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| 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 | ||
| 16 | |||
| 17 | def __call__(self): | ||
| 18 | taskonset.__call__(self) | ||
| 19 | # write to current file | ||
| 20 | if self.pos2 == self.btstep - 1 : | ||
| 21 | self.bt.do(self.dfframe,self.btoutput) | ||
| 22 | for i in range (self.btwinlen - self.btstep): | ||
| 23 | self.dfframe.set(self.dfframe.get(i+self.btstep,0),i,0) | ||
| 24 | for i in range(self.btwinlen - self.btstep, self.btwinlen): | ||
| 25 | self.dfframe.set(0,i,0) | ||
| 26 | self.pos2 = -1; | ||
| 27 | self.pos2 += 1 | ||
| 28 | val = self.opick.pp.getval() | ||
| 29 | self.dfframe.set(val,self.btwinlen - self.btstep + self.pos2,0) | ||
| 30 | i=0 | ||
| 31 | for i in range(1,int( self.btoutput.get(0,0) ) ): | ||
| 32 | if self.pos2 == self.btoutput.get(i,0) and \ | ||
| 33 | aubio_silence_detection(self.myvec(), | ||
| 34 | self.params.silence)!=1: | ||
| 35 | return self.frameread, 0 | ||
| 36 | |||
| 37 | def eval(self,results): | ||
| 38 | pass | ||
| 39 | |||
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| 1 | from task import task | ||
| 2 | from aubio.aubioclass import * | ||
| 3 | |||
| 4 | class taskcut(task): | ||
| 5 | def __init__(self,input,slicetimes,params=None,output=None): | ||
| 6 | """ open the input file and initialize arguments | ||
| 7 | parameters should be set *before* calling this method. | ||
| 8 | """ | ||
| 9 | task.__init__(self,input,output=None,params=params) | ||
| 10 | self.newname = "%s%s%09.5f%s%s" % (self.input.split(".")[0].split("/")[-1],".", | ||
| 11 | self.frameread*self.params.step,".",self.input.split(".")[-1]) | ||
| 12 | self.fileo = sndfile(self.newname,model=self.filei) | ||
| 13 | self.myvec = fvec(self.params.hopsize,self.channels) | ||
| 14 | self.mycopy = fvec(self.params.hopsize,self.channels) | ||
| 15 | self.slicetimes = slicetimes | ||
| 16 | |||
| 17 | def __call__(self): | ||
| 18 | task.__call__(self) | ||
| 19 | # write to current file | ||
| 20 | if len(self.slicetimes) and self.frameread >= self.slicetimes[0][0]: | ||
| 21 | self.slicetimes.pop(0) | ||
| 22 | # write up to 1st zero crossing | ||
| 23 | zerocross = 0 | ||
| 24 | while ( abs( self.myvec.get(zerocross,0) ) > self.params.zerothres ): | ||
| 25 | zerocross += 1 | ||
| 26 | writesize = self.fileo.write(zerocross,self.myvec) | ||
| 27 | fromcross = 0 | ||
| 28 | while (zerocross < self.readsize): | ||
| 29 | for i in range(self.channels): | ||
| 30 | self.mycopy.set(self.myvec.get(zerocross,i),fromcross,i) | ||
| 31 | fromcross += 1 | ||
| 32 | zerocross += 1 | ||
| 33 | del self.fileo | ||
| 34 | self.fileo = sndfile("%s%s%09.5f%s%s" % | ||
| 35 | (self.input.split(".")[0].split("/")[-1],".", | ||
| 36 | self.frameread*self.params.step,".",self.input.split(".")[-1]),model=self.filei) | ||
| 37 | writesize = self.fileo.write(fromcross,self.mycopy) | ||
| 38 | else: | ||
| 39 | writesize = self.fileo.write(self.readsize,self.myvec) | ||
| 40 | |||
| 41 | |||
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| 1 | from aubio.task.task import task | ||
| 2 | from aubio.task.utils import * | ||
| 3 | from aubio.aubioclass import * | ||
| 4 | |||
| 5 | class taskonset(task): | ||
| 6 | def __init__(self,input,output=None,params=None): | ||
| 7 | """ open the input file and initialize arguments | ||
| 8 | parameters should be set *before* calling this method. | ||
| 9 | """ | ||
| 10 | task.__init__(self,input,params=params) | ||
| 11 | self.opick = onsetpick(self.params.bufsize, | ||
| 12 | self.params.hopsize, | ||
| 13 | self.channels, | ||
| 14 | self.myvec, | ||
| 15 | self.params.threshold, | ||
| 16 | mode=get_onset_mode(self.params.onsetmode), | ||
| 17 | dcthreshold=self.params.dcthreshold, | ||
| 18 | derivate=self.params.derivate) | ||
| 19 | self.olist = [] | ||
| 20 | self.ofunc = [] | ||
| 21 | self.maxofunc = 0 | ||
| 22 | self.last = 0 | ||
| 23 | if self.params.localmin: | ||
| 24 | self.ovalist = [0., 0., 0., 0., 0.] | ||
| 25 | |||
| 26 | def __call__(self): | ||
| 27 | task.__call__(self) | ||
| 28 | isonset,val = self.opick.do(self.myvec) | ||
| 29 | if (aubio_silence_detection(self.myvec(),self.params.silence)): | ||
| 30 | isonset=0 | ||
| 31 | if self.params.storefunc: | ||
| 32 | self.ofunc.append(val) | ||
| 33 | if self.params.localmin: | ||
| 34 | if val > 0: self.ovalist.append(val) | ||
| 35 | else: self.ovalist.append(0) | ||
| 36 | self.ovalist.pop(0) | ||
| 37 | if (isonset == 1): | ||
| 38 | if self.params.localmin: | ||
| 39 | # find local minima before peak | ||
| 40 | i=len(self.ovalist)-1 | ||
| 41 | while self.ovalist[i-1] < self.ovalist[i] and i > 0: | ||
| 42 | i -= 1 | ||
| 43 | now = (self.frameread+1-i) | ||
| 44 | else: | ||
| 45 | now = self.frameread | ||
| 46 | # take back delay | ||
| 47 | if self.params.delay != 0.: now -= self.params.delay | ||
| 48 | if now < 0 : | ||
| 49 | now = 0 | ||
| 50 | if self.params.mintol: | ||
| 51 | # prune doubled | ||
| 52 | if (now - self.last) > self.params.mintol: | ||
| 53 | self.last = now | ||
| 54 | return now, val | ||
| 55 | else: | ||
| 56 | return now, val | ||
| 57 | |||
| 58 | |||
| 59 | def fprint(self,foo): | ||
| 60 | print self.params.step*foo[0] | ||
| 61 | |||
| 62 | def eval(self,inputdata,ftru,mode='roc',vmode=''): | ||
| 63 | from txtfile import read_datafile | ||
| 64 | from onsetcompare import onset_roc, onset_diffs, onset_rocloc | ||
| 65 | ltru = read_datafile(ftru,depth=0) | ||
| 66 | lres = [] | ||
| 67 | for i in range(len(inputdata)): lres.append(inputdata[i][0]*self.params.step) | ||
| 68 | if vmode=='verbose': | ||
| 69 | print "Running with mode %s" % self.params.onsetmode, | ||
| 70 | print " and threshold %f" % self.params.threshold, | ||
| 71 | print " on file", self.input | ||
| 72 | #print ltru; print lres | ||
| 73 | if mode == 'local': | ||
| 74 | l = onset_diffs(ltru,lres,self.params.tol) | ||
| 75 | mean = 0 | ||
| 76 | for i in l: mean += i | ||
