def uploadToEcho(filenames):
retry=[]
successTracks = []
i=0
if not os.path.isdir('echoNestUploads'):
os.mkdir('echoNestUploads')
for f in filenames:
time = t.localtime()
time = str(time.tm_hour) +'_' + str(time.tm_min) + '_' + str(time.tm_sec)
try:
print 'uploading...', f
rTrack = track.track_from_file(open(f, 'r'), 'mp3')
if rTrack:
print rTrack.tempo
print rTrack.time_signature
print 'gather track info'
trackInfo = [f, rTrack.tempo, rTrack.time_signature, rTrack.id]
successTracks.append(trackInfo)
pickle.dump(trackInfo, open('echoNestUploads/'+str(i)+'-'+time+'.pkl', 'w'))
try:
print 'saving id3'
tag = d3.load(f).tag
tag.bpm = rTrack.tempo
tag.copyright_url = 'echo'
except:
print 'id3 failed'
except:
print "couldn't upload"
retry.append(f)
i+=1
return successTracks, retry
def AnalyzeMP3File(file):
f = open(file)
theTrack = track.track_from_file(f, "mp3")
theTrack.get_analysis()
trackObj = models.trackInfo(theTrack, file)
try:
print theTrack.title
except:
print "unknown track"
trackObj.save()
f.close()
def get_timbre(wav_dir):
# from echonest capture the timbre and pitches loudness et.al.
config.ECHO_NEST_API_KEY = "BPQ7TEP9JXXDVIXA5" # daleloogn my api key
f = open(wav_dir)
print "process%s====================================================================" % wav_dir
# t = track.track_from_file(f, 'wav')
t = track.track_from_file(f, 'wav', 256, force_upload=True)
# if not with force_upload it will timed out for sockets
t.get_analysis()
segments = t.segments # list of dicts :timing,pitch,loudness and timbre for each segment
timbre = from_segments_get_timbre(wav_dir, segments)
return timbre
def get_timbre_pitches_loudness(wav_dir):
# from echonest capture the timbre and pitches loudness et.al.
config.ECHO_NEST_API_KEY = "BPQ7TEP9JXXDVIXA5" # daleloogn my api key
f = open(wav_dir)
print "process:============ %s =============" % wav_dir
t = track.track_from_file(f, 'wav', 256, force_upload=True)
t.get_analysis()
segments = t.segments # list of dicts :timing,pitch,loudness and timbre for each segment
timbre_pitches_loudness = from_segments_get_timbre_pitch_etal(wav_dir, segments)
timbre_pitches_loudness_file_txt = open('timbre_pitches_loudness_file.txt', 'a')
timbre_pitches_loudness_file_txt.write(wav_dir + '\r\n')
timbre_pitches_loudness_file_txt.write(str(timbre_pitches_loudness))
timbre_pitches_loudness_file_txt.close()
return segments
def main():
f = open("sonata.mp3")
t = track.track_from_file(f, "mp3")
print t.key
print t.title
t.get_analysis()
#t.sections is a list of dicts which describes the larger sections of a song
#print dir(t)
print t.sections
beatList = [(x['start'], x['start']+x['duration']) for x in t.beats]
print beatList
while myTime < 212:
time.sleep(0.05)
checkBeat(beatList)
def fetch_en_annotations(filename):
songname = filename.rstrip('.mp3')
print songname, "to json annotation"
# from pyechonest import artist
# bk = artist.Artist('bikini kill')
# print "Artists similar to: %s:" % (bk.name,)
# for similar_artist in bk.similar: print "\t%s" % (similar_artist.name,)
f = open(mypath + filename)
t = track.track_from_file(f, 'mp3')
outfile = songname + '.json'
print t.analysis_url
myurl = t.analysis_url
annotation = subprocess.check_output(["curl", myurl])
# ipdb.set_trace()
open(songname + '.json', 'w').write(json.dumps(annotation))
pickle.dump(t, open(songname + ".pickle", "w"))
def fetch_en_annotations(filename):
songname = filename.rstrip('.mp3')
print songname, "to json annotation"
# from pyechonest import artist
# bk = artist.Artist('bikini kill')
# print "Artists similar to: %s:" % (bk.name,)
# for similar_artist in bk.similar: print "\t%s" % (similar_artist.name,)
f = open(mypath + filename)
t = track.track_from_file(f, 'mp3')
outfile = songname + '.json'
print t.analysis_url
myurl = t.analysis_url
annotation = subprocess.check_output(["curl", myurl])
# ipdb.set_trace()
open(songname+'.json', 'w').write(json.dumps(annotation))
pickle.dump(t, open(songname + ".pickle", "w"))
def songDetails (songName):
global count
print songName
if re.search('\.[mM][pP]3$',songName): #Checking if the file is a mp3 file or not
startTime=time.time()
f = open(musicPath+songName)
t = track.track_from_file(f, 'mp3',30,False)
endTime=time.time();
print songName
print t.id
print t.artist
print t.duration
print t.title
print "Search Time : "+str(endTime-startTime)
print "----------------------"
fo = open("foo.txt", "a")
fo.write( songName+"\n")
fo.write( t.title+"\n")
fo.write( t.artist+"\n")
fo.write( "------------\n")
# Close opend file
fo.close()
count+=1
def upload(request):
"""
Handle the upload of the query file and store it in Mongo.
