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source: python/aubio/task/beat.py @ e83c895

feature/autosinkfeature/cnnfeature/cnn_orgfeature/constantqfeature/crepefeature/crepe_orgfeature/pitchshiftfeature/pydocstringsfeature/timestretchfix/ffmpeg5pitchshiftsamplertimestretchyinfft+

Last change on this file since e83c895 was 9bec8fe, checked in by Paul Brossier <piem@altern.org>, 19 years ago
first draft for beat evaluation first draft for beat evaluation
Property mode set to `100644`
File size: 6.8 KB

Rev	Line
[13c3fba]	1	from aubio.aubioclass import *
	2	from onset import taskonset
	3
	4	class taskbeat(taskonset):
	5	def __init__(self,input,params=None,output=None):
	6	""" open the input file and initialize arguments
	7	parameters should be set before calling this method.
	8	"""
	9	taskonset.__init__(self,input,output=None,params=params)
	10	self.btwinlen = 512**2/self.params.hopsize
	11	self.btstep = self.btwinlen/4
	12	self.btoutput = fvec(self.btstep,self.channels)
	13	self.dfframe = fvec(self.btwinlen,self.channels)
	14	self.bt = beattracking(self.btwinlen,self.channels)
	15	self.pos2 = 0
[9bec8fe]	16	self.old = -1000
[13c3fba]	17
	18	def __call__(self):
	19	taskonset.__call__(self)
	20	# write to current file
	21	if self.pos2 == self.btstep - 1 :
	22	self.bt.do(self.dfframe,self.btoutput)
	23	for i in range (self.btwinlen - self.btstep):
	24	self.dfframe.set(self.dfframe.get(i+self.btstep,0),i,0)
	25	for i in range(self.btwinlen - self.btstep, self.btwinlen):
	26	self.dfframe.set(0,i,0)
	27	self.pos2 = -1;
	28	self.pos2 += 1
	29	val = self.opick.pp.getval()
	30	self.dfframe.set(val,self.btwinlen - self.btstep + self.pos2,0)
	31	i=0
	32	for i in range(1,int( self.btoutput.get(0,0) ) ):
	33	if self.pos2 == self.btoutput.get(i,0) and \
	34	aubio_silence_detection(self.myvec(),
	35	self.params.silence)!=1:
[9bec8fe]	36	now = self.frameread-0
	37	period = (60 * self.params.samplerate) / ((now - self.old) * self.params.hopsize)
	38	self.old = now
	39	return now*self.params.step,period
[13c3fba]	40
[9bec8fe]	41	def eval(self,results,tol=0.20,tolcontext=0.25):
	42	obeats = self.gettruth()
	43	etime = [result[0] for result in results]
	44	otime = [obeat[0] for obeat in obeats]
	45	CML_tot, CML_max, CML_start, CML_end = 0,0,0,0
	46	AML_tot, AML_max, AML_start, AML_end = 0,0,0,0
	47	AMLd_tot, AMLd_max, AMLd_start, AMLd_end = 0,0,0,0
	48	AMLh_tot, AMLh_max, AMLh_start, AMLh_end = 0,0,0,0
	49	AMLo_tot, AMLo_max, AMLo_start, AMLo_end = 0,0,0,0
	50	# results iteration
	51	j = 1
	52	# for each annotation
	53	for i in range(2,len(otime)-2):
	54	if j+1 >= len(etime): break
	55	count = 0
	56	# look for next matching beat
	57	while otime[i] > etime[j] - (otime[i] - otime[i+1])*tol:
	58	if count > 0:
	59	#print "spurious etime"
	60	if CML_end - CML_start > CML_max:
	61	CML_max = CML_end - CML_start
	62	CML_start, CML_end = j, j
	63	if AMLh_end - AMLh_start > AMLh_max:
	64	AMLh_max = AMLh_end - AMLh_start
	65	AMLh_start, AMLh_end = j, j
	66	if AMLd_end - AMLd_start > AMLd_max:
	67	AMLd_max = AMLd_end - AMLd_start
	68	AMLd_start, AMLd_end = j, j
	69	if AMLo_end - AMLo_start > AMLo_max:
	70	AMLo_max = AMLo_end - AMLo_start
	71	AMLo_start, AMLo_end = j, j
	72	j += 1
	73	count += 1
	74	if j+1 >= len(etime): break
	75	#print otime[i-1],etime[j-1]," ",otime[i],etime[j]," ",otime[i+1],etime[j+1]
	76	prevtempo = (otime[i] - otime[i-1])
	77	nexttempo = (otime[i+1] - otime[i])
[13c3fba]	78
[9bec8fe]	79	current0 = (etime[j] > otime[i] - prevtempo*tol)
	80	current1 = (etime[j] < otime[i] + prevtempo*tol)
	81
	82	# check correct tempo
	83	prev0 = (etime[j-1] > otime[i-1] - prevtempo*tolcontext)
	84	prev1 = (etime[j-1] < otime[i-1] + prevtempo*tolcontext)
	85	next0 = (etime[j+1] > otime[i+1] - nexttempo*tolcontext)
	86	next1 = (etime[j+1] < otime[i+1] + nexttempo*tolcontext)
	87
	88	# check for off beat
	89	prevoffb0 = (etime[j-1] > otime[i-1] - prevtempo/2 - prevtempo*tolcontext)
