def run(self, fname):
baseFname, ext = os.path.splitext(os.path.basename(fname))
wavfname, created = util.docserver_get_wav_filename(self.musicbrainz_id)
panelWidth = 900 # pixels
panelHeight = 255 # pixels
zoomlevels = [4, 8, 16, 32] # seconds
options = coll.namedtuple('options', 'image_height fft_size image_width')
options.image_height = panelHeight
options.image_width = panelWidth
options.fft_size = 31
ret = {}
for zoom in zoomlevels:
wvFile = wave.Wave_read(wavfname)
framerate = wvFile.getframerate()
totalframes = wvFile.getnframes()
# We want this many frames per file at this zoom level.
framesperimage = framerate * zoom
wfname = "waveform%s" % zoom
specname = "spectrum%s" % zoom
wfdata = []
specdata = []
sumframes = 0
while sumframes < totalframes:
fp, smallname = tempfile.mkstemp(".wav")
os.close(fp)
data = wvFile.readframes(framesperimage)
wavout = wave.open(smallname, "wb")
# This will set nframes, but writeframes resets it
wavout.setparams(wvFile.getparams())
wavout.writeframes(data)
wavout.close()
sumframes += framesperimage
specio = StringIO()
# Set the name attr so that PIL gets the filetype hint
specio.name = "spec.png"
wavio = StringIO()
wavio.name = "wav.png"
w2png.genimages(smallname, wavio, specio, options)
os.unlink(smallname)
specdata.append(specio.getvalue())
wfdata.append(wavio.getvalue())
ret[wfname] = wfdata
ret[specname] = specdata
ret["smallfull"] = self.make_mini(wavfname)
if created:
os.unlink(wavfname)
return ret
def make_segments(file_id):
thefile = models.File.objects.get(pk=file_id)
patterns = thefile.pattern_set.all()
wav_file, wav_created = util.docserver_get_wav_filename(thefile.mbid)
print("Making segments for file %s" % thefile)
numpat = len(patterns)
print("Got %s segments to do" % numpat)
wav_in = wave.open(wav_file, 'rb')
params = wav_in.getparams()
samplerate = wav_in.getframerate()
with transaction.atomic():
for i, p in enumerate(patterns, 1):
if i % 100 == 0:
print(" - [%s]: Done %s/%s" % (file_id, i, numpat))
r_start = round(p.start_time, 1)
r_end = round(p.end_time, 1)
qs = models.Segment.objects.filter(file=thefile,
rounded_start=r_start,
rounded_end=r_end)
if qs.exists():
# we already have a segment for this start time and end time
s = qs.get()
p.segment = s
p.save()
else:
start_str = str(r_start)
end_str = str(r_end)
fname = "%s-%s.wav" % (start_str, end_str)
dname = start_str[0]
full_dir = os.path.join(ROOT_DIR, str(thefile.id), dname)
full_path = os.path.join(full_dir, fname)
try:
os.makedirs(full_dir)
except os.error:
pass
sframe = int(math.floor(r_start * samplerate))
eframe = int(math.ceil(r_end * samplerate))
wav_in.setpos(sframe)
frames = wav_in.readframes(eframe - sframe)
# create the file, save it, add a entry
# args = ["ffmpeg", "-i", wav_file, "-ss", str(r_start), "-t", str((r_end-r_start)), full_path]
# proc = subprocess.Popen(args, stdin=subprocess.PIPE, stdout=subprocess.PIPE)
# proc.communicate()
wav_out = wave.open(full_path, 'wb')
wav_out.setparams(params)
wav_out.writeframes(frames)
s = models.Segment.objects.create(file=thefile,
rounded_start=r_start,
rounded_end=r_end,
segment_path=full_path)
p.segment = s
p.save()
if wav_created:
os.unlink(wav_file)
def run(self, musicbrainzid, fname):
wavfname, created = util.docserver_get_wav_filename(musicbrainzid)
ret = {}
ret["smallfull"] = self.make_mini(wavfname)
if created:
os.unlink(wavfname)
return ret
def run(self, musicbrainzid, fname):
wavfname, created = util.docserver_get_wav_filename(musicbrainzid)
ret = {}
ret["smallfull"] = self.make_mini(wavfname)
if created:
os.unlink(wavfname)
return ret
def make_segments(file_id):