"""
f = request.FILES.get('files[]')
k = request.POST.get('k', 1)
# Send file to Echonest and request full analysis.
# Only MP3 supported for now.
# TODO: This is a bit unstable with large files.
try:
tr = track.track_from_file(f, 'mp3')
tr.get_analysis()
except EchoNestException:
return HttpResponse(status=500)
# Create object to store.
q = {
'id': tr.id,
'md5': tr.md5,
'bitrate': tr.bitrate,
'codestring': tr.codestring,
'duration': tr.duration,
'energy': tr.energy,
'segments': tr.segments,
}
queries.insert(q)
redirect_to = reverse('results', args=[tr.md5]) + '?k=' + k
response = JSONResponse([{
'name': f.name,
'url': redirect_to,
}], {}, response_mimetype(request))
response['Content-Disposition'] = 'inline; filename=file.json'
return response
def get_timbre_pitches_loudness(wav_dir):
turn_api()
f = open(wav_dir)
print "process%s====================================================================" % wav_dir
# t = track.track_from_file(f, 'wav')
t = track.track_from_file(f, 'wav', 256, force_upload=True)
# if not with force_upload it will timed out for sockets
t.get_analysis()
segments = t.segments # list of dicts :timing,pitch,loudness and timbre for each segment
timbre_pitches_loudness = []
# flag_test = 1
for segments_item in segments:
timbre = segments_item['timbre']
pitches = segments_item['pitches']
loudness_start = segments_item['loudness_start']
loudness_max_time = segments_item['loudness_max_time']
loudness_max = segments_item['loudness_max']
segments_item_union = timbre + pitches + [loudness_start, loudness_max_time, loudness_max]
timbre_pitches_loudness.append(segments_item_union)
timbre_pitches_loudness_file_txt = open('timbre_pitches_loudness_file_txt', 'a')
timbre_pitches_loudness_file_txt.write('\r\n' + wav_dir + '\r\n')
timbre_pitches_loudness_file_txt.write(timbre_pitches_loudness)
timbre_pitches_loudness_file_txt.close()
return timbre_pitches_loudness
def get_timbre_pitches_loudness(wav_dir):
turn_api()
f = open(wav_dir)
print "process%s====================================================================" % wav_dir
# t = track.track_from_file(f, 'wav')
t = track.track_from_file(f, "wav", 256, force_upload=True)
# if not with force_upload it will timed out for sockets
t.get_analysis()
segments = t.segments # list of dicts :timing,pitch,loudness and timbre for each segment
timbre_pitches_loudness = []
# flag_test = 1
for segments_item in segments:
timbre = segments_item["timbre"]
pitches = segments_item["pitches"]
loudness_start = segments_item["loudness_start"]
loudness_max_time = segments_item["loudness_max_time"]
loudness_max = segments_item["loudness_max"]
segments_item_union = timbre + pitches + [loudness_start, loudness_max_time, loudness_max]
timbre_pitches_loudness.append(segments_item_union)
timbre_pitches_loudness_file_txt = open("timbre_pitches_loudness_file.txt", "a")
timbre_pitches_loudness_file_txt.write("\r\n" + wav_dir + "\r\n")
timbre_pitches_loudness_file_txt.write(str(timbre_pitches_loudness))
timbre_pitches_loudness_file_txt.close()
return timbre_pitches_loudness
print e
if not t:
try:
f = open(item.master.path)
md5 = md5_for_file(f)
log.debug("query by md5: %s" % md5)
t = track.track_from_md5(md5)
except EchoNestAPIError, e:
print e
if not t:
try:
log.debug("query by file: %s" % item.master.path)
f = open(item.master.path)
t = track.track_from_file(f, "mp3")
except EchoNestAPIError, e:
print e
if t:
item.echonest_id = t.id
t.get_analysis()
# print t
print t.id
print t.analysis_url
print
print "danceability: %s" % t.danceability
print "energy: %s" % t.energy
print "key: %s" % t.key
if not t:
try:
f = open(item.master.path)
md5 = md5_for_file(f);
log.debug('query by md5: %s' % md5)
t = track.track_from_md5(md5)
except EchoNestAPIError, e:
print e
if not t:
try:
log.debug('query by file: %s' % item.master.path)
f = open(item.master.path)
t = track.track_from_file(f, 'mp3')
except EchoNestAPIError, e:
print e
if t:
item.echonest_id = t.id
t.get_analysis()
#print t
print t.id
print t.analysis_url
print
print 'danceability: %s' % t.danceability
print 'energy: %s' % t.energy
def get_attr(fp, pathstring, db):
try:
track = track_from_file(fp, 'mp3')
except Exception:
return
# all initial values are set to None
beatsavg = None
beatsdev = None
barsavg = None
barsdev = None
sectionsavg = None
sectionsdev = None
sectionscount = None
segmentsavg = None
segmentsdev = None
tatumsavg = None
tatumsdev = None
tatumscount = None
thisartist = None
thisdanceability = None
thisduration = None
thisfadein = None
thisenergy = None
thiskey = None
thiskeyconfidence = None
thisliveness = None
thisloudness = None
thismode = None
thismodeconfidence = None
thisoffset = None
thisspeechiness = None
thisfadeout = None
thistempo = None
thistempoconfidence = None
thistimesig = None
thistimesigcon = None
thistitle = None