| 77 | if len(l): mean = "%.3f" % (mean/len(l)) | ||
| 78 | else: mean = "?0" | ||
| 79 | return l, mean | ||
| 80 | elif mode == 'roc': | ||
| 81 | self.orig, self.missed, self.merged, \ | ||
| 82 | self.expc, self.bad, self.doubled = \ | ||
| 83 | onset_roc(ltru,lres,self.params.tol) | ||
| 84 | elif mode == 'rocloc': | ||
| 85 | self.v = {} | ||
| 86 | self.v['orig'], self.v['missed'], self.v['Tm'], \ | ||
| 87 | self.v['expc'], self.v['bad'], self.v['Td'], \ | ||
| 88 | self.v['l'], self.v['labs'] = \ | ||
| 89 | onset_rocloc(ltru,lres,self.params.tol) | ||
| 90 | |||
| 91 | def plot(self,onsets,ofunc,wplot,oplots,nplot=False): | ||
| 92 | import Gnuplot, Gnuplot.funcutils | ||
| 93 | import aubio.txtfile | ||
| 94 | import os.path | ||
| 95 | import numarray | ||
| 96 | from aubio.onsetcompare import onset_roc | ||
| 97 | |||
| 98 | x1,y1,y1p = [],[],[] | ||
| 99 | oplot = [] | ||
| 100 | if self.params.onsetmode in ('mkl','kl'): ofunc[0:10] = [0] * 10 | ||
| 101 | |||
| 102 | self.lenofunc = len(ofunc) | ||
| 103 | self.maxofunc = max(ofunc) | ||
| 104 | # onset detection function | ||
| 105 | downtime = numarray.arange(len(ofunc))*self.params.step | ||
| 106 | oplot.append(Gnuplot.Data(downtime,ofunc,with='lines',title=self.params.onsetmode)) | ||
| 107 | |||
| 108 | # detected onsets | ||
| 109 | if not nplot: | ||
| 110 | for i in onsets: | ||
| 111 | x1.append(i[0]*self.params.step) | ||
| 112 | y1.append(self.maxofunc) | ||
| 113 | y1p.append(-self.maxofunc) | ||
| 114 | #x1 = numarray.array(onsets)*self.params.step | ||
| 115 | #y1 = self.maxofunc*numarray.ones(len(onsets)) | ||
| 116 | if x1: | ||
| 117 | oplot.append(Gnuplot.Data(x1,y1,with='impulses')) | ||
| 118 | wplot.append(Gnuplot.Data(x1,y1p,with='impulses')) | ||
| 119 | |||
| 120 | oplots.append(oplot) | ||
| 121 | |||
| 122 | # check if ground truth datafile exists | ||
| 123 | datafile = self.input.replace('.wav','.txt') | ||
| 124 | if datafile == self.input: datafile = "" | ||
| 125 | if not os.path.isfile(datafile): | ||
| 126 | self.title = "" #"(no ground truth)" | ||
| 127 | else: | ||
| 128 | t_onsets = aubio.txtfile.read_datafile(datafile) | ||
| 129 | x2 = numarray.array(t_onsets).resize(len(t_onsets)) | ||
| 130 | y2 = self.maxofunc*numarray.ones(len(t_onsets)) | ||
| 131 | wplot.append(Gnuplot.Data(x2,y2,with='impulses')) | ||
| 132 | |||
| 133 | tol = 0.050 | ||
| 134 | |||
| 135 | orig, missed, merged, expc, bad, doubled = \ | ||
| 136 | onset_roc(x2,x1,tol) | ||
| 137 | self.title = "GD %2.3f%% FP %2.3f%%" % \ | ||
| 138 | ((100*float(orig-missed-merged)/(orig)), | ||
| 139 | (100*float(bad+doubled)/(orig))) | ||
| 140 | |||
| 141 | |||
| 142 | def plotplot(self,wplot,oplots,outplot=None): | ||
| 143 | from aubio.gnuplot import gnuplot_init, audio_to_array, make_audio_plot | ||
| 144 | import re | ||
| 145 | # audio data | ||
| 146 | time,data = audio_to_array(self.input) | ||
| 147 | wplot = [make_audio_plot(time,data)] + wplot | ||
| 148 | self.title = self.input | ||
| 149 | # prepare the plot | ||
| 150 | g = gnuplot_init(outplot) | ||
| 151 | |||
| 152 | g('set multiplot') | ||
| 153 | |||
| 154 | # hack to align left axis | ||
| 155 | g('set lmargin 6') | ||
| 156 | g('set tmargin 0') | ||
| 157 | g('set format x ""') | ||
| 158 | g('set format y ""') | ||
| 159 | g('set noytics') | ||
| 160 | |||
| 161 | for i in range(len(oplots)): | ||
| 162 | # plot onset detection functions | ||
| 163 | g('set size 1,%f' % (0.7/(len(oplots)))) | ||
| 164 | g('set origin 0,%f' % (float(i)*0.7/(len(oplots)))) | ||
| 165 | g('set xrange [0:%f]' % (self.lenofunc*self.params.step)) | ||
| 166 | g.plot(*oplots[i]) | ||
| 167 | |||
| 168 | g('set tmargin 3.0') | ||
| 169 | g('set xlabel "time (s)" 1,0') | ||
| 170 | g('set format x "%1.1f"') | ||
| 171 | |||
| 172 | g('set title \'%s %s\'' % (re.sub('.*/','',self.input),self.title)) | ||
| 173 | |||
| 174 | # plot waveform and onsets | ||
| 175 | g('set size 1,0.3') | ||
| 176 | g('set origin 0,0.7') | ||
| 177 | g('set xrange [0:%f]' % max(time)) | ||
| 178 | g('set yrange [-1:1]') | ||
| 179 | g.ylabel('amplitude') | ||
| 180 | g.plot(*wplot) | ||
| 181 | |||
| 182 | g('unset multiplot') | ||
| 183 | |||
| 184 | |||
| @@ -0,0 +1,26 @@ | |||
| 1 | from aubio.aubioclass import aubio_pitchm_freq | ||
| 2 | |||
| 3 | class taskparams(object): | ||
| 4 | """ default parameters for task classes """ | ||
| 5 | def __init__(self,input=None,output=None): | ||
| 6 | self.silence = -70 | ||
| 7 | self.derivate = False | ||
| 8 | self.localmin = False | ||
| 9 | self.delay = 4. | ||
| 10 | self.storefunc = False | ||
| 11 | self.bufsize = 512 | ||
| 12 | self.hopsize = 256 | ||
| 13 | self.samplerate = 44100 | ||
| 14 | self.tol = 0.05 | ||
| 15 | self.mintol = 0.0 | ||
| 16 | self.step = float(self.hopsize)/float(self.samplerate) | ||
| 17 | self.threshold = 0.1 | ||
| 18 | self.onsetmode = 'dual' | ||
| 19 | self.pitchmode = 'yin' | ||
| 20 | self.pitchsmooth = 7 | ||
| 21 | self.pitchmin=100. | ||
| 22 | self.pitchmax=1000. | ||
| 23 | self.dcthreshold = -1. | ||
| 24 | self.omode = aubio_pitchm_freq | ||
| 25 | self.verbose = False | ||
| 26 | |||
| @@ -0,0 +1,175 @@ | |||
| 1 | from aubio.task.task import task | ||
| 2 | from aubio.task.silence import tasksilence | ||
| 3 | from aubio.task.utils import * | ||
| 4 | from aubio.aubioclass import * | ||
| 5 | |||
| 6 | class taskpitch(task): | ||
| 7 | def __init__(self,input,params=None): | ||
| 8 | task.__init__(self,input,params=params) | ||
| 9 | self.shortlist = [0. for i in range(self.params.pitchsmooth)] | ||
| 10 | self.pitchdet = pitchdetection(mode=get_pitch_mode(self.params.pitchmode), | ||
| 11 | bufsize=self.params.bufsize, | ||
| 12 | hopsize=self.params.hopsize, | ||
| 13 | channels=self.channels, | ||
| 14 | samplerate=self.srate, | ||
| 15 | omode=self.params.omode) | ||
| 16 | |||
| 17 | def __call__(self): | ||
| 18 | from aubio.median import short_find | ||
| 19 | task.__call__(self) | ||