thefile = models.File.objects.get(pk=file_id)
patterns = thefile.pattern_set.all()
wav_file, wav_created = util.docserver_get_wav_filename(thefile.mbid)
print "Making segments for file %s" % thefile
numpat = len(patterns)
print "Got %s segments to do" % numpat
wav_in = wave.open(wav_file, 'rb')
params = wav_in.getparams()
samplerate = wav_in.getframerate()
with transaction.atomic():
for i, p in enumerate(patterns, 1):
if i % 100 == 0:
print " - [%s]: Done %s/%s" % (file_id, i, numpat)
r_start = round(p.start_time, 1)
r_end = round(p.end_time, 1)
qs = models.Segment.objects.filter(file=thefile, rounded_start=r_start, rounded_end=r_end)
if qs.exists():
# we already have a segment for this start time and end time
s = qs.get()
p.segment = s
p.save()
else:
start_str = str(r_start)
end_str = str(r_end)
fname = "%s-%s.wav" % (start_str, end_str)
dname = start_str[0]
full_dir = os.path.join(ROOT_DIR, str(thefile.id), dname)
full_path = os.path.join(full_dir, fname)
try:
os.makedirs(full_dir)
except os.error:
pass
sframe = int(math.floor(r_start * samplerate))
eframe = int(math.ceil(r_end * samplerate))
wav_in.setpos(sframe)
frames = wav_in.readframes(eframe-sframe)
# create the file, save it, add a entry
# args = ["ffmpeg", "-i", wav_file, "-ss", str(r_start), "-t", str((r_end-r_start)), full_path]
# proc = subprocess.Popen(args, stdin=subprocess.PIPE, stdout=subprocess.PIPE)
# proc.communicate()
wav_out = wave.open(full_path, 'wb')
wav_out.setparams(params)
wav_out.writeframes(frames)
s = models.Segment.objects.create(file=thefile, rounded_start=r_start, rounded_end=r_end, segment_path=full_path)
p.segment = s
p.save()
if wav_created:
os.unlink(wav_file)
def fix_segments(file_id):
thefile = models.File.objects.get(pk=file_id)
patterns = thefile.pattern_set.all()
wav_file, wav_created = util.docserver_get_wav_filename(thefile.mbid)
print("Making segments for file %s" % thefile)
numpat = len(patterns)
print("Got %s segments to do" % numpat)
wav_in = wave.open(wav_file, 'rb')
params = wav_in.getparams()
samplerate = wav_in.getframerate()
with transaction.atomic():
for i, p in enumerate(patterns, 1):
if i % 100 == 0:
print(" - [%s]: Done %s/%s" % (file_id, i, numpat))
r_start = round(p.start_time, 1)
r_end = round(p.end_time, 1)
qs = models.Segment.objects.filter(file=thefile,
rounded_start=r_start,
rounded_end=r_end)
if qs.exists():
start_str = str(r_start)
end_str = str(r_end)
fname = "%s-%s.wav" % (start_str, end_str)
dname = start_str[0]
full_dir = os.path.join(ROOT_DIR, str(thefile.id), dname)
full_path = os.path.join(full_dir, fname)
mp3_path = full_path[:-3] + "mp3"
if os.path.exists(mp3_path) and os.stat(mp3_path).st_size == 0:
print("deleting %s" % mp3_path)
os.unlink(mp3_path)
sframe = int(math.floor(r_start * samplerate))
eframe = int(math.ceil(r_end * samplerate))
wav_in.setpos(sframe)
frames = wav_in.readframes(eframe - sframe)
wav_out = wave.open(full_path, 'wb')
wav_out.setparams(params)
wav_out.writeframes(frames)
if wav_created:
os.unlink(wav_file)
def fix_segments(file_id):
thefile = models.File.objects.get(pk=file_id)
patterns = thefile.pattern_set.all()
wav_file, wav_created = util.docserver_get_wav_filename(thefile.mbid)
print "Making segments for file %s" % thefile
numpat = len(patterns)
print "Got %s segments to do" % numpat
wav_in = wave.open(wav_file, 'rb')
params = wav_in.getparams()
samplerate = wav_in.getframerate()
with transaction.atomic():
for i, p in enumerate(patterns, 1):
if i % 100 == 0:
print " - [%s]: Done %s/%s" % (file_id, i, numpat)
r_start = round(p.start_time, 1)
r_end = round(p.end_time, 1)