thisloudnessmaxaverage = None
thisloudnessmaxdeviation = None
thisloudnessmaxdifferential = None
thisloudnessmaxtimeaverage = None
thisloudnessmaxtimedeviation = None
thisloudnessmaxtimedifferential = None
thisloudnessstartaverage = None
thisloudnessstartdeviation = None
thisloudnessstartdifferential = None
thistimbreaverage = [None, None, None, None, None, None, None, None, None, None, None, None]
thistimbredev = [None, None, None, None, None, None, None, None, None, None, None, None]
thistimbrediff = [None, None, None, None, None, None, None, None, None, None, None, None]
thispitchaverage = [None, None, None, None, None, None, None, None, None, None, None, None]
thispitchdev = [None, None, None, None, None, None, None, None, None, None, None, None]
thispitchdiff = [None, None, None, None, None, None, None, None, None, None, None, None]
thispitchratioa = [None, None, None, None, None, None, None, None, None, None, None, None]
thispitchratiob = [None, None, None, None, None, None, None, None, None, None, None, None]
# features present in the track information are placed in the corresponding variable holders
## many of these call functions to process the data further
if hasattr(track, 'beats') and len(track.beats) > 0:
beatsavg = get_average(track.beats, 'duration')
beatsdev = get_deviation(track.beats, 'duration', beatsavg)
if hasattr(track, 'bars') and len(track.bars) > 0:
barsavg = get_average(track.bars, 'duration')
barsdev = get_deviation(track.bars, 'duration', barsavg)
if hasattr(track, 'sections') and len(track.sections) > 0:
sectionsavg = get_average(track.sections, 'duration')
sectionsdev = get_deviation(track.sections, 'duration', sectionsavg)
sectionscount = len(track.sections)
if hasattr(track, 'segments') and len(track.segments) > 0:
segmentsavg = get_average(track.segments, 'duration')
segmentsdev = get_deviation(track.segments, 'duration', segmentsavg)
if hasattr(track, 'tatums') and len(track.tatums) > 0:
tatumsavg = get_average(track.tatums, 'duration')
tatumsdev = get_deviation(track.tatums, 'duration', tatumsavg)
tatumscount = len(track.tatums)
if hasattr(track, 'artist'):
thisartist = str(track.artist)
if hasattr(track, 'danceability'):
thisdanceability = track.danceability
if hasattr(track, 'duration'):
thisduration = track.duration
if hasattr(track, 'end_of_fade_in'):
thisfadein = track.end_of_fade_in
if hasattr(track, 'energy'):
thisenergy = track.energy
if hasattr(track, 'key'):
thiskey = track.key
if hasattr(track, 'key_confidence'):
thiskeyconfidence = track.key_confidence
if hasattr(track, 'liveness'):
thisliveness = track.liveness
if hasattr(track, 'loudness'):
thisloudness = track.loudness
if hasattr(track, 'mode'):
thismode = track.mode
if hasattr(track, 'mode_confidence'):
thismodeconfidence = track.mode_confidence
if hasattr(track, 'offset_seconds'):
thisoffset = track.offset_seconds
if hasattr(track, 'speechiness'):
thisspeechiness = track.speechiness
if hasattr(track, 'start_of_fade_out'):
thisfadeout = track.start_of_fade_out
if hasattr(track, 'tempo'):
thistempo = track.tempo
if hasattr(track, 'tempo_confidence'):
thistempoconfidence = track.tempo_confidence
if hasattr(track, 'time_signature'):
thistimesig = track.time_signature
if hasattr(track, 'time_signature_confidence'):
thistimesigcon = track.time_signature_confidence
if hasattr(track, 'title'):
thistitle = str(track)
# segment data (individual notes) are extracted and processed into aggregate values for the track
if hasattr(track, 'segments') and len(track.segments) != 0:
loudness_maxarray = []
loudness_max_timearray = []
loudness_startarray = []
timbrearrays = [],[],[],[],[],[],[],[],[],[],[],[],[],[],[],[]
pitcharrays = [],[],[],[],[],[],[],[],[],[],[],[],[],[],[],[]
for k in track.segments:
loudness_maxarray.append(k['loudness_max'])
loudness_max_timearray.append(k['loudness_max_time'])
loudness_startarray.append(k['loudness_start'])
i = 0
while i < 12:
timbrearrays[i].append(k['timbre'][i])
i += 1
i = 0
while i < 12:
pitcharrays[i].append(k['pitches'][i])
i += 1
avg = get_aver(loudness_maxarray)
thisloudnessmaxaverage = avg
thisloudnessmaxdeviation = get_devi(loudness_maxarray, avg)
thisloudnessmaxdifferential = get_differential(loudness_maxarray)
avg = get_aver(loudness_max_timearray)
thisloudnessmaxtimeaverage = avg
thisloudnessmaxtimedeviation = get_devi(loudness_max_timearray, avg)
thisloudnessmaxtimedifferential = get_differential(loudness_max_timearray)
avg = get_aver(loudness_startarray)
thisloudnessstartaverage = avg
thisloudnessstartdeviation = get_devi(loudness_startarray, avg)
thisloudnessstartdifferential = get_differential(loudness_startarray)
i = 0
while i < 12:
avg = get_aver(timbrearrays[i])
thistimbreaverage[i] = avg
thistimbredev[i] = get_devi(timbrearrays[i], avg)
thistimbrediff[i] = get_differential(timbrearrays[i])
