ref: 4f4a8a4fdc1225669e4f821cc96945524c6addb0
parent: 7c9ad741f6f9584821ab660d827d8ed2d8aa528d
author: Paul Brossier <piem@altern.org>
date: Mon Dec 19 16:25:51 EST 2005
move to new nodes and tasks move to new nodes and tasks
--- a/python/aubiocut
+++ b/python/aubiocut
@@ -15,8 +15,8 @@
parser.add_option("-i","--input",action="store", dest="filename",
help="input sound file")
- parser.add_option("-m","--mode", action="callback", - callback=check_onset_mode, dest="mode", default=['dual'],
+ parser.add_option("-m","--mode", + action="store", dest="mode", default=['dual'],
help="onset detection mode [default=dual] \
complexdomain|hfc|phase|specdiff|energy|kl|mkl|dual")
parser.add_option("-B","--bufsize",@@ -80,18 +80,16 @@
options, args = parse_args()
filename = options.filename
-samplerate = float(sndfile(filename).samplerate())
-hopsize = int(options.hopsize)
-bufsize = int(options.bufsize)
-step = float(samplerate)/float(hopsize)
-threshold = float(options.threshold)
-zerothres = float(options.zerothres)
-silence = float(options.silence)
-mintol = float(options.mintol)*step
-mode = options.mode
+params = taskparams()
+params.hopsize = int(options.hopsize)
+params.bufsize = int(options.bufsize)
+params.threshold = float(options.threshold)
+params.zerothres = float(options.zerothres)
+params.silence = float(options.silence)
+params.mintol = float(options.mintol)
# default take back system delay
if options.delay: delay = float(options.delay)
-else: delay = 3./step
+else: delay = 3./params.step
if options.beat:
#onsets = getbeats(filename,threshold,silence,mode=options.mode)
@@ -98,27 +96,34 @@
exit("not implemented yet")elif options.silencecut:
onsets = getsilences(filename,hopsize=hopsize,silence=silence)
-elif options.plot: storefunc=True
-else: storefunc=False
+elif options.plot: params.storefunc=True
+else: params.storefunc=False
lonsets, lofunc = [], []
-for i in range(len(mode)):
- onsets, ofunc = getonsets(filename,threshold,silence,
- mode=mode[i],localmin=options.localmin,
- derivate=options.derivate,
- bufsize=bufsize,hopsize=hopsize,storefunc=True)
+modes = options.mode.split(',')+for i in range(len(modes)):
+ params.onsetmode = modes[i]
+ filetask = taskonset(filename,params=params)
+ onsets = filetask.compute_all()
+ ofunc = filetask.ofunc
+ #onsets, ofunc = getonsets(filename,threshold,silence,
+ # mode=mode[i],localmin=options.localmin,
+ # derivate=options.derivate,
+ # bufsize=bufsize,hopsize=hopsize,storefunc=True)
+
# take back system delay
if delay != 0:
- for i in range(len(onsets)):
- onsets[i] -= delay*step
+ for each in range(len(onsets)):
+ onsets[each] = onsets[each][0] - delay*params.step
# prune doubled
- if mintol > 0:
- last = -2*mintol
+ params.mintol *= params.step
+ if params.mintol > 0:
+ last = -2*params.mintol
newonsets = []
for new in onsets:
- if (new - last > mintol):
+ if (new - last > params.mintol):
newonsets.append(new)
last = new
onsets = newonsets
@@ -126,17 +131,17 @@
lonsets.append(onsets)
lofunc.append(ofunc)
-# print times in second
-if options.verbose:
- maxonset = 0
- for j in range(len(mode)):
- for i in range(len(lonsets[j])):
- print lonsets[j][i]/step
+ # print times in second
+ if options.verbose:
+ print modes[i]
+ maxonset = 0
+ for i in range(len(onsets)):
+ print onsets[i]*params.step
-if options.plot:
- from aubio.gnuplot import plot_onsets
- plot_onsets(filename, lonsets, lofunc,
- samplerate=samplerate, hopsize=hopsize, outplot=options.outplot)
+ if options.plot:
+ filetask.plot(onsets, ofunc)
+ filetask.plotplot(outplot=options.outplot)
if options.cut:
- cutfile(filename,onsets,zerothres=zerothres,bufsize=bufsize,hopsize=hopsize)
+ a = taskcut(filename,onsets,params=params)
+ a.compute_all()
--- a/python/bench-onset
+++ b/python/bench-onset
@@ -1,31 +1,17 @@
#! /usr/bin/python
-from aubio.bench.config import *
from aubio.bench.node import *