qs = models.Segment.objects.filter(file=thefile, rounded_start=r_start, rounded_end=r_end)
if qs.exists():
s = qs.get()
start_str = str(r_start)
end_str = str(r_end)
fname = "%s-%s.wav" % (start_str, end_str)
dname = start_str[0]
full_dir = os.path.join(ROOT_DIR, str(thefile.id), dname)
full_path = os.path.join(full_dir, fname)
mp3_path = full_path[:-3]+"mp3"
if os.path.exists(mp3_path) and os.stat(mp3_path).st_size == 0:
print "deleting", mp3_path
os.unlink(mp3_path)
sframe = int(math.floor(r_start * samplerate))
eframe = int(math.ceil(r_end * samplerate))
wav_in.setpos(sframe)
frames = wav_in.readframes(eframe-sframe)
wav_out = wave.open(full_path, 'wb')
wav_out.setparams(params)
wav_out.writeframes(frames)
if wav_created:
os.unlink(wav_file)
def run(self, musicbrainzid, fname):
baseFname, ext = os.path.splitext(os.path.basename(fname))
wavfname, created = util.docserver_get_wav_filename(musicbrainzid)
panelWidth = 900 # pixels
panelHeight = 255 # pixels
zoomlevels = self._zoom_levels # seconds
options = coll.namedtuple("options", "image_height fft_size image_width f_min f_max scale_exp pallete")
options.image_height = panelHeight
options.fft_size = self._fft_size
options.f_min = self._f_min
options.f_max = self._f_max
options.pallete = self._pallete
options.scale_exp = self._scale_exp
ret = {}
for zoom in zoomlevels:
# At the beginning of each zoom level we reset the image_width
# since we are modifying it at the end of the last zoom level
options.image_width = panelWidth
wvFile = wave.Wave_read(wavfname)
framerate = wvFile.getframerate()
totalframes = wvFile.getnframes()
# We want this many frames per file at this zoom level.
framesperimage = framerate * zoom
wfname = "waveform%s" % zoom
specname = "spectrum%s" % zoom
wfdata = []
specdata = []
sumframes = 0
while sumframes < totalframes:
if sumframes + framesperimage > totalframes:
remaining_frames = totalframes - sumframes
options.image_width = options.image_width * remaining_frames / framesperimage
else:
remaining_frames = framesperimage
fp, smallname = tempfile.mkstemp(".wav")
os.close(fp)
data = wvFile.readframes(remaining_frames)
wavout = wave.open(smallname, "wb")
# This will set nframes, but writeframes resets it
wavout.setparams(wvFile.getparams())
wavout.writeframes(data)
wavout.close()
sumframes += framesperimage
specio = StringIO()
# Set the name attr so that PIL gets the filetype hint
specio.name = "spec.png"
wavio = StringIO()
wavio.name = "wav.png"
w2png.genimages(smallname, wavio, specio, options)
os.unlink(smallname)
specdata.append(specio.getvalue())
wfdata.append(wavio.getvalue())
ret[wfname] = wfdata
ret[specname] = specdata
ret["smallfull"] = self.make_mini(wavfname)
if created:
os.unlink(wavfname)
return ret
def run(self, musicbrainzid, fname):
baseFname, ext = os.path.splitext(os.path.basename(fname))
wavfname, created = util.docserver_get_wav_filename(musicbrainzid)
panelWidth = 900 # pixels
panelHeight = 255 # pixels
zoomlevels = self._zoom_levels # seconds
options = coll.namedtuple(
'options',
'image_height fft_size image_width f_min f_max scale_exp pallete')
options.image_height = panelHeight
options.fft_size = self._fft_size
options.f_min = self._f_min
options.f_max = self._f_max
options.pallete = self._pallete
options.scale_exp = self._scale_exp
ret = {}
for zoom in zoomlevels:
# At the beginning of each zoom level we reset the image_width
# since we are modifying it at the end of the last zoom level
options.image_width = panelWidth
wvFile = wave.Wave_read(wavfname)
framerate = wvFile.getframerate()
totalframes = wvFile.getnframes()