avg = get_aver(pitcharrays[i])
thispitchaverage[i] = avg
thispitchdev[i] = get_devi(pitcharrays[i], avg)
thispitchdiff[i] = get_differential(pitcharrays[i])
thispitchratioa[i] = get_ratio(pitcharrays[i], .5)
thispitchratiob[i] = get_ratio(pitcharrays[i], 1)
i += 1
# a dictionary is created with all the features present, which can then be read into a DB
song = { commonPath: pathstring,
commonTitle: thistitle,
commonArtist: thisartist,
songBeatAverage.name: beatsavg,
songBeatDeviation.name: beatsdev,
songBarsAverage.name: barsavg,
songBarsDeviation.name: barsdev,
songDanceability.name: thisdanceability,
songDuration.name: thisduration,
songEndOfFadeIn.name: thisfadein,
songEnergy.name: thisenergy,
songKey.name: thiskey,
songKeyConfidence.name: thiskeyconfidence,
songLiveness.name: thisliveness,
songLoudness.name: thisloudness,
songMode.name: thismode,
songModeConfidence.name: thismodeconfidence,
songOffsetSeconds.name: thisoffset,
songSectionsAverage.name: sectionsavg,
songSectionsDeviation.name: sectionsdev,
songSectionsCount.name: sectionscount,
songSpeechiness.name: thisspeechiness,
songStartOfFadeOut.name: thisfadeout,
songTatumsAverage.name: tatumsavg,
songTatumsDeviation.name: tatumsdev,
songTatumsCount.name: tatumscount,
songTempo.name: thistempo,
songTempoConfidence.name: thistempoconfidence,
songTimeSignature.name: thistimesig,
songTimeSignatureConfidence.name: thistimesigcon,
songLoudnessMaxAverage.name: thisloudnessmaxaverage,
songLoudnessMaxDeviation.name: thisloudnessmaxdeviation,
songLoudnessMaxDifferential.name: thisloudnessmaxdifferential,
songLoudnessMaxTimeAverage.name: thisloudnessmaxtimeaverage,
songLoudnessMaxTimeDeviation.name: thisloudnessmaxtimedeviation,
songLoudnessMaxTimeDifferential.name: thisloudnessmaxtimedifferential,
songLoudnessStartAverage.name: thisloudnessstartaverage,
songLoudnessStartDeviation.name: thisloudnessstartdeviation,
songLoudnessStartDifferential.name: thisloudnessstartdifferential,
songTimbre1Average.name: thistimbreaverage[0],
songTimbre1Dev.name: thistimbredev[0],
songTimbre1Diff.name: thistimbrediff[0],
songTimbre2Average.name: thistimbreaverage[1],
songTimbre2Dev.name: thistimbredev[1],
songTimbre2Diff.name: thistimbrediff[1],
songTimbre3Average.name: thistimbreaverage[2],
songTimbre3Dev.name: thistimbredev[2],
songTimbre3Diff.name: thistimbrediff[2],
songTimbre4Average.name: thistimbreaverage[3],
songTimbre4Dev.name: thistimbredev[3],
songTimbre4Diff.name: thistimbrediff[3],
songTimbre5Average.name: thistimbreaverage[4],
songTimbre5Dev.name: thistimbredev[4],
songTimbre5Diff.name: thistimbrediff[4],
songTimbre6Average.name: thistimbreaverage[5],
songTimbre6Dev.name: thistimbredev[5],
songTimbre6Diff.name: thistimbrediff[5],
songTimbre7Average.name: thistimbreaverage[6],
songTimbre7Dev.name: thistimbredev[6],
songTimbre7Diff.name: thistimbrediff[6],
songTimbre8Average.name: thistimbreaverage[7],
songTimbre8Dev.name: thistimbredev[7],
songTimbre8Diff.name: thistimbrediff[7],
songTimbre9Average.name: thistimbreaverage[8],
songTimbre9Dev.name: thistimbredev[8],
songTimbre9Diff.name: thistimbrediff[8],
songTimbre10Average.name: thistimbreaverage[9],
songTimbre10Dev.name: thistimbredev[9],
songTimbre10Diff.name: thistimbrediff[9],
songTimbre11Average.name: thistimbreaverage[10],
songTimbre11Dev.name: thistimbredev[10],
songTimbre11Diff.name: thistimbrediff[10],
songTimbre12Average.name: thistimbreaverage[11],
songTimbre12Dev.name: thistimbredev[11],
songTimbre12Diff.name: thistimbrediff[11],
songPitch1Average.name: thispitchaverage[0],
songPitch1Dev.name: thispitchdev[0],
songPitch1Diff.name: thispitchdiff[0],
songPitch2Average.name: thispitchaverage[1],
songPitch2Dev.name: thispitchdev[1],
songPitch2Diff.name: thispitchdiff[1],
songPitch3Average.name: thispitchaverage[2],
songPitch3Dev.name: thispitchdev[2],
songPitch3Diff.name: thispitchdiff[2],
songPitch4Average.name: thispitchaverage[3],
songPitch4Dev.name: thispitchdev[3],
songPitch4Diff.name: thispitchdiff[3],
songPitch5Average.name: thispitchaverage[4],
songPitch5Dev.name: thispitchdev[4],
songPitch5Diff.name: thispitchdiff[4],
songPitch6Average.name: thispitchaverage[5],
songPitch6Dev.name: thispitchdev[5],
songPitch6Diff.name: thispitchdiff[5],
songPitch7Average.name: thispitchaverage[6],
songPitch7Dev.name: thispitchdev[6],
songPitch7Diff.name: thispitchdiff[6],
songPitch8Average.name: thispitchaverage[7],
songPitch8Dev.name: thispitchdev[7],
songPitch8Diff.name: thispitchdiff[7],
songPitch9Average.name: thispitchaverage[8],
songPitch9Dev.name: thispitchdev[8],
songPitch9Diff.name: thispitchdiff[8],
songPitch10Average.name: thispitchaverage[9],
songPitch10Dev.name: thispitchdev[9],
songPitch10Diff.name: thispitchdiff[9],
songPitch11Average.name: thispitchaverage[10],