| 20 | if (aubio_silence_detection(self.myvec(),self.params.silence)==1): | ||
| 21 | freq = -1. | ||
| 22 | else: | ||
| 23 | freq = self.pitchdet(self.myvec) | ||
| 24 | minpitch = self.params.pitchmin | ||
| 25 | maxpitch = self.params.pitchmax | ||
| 26 | if maxpitch and freq > maxpitch : | ||
| 27 | freq = -1. | ||
| 28 | elif minpitch and freq < minpitch : | ||
| 29 | freq = -1. | ||
| 30 | if self.params.pitchsmooth: | ||
| 31 | self.shortlist.append(freq) | ||
| 32 | self.shortlist.pop(0) | ||
| 33 | smoothfreq = short_find(self.shortlist, | ||
| 34 | len(self.shortlist)/2) | ||
| 35 | return smoothfreq | ||
| 36 | else: | ||
| 37 | return freq | ||
| 38 | |||
| 39 | def compute_all(self): | ||
| 40 | """ Compute data """ | ||
| 41 | mylist = [] | ||
| 42 | while(self.readsize==self.params.hopsize): | ||
| 43 | freq = self() | ||
| 44 | mylist.append(freq) | ||
| 45 | if self.params.verbose: | ||
| 46 | self.fprint("%s\t%s" % (self.frameread*self.params.step,freq)) | ||
| 47 | return mylist | ||
| 48 | |||
| 49 | def gettruth(self): | ||
| 50 | """ extract ground truth array in frequency """ | ||
| 51 | import os.path | ||
| 52 | """ from wavfile.txt """ | ||
| 53 | datafile = self.input.replace('.wav','.txt') | ||
| 54 | if datafile == self.input: datafile = "" | ||
| 55 | """ from file.<midinote>.wav """ | ||
| 56 | # FIXME very weak check | ||
| 57 | floatpit = self.input.split('.')[-2] | ||
| 58 | if not os.path.isfile(datafile) and len(self.input.split('.')) < 3: | ||
| 59 | print "no ground truth " | ||
| 60 | return False,False | ||
| 61 | elif floatpit: | ||
| 62 | try: | ||
| 63 | self.truth = aubio_miditofreq(float(floatpit)) | ||
| 64 | print "ground truth found in filename:", self.truth | ||
| 65 | tasksil = tasksilence(self.input) | ||
| 66 | time,pitch =[],[] | ||
| 67 | while(tasksil.readsize==tasksil.params.hopsize): | ||
| 68 | tasksil() | ||
| 69 | time.append(tasksil.params.step*tasksil.frameread) | ||
| 70 | if not tasksil.issilence: | ||
| 71 | pitch.append(self.truth) | ||
| 72 | else: | ||
| 73 | pitch.append(-1.) | ||
| 74 | return time,pitch #0,aubio_miditofreq(float(floatpit)) | ||
| 75 | except ValueError: | ||
| 76 | # FIXME very weak check | ||
| 77 | if not os.path.isfile(datafile): | ||
| 78 | print "no ground truth found" | ||
| 79 | return 0,0 | ||
| 80 | else: | ||
| 81 | from aubio.txtfile import read_datafile | ||
| 82 | values = read_datafile(datafile) | ||
| 83 | time, pitch = [], [] | ||
| 84 | for i in range(len(values)): | ||
| 85 | time.append(values[i][0]) | ||
| 86 | pitch.append(values[i][1]) | ||
| 87 | return time,pitch | ||
| 88 | |||
| 89 | def eval(self,results): | ||
| 90 | def mmean(l): | ||
| 91 | return sum(l)/max(float(len(l)),1) | ||
| 92 | |||
| 93 | from aubio.median import percental | ||
| 94 | timet,pitcht = self.gettruth() | ||
| 95 | res = [] | ||
| 96 | for i in results: | ||
| 97 | #print i,self.truth | ||
| 98 | if i <= 0: pass | ||
| 99 | else: res.append(self.truth-i) | ||
| 100 | if not res or len(res) < 3: | ||
| 101 | avg = self.truth; med = self.truth | ||
| 102 | else: | ||
| 103 | avg = mmean(res) | ||
| 104 | med = percental(res,len(res)/2) | ||
| 105 | return self.truth, self.truth-med, self.truth-avg | ||
| 106 | |||
| 107 | def neweval(self,results): | ||
| 108 | timet,pitcht = self.gettruth() | ||
| 109 | for i in timet: | ||
| 110 | print results[i] | ||
| 111 | return self.truth, self.truth-med, self.truth-avg | ||
| 112 | |||
| 113 | def plot(self,pitch,wplot,oplots,outplot=None): | ||
| 114 | import numarray | ||
| 115 | import Gnuplot | ||
| 116 | |||
| 117 | self.eval(pitch) | ||
| 118 | downtime = self.params.step*numarray.arange(len(pitch)) | ||
| 119 | oplots.append(Gnuplot.Data(downtime,pitch,with='lines', | ||
| 120 | title=self.params.pitchmode)) | ||
| 121 | |||
| 122 | |||
| 123 | def plotplot(self,wplot,oplots,outplot=None,multiplot = 1): | ||
| 124 | from aubio.gnuplot import gnuplot_init, audio_to_array, make_audio_plot | ||
| 125 | import re | ||
| 126 | import Gnuplot | ||
| 127 | # audio data | ||
| 128 | time,data = audio_to_array(self.input) | ||
| 129 | f = make_audio_plot(time,data) | ||
| 130 | |||
| 131 | # check if ground truth exists | ||
| 132 | timet,pitcht = self.gettruth() | ||
| 133 | if timet and pitcht: | ||
| 134 | oplots = [Gnuplot.Data(timet,pitcht,with='lines', | ||
| 135 | title='ground truth')] + oplots | ||
| 136 | |||
| 137 | t = Gnuplot.Data(0,0,with='impulses') | ||
| 138 | |||
| 139 | g = gnuplot_init(outplot) | ||
| 140 | g('set title \'%s\'' % (re.sub('.*/','',self.input))) | ||
| 141 | g('set multiplot') | ||
| 142 | # hack to align left axis | ||
| 143 | g('set lmargin 15') | ||
| 144 | # plot waveform and onsets | ||
| 145 | g('set size 1,0.3') | ||
| 146 | g('set origin 0,0.7') | ||
| 147 | g('set xrange [0:%f]' % max(time)) | ||
| 148 | g('set yrange [-1:1]') | ||
| 149 | g.ylabel('amplitude') | ||
| 150 | g.plot(f) | ||
| 151 | g('unset title') | ||
| 152 | # plot onset detection function | ||
| 153 | |||
| 154 | |||
| 155 | g('set size 1,0.7') | ||
| 156 | g('set origin 0,0') | ||
| 157 | g('set xrange [0:%f]' % max(time)) | ||
| 158 | g('set yrange [100:%f]' % self.params.pitchmax) | ||
| 159 | g('set key right top') | ||
| 160 | g('set noclip one') | ||
| 161 | g('set format x ""') | ||
| 162 | g('set log y') | ||
| 163 | #g.xlabel('time (s)') | ||
| 164 | g.ylabel('f0 (Hz)') | ||
| 165 | if multiplot: | ||
| 166 | for i in range(len(oplots)): | ||
| 167 | # plot onset detection functions | ||
| 168 | g('set size 1,%f' % (0.7/(len(oplots)))) | ||
| 169 | g('set origin 0,%f' % (float(i)*0.7/(len(oplots)))) | ||
| 170 | g('set xrange [0:%f]' % max(time)) | ||
| 171 | g.plot(oplots[i]) | ||
| 172 | else: | ||
| 173 | g.plot(*oplots) | ||
| 174 | g('unset multiplot') | ||
| 175 | |||
| @@ -0,0 +1,28 @@ | |||
| 1 | from aubio.task.task import task | ||
| 2 | from aubio.aubioclass import * | ||
| 3 | |||
| 4 | class tasksilence(task): | ||
