def post_(id_item, fp,token):
classpath= os.path.join(settings.BASE_DIR, 'plugins_script',"speaker_extractor","lium_spkdiarization-8.4.1.jar" )
ubm= os.path.join(settings.MEDIA_ROOT,"models/audio/globals/ubm.gmm")
id_persona=None
result=segfile_compact_name2(fp)
uniform_tag_ids_arr =[]
for res in result:
try:
name=res[0]
feature_path = None
model = None
p=re.compile('[A-Z]')
st=int( float(res[1]))#*1000 )
dur=int (float(res[2]))#*1000)
feature_path = split4diarization(os.path.join(settings.MEDIA_ROOT, 'items', str(id_item), 'audio.wav'),st,dur,"/tmp/model.wav")
inst = create_instance('audio', False, token=token) # impostare id modello
set_instance_feature(inst['id'], feature_path, token)
mai=p.findall(name)
f_name="Unknown"
s_name=name + '_' + str(id_item)
print "f_name, s_name ", f_name, s_name
# corregge il problema delle identita' duplicate
persona = None
#feature_path = split4diarization(fp,st,dur,"/tmp/model_wav")
if f_name == "Unknown":
id_persona=persona["id"]
tag=create_tag(id_item,id_persona, "speaker", token)
dtag=create_dtag(tag["id"], st*10, dur*10, token=token)
uniform_tag = create_tag(id_item, id_persona, "face+speaker", token)
uniform_tag_ids_arr.append(uniform_tag['id'])
except Exception, e:
print e
def __generate_instances(auth_params, func_params):
"""
Funzione utilizzata per estrarre le istanze da un file audio e
salvarle nel database senza associarle ad alcuna entita'/modello.
Le istanze sono ottenute applicando prima una conversione sulla traccia
audio originale e successivamente splittandola sul parlato delle persone.
Il parametro generato dalle funzioni contiene i dati associati al nuovo
"""
try:
# extract all needed parameters
item_id = func_params['id']
item_path = os.path.join(get_media_root(), func_params['file'])
temp_root = os.path.join('/tmp', 'speak_recog_' + str(item_id))
dest_path = os.path.join(temp_root, 'audio.wav')
properties_path = dest_path.split(".")[-2]+'.properties'
settings_path = os.path.join(get_media_root(), 'models/audio/globals/settings.properties')
token = auth_params.get('token', '1234')
#print 'item_id', item_id
#print 'item_path', item_path
#print 'temp_root', temp_root
#print 'dest_path', dest_path
#print 'properties_path', properties_path
#print 'settings_path', settings_path
# create a directory for temporary files for diarization phase
if os.path.exists(temp_root):
shutil.rmtree(temp_root)
os.mkdir(temp_root)
os.chmod(temp_root, 0o777)
os.mkdir(temp_root + '/out')
os.chmod(temp_root + '/out', 0o777)
# extract the item audio and convert it in the wav format
command = '/usr/bin/ffmpeg -y -i "' + item_path + '"'
command += ' -strict -2 -acodec pcm_s16le -ac 1 -ar 16000 '
command += '"' + dest_path + '"'
subprocess.call(command, shell=True)
#print command
# generate the local settings file
with open(properties_path, "w") as f:
f.write("fileName=" + dest_path)
with open(settings_path) as fp:
for line in fp:
f.write(line)
#print line
f.writelines("outputRoot=" + temp_root + "/out/")
# applica la fase di diarization e calcola gli spezzoni audio
diarization(properties_path) # salva gli spezzoni audio nel file di settings?