songPitch11Dev.name: thispitchdev[10],
songPitch11Diff.name: thispitchdiff[10],
songPitch12Average.name: thispitchaverage[11],
songPitch12Dev.name: thispitchdev[11],
songPitch12Diff.name: thispitchdiff[11],
songPitch1Ratioa.name: thispitchratioa[0],
songPitch2Ratioa.name: thispitchratioa[1],
songPitch3Ratioa.name: thispitchratioa[2],
songPitch4Ratioa.name: thispitchratioa[3],
songPitch5Ratioa.name: thispitchratioa[4],
songPitch6Ratioa.name: thispitchratioa[5],
songPitch7Ratioa.name: thispitchratioa[6],
songPitch8Ratioa.name: thispitchratioa[7],
songPitch9Ratioa.name: thispitchratioa[8],
songPitch10Ratioa.name: thispitchratioa[9],
songPitch11Ratioa.name: thispitchratioa[10],
songPitch12Ratioa.name: thispitchratioa[11],
songPitch1Ratiob.name: thispitchratiob[0],
songPitch2Ratiob.name: thispitchratiob[1],
songPitch3Ratiob.name: thispitchratiob[2],
songPitch4Ratiob.name: thispitchratiob[3],
songPitch5Ratiob.name: thispitchratiob[4],
songPitch6Ratiob.name: thispitchratiob[5],
songPitch7Ratiob.name: thispitchratiob[6],
songPitch8Ratiob.name: thispitchratiob[7],
songPitch9Ratiob.name: thispitchratiob[8],
songPitch10Ratiob.name: thispitchratiob[9],
songPitch11Ratiob.name: thispitchratiob[10],
songPitch12Ratiob.name: thispitchratiob[11]}
## calls a function to place these attributes in the DB
db.add_song(song)
def get_attr(fp, pathstring, db):
try:
track = track_from_file(fp, 'mp3')
except Exception:
return
# all initial values are set to None
beatsavg = None
beatsdev = None
barsavg = None
barsdev = None
sectionsavg = None
sectionsdev = None
sectionscount = None
segmentsavg = None
segmentsdev = None
tatumsavg = None
tatumsdev = None
tatumscount = None
thisartist = None
thisdanceability = None
thisduration = None
thisfadein = None
thisenergy = None
thiskey = None
thiskeyconfidence = None
thisliveness = None
thisloudness = None
thismode = None
thismodeconfidence = None
thisoffset = None
thisspeechiness = None
thisfadeout = None
thistempo = None
thistempoconfidence = None
thistimesig = None
thistimesigcon = None
thistitle = None
thisloudnessmaxaverage = None
thisloudnessmaxdeviation = None
thisloudnessmaxdifferential = None
thisloudnessmaxtimeaverage = None
thisloudnessmaxtimedeviation = None
thisloudnessmaxtimedifferential = None
thisloudnessstartaverage = None
thisloudnessstartdeviation = None
thisloudnessstartdifferential = None
thistimbreaverage = [
None, None, None, None, None, None, None, None, None, None, None, None
]
thistimbredev = [
None, None, None, None, None, None, None, None, None, None, None, None
]
thistimbrediff = [
None, None, None, None, None, None, None, None, None, None, None, None
]
thispitchaverage = [
None, None, None, None, None, None, None, None, None, None, None, None
]
thispitchdev = [
None, None, None, None, None, None, None, None, None, None, None, None
]
thispitchdiff = [
None, None, None, None, None, None, None, None, None, None, None, None
]
thispitchratioa = [
None, None, None, None, None, None, None, None, None, None, None, None
]
thispitchratiob = [
None, None, None, None, None, None, None, None, None, None, None, None
]
# features present in the track information are placed in the corresponding variable holders
## many of these call functions to process the data further
if hasattr(track, 'beats') and len(track.beats) > 0:
beatsavg = get_average(track.beats, 'duration')
beatsdev = get_deviation(track.beats, 'duration', beatsavg)
if hasattr(track, 'bars') and len(track.bars) > 0:
barsavg = get_average(track.bars, 'duration')
barsdev = get_deviation(track.bars, 'duration', barsavg)
if hasattr(track, 'sections') and len(track.sections) > 0:
sectionsavg = get_average(track.sections, 'duration')
sectionsdev = get_deviation(track.sections, 'duration', sectionsavg)
sectionscount = len(track.sections)
if hasattr(track, 'segments') and len(track.segments) > 0:
segmentsavg = get_average(track.segments, 'duration')
segmentsdev = get_deviation(track.segments, 'duration', segmentsavg)
if hasattr(track, 'tatums') and len(track.tatums) > 0:
tatumsavg = get_average(track.tatums, 'duration')
tatumsdev = get_deviation(track.tatums, 'duration', tatumsavg)
tatumscount = len(track.tatums)
if hasattr(track, 'artist'):
thisartist = str(track.artist)
if hasattr(track, 'danceability'):
thisdanceability = track.danceability
if hasattr(track, 'duration'):
thisduration = track.duration
if hasattr(track, 'end_of_fade_in'):
thisfadein = track.end_of_fade_in
if hasattr(track, 'energy'):
thisenergy = track.energy
if hasattr(track, 'key'):
thiskey = track.key
if hasattr(track, 'key_confidence'):
thiskeyconfidence = track.key_confidence
if hasattr(track, 'liveness'):
thisliveness = track.liveness
if hasattr(track, 'loudness'):
thisloudness = track.loudness
if hasattr(track, 'mode'):
thismode = track.mode
if hasattr(track, 'mode_confidence'):
