class Capture(object):
_ask_data = None
_captor = None
_save_path = None
_processor_sleep_time = 0.01
_process_buf = None
_sample_rate = 16000
def __init__(self, min_time, max_time, path=None):
if path is not None:
if not os.path.exists(path):
raise FileNotFoundError('"{}" doesn\'t exist'.format(path))
if not os.path.isdir(path):
raise FileNotFoundError('"{}" isn\'t a directory'.format(path))
monitorhook = open('monitorhook.log', 'w')
monitorhook.write('{:.0f}'.format(time.time()))
monitorhook.close()
self._save_path = path
self._ask_data = threading.Event()
self._captor = Captor(min_time, max_time, self._ask_data,
self._process)
def start(self):
self._captor.start()
self._process_loop()
def _process(self, data):
self._process_buf = np.frombuffer(data, dtype=np.int16)
def _process_loop(self):
with WavProcessor() as proc:
self._ask_data.set()
while True:
if self._process_buf is None:
# Waiting for data to process
time.sleep(self._processor_sleep_time)
continue
self._ask_data.clear()
if self._save_path:
f_path = os.path.join(
self._save_path,
'record_{:.0f}.wav'.format(time.time()))
wavfile.write(f_path, self._sample_rate, self._process_buf)
logger.info('"{}" saved.'.format(f_path))
logger.info('Start processing.')
monitorhook = open('monitorhook.log', 'w')
monitorhook.write('{:.0f}'.format(time.time()))
monitorhook.close()
predictions = proc.get_predictions(self._sample_rate,
self._process_buf)
logger.info('Predictions: {}'.format(
format_predictions(predictions)))
logger.info('Stop processing.')
self._process_buf = None
self._ask_data.set()
class Capture(object):
_ask_data = None
_captor = None
_save_path = None
_processor_sleep_time = 0.01
_process_buf = None
_sample_rate = 16000
def __init__(self, min_time, max_time, path=None):
if path is not None:
if not os.path.exists(path):
raise FileNotFoundError('"{}" doesn\'t exist'.format(path))
if not os.path.isdir(path):
raise FileNotFoundError('"{}" isn\'t a directory'.format(path))
self._save_path = path
self._ask_data = threading.Event()
self._captor = Captor(min_time, max_time, self._ask_data, self._process)
def start(self):
self._captor.start()
self._process_loop()
def _process(self, data):
self._process_buf = np.frombuffer(data, dtype=np.int16)
def _process_loop(self):
with WavProcessor() as proc:
self._ask_data.set()
while True:
if self._process_buf is None:
# Waiting for data to process
time.sleep(self._processor_sleep_time)
continue
self._ask_data.clear()
if self._save_path:
f_path = os.path.join(
self._save_path, 'record_{:.0f}.wav'.format(time.time())
)
wavfile.write(f_path, self._sample_rate, self._process_buf)
logger.info('"{}" saved.'.format(f_path))
logger.info('Start processing.')
predictions = proc.get_predictions(
self._sample_rate, self._process_buf)
logger.info(
'Predictions: {}'.format(format_predictions(predictions))
)
logger.info('Stop processing.')