# extract the audio portions and save them in a temp directory
occurrences = segfile_compact_name2(temp_root + '/out/audio')
for o in occurrences:
start = int(o[1])*10
duration = int(o[2])*10
# genera lo spezzone a partire dal file audio
feature_path = temp_root + '/out/segment_' + str(item_id) + '_' + str(o[1]) + '.wav'
split4diarization(dest_path, start, duration, feature_path)
# genera il tag e il dtag da associare all'istanza
persona = create_person('Unknown', o[0] + '_' + str(item_id), token=token)
tag = create_tag(item_id, persona['id'], 'speaker', token=token)
dtag = create_dtag(tag['id'], start, duration, token=token)
# crea l'istanza e la carica nel database
inst = create_instance('audio', False, token=token)
set_instance_feature(inst['id'], feature_path, token=token)
# remove all temporary directories and files
#os.remove(temp_path)
except Exception as e:
print e
def post_di_esempio(id_item, fp,token):
print "***** PLUGIN SPEAKER RECOGNITION: POST DI ESEMPIO ---> Start"
classpath= os.path.join(get_base_dir(), 'plugins_script',"speaker_extractor","lium_spkdiarization-8.4.1.jar" )
ubm= os.path.join(get_media_root(),"models/audio/globals/ubm.gmm")
id_persona=None
#id_item=3601
#name_p=open(name_file, "r")
#name_p_list=name_p.readlines()
#result=make_name_compact(fp) #result simile a [[nome,start,stop][nome,start,stop]]
result=segfile_compact_name2(fp)
print "result=",result
uniform_tag_ids_arr =[]
for res in result:
try:
name=res[0]
feature_path = None
model = None
p=re.compile('[A-Z]')
print "find name ", name
st=int( float(res[1]))#*1000 )
print "start ", st
dur=int (float(res[2]))#*1000)
print "dur ",dur
#feature_path = split4diarization(fp,st,dur,fp+"_"+str(st)+"_"+str(dur))
feature_path = split4diarization(os.path.join(get_media_root(), 'items', str(id_item), 'audio.wav'),st,dur,"/tmp/model.wav")
print "feature_path ", feature_path
inst = create_instance('audio', False, token=token) # impostare id modello
set_instance_feature(inst['id'], feature_path, token)
#if name.find("GiacomoMameli")>-1:
# print "trovato giacomino"
# id_persona=create_person("Giacomo","Mameli", token)["id"]
# #createTagKeyword(id_item, 'Giacomo', 'Mameli', token)
# print "id persona ",id_persona
#else:
if True:
mai=p.findall(name)
print "mai ",mai
#if len(mai)==2:
if True:
#f_name=name.split(mai[1])[0]
#s_name=mai[1]+name.split(mai[1])[1]
f_name="Unknown"
s_name=name + '_' + str(id_item)
print "f_name, s_name ", f_name, s_name
# corregge il problema delle identita' duplicate
persona = None
#feature_path = split4diarization(fp,st,dur,"/tmp/model_wav")
if f_name == "Unknown":
print "name Unknown"
persona=create_person(f_name,s_name, token)
#feature_path = split4diarization(fp,0,None,"/tmp/model_wav")
#model_path=_build_model("/tmp/model.wav", None, [f_name, s_name],dur, token) # crea il modello associato alla persona sconosciuta
#model_path= create_new_model (classpath, ubm,feature_path, 0, dur,None) #f_name+"_"+ s_name)
#print "model_path ",model_path
#model = create_model(persona['id'], 'audio', f_name + ' ' + s_name, last_update=None, token=token)
##set_model_file(model['id'], model_path, token=token)
#else:
# print " persona nota ", f_name, s_name
# persona=create_person(f_name, s_name, token)
# print "persona ", persona
# # list out of bound
# model = get_models_by_entity(persona['id'], token=token)[0]
# print "model ", model
# create a tag for person name
#createTagKeyword(id_item, persona['first_name'], persona['last_name'], token)
print "calcolo id persona"
id_persona=persona["id"]
print "id_persona ",id_persona
#else:
# persona=create_person("Il","Manutentore", token)
# id_persona=persona["id"]
print "create_tag id_item,id_persona ", id_item, " ",id_persona
tag=create_tag(id_item,id_persona, "speaker", token)
print "tag ",tag
dtag=create_dtag(tag["id"], st*10, dur*10, token=token)
print "dtag ",dtag
uniform_tag = create_tag(id_item, id_persona, "face+speaker", token)
print 'uniform tag', uniform_tag
uniform_tag_ids_arr.append(uniform_tag['id'])
# update the instance with the model id
print 'instance, model', inst, model
#edit_instance(inst['id'], model_id=model['id'], token=token)
print 'ascallo'
except Exception, e:
print e