thismodeconfidence = track.mode_confidence
if hasattr(track, 'offset_seconds'):
thisoffset = track.offset_seconds
if hasattr(track, 'speechiness'):
thisspeechiness = track.speechiness
if hasattr(track, 'start_of_fade_out'):
thisfadeout = track.start_of_fade_out
if hasattr(track, 'tempo'):
thistempo = track.tempo
if hasattr(track, 'tempo_confidence'):
thistempoconfidence = track.tempo_confidence
if hasattr(track, 'time_signature'):
thistimesig = track.time_signature
if hasattr(track, 'time_signature_confidence'):
thistimesigcon = track.time_signature_confidence
if hasattr(track, 'title'):
thistitle = str(track)
# segment data (individual notes) are extracted and processed into aggregate values for the track
if hasattr(track, 'segments') and len(track.segments) != 0:
loudness_maxarray = []
loudness_max_timearray = []
loudness_startarray = []
timbrearrays = [],[],[],[],[],[],[],[],[],[],[],[],[],[],[],[]
pitcharrays = [],[],[],[],[],[],[],[],[],[],[],[],[],[],[],[]
for k in track.segments:
loudness_maxarray.append(k['loudness_max'])
loudness_max_timearray.append(k['loudness_max_time'])
loudness_startarray.append(k['loudness_start'])
i = 0
while i < 12:
timbrearrays[i].append(k['timbre'][i])
i += 1
i = 0
while i < 12:
pitcharrays[i].append(k['pitches'][i])
i += 1
avg = get_aver(loudness_maxarray)
thisloudnessmaxaverage = avg
thisloudnessmaxdeviation = get_devi(loudness_maxarray, avg)
thisloudnessmaxdifferential = get_differential(loudness_maxarray)
avg = get_aver(loudness_max_timearray)
thisloudnessmaxtimeaverage = avg
thisloudnessmaxtimedeviation = get_devi(loudness_max_timearray, avg)
thisloudnessmaxtimedifferential = get_differential(
loudness_max_timearray)
avg = get_aver(loudness_startarray)
thisloudnessstartaverage = avg
thisloudnessstartdeviation = get_devi(loudness_startarray, avg)
thisloudnessstartdifferential = get_differential(loudness_startarray)
i = 0
while i < 12:
avg = get_aver(timbrearrays[i])
thistimbreaverage[i] = avg
thistimbredev[i] = get_devi(timbrearrays[i], avg)
thistimbrediff[i] = get_differential(timbrearrays[i])
avg = get_aver(pitcharrays[i])
thispitchaverage[i] = avg
thispitchdev[i] = get_devi(pitcharrays[i], avg)
thispitchdiff[i] = get_differential(pitcharrays[i])
thispitchratioa[i] = get_ratio(pitcharrays[i], .5)
thispitchratiob[i] = get_ratio(pitcharrays[i], 1)
i += 1
# a dictionary is created with all the features present, which can then be read into a DB
song = {
commonPath: pathstring,
commonTitle: thistitle,
commonArtist: thisartist,
songBeatAverage.name: beatsavg,
songBeatDeviation.name: beatsdev,
songBarsAverage.name: barsavg,
songBarsDeviation.name: barsdev,
songDanceability.name: thisdanceability,
songDuration.name: thisduration,
songEndOfFadeIn.name: thisfadein,
songEnergy.name: thisenergy,
songKey.name: thiskey,
songKeyConfidence.name: thiskeyconfidence,
songLiveness.name: thisliveness,
songLoudness.name: thisloudness,
songMode.name: thismode,
songModeConfidence.name: thismodeconfidence,
songOffsetSeconds.name: thisoffset,
songSectionsAverage.name: sectionsavg,
songSectionsDeviation.name: sectionsdev,
songSectionsCount.name: sectionscount,
songSpeechiness.name: thisspeechiness,
songStartOfFadeOut.name: thisfadeout,
songTatumsAverage.name: tatumsavg,
songTatumsDeviation.name: tatumsdev,
songTatumsCount.name: tatumscount,
songTempo.name: thistempo,
songTempoConfidence.name: thistempoconfidence,
songTimeSignature.name: thistimesig,
songTimeSignatureConfidence.name: thistimesigcon,
songLoudnessMaxAverage.name: thisloudnessmaxaverage,
songLoudnessMaxDeviation.name: thisloudnessmaxdeviation,
songLoudnessMaxDifferential.name: thisloudnessmaxdifferential,
songLoudnessMaxTimeAverage.name: thisloudnessmaxtimeaverage,
songLoudnessMaxTimeDeviation.name: thisloudnessmaxtimedeviation,
songLoudnessMaxTimeDifferential.name: thisloudnessmaxtimedifferential,
songLoudnessStartAverage.name: thisloudnessstartaverage,
songLoudnessStartDeviation.name: thisloudnessstartdeviation,
songLoudnessStartDifferential.name: thisloudnessstartdifferential,
songTimbre1Average.name: thistimbreaverage[0],
songTimbre1Dev.name: thistimbredev[0],
songTimbre1Diff.name: thistimbrediff[0],
songTimbre2Average.name: thistimbreaverage[1],
songTimbre2Dev.name: thistimbredev[1],
songTimbre2Diff.name: thistimbrediff[1],
songTimbre3Average.name: thistimbreaverage[2],
songTimbre3Dev.name: thistimbredev[2],
songTimbre3Diff.name: thistimbrediff[2],
songTimbre4Average.name: thistimbreaverage[3],
songTimbre4Dev.name: thistimbredev[3],
songTimbre4Diff.name: thistimbrediff[3],
songTimbre5Average.name: thistimbreaverage[4],
songTimbre5Dev.name: thistimbredev[4],
songTimbre5Diff.name: thistimbrediff[4],
songTimbre6Average.name: thistimbreaverage[5],
songTimbre6Dev.name: thistimbredev[5],
songTimbre6Diff.name: thistimbrediff[5],