| 5 | wassilence = 1 | ||
| 6 | issilence = 1 | ||
| 7 | def __call__(self): | ||
| 8 | task.__call__(self) | ||
| 9 | if (aubio_silence_detection(self.myvec(),self.params.silence)==1): | ||
| 10 | if self.wassilence == 1: self.issilence = 1 | ||
| 11 | else: self.issilence = 2 | ||
| 12 | self.wassilence = 1 | ||
| 13 | else: | ||
| 14 | if self.wassilence <= 0: self.issilence = 0 | ||
| 15 | else: self.issilence = -1 | ||
| 16 | self.wassilence = 0 | ||
| 17 | if self.issilence == -1: | ||
| 18 | return max(self.frameread-self.params.delay,0.), -1 | ||
| 19 | elif self.issilence == 2: | ||
| 20 | return max(self.frameread+self.params.delay,0.), 2 | ||
| 21 | |||
| 22 | def fprint(self,foo): | ||
| 23 | print self.params.step*foo[0], | ||
| 24 | if foo[1] == 2: print "OFF" | ||
| 25 | else: print "ON" | ||
| 26 | |||
| 27 | |||
| 28 | |||
| @@ -0,0 +1,54 @@ | |||
| 1 | from aubio.aubioclass import * | ||
| 2 | from params import taskparams | ||
| 3 | |||
| 4 | class task(taskparams): | ||
| 5 | """ default template class to apply tasks on a stream """ | ||
| 6 | def __init__(self,input,output=None,params=None): | ||
| 7 | """ open the input file and initialize default argument | ||
| 8 | parameters should be set *before* calling this method. | ||
| 9 | """ | ||
| 10 | import time | ||
| 11 | self.tic = time.time() | ||
| 12 | if params == None: self.params = taskparams() | ||
| 13 | else: self.params = params | ||
| 14 | self.frameread = 0 | ||
| 15 | self.readsize = self.params.hopsize | ||
| 16 | self.input = input | ||
| 17 | self.filei = sndfile(self.input) | ||
| 18 | self.srate = self.filei.samplerate() | ||
| 19 | self.channels = self.filei.channels() | ||
| 20 | self.params.step = float(self.params.hopsize)/float(self.srate) | ||
| 21 | self.myvec = fvec(self.params.hopsize,self.channels) | ||
| 22 | self.output = output | ||
| 23 | |||
| 24 | def __call__(self): | ||
| 25 | self.readsize = self.filei.read(self.params.hopsize,self.myvec) | ||
| 26 | self.frameread += 1 | ||
| 27 | |||
| 28 | def compute_all(self): | ||
| 29 | """ Compute data """ | ||
| 30 | mylist = [] | ||
| 31 | while(self.readsize==self.params.hopsize): | ||
| 32 | tmp = self() | ||
| 33 | if tmp: | ||
| 34 | mylist.append(tmp) | ||
| 35 | if self.params.verbose: | ||
| 36 | self.fprint(tmp) | ||
| 37 | return mylist | ||
| 38 | |||
| 39 | def fprint(self,foo): | ||
| 40 | print foo | ||
| 41 | |||
| 42 | def eval(self,results): | ||
| 43 | """ Eval data """ | ||
| 44 | pass | ||
| 45 | |||
| 46 | def plot(self): | ||
| 47 | """ Plot data """ | ||
| 48 | pass | ||
| 49 | |||
| 50 | def time(self): | ||
| 51 | import time | ||
| 52 | print "CPU time is now %f seconds," % time.clock(), | ||
| 53 | print "task execution took %f seconds" % (time.time() - self.tic) | ||
| 54 | |||
| @@ -0,0 +1,74 @@ | |||
| 1 | from aubio.aubioclass import * | ||
| 2 | |||
| 3 | def get_onset_mode(nvalue): | ||
| 4 | """ utility function to convert a string to aubio_onsetdetection_type """ | ||
| 5 | if nvalue == 'complexdomain' or nvalue == 'complex' : | ||
| 6 | return aubio_onset_complex | ||
| 7 | elif nvalue == 'hfc' : | ||
| 8 | return aubio_onset_hfc | ||
| 9 | elif nvalue == 'phase' : | ||
| 10 | return aubio_onset_phase | ||
| 11 | elif nvalue == 'specdiff' : | ||
| 12 | return aubio_onset_specdiff | ||
| 13 | elif nvalue == 'energy' : | ||
| 14 | return aubio_onset_energy | ||
| 15 | elif nvalue == 'kl' : | ||
| 16 | return aubio_onset_kl | ||
| 17 | elif nvalue == 'mkl' : | ||
| 18 | return aubio_onset_mkl | ||
| 19 | elif nvalue == 'dual' : | ||
| 20 | return 'dual' | ||
| 21 | else: | ||
| 22 | import sys | ||
| 23 | print "unknown onset detection function selected" | ||
| 24 | sys.exit(1) | ||
| 25 | |||
| 26 | def get_pitch_mode(nvalue): | ||
| 27 | """ utility function to convert a string to aubio_pitchdetection_type """ | ||
| 28 | if nvalue == 'mcomb' : | ||
| 29 | return aubio_pitch_mcomb | ||
| 30 | elif nvalue == 'yin' : | ||
| 31 | return aubio_pitch_yin | ||
| 32 | elif nvalue == 'fcomb' : | ||
| 33 | return aubio_pitch_fcomb | ||
| 34 | elif nvalue == 'schmitt': | ||
| 35 | return aubio_pitch_schmitt | ||
| 36 | else: | ||
| 37 | import sys | ||
| 38 | print "error: unknown pitch detection function selected" | ||
| 39 | sys.exit(1) | ||
| 40 | |||
| 41 | def check_onset_mode(option, opt, value, parser): | ||
| 42 | """ wrapper function to convert a list of modes to | ||
| 43 | aubio_onsetdetection_type """ | ||
| 44 | nvalues = parser.rargs[0].split(',') | ||
| 45 | val = [] | ||
| 46 | for nvalue in nvalues: | ||
| 47 | val.append(get_onset_mode(nvalue)) | ||
| 48 | setattr(parser.values, option.dest, val) | ||
| 49 | |||
| 50 | def check_pitch_mode(option, opt, value, parser): | ||
| 51 | """ utility function to convert a string to aubio_pitchdetection_type""" | ||
| 52 | nvalues = parser.rargs[0].split(',') | ||
| 53 | val = [] | ||
| 54 | for nvalue in nvalues: | ||
| 55 | val.append(get_pitch_mode(nvalue)) | ||
| 56 | setattr(parser.values, option.dest, val) | ||
| 57 | |||
| 58 | def check_pitchm_mode(option, opt, value, parser): | ||
| 59 | """ utility function to convert a string to aubio_pitchdetection_mode """ | ||
| 60 | nvalue = parser.rargs[0] | ||
| 61 | if nvalue == 'freq' : | ||
| 62 | setattr(parser.values, option.dest, aubio_pitchm_freq) | ||
| 63 | elif nvalue == 'midi' : | ||
| 64 | setattr(parser.values, option.dest, aubio_pitchm_midi) | ||
| 65 | elif nvalue == 'cent' : | ||
| 66 | setattr(parser.values, option.dest, aubio_pitchm_cent) | ||
| 67 | elif nvalue == 'bin' : | ||
| 68 | setattr(parser.values, option.dest, aubio_pitchm_bin) | ||
| 69 | else: | ||
| 70 | import sys | ||
| 71 | print "error: unknown pitch detection output selected" | ||
| 72 | sys.exit(1) | ||
| 73 | |||
| 74 | |||
| @@ -1,587 +0,0 @@ | |||
| 1 | from aubioclass import * | ||
| 2 | |||
| 3 | def get_onset_mode(nvalue): | ||
| 4 | """ utility function to convert a string to aubio_onsetdetection_type """ | ||