+from aubio.tasks import *
-class onset_parameters:
- def __init__(self):
- """ set default parameters """
- self.silence = -70
- self.derivate = False
- self.localmin = False
- self.bufsize = 512
- self.hopsize = 256
- self.samplerate = 44100
- self.tol = 0.05
- self.step = float(self.hopsize)/float(self.samplerate)
- self.threshold = 0.1
- self.mode = 'dual'
-
class benchonset(bench):
- def compute_results(self):
+ def dir_eval(self):
self.P = 100*float(self.expc-self.missed-self.merged)/(self.expc-self.missed-self.merged + self.bad+self.doubled)
self.R = 100*float(self.expc-self.missed-self.merged)/(self.expc-self.missed-self.merged + self.missed+self.merged)
if self.R < 0: self.R = 0
self.F = 2* self.P*self.R / (self.P+self.R)
- self.values = [self.params.mode,
+ self.values = [self.params.onsetmode,
"%2.3f" % self.params.threshold,
self.orig,
self.expc,
@@ -42,51 +28,17 @@
"%2.3f" % self.R,
"%2.3f" % self.F ]
- def compute_onset(self,input,output):
- from aubio.tasks import getonsets, get_onset_mode
- from aubio.onsetcompare import onset_roc, onset_diffs
- from aubio.txtfile import read_datafile
- amode = 'roc'
- vmode = 'verbose'
- vmode = ''
- lres, ofunc = getonsets(input,
- self.params.threshold,
- self.params.silence,
- mode=get_onset_mode(self.params.mode),
- localmin=self.params.localmin,
- derivate=self.params.derivate,
- bufsize=self.params.bufsize,
- hopsize=self.params.hopsize,
- storefunc=False)
+ def file_exec(self,input,output):
+ filetask = self.task(input,params=self.params)
+ computed_data = filetask.compute_all()
+ results = filetask.eval(computed_data)
+ self.orig += filetask.orig
+ self.missed += filetask.missed
+ self.merged += filetask.merged
+ self.expc += filetask.expc
+ self.bad += filetask.bad
+ self.doubled += filetask.doubled
- for i in range(len(lres)): lres[i] = lres[i]*self.params.step
- ltru = read_datafile(input.replace('.wav','.txt'),depth=0)- if vmode=='verbose':
- print "Running with mode %s" % self.params.mode,
- print " and threshold %f" % self.params.threshold,
- print " on file", input
- #print ltru; print lres
- if amode == 'localisation':
- l = onset_diffs(ltru,lres,self.params.tol)
- mean = 0
- for i in l: mean += i
- if len(l): print "%.3f" % (mean/len(l))
- else: print "?0"
- elif amode == 'roc':
- orig, missed, merged, expc, bad, doubled = onset_roc(ltru,lres,self.params.tol)
- self.orig += orig
- self.missed += missed
- self.merged += merged
- self.expc += expc
- self.bad += bad
- self.doubled += doubled
- self.compute_results()
-
- def compute_data(self):
- self.orig, self.missed, self.merged, self.expc, \
- self.bad, self.doubled = 0, 0, 0, 0, 0, 0
- act_on_data(self.compute_onset,self.datadir,self.resdir, \
- suffix='',filter='f -name \'*.wav\'')
def run_bench(self,modes=['dual'],thresholds=[0.5]):
self.modes = modes
@@ -94,11 +46,11 @@
self.pretty_print(self.titles)
for mode in self.modes:
- self.params.mode = mode
+ self.params.onsetmode = mode
for threshold in self.thresholds:
self.params.threshold = threshold
- self.compute_data()
- self.compute_results()
+ self.dir_exec()
+ self.dir_eval()
self.pretty_print(self.values)
def auto_learn(self,modes=['dual'],thresholds=[0.1,1.5]):
@@ -109,21 +61,24 @@
steps = 10
lesst = thresholds[0]
topt = thresholds[1]
- self.params.mode = mode
+ self.params.onsetmode = mode
self.params.threshold = topt
- self.compute_data()
+ self.dir_exec()
+ self.dir_eval()
self.pretty_print(self.values)
topF = self.F
self.params.threshold = lesst
- self.compute_data()
+ self.dir_exec()
+ self.dir_eval()
self.pretty_print(self.values)
lessF = self.F
for i in range(steps):
self.params.threshold = ( lesst + topt ) * .5
- self.compute_data()
+ self.dir_exec()
+ self.dir_eval()
self.pretty_print(self.values)
if self.F == 100.0 or self.F == topF:
print "assuming we converged, stopping"
@@ -143,34 +98,31 @@
lesst /= 2.