	90	prevoffb1 = (etime[j-1] < otime[i-1] - prevtempo/2 + prevtempo*tolcontext)
	91	nextoffb0 = (etime[j+1] > otime[i+1] - nexttempo/2 - nexttempo*tolcontext)
	92	nextoffb1 = (etime[j+1] < otime[i+1] - nexttempo/2 + nexttempo*tolcontext)
	93
	94	# check half tempo
	95	prevhalf0 = (etime[j-1] > otime[i-1] + prevtempo - prevtempo/2*tolcontext)
	96	prevhalf1 = (etime[j-1] < otime[i-1] + prevtempo + prevtempo/2*tolcontext)
	97	nexthalf0 = (etime[j+1] > otime[i+1] - nexttempo - nexttempo/2*tolcontext)
	98	nexthalf1 = (etime[j+1] < otime[i+1] - nexttempo + nexttempo/2*tolcontext)
	99
	100	# check double tempo
	101	prevdoub0 = (etime[j-1] > otime[i-1] - prevtempo - prevtempo2tolcontext)
	102	prevdoub1 = (etime[j-1] < otime[i-1] - prevtempo + prevtempo2tolcontext)
	103	nextdoub0 = (etime[j+1] > otime[i+1] + nexttempo - nexttempo2tolcontext)
	104	nextdoub1 = (etime[j+1] < otime[i+1] + nexttempo + nexttempo2tolcontext)
	105
	106	if current0 and current1 and prev0 and prev1 and next0 and next1:
	107	#print "YES!"
	108	CML_end = j
	109	CML_tot += 1
	110	else:
	111	if CML_end - CML_start > CML_max:
	112	CML_max = CML_end - CML_start
	113	CML_start, CML_end = j, j
	114	if current0 and current1 and prevhalf0 and prevhalf1 and nexthalf0 and nexthalf1:
	115	AMLh_end = j
	116	AMLh_tot += 1
	117	else:
	118	if AMLh_end - AMLh_start > AMLh_max:
	119	AMLh_max = AMLh_end - AMLh_start
	120	AMLh_start, AMLh_end = j, j
	121	if current0 and current1 and prevdoub0 and prevdoub1 and nextdoub0 and nextdoub1:
	122	AMLd_end = j
	123	AMLd_tot += 1
	124	else:
	125	if AMLd_end - AMLd_start > AMLd_max:
	126	AMLd_max = AMLd_end - AMLd_start
	127	AMLd_start, AMLd_end = j, j
	128	if current0 and current1 and prevoffb0 and prevoffb1 and nextoffb0 and nextoffb1:
	129	AMLo_end = j
	130	AMLo_tot += 1
	131	else:
	132	if AMLo_end - AMLo_start > AMLo_max:
	133	AMLo_max = AMLo_end - AMLo_start
	134	AMLo_start, AMLo_end = j, j
	135	# look for next matching beat
	136	count = 0
	137	while otime[i] > etime[j] - (otime[i] - otime[i+1])*tolcontext:
	138	j += 1
	139	if count > 0:
	140	#print "spurious etime"
	141	start = j
	142	count += 1
	143	total = float(len(otime))
	144	CML_tot /= total
	145	AMLh_tot /= total
	146	AMLd_tot /= total
	147	AMLo_tot /= total
	148	CML_cont = CML_max/total
	149	AMLh_cont = AMLh_max/total
	150	AMLd_cont = AMLd_max/total
	151	AMLo_cont = AMLo_max/total
	152	return CML_cont, CML_tot, AMLh_cont, AMLh_tot, AMLd_cont, AMLd_tot, AMLo_cont, AMLo_tot
	153
	154	# for i in allfreq:
	155	# freq.append(float(i) / 2. / N * samplerate )
	156	# while freq[i]>freqs[j]:
	157	# j += 1
	158	# a0 = weight[j-1]
	159	# a1 = weight[j]
	160	# f0 = freqs[j-1]
	161	# f1 = freqs[j]
	162	# if f0!=0:
	163	# iweight.append((a1-a0)/(f1-f0)*freq[i] + (a0 - (a1 - a0)/(f1/f0 -1.)))
	164	# else:
	165	# iweight.append((a1-a0)/(f1-f0)*freq[i] + a0)
	166	# while freq[i]>freqs[j]:
	167	# j += 1
	168
	169
	170	def gettruth(self):
	171	import os.path
	172	from aubio.txtfile import read_datafile
	173	datafile = self.input.replace('.wav','.txt')
	174	if not os.path.isfile(datafile):
	175	print "no ground truth "
	176	return False,False
	177	else:
	178	values = read_datafile(datafile,depth=0)
	179	old = -1000
	180	for i in range(len(values)):
	181	now = values[i]
	182	period = 60 / (now - old)
	183	old = now
	184	values[i] = [now,period]
	185	return values
	186
	187
	188	def plot(self,oplots,results):
	189	import Gnuplot
	190	oplots.append(Gnuplot.Data(results,with='linespoints',title="auto"))
	191
	192	def plotplot(self,oplots,outplot=None):
	193	import Gnuplot
	194	from aubio.gnuplot import gnuplot_init, audio_to_array, make_audio_plot
	195	import re
	196	# audio data
	197	#time,data = audio_to_array(self.input)
	198	#f = make_audio_plot(time,data)
	199
	200	g = gnuplot_init(outplot)
	201	oplots = [Gnuplot.Data(self.gettruth(),with='linespoints',title="orig")] + oplots
	202	g.plot(*oplots)

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