self._process_buf = None
self._ask_data.set()
class Daemon(Server):
_process_thread = None
_process_buf = None
_ask_data_event = None
_shutdown_event = None
_captor = None
_sample_rate = 16000
_processor_sleep_time = 0.01
events_queue = None
def __init__(self, *args, **kwargs):
min_time = kwargs.pop('min_capture_time', 5)
max_time = kwargs.pop('max_capture_time', 5)
self._save_path = kwargs.pop('save_path', None)
super(Daemon, self).__init__(*args, **kwargs)
self.events_queue = deque(maxlen=10)
self._ask_data_event = threading.Event()
self._shutdown_event = threading.Event()
self._process_thread = threading.Thread(target=self._process_loop,
name='processor')
self._process_thread.setDaemon(True)
self._captor = Captor(min_time, max_time, self._ask_data_event,
self._process, self._shutdown_event)
def _start_capture(self):
logger.info('Start captor')
self._captor.start()
def _start_process(self):
logger.info('Start processor loop')
self._process_thread.start()
def _process(self, data):
self._process_buf = np.frombuffer(data, dtype=np.int16)
def _on_startup(self):
self._start_process()
self._start_capture()
def _on_shutdown(self):
self._shutdown_event.set()
def _process_loop(self):
with WavProcessor() as proc:
self._ask_data_event.set()
while self.is_running:
if self._process_buf is None:
# Waiting for data to process
time.sleep(self._processor_sleep_time)
continue
self._ask_data_event.clear()
if self._save_path:
f_path = os.path.join(
self._save_path, 'record_{:.0f}.wav'.format(time.time())
)
wavfile.write(f_path, self._sample_rate, self._process_buf)
logger.info('"{}" saved'.format(f_path))
logger.info('Start processing')
predictions = proc.get_predictions(
self._sample_rate, self._process_buf)
formatted = format_predictions(predictions)
logger.info('Predictions: {}'.format(formatted))
self.events_queue.append((datetime.datetime.now(), formatted))
self._send_dh(predictions)
logger.info('Stop processing')
self._process_buf = None
self._ask_data_event.set()
def _send_dh(self, data):
if not self.dh_status.connected:
logger.error('Devicehive is not connected')
return
self.deviceHive.handler.send(data)
class Capture(object):
_ask_data = None
_captor = None
_save_path = None
_processor_sleep_time = 0.01
_process_buf = None
_sample_rate = 16000
def __init__(self, min_time, max_time, path=None):
if path is not None:
if not os.path.exists(path):
raise FileNotFoundError('"{}" doesn\'t exist'.format(path))
if not os.path.isdir(path):
raise FileNotFoundError('"{}" isn\'t a directory'.format(path))
self._save_path = path
self._ask_data = threading.Event()
self._captor = Captor(min_time, max_time, self._ask_data,
self._process)
def start(self):
self._captor.start()
self._process_loop()
def _process(self, data):
self._process_buf = np.frombuffer(data, dtype=np.int16)
def _process_loop(self):
with WavProcessor() as proc:
self._ask_data.set()
while True:
i = 0
pred_values = [
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0
]
while i < 50:
if self._process_buf is None:
# Waiting for data to process
time.sleep(self._processor_sleep_time)
continue
self._ask_data.clear()
if self._save_path:
f_path = os.path.join(
self._save_path,
'record_{:.0f}.wav'.format(time.time()))
wavfile.write(f_path, self._sample_rate,
self._process_buf)
logger.info('"{}" saved.'.format(f_path))
logger.info(str(i) + ' Start processing.')
predictions = proc.get_predictions(self._sample_rate,
self._process_buf)
for p in predictions:
pred_values = [
x + y
for x, y in zip(pred_values, get_labels(p[0]))
]
# print(get_labels(x[0]))
# logger.info(
# 'Predictions: {}'.format(format_predictions(predictions))
# )
logger.info('Stop processing.')