| 5 | if nvalue == 'complexdomain' or nvalue == 'complex' : | ||
| 6 | return aubio_onset_complex | ||
| 7 | elif nvalue == 'hfc' : | ||
| 8 | return aubio_onset_hfc | ||
| 9 | elif nvalue == 'phase' : | ||
| 10 | return aubio_onset_phase | ||
| 11 | elif nvalue == 'specdiff' : | ||
| 12 | return aubio_onset_specdiff | ||
| 13 | elif nvalue == 'energy' : | ||
| 14 | return aubio_onset_energy | ||
| 15 | elif nvalue == 'kl' : | ||
| 16 | return aubio_onset_kl | ||
| 17 | elif nvalue == 'mkl' : | ||
| 18 | return aubio_onset_mkl | ||
| 19 | elif nvalue == 'dual' : | ||
| 20 | return 'dual' | ||
| 21 | else: | ||
| 22 | import sys | ||
| 23 | print "unknown onset detection function selected" | ||
| 24 | sys.exit(1) | ||
| 25 | |||
| 26 | def get_pitch_mode(nvalue): | ||
| 27 | """ utility function to convert a string to aubio_pitchdetection_type """ | ||
| 28 | if nvalue == 'mcomb' : | ||
| 29 | return aubio_pitch_mcomb | ||
| 30 | elif nvalue == 'yin' : | ||
| 31 | return aubio_pitch_yin | ||
| 32 | elif nvalue == 'fcomb' : | ||
| 33 | return aubio_pitch_fcomb | ||
| 34 | elif nvalue == 'schmitt': | ||
| 35 | return aubio_pitch_schmitt | ||
| 36 | else: | ||
| 37 | import sys | ||
| 38 | print "error: unknown pitch detection function selected" | ||
| 39 | sys.exit(1) | ||
| 40 | |||
| 41 | def check_onset_mode(option, opt, value, parser): | ||
| 42 | """ wrapper function to convert a list of modes to | ||
| 43 | aubio_onsetdetection_type """ | ||
| 44 | nvalues = parser.rargs[0].split(',') | ||
| 45 | val = [] | ||
| 46 | for nvalue in nvalues: | ||
| 47 | val.append(get_onset_mode(nvalue)) | ||
| 48 | setattr(parser.values, option.dest, val) | ||
| 49 | |||
| 50 | def check_pitch_mode(option, opt, value, parser): | ||
| 51 | """ utility function to convert a string to aubio_pitchdetection_type""" | ||
| 52 | nvalues = parser.rargs[0].split(',') | ||
| 53 | val = [] | ||
| 54 | for nvalue in nvalues: | ||
| 55 | val.append(get_pitch_mode(nvalue)) | ||
| 56 | setattr(parser.values, option.dest, val) | ||
| 57 | |||
| 58 | def check_pitchm_mode(option, opt, value, parser): | ||
| 59 | """ utility function to convert a string to aubio_pitchdetection_mode """ | ||
| 60 | nvalue = parser.rargs[0] | ||
| 61 | if nvalue == 'freq' : | ||
| 62 | setattr(parser.values, option.dest, aubio_pitchm_freq) | ||
| 63 | elif nvalue == 'midi' : | ||
| 64 | setattr(parser.values, option.dest, aubio_pitchm_midi) | ||
| 65 | elif nvalue == 'cent' : | ||
| 66 | setattr(parser.values, option.dest, aubio_pitchm_cent) | ||
| 67 | elif nvalue == 'bin' : | ||
| 68 | setattr(parser.values, option.dest, aubio_pitchm_bin) | ||
| 69 | else: | ||
| 70 | import sys | ||
| 71 | print "error: unknown pitch detection output selected" | ||
| 72 | sys.exit(1) | ||
| 73 | |||
| 74 | class taskparams(object): | ||
| 75 | """ default parameters for task classes """ | ||
| 76 | def __init__(self,input=None,output=None): | ||
| 77 | self.silence = -70 | ||
| 78 | self.derivate = False | ||
| 79 | self.localmin = False | ||
| 80 | self.delay = 4. | ||
| 81 | self.storefunc = False | ||
| 82 | self.bufsize = 512 | ||
| 83 | self.hopsize = 256 | ||
| 84 | self.samplerate = 44100 | ||
| 85 | self.tol = 0.05 | ||
| 86 | self.mintol = 0.0 | ||
| 87 | self.step = float(self.hopsize)/float(self.samplerate) | ||
| 88 | self.threshold = 0.1 | ||
| 89 | self.onsetmode = 'dual' | ||
| 90 | self.pitchmode = 'yin' | ||
| 91 | self.pitchsmooth = 7 | ||
| 92 | self.pitchmin=100. | ||
| 93 | self.pitchmax=1000. | ||
| 94 | self.dcthreshold = -1. | ||
| 95 | self.omode = aubio_pitchm_freq | ||
| 96 | self.verbose = False | ||
| 97 | |||
| 98 | class task(taskparams): | ||
| 99 | """ default template class to apply tasks on a stream """ | ||
| 100 | def __init__(self,input,output=None,params=None): | ||
| 101 | """ open the input file and initialize default argument | ||
| 102 | parameters should be set *before* calling this method. | ||
| 103 | """ | ||
| 104 | import time | ||
| 105 | self.tic = time.time() | ||
| 106 | if params == None: self.params = taskparams() | ||
| 107 | else: self.params = params | ||
| 108 | self.frameread = 0 | ||
| 109 | self.readsize = self.params.hopsize | ||
| 110 | self.input = input | ||
| 111 | self.filei = sndfile(self.input) | ||
| 112 | self.srate = self.filei.samplerate() | ||
| 113 | self.channels = self.filei.channels() | ||
| 114 | self.params.step = float(self.params.hopsize)/float(self.srate) | ||
| 115 | self.myvec = fvec(self.params.hopsize,self.channels) | ||
| 116 | self.output = output | ||
| 117 | |||
| 118 | def __call__(self): | ||
| 119 | self.readsize = self.filei.read(self.params.hopsize,self.myvec) | ||
| 120 | self.frameread += 1 | ||
| 121 | |||
| 122 | def compute_all(self): | ||
| 123 | """ Compute data """ | ||
| 124 | mylist = [] | ||
| 125 | while(self.readsize==self.params.hopsize): | ||
| 126 | tmp = self() | ||
| 127 | if tmp: | ||
| 128 | mylist.append(tmp) | ||
| 129 | if self.params.verbose: | ||
| 130 | self.fprint(tmp) | ||
| 131 | return mylist | ||
| 132 | |||
| 133 | def fprint(self,foo): | ||
| 134 | print foo | ||
| 135 | |||
| 136 | def eval(self,results): | ||
| 137 | """ Eval data """ | ||
| 138 | pass | ||
| 139 | |||
| 140 | def plot(self): | ||
| 141 | """ Plot data """ | ||
| 142 | pass | ||
| 143 | |||
| 144 | def time(self): | ||
| 145 | import time | ||
| 146 | print "CPU time is now %f seconds," % time.clock(), | ||
| 147 | print "task execution took %f seconds" % (time.time() - self.tic) | ||
| 148 | |||
| 149 | class tasksilence(task): | ||
| 150 | wassilence = 1 | ||
| 151 | issilence = 1 | ||
| 152 | def __call__(self): | ||
| 153 | task.__call__(self) | ||
| 154 | if (aubio_silence_detection(self.myvec(),self.params.silence)==1): | ||
| 155 | if self.wassilence == 1: self.issilence = 1 | ||
| 156 | else: self.issilence = 2 | ||
| 157 | self.wassilence = 1 | ||
| 158 | else: | ||
| 159 | if self.wassilence <= 0: self.issilence = 0 | ||