songTimbre7Average.name: thistimbreaverage[6],
songTimbre7Dev.name: thistimbredev[6],
songTimbre7Diff.name: thistimbrediff[6],
songTimbre8Average.name: thistimbreaverage[7],
songTimbre8Dev.name: thistimbredev[7],
songTimbre8Diff.name: thistimbrediff[7],
songTimbre9Average.name: thistimbreaverage[8],
songTimbre9Dev.name: thistimbredev[8],
songTimbre9Diff.name: thistimbrediff[8],
songTimbre10Average.name: thistimbreaverage[9],
songTimbre10Dev.name: thistimbredev[9],
songTimbre10Diff.name: thistimbrediff[9],
songTimbre11Average.name: thistimbreaverage[10],
songTimbre11Dev.name: thistimbredev[10],
songTimbre11Diff.name: thistimbrediff[10],
songTimbre12Average.name: thistimbreaverage[11],
songTimbre12Dev.name: thistimbredev[11],
songTimbre12Diff.name: thistimbrediff[11],
songPitch1Average.name: thispitchaverage[0],
songPitch1Dev.name: thispitchdev[0],
songPitch1Diff.name: thispitchdiff[0],
songPitch2Average.name: thispitchaverage[1],
songPitch2Dev.name: thispitchdev[1],
songPitch2Diff.name: thispitchdiff[1],
songPitch3Average.name: thispitchaverage[2],
songPitch3Dev.name: thispitchdev[2],
songPitch3Diff.name: thispitchdiff[2],
songPitch4Average.name: thispitchaverage[3],
songPitch4Dev.name: thispitchdev[3],
songPitch4Diff.name: thispitchdiff[3],
songPitch5Average.name: thispitchaverage[4],
songPitch5Dev.name: thispitchdev[4],
songPitch5Diff.name: thispitchdiff[4],
songPitch6Average.name: thispitchaverage[5],
songPitch6Dev.name: thispitchdev[5],
songPitch6Diff.name: thispitchdiff[5],
songPitch7Average.name: thispitchaverage[6],
songPitch7Dev.name: thispitchdev[6],
songPitch7Diff.name: thispitchdiff[6],
songPitch8Average.name: thispitchaverage[7],
songPitch8Dev.name: thispitchdev[7],
songPitch8Diff.name: thispitchdiff[7],
songPitch9Average.name: thispitchaverage[8],
songPitch9Dev.name: thispitchdev[8],
songPitch9Diff.name: thispitchdiff[8],
songPitch10Average.name: thispitchaverage[9],
songPitch10Dev.name: thispitchdev[9],
songPitch10Diff.name: thispitchdiff[9],
songPitch11Average.name: thispitchaverage[10],
songPitch11Dev.name: thispitchdev[10],
songPitch11Diff.name: thispitchdiff[10],
songPitch12Average.name: thispitchaverage[11],
songPitch12Dev.name: thispitchdev[11],
songPitch12Diff.name: thispitchdiff[11],
songPitch1Ratioa.name: thispitchratioa[0],
songPitch2Ratioa.name: thispitchratioa[1],
songPitch3Ratioa.name: thispitchratioa[2],
songPitch4Ratioa.name: thispitchratioa[3],
songPitch5Ratioa.name: thispitchratioa[4],
songPitch6Ratioa.name: thispitchratioa[5],
songPitch7Ratioa.name: thispitchratioa[6],
songPitch8Ratioa.name: thispitchratioa[7],
songPitch9Ratioa.name: thispitchratioa[8],
songPitch10Ratioa.name: thispitchratioa[9],
songPitch11Ratioa.name: thispitchratioa[10],
songPitch12Ratioa.name: thispitchratioa[11],
songPitch1Ratiob.name: thispitchratiob[0],
songPitch2Ratiob.name: thispitchratiob[1],
songPitch3Ratiob.name: thispitchratiob[2],
songPitch4Ratiob.name: thispitchratiob[3],
songPitch5Ratiob.name: thispitchratiob[4],
songPitch6Ratiob.name: thispitchratiob[5],
songPitch7Ratiob.name: thispitchratiob[6],
songPitch8Ratiob.name: thispitchratiob[7],
songPitch9Ratiob.name: thispitchratiob[8],
songPitch10Ratiob.name: thispitchratiob[9],
songPitch11Ratiob.name: thispitchratiob[10],
songPitch12Ratiob.name: thispitchratiob[11]
}
## calls a function to place these attributes in the DB
db.add_song(song)
def run(self):
log.info('maintenance walker')
log.info('action: %s' % self.action)
if self.action == 'check_media':
from alibrary.models import Media
if self.id:
items = Media.objects.filter(id=self.id)
else:
items = Media.objects.filter()[0:self.limit]
for item in items:
delete = False
if not item.master:
log.info('no master for: %s' % item)
if self.delete_missing:
log.info('delete item: %s' % item)
delete = True
else:
log.debug('got master for: %s' % item)
log.debug('path: %s' % item.master.path)
#print item.master.path
if os.path.isfile(item.master.path):
size = b = os.path.getsize(item.master.path)
log.debug('filesize: %s' % size)
if size < 10:
log.debug('size too small or zero > delete: %s' % size)
else:
log.debug('file does not exist')
delete = True
if delete and self.delete_missing:
log.info('delete item: %s' % item)
item.delete()
if not delete:
item.status = 1
item.save()
if self.action == 'echonest_media':
from alibrary.models import Media
if self.id:
items = Media.objects.filter(id=self.id)
else:
items = Media.objects.filter(echonest_id=None)[0:self.limit]
for item in items:
log.info('analyze: %s' % item)
item.echonest_analyze()
if self.action == 'clean_playlists':
from alibrary.models import PlaylistItem
from alibrary.models import Media
items = PlaylistItem.objects.all()
for item in items:
log.info('clean: %s' % item.pk)
if not item.content_object:
log.info('no content object > delete: %s' % item.pk)
item.delete()