-#modes = [ 'complex' ]
-modes = ['complex', 'energy', 'phase', 'specdiff', 'kl', 'mkl', 'dual']
-#thresholds = [1.5]
-thresholds = [ 0.01, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5]
+if __name__ == "__main__":
+ import sys
+ if len(sys.argv) > 1: datapath = sys.argv[1]
+ else: print "ERR: a path is required"; sys.exit(1)
+ modes = ['complex', 'energy', 'phase', 'specdiff', 'kl', 'mkl', 'dual']
+ #modes = [ 'complex' ]
+ thresholds = [ 0.01, 0.05, 0.1, 0.2, 0.3, 0.4, 0.5]
+ #thresholds = [1.5]
-#datapath = "%s%s" % (DATADIR,'/onset/DB/*/')
-datapath = "%s%s" % (DATADIR,'/onset/DB/PercussivePhrases/RobertRich')
-respath = '/var/tmp/DB-testings'
+ #datapath = "%s%s" % (DATADIR,'/onset/DB/*/')
+ respath = '/var/tmp/DB-testings'
-benchonset = benchonset(datapath,respath,checkres=True,checkanno=True)
+ benchonset = benchonset(datapath,respath,checkres=True,checkanno=True)
+ benchonset.params = taskparams()
+ benchonset.task = taskonset
-benchonset.params = onset_parameters()
+ benchonset.titles = [ 'mode', 'thres', 'orig', 'expc', 'missd', 'mergd',
+ 'bad', 'doubl', 'corrt', 'GD', 'FP', 'GD-merged', 'FP-pruned',
+ 'prec', 'recl', 'dist' ]
+ benchonset.formats = ["%12s" , "| %6s", "| %6s", "| %6s", "| %6s", "| %6s",
+ "| %6s", "| %6s", "| %6s", "| %8s", "| %8s", "| %8s", "| %8s",
+ "| %6s", "| %6s", "| %6s"]
-benchonset.titles = [ 'mode', 'thres', 'orig', 'expc', 'missd', 'mergd',
-'bad', 'doubl', 'corrt', 'GD', 'FP', 'GD-merged', 'FP-pruned',
-'prec', 'recl', 'dist' ]
-benchonset.formats = ["%12s" , "| %6s", "| %6s", "| %6s", "| %6s", "| %6s",
-"| %6s", "| %6s", "| %6s", "| %8s", "| %8s", "| %8s", "| %8s",
-"| %6s", "| %6s", "| %6s"]
-
-#benchonset.run_bench(modes=modes,thresholds=thresholds)
-benchonset.auto_learn(modes=modes)
-
-# gatherdata
-#act_on_data(my_print,datapath,respath,suffix='.txt',filter='f -name \'*.wav\'')
-# gatherthreshold
-# gathermodes
-# comparediffs
-# gatherdiffs
-
-
+ try:
+ benchonset.auto_learn(modes=modes)
+ #benchonset.run_bench(modes=modes)
+ except KeyboardInterrupt:
+ sys.exit(1)
--- a/python/bench-pitch
+++ b/python/bench-pitch
@@ -5,7 +5,7 @@
class benchpitch(bench):
- def compute_file(self,input,output):
+ def file_exec(self,input,output):
filetask = self.task(input,params=self.params)
computed_data = filetask.compute_all()
results = filetask.eval(computed_data)
@@ -12,38 +12,31 @@
self.results.append(results)
truth = filetask.gettruth()
#print input, results, results - float(input.split('.')[-2])- self.pretty_print((self.params.mode, truth,
+ self.pretty_print((self.params.pitchmode, truth,
truth - results[0], results[0],
truth - results[1], results[1]))
- def compute_data(self):
- self.orig, self.missed, self.merged, self.expc, \
- self.bad, self.doubled = 0, 0, 0, 0, 0, 0
- act_on_data(self.compute_file,self.datadir, \
- suffix='',filter='f -name \'*.wav\'')
-
- def compute_results(self,truth):
- for i in self.results: print i
-
- def run_bench(self,modes=['dual']):
+ def run_bench(self,modes=['schmitt']):
self.modes = modes
self.pretty_print(self.titles)
for mode in self.modes:
- self.params.mode = mode
- self.compute_data()
- #self.compute_results()
- #self.pretty_print(self.results)
+ self.params.pitchmode = mode
+ self.dir_exec()
+ self.dir_eval()
+ self.dir_plot()
if __name__ == "__main__":
import sys
if len(sys.argv) > 1: datapath = sys.argv[1]
else: print "error: a path is required"; sys.exit(1)
+ if len(sys.argv) > 2:
+ for each in sys.argv[3:-1]: print each
+ modes = ['yin', 'schmitt', 'mcomb', 'fcomb']
- modes = ['schmitt', 'yin', 'mcomb', 'fcomb']
-
benchpitch = benchpitch(datapath)
benchpitch.params = taskparams()
benchpitch.task = taskpitch
+
benchpitch.titles = [ 'mode', 'thres', 'avg', 'avgdist' ]
benchpitch.formats = ["%12s" , "| %6s", "| %6s", "| %6s", "| %6s", "| %6s" ]