,4736926,1465650,2954978,6202576,1508705,2954979,7711282,1465650,2955009,9176962,7321185
+15,Fried Bananas,Gordon,V82_01 Fried Bananas,.mp3,01a61d2254fca9533d4c4de2cb311400,-34,17479571,0,4,-44197,97583,9313089,-44197,9410672,1803648,1759451,11214320,1803648,1759451,13017968,4461603,,,,,,,,,,,,
+16,Gone With The Wind,Getz,V58_02 Gone With the Wind,.mp3,afad7f464b6d94c411f4a91a22babbfa,-10639,16739108,0,4,-101414,37541,10462878,-101414,10500420,1954376,1852963,12454796,1954376,1852963,14409172,2099546,,,,,,,,,,,,
+17,Have You Met Miss Jones?,Getz,02 - Have You Met Miss Jones,.mp3,48a9240d69d6b3130f04d3a57a1d0ab0,-1,17055554,0,4,-81743,44100,9159747,-81763,9203827,2935060,2853297,12138887,2935060,2853313,15073963,1979487,,,,,,,,,,,,
+18,Honeysuckle Rose,Webster,Vol. 130_2-06 Honeysuckle Rose,.mp3,5f95b0710b1fc54dc75ecf5d545c8ade,0,17550984,0,5,-132831,33075,8620873,-132831,8653948,2091312,1958481,10745260,2091312,1958481,12836572,2089700,1958481,14926272,2624712,,,,,,,,,
+19,I’ll Remember April,Getz,V43_08 I'll Remember April,.mp3,1e78a409410396dec3f1c6a69e96dcbc,766,16558411,23632,4,-2791418,22048,1969139,-451301,1991188,9611511,1828135,11602699,4446456,422376,16049155,486592,,,,,,,,,,,,
+20,In A Mellow Tone,Webster,V48_02 In A Mellow Tone,.mp3,d8930039dfb3f24b7bf8dc42d79fe521,776,18586498,0,5,-66895,119563,8881829,-66895,9001392,2956572,2889677,11957964,2956572,2889677,14914536,2728104,2889677,17642640,936537,,,,,,,,,
+21,In Your Own Sweet Way,Rollins,Vol. 105_02 In Your Own Sweet Way,.mp3,d2449b542f957a5b896c3c8ecf5eb6b3,119,19229465,0,1,-85316,117811,19105847,,,,,,,,,,,,,,,,,,,,,
+22,Invitation,Getz,06 - Invitation,.mp3,637f2ecef21c33b6ee14832bb0df8232,-2,16459224,0,4,-87546,43421,7773214,-87545,7816636,2594036,2506491,10410672,2594036,2506491,13004708,3449230,,,,,,,,,,,,
+23,Isotope,Henderson,Vol. 108_07 Isotope,.mp3,38ac7e05c73d0a9132f159670a0f94c0,165,16795362,0,6,-45838,103112,7183932,-45838,7287044,726908,-45838,8013952,3632207,4313277,11646159,726908,4313277,12393067,3632207,4313277,16005274,790088,,,,,,
+24,Just Friends,Gordon,03 - Just Friends,.mp3,18fb9e945e173ba77822741c1b86710b,-14,16363891,0,4,-33502,100876,7028560,-32793,7130145,3415612,3382820,10545758,3415612,3382820,13961371,2400904,,,,,,,,,,,,
+25,Lady Bird,Gordon,V36_02 Lady Bird,.mp3,b7466d88ce702d625183e4b065da00ff,3372,16795588,0,3,-84068,38585,15368881,-84067,15407467,679039,-2477730,16086502,701365,,,,,,,,,,,,,,,
+26,Milestones,Henderson,08-Milestones,.mp3,6b6c9f2f3cbe602d5e32a8f91c75563c,-5,16811716,0,4,-118972,44100,9283488,-118972,9327588,2343596,2224624,11671184,2343596,2224624,14014780,2796936,,,,,,,,,,,,
+27,Montmartre,Gordon,V82_03 Montmartre,.mp3,8d31b01d2bfd88a6b5e213eb3922297d,-40,16037428,0,4,-288224,43088,5514103,-288223,5557192,5031336,4743113,10588528,5031336,4743113,15619864,366874,,,,,,,,,,,,
+28,Namely You,Rollins,V40_2-02 Namely You,.mp3,5968d5f697ccb2e8250d1f5e737ea093,153,15243178,0,4,-132630,42261,7345822,-132629,7388084,2463517,2330906,9851619,2463514,2330906,12315151,2803603,,,,,,,,,,,,
+29,Now’s The Time,Hayes,V02_10 Fast Blues In F Concert,.mp3,4ea41fdf288a62d3ea1bfc3e52dfe5c8,809,16018068,0,6,-40692,100348,1326252,-40692,1426600,2631476,-40692,4058076,3914184,3873492,7972260,3914184,7787676,11886444,3914184,7787676,15800628,217440,,,,,,
+30,Oleo,Webster,V51_04 I Got Rhythm,.mp3,c5013f8d4b1dca38d4fb952289bfd09f,-1767,16974603,0,6,-70392,42548,3033671,-70391,3076220,2922484,-70391,5998704,2900828,2830443,8899538,2900828,5731277,11800372,2900828,5731290,14701213,2134109,,,,,,
+31,On Green Dolphin Street,Rollins,02 - On Green Dolphin Street,.mp3,4f9e87eea431c5da2e83e67e4a5b50bf,2,16159626,0,4,-765947,44100,6756747,-765936,6800858,3199440,2433504,10000298,3199440,2433504,13199738,2809588,,,,,,,,,,,,