self._process_buf = None
self._ask_data.set()
i += 1
#arr_index = np.argmax(np.array(pred_values))
arr_index = np.argwhere(pred_values == np.amax(pred_values))
arr_index = arr_index.flatten().tolist()
#print(pred_values[int(arr_index)])
#print(arr_index)
# if(isinstance(arr_index,np.int64)):
# print(labels[int(arr_index)])
# else:
for x in arr_index:
print(labels[int(x)])
print(pred_values)
class Daemon(Server):
_dh_thread = None
_process_thread = None
_web_thread = None
_process_buf = None
_ask_data_event = None
_captor = None
_sample_rate = 16000
_processor_sleep_time = 0.01
dh_cfg = None
deviceHive = None
dh_status = None
events_queue = None
base_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'web')
def __init__(self, *args, **kwargs):
kwargs.setdefault('routes', routes)
min_time = kwargs.pop('min_capture_time', 5)
max_time = kwargs.pop('max_capture_time', 5)
self._save_path = kwargs.pop('max_capture_time', None)
super(Daemon, self).__init__(*args, **kwargs)
self.events_queue = deque(maxlen=10)
self.dh_cfg = Config('config.json', update_callback=self._restart_dh)
self.dh_status = DHStatus()
self._web_thread = threading.Thread(
target=self._web_loop, daemon=True, name='web')
self._ask_data_event = threading.Event()
self._process_thread = threading.Thread(
target=self._process_loop, daemon=True, name='processor')
self._captor = Captor(
min_time, max_time, self._ask_data_event, self._process)
def send_dh(self, data):
if not self._is_dh_connected():
logger.warning('Devicehive is not connected')
return
self.deviceHive.handler.send(data)
def start(self):
self._start_web()
self.dh_cfg.load() # this will start DH thread automatically
self._start_capture()
self._start_process()
def _start_web(self):
logger.info('Start server http://{}:{}'.format(*self.server_address))
self._web_thread.start()
def _start_dh(self):
if self._is_dh_connected():
logging.info('Devicehive already started')
return
logger.info('Start devicehive')
self._dh_thread = threading.Thread(
target=self._dh_loop, daemon=True, name='device_hive')
self._dh_thread.start()
def _stop_dh(self):
if not self._is_dh_connected():
logging.info('Devicehive already stopped')
return
# TODO: Now it's only one proper way to call disconnect, we need
# implement better way to do it
self.deviceHive.transport.handler.handler.api.disconnect()
def _restart_dh(self):
if self._is_dh_connected():
self._stop_dh()
self._start_dh()
def _is_dh_connected(self):
return self.dh_status.connected
def _start_capture(self):
logger.info('Start captor')
self._captor.start()
def _start_process(self):
logger.info('Start processor loop')
self._process_thread.start()
def _web_loop(self):
self.serve_forever()
def _dh_loop(self):
self.dh_status.set_connecting()
self.deviceHive = DeviceHive(
DeviceHiveHandler, self.dh_cfg.data['deviceid'])
error = ''
try:
self.dh_status.set_connected()
url = self.dh_cfg.data['url']
refresh_token = self.dh_cfg.data['token']
self.deviceHive.connect(url, refresh_token=refresh_token)
except TransportError as e:
logger.exception(e)
error = str(e)
finally:
self.dh_status.set_disconnected(error)
logger.info('Stop devicehive')
def _process(self, data):
self._process_buf = np.frombuffer(data, dtype=np.int16)
def _process_loop(self):
with WavProcessor() as proc:
self._ask_data_event.set()
while True:
if self._process_buf is None:
# Waiting for data to process
time.sleep(self._processor_sleep_time)
continue
self._ask_data_event.clear()
if self._save_path:
f_path = os.path.join(
self._save_path, 'record_{:.0f}.wav'.format(time.time())
)
wavfile.write(f_path, self._sample_rate, self._process_buf)
logger.info('"{}" saved'.format(f_path))
logger.info('Start processing')
predictions = proc.get_predictions(
self._sample_rate, self._process_buf)
formatted = format_predictions(predictions)
logger.info(
'Predictions: {}'.format(formatted))