| 160 | else: self.issilence = -1 | ||
| 161 | self.wassilence = 0 | ||
| 162 | if self.issilence == -1: | ||
| 163 | return max(self.frameread-self.params.delay,0.), -1 | ||
| 164 | elif self.issilence == 2: | ||
| 165 | return max(self.frameread+self.params.delay,0.), 2 | ||
| 166 | |||
| 167 | def fprint(self,foo): | ||
| 168 | print self.params.step*foo[0], | ||
| 169 | if foo[1] == 2: print "OFF" | ||
| 170 | else: print "ON" | ||
| 171 | |||
| 172 | class taskpitch(task): | ||
| 173 | def __init__(self,input,params=None): | ||
| 174 | task.__init__(self,input,params=params) | ||
| 175 | self.shortlist = [0. for i in range(self.params.pitchsmooth)] | ||
| 176 | self.pitchdet = pitchdetection(mode=get_pitch_mode(self.params.pitchmode), | ||
| 177 | bufsize=self.params.bufsize, | ||
| 178 | hopsize=self.params.hopsize, | ||
| 179 | channels=self.channels, | ||
| 180 | samplerate=self.srate, | ||
| 181 | omode=self.params.omode) | ||
| 182 | |||
| 183 | def __call__(self): | ||
| 184 | from median import short_find | ||
| 185 | task.__call__(self) | ||
| 186 | if (aubio_silence_detection(self.myvec(),self.params.silence)==1): | ||
| 187 | freq = -1. | ||
| 188 | else: | ||
| 189 | freq = self.pitchdet(self.myvec) | ||
| 190 | minpitch = self.params.pitchmin | ||
| 191 | maxpitch = self.params.pitchmax | ||
| 192 | if maxpitch and freq > maxpitch : | ||
| 193 | freq = -1. | ||
| 194 | elif minpitch and freq < minpitch : | ||
| 195 | freq = -1. | ||
| 196 | if self.params.pitchsmooth: | ||
| 197 | self.shortlist.append(freq) | ||
| 198 | self.shortlist.pop(0) | ||
| 199 | smoothfreq = short_find(self.shortlist, | ||
| 200 | len(self.shortlist)/2) | ||
| 201 | return smoothfreq | ||
| 202 | else: | ||
| 203 | return freq | ||
| 204 | |||
| 205 | def compute_all(self): | ||
| 206 | """ Compute data """ | ||
| 207 | mylist = [] | ||
| 208 | while(self.readsize==self.params.hopsize): | ||
| 209 | freq = self() | ||
| 210 | mylist.append(freq) | ||
| 211 | if self.params.verbose: | ||
| 212 | self.fprint("%s\t%s" % (self.frameread*self.params.step,freq)) | ||
| 213 | return mylist | ||
| 214 | |||
| 215 | def gettruth(self): | ||
| 216 | """ extract ground truth array in frequency """ | ||
| 217 | import os.path | ||
| 218 | """ from wavfile.txt """ | ||
| 219 | datafile = self.input.replace('.wav','.txt') | ||
| 220 | if datafile == self.input: datafile = "" | ||
| 221 | """ from file.<midinote>.wav """ | ||
| 222 | # FIXME very weak check | ||
| 223 | floatpit = self.input.split('.')[-2] | ||
| 224 | |||
| 225 | if not os.path.isfile(datafile) and not len(self.input.split('.')) < 3: | ||
| 226 | print "no ground truth " | ||
| 227 | return False,False | ||
| 228 | elif floatpit: | ||
| 229 | try: | ||
| 230 | self.truth = aubio_miditofreq(float(floatpit)) | ||
| 231 | print "ground truth found in filename:", self.truth | ||
| 232 | tasksil = tasksilence(self.input) | ||
| 233 | time,pitch =[],[] | ||
| 234 | while(tasksil.readsize==tasksil.params.hopsize): | ||
| 235 | tasksil() | ||
| 236 | time.append(tasksil.params.step*tasksil.frameread) | ||
| 237 | if not tasksil.issilence: | ||
| 238 | pitch.append(self.truth) | ||
| 239 | else: | ||
| 240 | pitch.append(-1.) | ||
| 241 | return time,pitch #0,aubio_miditofreq(float(floatpit)) | ||
| 242 | except ValueError: | ||
| 243 | # FIXME very weak check | ||
| 244 | if not os.path.isfile(datafile): | ||
| 245 | print "no ground truth found" | ||
| 246 | return 0,0 | ||
| 247 | else: | ||
| 248 | from aubio.txtfile import read_datafile | ||
| 249 | values = read_datafile(datafile) | ||
| 250 | time, pitch = [], [] | ||
| 251 | for i in range(len(values)): | ||
| 252 | time.append(values[i][0]) | ||
| 253 | pitch.append(values[i][1]) | ||
| 254 | return time,pitch | ||
| 255 | |||
| 256 | def eval(self,results): | ||
| 257 | def mmean(l): | ||
| 258 | return sum(l)/max(float(len(l)),1) | ||
| 259 | |||
| 260 | from median import percental | ||
| 261 | timet,pitcht = self.gettruth() | ||
| 262 | res = [] | ||
| 263 | for i in results: | ||
| 264 | #print i,self.truth | ||
| 265 | if i <= 0: pass | ||
| 266 | else: res.append(self.truth-i) | ||
| 267 | if not res or len(res) < 3: | ||
| 268 | avg = self.truth; med = self.truth | ||
| 269 | else: | ||
| 270 | avg = mmean(res) | ||
| 271 | med = percental(res,len(res)/2) | ||
| 272 | return self.truth, self.truth-med, self.truth-avg | ||
| 273 | |||
| 274 | def plot(self,pitch,wplot,oplots,outplot=None): | ||
| 275 | import numarray | ||
| 276 | import Gnuplot | ||
| 277 | |||
| 278 | downtime = self.params.step*numarray.arange(len(pitch)) | ||
| 279 | oplots.append(Gnuplot.Data(downtime,pitch,with='lines', | ||
| 280 | title=self.params.pitchmode)) | ||
| 281 | |||
| 282 | |||
| 283 | def plotplot(self,wplot,oplots,outplot=None,multiplot = 1): | ||
| 284 | from aubio.gnuplot import gnuplot_init, audio_to_array, make_audio_plot | ||
| 285 | import re | ||
| 286 | import Gnuplot | ||
| 287 | # audio data | ||
| 288 | time,data = audio_to_array(self.input) | ||
| 289 | f = make_audio_plot(time,data) | ||
| 290 | |||
| 291 | # check if ground truth exists | ||
| 292 | timet,pitcht = self.gettruth() | ||
| 293 | if timet and pitcht: | ||
| 294 | oplots = [Gnuplot.Data(timet,pitcht,with='lines', | ||
| 295 | title='ground truth')] + oplots | ||
| 296 | |||
| 297 | t = Gnuplot.Data(0,0,with='impulses') | ||
| 298 | |||
| 299 | g = gnuplot_init(outplot) | ||
| 300 | g('set title \'%s\'' % (re.sub('.*/','',self.input))) | ||
| 301 | g('set multiplot') | ||
| 302 | # hack to align left axis | ||
| 303 | g('set lmargin 15') | ||
| 304 | # plot waveform and onsets | ||
| 305 | g('set size 1,0.3') | ||
| 306 | g('set origin 0,0.7') | ||
| 307 | g('set xrange [0:%f]' % max(time)) | ||
| 308 | g('set yrange [-1:1]') | ||
| 309 | g.ylabel('amplitude') | ||
| 310 | g.plot(f) | ||
| 311 | g('unset title') | ||
| 312 | # plot onset detection function | ||
| 313 | |||
| 314 | |||
| 315 | g('set size 1,0.7') | ||