+32,Out Of The Night,Henderson,Vol. 108_04 Out Of The Night,.mp3,ee46bc05dd6c1d9a562c045fcd06ba06,172,16330212,0,5,-73227,66384,6613568,-73227,6679952,3313188,3239961,9993140,3313188,3239961,13306328,1092960,3239961,14399288,1930924,,,,,,,,,
+33,Parisian Thoroughfare,Hayes,Vol. 95_04 Parisian Thoroughfare,.mp3,d4ac4139c92ee172bf0d5fdbcd988eaa,27,17343468,0,5,-43204,94730,8634510,-43204,8729240,3355404,3312200,12084644,3355404,3312200,15440048,829352,3312200,16269400,1023212,,,,,,,,,
+34,Pennies From Heaven,Webster,Vol. 130_1-01 Pennies From Heaven,.mp3,4aef5bcfcf3c8547e3160d08084361e8,11,15567102,0,5,-170312,42262,2957414,-170312,2999676,2917588,-170312,5917264,2909844,2739532,8827108,2909844,2739532,11736952,3830150,,,,,,,,,
+35,Satin Doll,Webster,V12_02 Satin Doll,.mp3,5a8be2388d4f0deda52812f490917441,475,17604154,0,4,-141487,38586,2963497,-141490,3002080,5437043,5295553,8439123,5437043,5295553,13876166,3625387,,,,,,,,,,,,
+36,Scrapple From The Apple,Getz,V06_09 Scrapple From The Apple,.mp3,207be4a808c1ac69ea188b32a5b63b41,1049,16553124,0,4,-72421,42261,4894698,-72420,4936960,4843276,4770856,9780236,4843276,4770856,14623512,1880532,,,,,,,,,,,,
+37,Sonnymoon For Two,Rollins,V82_02 Sticky Wicket,.mp3,59dd6ecca5ece1b345411c4d5803689a,-32,15845727,0,5,-144019,44100,3606468,-144019,3650568,3623676,3479657,7274244,3623676,3479657,10897920,3558187,3479657,14456107,1369317,,,,,,,,,
+38,Soon,Hayes,V22_2-02 Soon,.mp3,90e1d297b5b18b527bd302d73c8a6ac8,-1998,15640120,0,4,-107426,43444,9444051,-107425,9487496,1843684,1736259,11331180,1843684,1736259,13194864,2465256,,,,,,,,,,,,
+39,Star Eyes,Hayes,08 - Star Eyes,.mp3,ea2b7bcf2c4af77d7cfd74436667c351,3,16448094,0,5,-519362,44099,11046411,-519362,11090510,1739000,1219638,12829510,1739000,1219638,14568510,1677880,905954,16246390,49229,,,,,,,,,
+40,Stella By Starlight,Henderson,03 - Stella,.mp3,05cc4934bcbaa474c2304dc812c3c986,-2,17670523,0,8,-36811,98382,5859891,3867181,5958273,1791618,3867181,7929891,1932374,5799555,9862265,1932374,5799555,11794639,954852,5799555,12749491,940952,5799555,13690443,1858440,5799555,15548883,2003848
+41,Step Lightly,Henderson,Vol. 108_01 Step Lightly,.mp3,fb1b77c5dacfd1a742022c6f6a6f2763,162,16848298,0,5,-174106,43180,4649715,-174106,4692896,1587290,1413185,6280186,1587290,1413185,7867476,6249342,1413185,14116818,2731480,,,,,,,,,
+42,Sweet Georgia Brown,Webster,V70_09 Sweet Georgia Brown,.mp3,9316b004a2e05c816ae97a073cfdde63,21030,16001571,0,1,-184261,42262,15959309,,,,,,,,,,,,,,,,,,,,,
+43,Take The A Train,Henderson,V12_09 Take The 'a' Train,.mp3,37a019b3662d3fd1a08e87fd864ab484,471,15530960,0,5,-585807,39745,2010335,-585807,2050080,2050452,1464645,4100532,2050452,1464645,6150984,6290372,1464645,12441356,3020420,,,,,,,,,
+44,Tangerine,Getz,V22_2-07 Tangerine,.mp3,f8d6522a5c1f65c7029023bd69604221,-814,16904430,0,4,-32920,93867,4908461,-32920,5002328,4842971,4797210,9845298,4817290,4797210,14662588,2041554,,,,,,,,,,,,
+45,The Rainbow People,Gordon,V82_05 The Rainbow People,.mp3,254c33daa3b15102ed3902297a88b898,-48,16939336,0,4,-184294,38587,8515929,-184294,8554516,2810448,2604550,11364963,2767241,2604550,14132204,2636428,,,,,,,,,,,,
+46,There Will Never Be Another You,Hayes,V44_08 There Will Never Be Another You,.mp3,ac9d668930eb6558fd03d062956e27ad,7794,16391080,0,4,-44719,98349,10580943,-44719,10679292,1685088,1640369,12364380,1685088,1640369,14049468,2341612,,,,,,,,,,,,
+47,Three Little Words,Rollins,V51_07 Three Little Words,.mp3,ffb98f6fd813577e2b731dc0ee704c46,-5864,16764213,0,4,-74589,44217,4599186,-74603,4641389,1474592,1400040,6116032,1381948,1400040,7498032,9264270,,,,,,,,,,,,