self.events_queue.append((datetime.datetime.now(), formatted))
self.send_dh(predictions)
logger.info('Stop processing')
self._process_buf = None
self._ask_data_event.set()
class Capture(object):
_ask_data = None
_captor = None
_save_path = None
_processor_sleep_time = 0.01
_process_buf = None
_sample_rate = 16000
def __init__(self, min_time, max_time, path=None):
if path is not None:
if not os.path.exists(path):
raise FileNotFoundError('"{}" doesn\'t exist'.format(path))
if not os.path.isdir(path):
raise FileNotFoundError('"{}" isn\'t a directory'.format(path))
self._save_path = path
self._ask_data = threading.Event()
self._captor = Captor(min_time, max_time, self._ask_data,
self._process)
def start(self):
self._captor.start()
self._process_loop()
def _process(self, data):
self._process_buf = np.frombuffer(data, dtype=np.int16)
def _process_loop(self):
with WavProcessor() as proc:
self._ask_data.set()
try:
producer = KafkaProducer(
bootstrap_servers=config['KAFKA']['bootstrap_servers'])
except NoBrokersAvailable:
producer = None
print("No brokers available, running off-line")
while True:
if self._process_buf is None:
# Waiting for data to process
time.sleep(self._processor_sleep_time)
continue
self._ask_data.clear()
if self._save_path:
f_path = os.path.join(
self._save_path,
'record_{:.0f}.wav'.format(time.time()))
wavfile.write(f_path, self._sample_rate, self._process_buf)
predictions = proc.get_predictions(self._sample_rate,
self._process_buf)
for prediction in predictions:
if prediction[1] > 0.4:
if producer is not None:
producer.send(config['KAFKA']['topic'],
bytes(str(prediction[0]).encode()))
print(prediction[0])
self._process_buf = None
self._ask_data.set()
class Daemon(Server):
_dh_thread = None
_process_thread = None
_web_thread = None
_process_buf = None
_ask_data_event = None
_captor = None
_sample_rate = 16000
_processor_sleep_time = 0.01
dh_cfg = None
deviceHive = None
dh_status = None
events_queue = None
base_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'web')
def __init__(self, *args, **kwargs):
kwargs.setdefault('routes', routes)
min_time = kwargs.pop('min_capture_time', 5)
max_time = kwargs.pop('max_capture_time', 5)
self._save_path = kwargs.pop('max_capture_time', None)
super(Daemon, self).__init__(*args, **kwargs)
self.events_queue = deque(maxlen=10)
self.dh_cfg = Config('config.json', update_callback=self._restart_dh)
self.dh_status = DHStatus()
self._web_thread = threading.Thread(target=self._web_loop,
daemon=True,
name='web')
self._ask_data_event = threading.Event()
self._process_thread = threading.Thread(target=self._process_loop,
daemon=True,
name='processor')
self._captor = Captor(min_time, max_time, self._ask_data_event,
self._process)
def send_dh(self, data):
if not self._is_dh_connected():
logger.warning('Devicehive is not connected')
return
self.deviceHive.handler.send(data)
def start(self):
self._start_web()
self.dh_cfg.load() # this will start DH thread automatically
self._start_capture()
self._start_process()
def _start_web(self):
logger.info('Start server http://{}:{}'.format(*self.server_address))
self._web_thread.start()
def _start_dh(self):
if self._is_dh_connected():
logging.info('Devicehive already started')
return
logger.info('Start devicehive')
self._dh_thread = threading.Thread(target=self._dh_loop,
daemon=True,
name='device_hive')
self._dh_thread.start()
def _stop_dh(self):
if not self._is_dh_connected():
logging.info('Devicehive already stopped')
return
# TODO: Now it's only one proper way to call disconnect, we need
# implement better way to do it
self.deviceHive.transport.handler.handler.api.disconnect()
def _restart_dh(self):
if self._is_dh_connected():
self._stop_dh()
self._start_dh()
def _is_dh_connected(self):
return self.dh_status.connected
def _start_capture(self):
logger.info('Start captor')
self._captor.start()
def _start_process(self):
logger.info('Start processor loop')