| 316 | g('set origin 0,0') | ||
| 317 | g('set xrange [0:%f]' % max(time)) | ||
| 318 | g('set yrange [100:%f]' % self.params.pitchmax) | ||
| 319 | g('set key right top') | ||
| 320 | g('set noclip one') | ||
| 321 | g('set format x ""') | ||
| 322 | g('set log y') | ||
| 323 | #g.xlabel('time (s)') | ||
| 324 | g.ylabel('f0 (Hz)') | ||
| 325 | if multiplot: | ||
| 326 | for i in range(len(oplots)): | ||
| 327 | # plot onset detection functions | ||
| 328 | g('set size 1,%f' % (0.7/(len(oplots)))) | ||
| 329 | g('set origin 0,%f' % (float(i)*0.7/(len(oplots)))) | ||
| 330 | g('set xrange [0:%f]' % max(time)) | ||
| 331 | g.plot(oplots[i]) | ||
| 332 | else: | ||
| 333 | g.plot(*oplots) | ||
| 334 | g('unset multiplot') | ||
| 335 | |||
| 336 | |||
| 337 | class taskonset(task): | ||
| 338 | def __init__(self,input,output=None,params=None): | ||
| 339 | """ open the input file and initialize arguments | ||
| 340 | parameters should be set *before* calling this method. | ||
| 341 | """ | ||
| 342 | task.__init__(self,input,params=params) | ||
| 343 | self.opick = onsetpick(self.params.bufsize, | ||
| 344 | self.params.hopsize, | ||
| 345 | self.channels, | ||
| 346 | self.myvec, | ||
| 347 | self.params.threshold, | ||
| 348 | mode=get_onset_mode(self.params.onsetmode), | ||
| 349 | dcthreshold=self.params.dcthreshold, | ||
| 350 | derivate=self.params.derivate) | ||
| 351 | self.olist = [] | ||
| 352 | self.ofunc = [] | ||
| 353 | self.maxofunc = 0 | ||
| 354 | self.last = 0 | ||
| 355 | if self.params.localmin: | ||
| 356 | self.ovalist = [0., 0., 0., 0., 0.] | ||
| 357 | |||
| 358 | def __call__(self): | ||
| 359 | task.__call__(self) | ||
| 360 | isonset,val = self.opick.do(self.myvec) | ||
| 361 | if (aubio_silence_detection(self.myvec(),self.params.silence)): | ||
| 362 | isonset=0 | ||
| 363 | if self.params.storefunc: | ||
| 364 | self.ofunc.append(val) | ||
| 365 | if self.params.localmin: | ||
| 366 | if val > 0: self.ovalist.append(val) | ||
| 367 | else: self.ovalist.append(0) | ||
| 368 | self.ovalist.pop(0) | ||
| 369 | if (isonset == 1): | ||
| 370 | if self.params.localmin: | ||
| 371 | # find local minima before peak | ||
| 372 | i=len(self.ovalist)-1 | ||
| 373 | while self.ovalist[i-1] < self.ovalist[i] and i > 0: | ||
| 374 | i -= 1 | ||
| 375 | now = (self.frameread+1-i) | ||
| 376 | else: | ||
| 377 | now = self.frameread | ||
| 378 | # take back delay | ||
| 379 | if self.params.delay != 0.: now -= self.params.delay | ||
| 380 | if now < 0 : | ||
| 381 | now = 0 | ||
| 382 | if self.params.mintol: | ||
| 383 | # prune doubled | ||
| 384 | if (now - self.last) > self.params.mintol: | ||
| 385 | self.last = now | ||
| 386 | return now, val | ||
| 387 | else: | ||
| 388 | return now, val | ||
| 389 | |||
| 390 | |||
| 391 | def fprint(self,foo): | ||
| 392 | print self.params.step*foo[0] | ||
| 393 | |||
| 394 | def eval(self,inputdata,ftru,mode='roc',vmode=''): | ||
| 395 | from txtfile import read_datafile | ||
| 396 | from onsetcompare import onset_roc, onset_diffs, onset_rocloc | ||
| 397 | ltru = read_datafile(ftru,depth=0) | ||
| 398 | lres = [] | ||
| 399 | for i in range(len(inputdata)): lres.append(inputdata[i][0]*self.params.step) | ||
| 400 | if vmode=='verbose': | ||
| 401 | print "Running with mode %s" % self.params.onsetmode, | ||
| 402 | print " and threshold %f" % self.params.threshold, | ||
| 403 | print " on file", self.input | ||
| 404 | #print ltru; print lres | ||
| 405 | if mode == 'local': | ||
| 406 | l = onset_diffs(ltru,lres,self.params.tol) | ||
| 407 | mean = 0 | ||
| 408 | for i in l: mean += i | ||
| 409 | if len(l): mean = "%.3f" % (mean/len(l)) | ||
| 410 | else: mean = "?0" | ||
| 411 | return l, mean | ||
| 412 | elif mode == 'roc': | ||
| 413 | self.orig, self.missed, self.merged, \ | ||
| 414 | self.expc, self.bad, self.doubled = \ | ||
| 415 | onset_roc(ltru,lres,self.params.tol) | ||
| 416 | elif mode == 'rocloc': | ||
| 417 | self.v = {} | ||
| 418 | self.v['orig'], self.v['missed'], self.v['Tm'], \ | ||
| 419 | self.v['expc'], self.v['bad'], self.v['Td'], \ | ||
| 420 | self.v['l'], self.v['labs'] = \ | ||
| 421 | onset_rocloc(ltru,lres,self.params.tol) | ||
| 422 | |||
| 423 | def plot(self,onsets,ofunc,wplot,oplots,nplot=False): | ||
| 424 | import Gnuplot, Gnuplot.funcutils | ||
| 425 | import aubio.txtfile | ||
| 426 | import os.path | ||
| 427 | import numarray | ||
| 428 | from aubio.onsetcompare import onset_roc | ||
| 429 | |||
| 430 | x1,y1,y1p = [],[],[] | ||
| 431 | oplot = [] | ||
| 432 | if self.params.onsetmode in ('mkl','kl'): ofunc[0:10] = [0] * 10 | ||
| 433 | |||
| 434 | self.lenofunc = len(ofunc) | ||
| 435 | self.maxofunc = max(ofunc) | ||
| 436 | # onset detection function | ||
| 437 | downtime = numarray.arange(len(ofunc))*self.params.step | ||
| 438 | oplot.append(Gnuplot.Data(downtime,ofunc,with='lines',title=self.params.onsetmode)) | ||
| 439 | |||
| 440 | # detected onsets | ||
| 441 | if not nplot: | ||
| 442 | for i in onsets: | ||
| 443 | x1.append(i[0]*self.params.step) | ||
| 444 | y1.append(self.maxofunc) | ||
| 445 | y1p.append(-self.maxofunc) | ||
| 446 | #x1 = numarray.array(onsets)*self.params.step | ||
| 447 | #y1 = self.maxofunc*numarray.ones(len(onsets)) | ||
| 448 | if x1: | ||
| 449 | oplot.append(Gnuplot.Data(x1,y1,with='impulses')) | ||
| 450 | wplot.append(Gnuplot.Data(x1,y1p,with='impulses')) | ||
| 451 | |||
| 452 | oplots.append(oplot) | ||
| 453 | |||
| 454 | # check if ground truth datafile exists | ||
| 455 | datafile = self.input.replace('.wav','.txt') | ||
| 456 | if datafile == self.input: datafile = "" | ||
| 457 | if not os.path.isfile(datafile): | ||
| 458 | self.title = "" #"(no ground truth)" | ||
| 459 | else: | ||
| 460 | t_onsets = aubio.txtfile.read_datafile(datafile) | ||
| 461 | x2 = numarray.array(t_onsets).resize(len(t_onsets)) | ||
| 462 | y2 = self.maxofunc*numarray.ones(len(t_onsets)) | ||
| 463 | wplot.append(Gnuplot.Data(x2,y2,with='impulses')) | ||