# m = Media.objects.get(pk=item.)
if self.action == 'self_check_playlists':
from alibrary.models.playlistmodels import self_check_playlists
# reset
# ps = Playlist.objects.all()
# ps.update(status=1)
self_check_playlists()
if self.action == 'degrade_playlists':
from alibrary.models.playlistmodels import Playlist
ps = Playlist.objects.filter(type='broadcast').exclude(status=1)
ps.update(type='playlist', status=1)
if self.action == 'map_tags':
from alibrary.models import Media
if self.id:
items = Media.objects.filter(id=self.id)
else:
items = Media.objects.filter()[0:self.limit]
for item in items:
if item.tags.count() < 1:
print item
print 'map release tags'
if item.release and item.release.tags.count() > 0:
item.tags = item.release.tags
item.save()
if self.action == 'echonest_media__':
from alibrary.models import Media
from pyechonest.util import EchoNestAPIError
from pyechonest import track
from pyechonest import config as echonest_config
echonest_config.ECHO_NEST_API_KEY=ECHONEST_API_KEY
if self.id:
items = Media.objects.filter(id=self.id)
else:
items = Media.objects.filter(status=0)[0:self.limit]
for item in items:
log.info('analyze: %s' % item)
#md5 = '96fa0180d225f14e9f8cbfffbf5eb81d'
t = None
if item.echonest_id:
try:
log.debug('query by echonest id: %s' % item.echonest_id)
t = track.track_from_id(item.echonest_id)
except EchoNestAPIError, e:
print e
if not t:
try:
f = open(item.master.path)
md5 = md5_for_file(f);
log.debug('query by md5: %s' % md5)
t = track.track_from_md5(md5)
except EchoNestAPIError, e:
print e
if not t:
try:
log.debug('query by file: %s' % item.master.path)
f = open(item.master.path)
t = track.track_from_file(f, 'mp3')
except EchoNestAPIError, e:
print e
from pyechonest import artist
from pyechonest import track
midifilename = sys.argv[1]
audiofilename = sys.argv[2]
try:
config.ECHO_NEST_API_KEY = sys.argv[3]
except:
config.ECHO_NEST_API_KEY = raw_input('Enter your Echo Nest API key: ')
midifile=midi.read_midifile(midifilename)
audiofile=file(audiofilename)
echoTrack = track.track_from_file(audiofile,audiofilename[-3:])
audioSegments = echoTrack.segments
audioSegments = sorted(audioSegments,key=lambda x:x['start'])
events = reduce(lambda x,y :x+y,midifile)
events = sorted(events,key=lambda x: x.msdelay)
t = 0
audioSegments_ix = 0
events_ix=0
while True:
try:
except OSError, e:
print e
sys.exit()
print "Recursively gathering all filenames..."
file_list = get_file_list(dir_list, dir_name)
for filename in file_list:
print "Opening file:", filename
dir_path, file_name = os.path.split(filename)
if len(file_name) <= 8:
ext = filename.split('.')[-1]
f = open(filename)
print "Getting track from Echo Nest..."
try:
music = track.track_from_file(f, ext)
except socket.error, e:
print 'Socket Error:', e
print 'Sleeping...'
time.sleep(60)
print 'Continuing...'
continue
except echo_util.EchoNestAPIError, e:
print 'API Error:', e
print 'Sleeping...'
time.sleep(60)
print 'Continuing...'
continue
if hasattr(music, 'title'):
new_title = music.title.replace(' ', '')
new_filename = '%s/%s.%s' % (dir_path, new_title, ext)
import pyechonest
from pyechonest import config
from pyechonest.track import track_from_file
import pickle
import numpy as np
import pylab as pl
import os
api_key = "DMSARFFYEZKLFL9LE"
config.ECHO_NEST_API_KEY = api_key
fpath = "02-Heir-Apparent.mp3"
if not os.path.exists("track.p"):
with open(fpath, 'rb') as fin:
track = track_from_file(fin, 'mp3')
pickle.dump(track, open('track.p', 'wb'))
else:
track = pickle.load(open('track.p', 'rb'))
t = [seg['start'] for seg in track.segments]
loud = [seg['loudness_max'] for seg in track.segments]
pl.plot(t, loud)
#pl.xticks(t,np.arange(len(t)))
pl.xlabel("Time Segment")
pl.ylabel("Loudness")
pl.show()
def get_beats(filename):
audio_file = open(filename)
track_analysis = track.track_from_file(audio_file, 'mp3')
return track_analysis
import pyechonest
from pyechonest import config
from pyechonest.track import track_from_file
import pickle
import numpy as np
import pylab as pl
import os
api_key = "DMSARFFYEZKLFL9LE"
config.ECHO_NEST_API_KEY = api_key
fpath = "02-Heir-Apparent.mp3"
if not os.path.exists("track.p") :
with open(fpath,'rb') as fin :
track = track_from_file(fin,'mp3')
pickle.dump(track,open('track.p','wb'))
else :
track = pickle.load(open('track.p','rb'))
t = [seg['start'] for seg in track.segments]
loud = [seg['loudness_max'] for seg in track.segments]
pl.plot(t,loud)
#pl.xticks(t,np.arange(len(t)))
pl.xlabel("Time Segment")
pl.ylabel("Loudness")
pl.show()
config.ECHO_NEST_API_KEY="5TSYCVEZEIQ9R3HEO"
#os.environ['ECHONEST_API_KEY'] = config.ECHO_NEST_API_KEY
# the goal is to get the feature information for the learn subbase of rwc audio samples
input_dir = '/home/manu/workspace/databases/genres/jazz/'
output_dir = '/home/manu/workspace/databases/genres/jazz/hdf5/'
# Single file is working, now loop on all files from the learning directory17
#from pyechonest import track
for audiofile in features.get_filepaths(input_dir, ext='.au'):
print "Starting work on ", audiofile
output = output_dir + os.path.splitext(os.path.split(audiofile)[-1])[0] + '.h5'
if os.path.exists(output):
continue
file_object = open(audiofile)
curtrack = track.track_from_file(file_object, 'au', force_upload=True)
#
HDF5.create_song_file(output,force=False)
h5 = HDF5.open_h5_file_append(output)
# HACK we need to fill missing values
curtrack.__setattr__('foreign_id','')
curtrack.__setattr__('foreign_release_id','')
curtrack.__setattr__('audio_md5','')
HDF5.fill_hdf5_from_track(h5,curtrack)
h5.close()
del h5
# first testing on a single song
#audiofile = input_dir + 'rwc-g-m01_1.wav'
#output = output_dir + 'rwc-g-m01_1.h5'