+48,UMMG,Henderson,V66_02 UMMG,.mp3,b54bb70a26ac917cfec07c49b293a6a0,223,17027202,0,6,-86636,41342,3622193,-296507,3663536,1701226,-505017,5364762,5636196,-505017,11000958,1862880,1357863,12863838,1862880,1357863,14726718,2300485,,,,,,

notebooks_and_scripts/Remove_Repeats.py

@@ -0,0 +1,99 @@
+from pathlib import Path
+import librosa
+import csv
+import json
+import numpy as np
+import music21 as m21
+
+CSV_FILENAME = "./Edit_Data.csv"
+SR = 44100
+CROSS_FADE_SAMPLES = int(SR / 10)
+
+def load_data():
+    # Load data from CSV file
+    csv_path = Path(__file__).parent / Path(CSV_FILENAME)
+
+    with open(csv_path) as csv_file:
+        csv_reader = csv.DictReader(csv_file, delimiter=',')
+        return list(csv_reader)
+
+def load_syncpoints(score):
+    json_path = Path(__file__).parent / Path("../syncpoints/") / score.with_suffix(".json").name
+    return json.loads(json_path.read_text())
+
+def get_nearest_measure(syncpoints, sample):
+    for measure_no, time_s in syncpoints:
+        if np.isclose(sample / SR, time_s, atol=0.6):
+            return measure_no
+    return None
+
+def remove_measure_ranges(score, ranges):
+    for part in score.parts:
+        measures_to_remove = []
+        for measure in part.getElementsByClass(m21.stream.Measure):
+            if any(start <= measure.number <= end for start, end in ranges):
+                measures_to_remove.append(measure)
+        
+        for measure in measures_to_remove:
+            part.remove(measure)
+
+    return score
+
+musicxml_files = sorted((Path(__file__).parent / Path("../musicxml/")).glob("*.xml"))
+
+for row in load_data():
+    edits = []
+
+    score = musicxml_files[int(row['Track ID']) - 1]
+    num_edits = int(row['Num Edits'])
+    adjust_samples = int(row['Adjust Samples'])
+
+
+    for n in range(num_edits):
+        edit_idx = str(n + 1)
+        edit_ref = int(row['Edit ' + edit_idx + ' Ref'])
+        edit_start = int(row['Edit ' + edit_idx + ' Start'])
+        edit_dur = int(row['Edit ' + edit_idx + ' Duration'])
+
+        # not needed for our purpose here
+        # if (n > 0):
+        #     edit_start -= CROSS_FADE_SAMPLES
+        #     edit_dur += CROSS_FADE_SAMPLES
+
+        source_start = edit_start - edit_ref - adjust_samples
+        source_end = source_start + edit_dur
+
+        edits.append([source_start, source_end, edit_start, (edit_start+edit_dur), row['Track ID']])
+
+    if len(edits) > 1:
+        seen_sections = []
+        repeated_measures = []
+        syncpoints = load_syncpoints(score)
+        for edit in edits:
+            source_section_times = (edit[0], edit[1])
+            if source_section_times in seen_sections:
+                target_section_times = (edit[2], edit[3])
+
+                # lookup measure number via syncpoints file
+                measure_from = get_nearest_measure(syncpoints, edit[2])
+                measure_to = get_nearest_measure(syncpoints, edit[3])
+
+                # print duration in minutes that were repeated
+                print(f"{score.name} {measure_from} to {measure_to} ({(edit[3] - edit[2]) / SR / 60:.2f} minutes)")
+                # collect measure ranges
+                repeated_measures.append((measure_from, measure_to))
+            
+            seen_sections.append(source_section_times)
+        
+        m21_score = m21.converter.parse(score)
+        remove_measure_ranges(m21_score, repeated_measures)
+    else:
+        m21_score = m21.converter.parse(score)
+
+    # make a new folder for the scores
+    new_folder = Path(__file__).parent / Path("../musicxml_no_repeats/")
+    new_folder.mkdir(parents=True, exist_ok=True)
+
+    # save new score
+    new_score_path = new_folder / Path(f"{row['Track ID']}.xml")
+    m21_score.write('musicxml', fp=new_score_path)