# We want this many frames per file at this zoom level.
framesperimage = framerate * zoom
wfname = "waveform%s" % zoom
specname = "spectrum%s" % zoom
inv_mfcc_name = "inv_mfcc_spectrum%s" % zoom
wfdata = []
specdata = []
inv_mfcc_data = []
sumframes = 0
while sumframes < totalframes:
if sumframes + framesperimage > totalframes:
remaining_frames = (totalframes - sumframes)
options.image_width = options.image_width * remaining_frames / framesperimage
else:
remaining_frames = framesperimage
fp, smallname = tempfile.mkstemp(".wav")
os.close(fp)
data = wvFile.readframes(remaining_frames)
wavout = wave.open(smallname, "wb")
# This will set nframes, but writeframes resets it
wavout.setparams(wvFile.getparams())
wavout.writeframes(data)
wavout.close()
sumframes += framesperimage
specio = io.BytesIO()
# Set the name attr so that PIL gets the filetype hint
specio.name = "spec.png"
wavio = io.BytesIO()
wavio.name = "wav.png"
in_mfcc_io = io.BytesIO()
in_mfcc_io.name = "melspec.png"
w2png.genimages(smallname, wavio, specio, in_mfcc_io, options)
os.unlink(smallname)
specdata.append(specio.getvalue())
wfdata.append(wavio.getvalue())
inv_mfcc_data.append(in_mfcc_io.getvalue())
ret[wfname] = wfdata
ret[specname] = specdata
ret[inv_mfcc_name] = inv_mfcc_data
ret["smallfull"] = self.make_mini(wavfname)
if created:
os.unlink(wavfname)
return ret
def run(self, musicbrainzid, fname):
#### output
ret = {'alignedLyricsSyllables': {}, 'sectionlinks': {}}
recIDoutputDir = os.path.join(self.dataOutputDir, musicbrainzid)
if not os.path.isdir(recIDoutputDir):
os.mkdir(recIDoutputDir)
w = getWork(musicbrainzid)
# TODO: mark IDs with second verse symbTr missing and get from a separate reposotory
# on dunya server. API might be outdated, as some symbtr names are changed. better use line below
# symbtrtxtURI = util.docserver_get_symbtrtxt(w['mbid'])
# prefer to fetch symbTr directly from github, as Dunya might not be updated with lyrics changes, etc.
symbtrtxtURI = downloadSymbTr(w['mbid'], recIDoutputDir,
self.hasSecondVerse)
if not symbtrtxtURI:
sys.exit("no symbTr found for work {}".format(w['mbid']))
############ score section metadata
if WITH_SECTION_ANNOTATIONS: # becasue complying with score metadata for symbTr1, on which annotations are done
dir_ = 'scores/metadata/'
sectionMetadataDict = get_section_metadata_dict(
w['mbid'], dir_, recIDoutputDir,
self.hasSectionNumberDiscrepancy)
else:
sectionMetadataDict = dunya.docserver.get_document_as_json(
w['mbid'], "metadata", "metadata", 1,
version="0.1") # NOTE: this is default for note onsets
##################### audio section annotation or result from section linking
if WITH_SECTION_ANNOTATIONS: # because complying with section annotations
try:
dir_ = 'audio_metadata/'
sectionLinksDict = get_section_annotaions_dict(
musicbrainzid, dir_, self.dataOutputDir,
self.hasSectionNumberDiscrepancy)
except Exception as e:
sys.exit("no section annotations found for audio {} ".format(
musicbrainzid))
else:
try:
sectionLinksDict = dunya.docserver.get_document_as_json(
musicbrainzid,
"joinanalysis",
"sections",
1,
version="0.2")
except dunya.conn.HTTPError:
logging.error("section link {} missing".format(musicbrainzid))
return ret
if not sectionLinksDict:
logging.error("section link {} missing".format(musicbrainzid))
return ret
try:
extractedPitch = dunya.docserver.get_document_as_json(
musicbrainzid, "jointanalysis", "pitch", 1, version="0.1")
extractedPitch = extractedPitch['pitch']
except Exception as e:
sys.exit("no initialmakampitch series could be downloaded. ")
if ON_SERVER:
from docserver import util
wavFileURI, created = util.docserver_get_wav_filename(
musicbrainzid)
#
else:
wavFileURI = fetch_audio_wav(self.dataOutputDir, musicbrainzid,
ParametersAlgo.POLYPHONIC)
wavFileURIMono = stereoToMono(wavFileURI)
if ParametersAlgo.WITH_ORACLE_ONSETS == 1:
fetchNoteOnsetFile(musicbrainzid, recIDoutputDir,
ParametersAlgo.ANNOTATION_RULES_ONSETS_EXT)
recording = loadMakamRecording(musicbrainzid, wavFileURIMono,
symbtrtxtURI, sectionMetadataDict,
sectionLinksDict,
WITH_SECTION_ANNOTATIONS)
lyricsAligner = LyricsAligner(recording, WITH_SECTION_ANNOTATIONS,
PATH_TO_HCOPY)
totalDetectedTokenList, sectionLinksDict = lyricsAligner.alignRecording(
extractedPitch, self.dataOutputDir)
# lyricsAligner.evalAccuracy()
ret['alignedLyricsSyllables'] = totalDetectedTokenList
ret['sectionlinks'] = sectionLinksDict
print(ret)
return ret
def run(self, musicbrainzid, fname):
#### output
ret = {'alignedLyricsSyllables': {}, 'sectionlinks': {}}
recIDoutputDir = os.path.join(self.dataOutputDir, musicbrainzid)
if not os.path.isdir(recIDoutputDir):
os.mkdir(recIDoutputDir)
w = getWork(musicbrainzid)