| 464 | |||
| 465 | tol = 0.050 | ||
| 466 | |||
| 467 | orig, missed, merged, expc, bad, doubled = \ | ||
| 468 | onset_roc(x2,x1,tol) | ||
| 469 | self.title = "GD %2.3f%% FP %2.3f%%" % \ | ||
| 470 | ((100*float(orig-missed-merged)/(orig)), | ||
| 471 | (100*float(bad+doubled)/(orig))) | ||
| 472 | |||
| 473 | |||
| 474 | def plotplot(self,wplot,oplots,outplot=None): | ||
| 475 | from aubio.gnuplot import gnuplot_init, audio_to_array, make_audio_plot | ||
| 476 | import re | ||
| 477 | # audio data | ||
| 478 | time,data = audio_to_array(self.input) | ||
| 479 | wplot = [make_audio_plot(time,data)] + wplot | ||
| 480 | self.title = self.input | ||
| 481 | # prepare the plot | ||
| 482 | g = gnuplot_init(outplot) | ||
| 483 | |||
| 484 | g('set multiplot') | ||
| 485 | |||
| 486 | # hack to align left axis | ||
| 487 | g('set lmargin 6') | ||
| 488 | g('set tmargin 0') | ||
| 489 | g('set format x ""') | ||
| 490 | g('set format y ""') | ||
| 491 | g('set noytics') | ||
| 492 | |||
| 493 | for i in range(len(oplots)): | ||
| 494 | # plot onset detection functions | ||
| 495 | g('set size 1,%f' % (0.7/(len(oplots)))) | ||
| 496 | g('set origin 0,%f' % (float(i)*0.7/(len(oplots)))) | ||
| 497 | g('set xrange [0:%f]' % (self.lenofunc*self.params.step)) | ||
| 498 | g.plot(*oplots[i]) | ||
| 499 | |||
| 500 | g('set tmargin 3.0') | ||
| 501 | g('set xlabel "time (s)" 1,0') | ||
| 502 | g('set format x "%1.1f"') | ||
| 503 | |||
| 504 | g('set title \'%s %s\'' % (re.sub('.*/','',self.input),self.title)) | ||
| 505 | |||
| 506 | # plot waveform and onsets | ||
| 507 | g('set size 1,0.3') | ||
| 508 | g('set origin 0,0.7') | ||
| 509 | g('set xrange [0:%f]' % max(time)) | ||
| 510 | g('set yrange [-1:1]') | ||
| 511 | g.ylabel('amplitude') | ||
| 512 | g.plot(*wplot) | ||
| 513 | |||
| 514 | g('unset multiplot') | ||
| 515 | |||
| 516 | class taskcut(task): | ||
| 517 | def __init__(self,input,slicetimes,params=None,output=None): | ||
| 518 | """ open the input file and initialize arguments | ||
| 519 | parameters should be set *before* calling this method. | ||
| 520 | """ | ||
| 521 | task.__init__(self,input,output=None,params=params) | ||
| 522 | self.newname = "%s%s%09.5f%s%s" % (self.input.split(".")[0].split("/")[-1],".", | ||
| 523 | self.frameread*self.params.step,".",self.input.split(".")[-1]) | ||
| 524 | self.fileo = sndfile(self.newname,model=self.filei) | ||
| 525 | self.myvec = fvec(self.params.hopsize,self.channels) | ||
| 526 | self.mycopy = fvec(self.params.hopsize,self.channels) | ||
| 527 | self.slicetimes = slicetimes | ||
| 528 | |||
| 529 | def __call__(self): | ||
| 530 | task.__call__(self) | ||
| 531 | # write to current file | ||
| 532 | if len(self.slicetimes) and self.frameread >= self.slicetimes[0][0]: | ||
| 533 | self.slicetimes.pop(0) | ||
| 534 | # write up to 1st zero crossing | ||
| 535 | zerocross = 0 | ||
| 536 | while ( abs( self.myvec.get(zerocross,0) ) > self.params.zerothres ): | ||
| 537 | zerocross += 1 | ||
| 538 | writesize = self.fileo.write(zerocross,self.myvec) | ||
| 539 | fromcross = 0 | ||
| 540 | while (zerocross < self.readsize): | ||
| 541 | for i in range(self.channels): | ||
| 542 | self.mycopy.set(self.myvec.get(zerocross,i),fromcross,i) | ||
| 543 | fromcross += 1 | ||
| 544 | zerocross += 1 | ||
| 545 | del self.fileo | ||
| 546 | self.fileo = sndfile("%s%s%09.5f%s%s" % | ||
| 547 | (self.input.split(".")[0].split("/")[-1],".", | ||
| 548 | self.frameread*self.params.step,".",self.input.split(".")[-1]),model=self.filei) | ||
| 549 | writesize = self.fileo.write(fromcross,self.mycopy) | ||
| 550 | else: | ||
| 551 | writesize = self.fileo.write(self.readsize,self.myvec) | ||
| 552 | |||
| 553 | class taskbeat(taskonset): | ||
| 554 | def __init__(self,input,params=None,output=None): | ||
| 555 | """ open the input file and initialize arguments | ||
| 556 | parameters should be set *before* calling this method. | ||
| 557 | """ | ||
| 558 | taskonset.__init__(self,input,output=None,params=params) | ||
| 559 | self.btwinlen = 512**2/self.params.hopsize | ||
| 560 | self.btstep = self.btwinlen/4 | ||
| 561 | self.btoutput = fvec(self.btstep,self.channels) | ||
| 562 | self.dfframe = fvec(self.btwinlen,self.channels) | ||
| 563 | self.bt = beattracking(self.btwinlen,self.channels) | ||
| 564 | self.pos2 = 0 | ||
| 565 | |||
| 566 | def __call__(self): | ||
| 567 | taskonset.__call__(self) | ||
| 568 | # write to current file | ||
| 569 | if self.pos2 == self.btstep - 1 : | ||
| 570 | self.bt.do(self.dfframe,self.btoutput) | ||
| 571 | for i in range (self.btwinlen - self.btstep): | ||
| 572 | self.dfframe.set(self.dfframe.get(i+self.btstep,0),i,0) | ||
| 573 | for i in range(self.btwinlen - self.btstep, self.btwinlen): | ||
| 574 | self.dfframe.set(0,i,0) | ||
| 575 | self.pos2 = -1; | ||
| 576 | self.pos2 += 1 | ||
| 577 | val = self.opick.pp.getval() | ||
| 578 | self.dfframe.set(val,self.btwinlen - self.btstep + self.pos2,0) | ||
| 579 | i=0 | ||
| 580 | for i in range(1,int( self.btoutput.get(0,0) ) ): | ||
| 581 | if self.pos2 == self.btoutput.get(i,0) and \ | ||
| 582 | aubio_silence_detection(self.myvec(), | ||
| 583 | self.params.silence)!=1: | ||
| 584 | return self.frameread, 0 | ||
| 585 | |||
| 586 | def eval(self,results): | ||
| 587 | pass | ||
| @@ -5,7 +5,7 @@ · 4 unmodified lines | |||
| 5 | """ | 5 | """ |
| 6 | 6 | ||
| 7 | import sys | 7 | import sys |
| 8 | from aubio.tasks import * | 8 | from aubio.task import * |
| 9 | 9 | ||
| 10 | usage = "usage: %s [options] -i soundfile" % sys.argv[0] | 10 | usage = "usage: %s [options] -i soundfile" % sys.argv[0] |
| 11 | 11 | ||
| @@ -5,7 +5,7 @@ · 4 unmodified lines | |||
| 5 | """ | 5 | """ |
| 6 | 6 | ||
| 7 | import sys | 7 | import sys |
| 8 | from aubio.tasks import * | 8 | from aubio.task import * |
| 9 | 9 | ||
| 10 | usage = "usage: %s [options] -i soundfile" % sys.argv[0] | 10 | usage = "usage: %s [options] -i soundfile" % sys.argv[0] |
| 11 | 11 | ||