def process(request, audio_id):
# query db for the audio file
audio = get_object_or_404(Audio, pk=audio_id)
guitar_model = True
try:
frets = int(request.GET['frets'])
capo = int(request.GET['capo'])
tuning = request.GET['tuning']
pitch_sanitize_prune = True if request.GET['sanitize'] == 'prune' else False
except KeyError:
# don't use a guitar model for polyphonic transcription
guitar_model = False
db_fields = {'fk_audio': audio}
if guitar_model:
guitar = GuitarModel(
num_frets=frets,
capo=capo,
tuning=tuning
)
guitar.save()
db_fields['fk_guitar'] = guitar
db_fields['pitch_sanitize_prune'] = pitch_sanitize_prune
pestimator = PitchDetect(**db_fields)
# writing to the database writes the analysis start timestamp
pestimator.save()
# TODO: create spinner on the interface
audio_url = request.build_absolute_uri(audio.audio_file.url)
pestimator.estimate_pitches(audio_url)
# redirect to xml display
return HttpResponseRedirect('/media/%s' % pestimator.fk_pmei.mei_file.name)
def transcribe(self, frets, capo, tuning, pitch_sanitize_prune, audio_url):
# get path of audio file being transcribed
path = os.path.join(settings.MEDIA_ROOT, str(self.fk_audio.audio_file))
####################
# PITCH ESTIMATION #
####################
guitar = GuitarModel(
num_frets=frets,
capo=capo,
tuning=tuning
)
guitar.save()
pestimator = PitchDetect(fk_audio=self.fk_audio, fk_guitar=guitar, pitch_sanitize_prune=pitch_sanitize_prune)
# writing to the database writes the analysis start timestamp
pestimator.save()
pestimator.estimate_pitches(audio_url)
# attach the pitch detection analysis information to the transcription model
self.fk_pid = pestimator
########################
# TABLATURE GENERATION #
########################
taber = Tabulate(fk_pmei=self.fk_pid.fk_pmei, fk_guitar=guitar, pitch_sanitize_prune=pitch_sanitize_prune)
# writing to the database writes the analysis start timestamp
taber.save()
taber.gen_tab()
# attach the tablature to the transcription model
self.fk_tabid = taber
self.save()
def transcribe(self, frets, capo, tuning, pitch_sanitize_prune, audio_url):
# get path of audio file being transcribed
path = os.path.join(settings.MEDIA_ROOT, str(self.fk_audio.audio_file))
####################
# PITCH ESTIMATION #
####################
guitar = GuitarModel(num_frets=frets, capo=capo, tuning=tuning)
guitar.save()
pestimator = PitchDetect(fk_audio=self.fk_audio,
fk_guitar=guitar,
pitch_sanitize_prune=pitch_sanitize_prune)
# writing to the database writes the analysis start timestamp
pestimator.save()
pestimator.estimate_pitches(audio_url)
# attach the pitch detection analysis information to the transcription model
self.fk_pid = pestimator
########################
# TABLATURE GENERATION #
########################
taber = Tabulate(fk_pmei=self.fk_pid.fk_pmei,
fk_guitar=guitar,
pitch_sanitize_prune=pitch_sanitize_prune)
# writing to the database writes the analysis start timestamp
taber.save()
taber.gen_tab()
# attach the tablature to the transcription model
self.fk_tabid = taber
self.save()