# TODO: mark IDs with second verse symbTr missing and get from a separate reposotory
# on dunya server. API might be outdated, as some symbtr names are changed. better use line below
# symbtrtxtURI = util.docserver_get_symbtrtxt(w['mbid'])
# prefer to fetch symbTr directly from github, as Dunya might not be updated with lyrics changes, etc.
symbtrtxtURI = downloadSymbTr(w['mbid'], recIDoutputDir, self.hasSecondVerse)
if not symbtrtxtURI:
sys.exit("no symbTr found for work {}".format(w['mbid']))
############ score section metadata
if WITH_SECTION_ANNOTATIONS: # becasue complying with score metadata for symbTr1, on which annotations are done
dir_ = 'scores/metadata/'
sectionMetadataDict = get_section_metadata_dict(w['mbid'], dir_, recIDoutputDir,
self.hasSectionNumberDiscrepancy)
else:
sectionMetadataDict = dunya.docserver.get_document_as_json(w['mbid'], "metadata", "metadata", 1,
version="0.1") # NOTE: this is default for note onsets
##################### audio section annotation or result from section linking
if WITH_SECTION_ANNOTATIONS: # because complying with section annotations
try:
dir_ = 'audio_metadata/'
sectionLinksDict = get_section_annotaions_dict(musicbrainzid, dir_, self.dataOutputDir,
self.hasSectionNumberDiscrepancy)
except Exception as e:
sys.exit("no section annotations found for audio {} ".format(musicbrainzid))
else:
try:
sectionLinksDict = dunya.docserver.get_document_as_json(musicbrainzid, "joinanalysis", "sections", 1,
version="0.2")
except dunya.conn.HTTPError:
logging.error("section link {} missing".format(musicbrainzid))
return ret
if not sectionLinksDict:
logging.error("section link {} missing".format(musicbrainzid))
return ret
try:
extractedPitch = dunya.docserver.get_document_as_json(musicbrainzid, "jointanalysis", "pitch", 1,
version="0.1")
extractedPitch = extractedPitch['pitch']
except Exception as e:
sys.exit("no initialmakampitch series could be downloaded. ")
if ON_SERVER:
from docserver import util
wavFileURI, created = util.docserver_get_wav_filename(musicbrainzid)
#
else:
wavFileURI = fetch_audio_wav(self.dataOutputDir, musicbrainzid, ParametersAlgo.POLYPHONIC)
wavFileURIMono = stereoToMono(wavFileURI)
if ParametersAlgo.WITH_ORACLE_ONSETS == 1:
fetchNoteOnsetFile(musicbrainzid, recIDoutputDir, ParametersAlgo.ANNOTATION_RULES_ONSETS_EXT)
recording = loadMakamRecording(musicbrainzid, wavFileURIMono, symbtrtxtURI, sectionMetadataDict,
sectionLinksDict, WITH_SECTION_ANNOTATIONS)
lyricsAligner = LyricsAligner(recording, WITH_SECTION_ANNOTATIONS, PATH_TO_HCOPY)
totalDetectedTokenList, sectionLinksDict = lyricsAligner.alignRecording(extractedPitch, self.dataOutputDir)
# lyricsAligner.evalAccuracy()
ret['alignedLyricsSyllables'] = totalDetectedTokenList
ret['sectionlinks'] = sectionLinksDict
print(ret)
return ret
logging.error("section link {} missing".format(musicbrainzid))
return ret
if not sectionLinksDict:
logging.error("section link {} missing".format(musicbrainzid))
return ret
try:
extractedPitch = dunya.docserver.get_document_as_json(
musicbrainzid, "jointanalysis", "pitch", 1, version="0.1")
extractedPitch = extractedPitch['pitch']
except Exception, e:
sys.exit("no initialmakampitch series could be downloaded. ")
if ON_SERVER:
from docserver import util
wavFileURI, created = util.docserver_get_wav_filename(
musicbrainzid)
#
else:
wavFileURI = fetch_audio_wav(self.dataOutputDir, musicbrainzid,
ParametersAlgo.POLYPHONIC)
wavFileURIMono = stereoToMono(wavFileURI)
if ParametersAlgo.WITH_ORACLE_ONSETS == 1:
fetchNoteOnsetFile(musicbrainzid, recIDoutputDir,
ParametersAlgo.ANNOTATION_RULES_ONSETS_EXT)
recording = loadMakamRecording(musicbrainzid, wavFileURIMono,
symbtrtxtURI, sectionMetadataDict,
sectionLinksDict,