self._process_thread.start()
def _web_loop(self):
self.serve_forever()
def _dh_loop(self):
self.dh_status.set_connecting()
self.deviceHive = DeviceHive(DeviceHiveHandler,
self.dh_cfg.data['deviceid'])
error = ''
try:
self.dh_status.set_connected()
url = self.dh_cfg.data['url']
refresh_token = self.dh_cfg.data['token']
self.deviceHive.connect(url, refresh_token=refresh_token)
except TransportError as e:
logger.exception(e)
error = str(e)
finally:
self.dh_status.set_disconnected(error)
logger.info('Stop devicehive')
def _process(self, data):
self._process_buf = np.frombuffer(data, dtype=np.int16)
def _process_loop(self):
with WavProcessor() as proc:
self._ask_data_event.set()
while True:
if self._process_buf is None:
# Waiting for data to process
time.sleep(self._processor_sleep_time)
continue
self._ask_data_event.clear()
if self._save_path:
f_path = os.path.join(
self._save_path,
'record_{:.0f}.wav'.format(time.time()))
wavfile.write(f_path, self._sample_rate, self._process_buf)
logger.info('"{}" saved'.format(f_path))
logger.info('Start processing')
predictions = proc.get_predictions(self._sample_rate,
self._process_buf)
formatted = format_predictions(predictions)
logger.info('Predictions: {}'.format(formatted))
self.events_queue.append((datetime.datetime.now(), formatted))
self.send_dh(predictions)
logger.info('Stop processing')
self._process_buf = None
self._ask_data_event.set()
class Capture(object):
_ask_data = None
_captor = None
_save_path = None
_processor_sleep_time = 0.01
_process_buf = None
_sample_rate = 16000
def __init__(self, min_time, max_time, path=None):
if path is not None:
if not os.path.exists(path):
raise FileNotFoundError('"{}" doesn\'t exist'.format(path))
if not os.path.isdir(path):
raise FileNotFoundError('"{}" isn\'t a directory'.format(path))
self._save_path = path
self._ask_data = threading.Event()
self._captor = Captor(min_time, max_time, self._ask_data,
self._process)
def start(self):
self._captor.start()
self._process_loop()
def _process(self, data):
self._process_buf = np.frombuffer(data, dtype=np.int16)
def _process_loop(self):
with WavProcessor() as proc:
self._ask_data.set()
while True:
if self._process_buf is None:
# Waiting for data to process
time.sleep(self._processor_sleep_time)
continue
self._ask_data.clear()
if self._save_path:
f_path = os.path.join(
self._save_path,
'record_{:.0f}.wav'.format(time.time()))
wavfile.write(f_path, self._sample_rate, self._process_buf)
logger.info('"{}" saved.'.format(f_path))
logger.info('Start processing.')
predictions = proc.get_predictions(self._sample_rate,
self._process_buf)
logger.info('Predictions: {}'.format(
format_predictions(predictions)))
my_dict = {x[0]: x[1] for x in predictions}
msg_json = {
"app_id": "openears",
"dev_id": "TEST001",
"payload_fields": my_dict,
"time": int(time.time() * 1e3)
}
msg_str = json.dumps(msg_json)
auth = {"username": mqtt_user, "password": mqtt_password}
publish.single("pipeline/openears/TEST001",
payload=msg_str,
hostname=mqtt_host,
port=mqtt_port,
auth=auth)
print('message sent')
logger.info('Stop processing.')
self._process_buf = None
self._ask_data.set()
class Capture(object):
_ask_data = None
_captor = None
_save_path = None
_processor_sleep_time = 0.01
_process_buf = None
_sample_rate = 16000
def __init__(self, min_time, max_time, path=None):
if path is not None:
if not os.path.exists(path):
raise FileNotFoundError('"{}" doesn\'t exist'.format(path))
if not os.path.isdir(path):
raise FileNotFoundError('"{}" isn\'t a directory'.format(path))
self._save_path = path
self._ask_data = threading.Event()
self._captor = Captor(min_time, max_time, self._ask_data,
self._process)
def start(self):
self._captor.start()
self._process_loop()
def _process(self, data):
self._process_buf = np.frombuffer(data, dtype=np.int16)
def _process_loop(self):
with WavProcessor() as proc:
self._ask_data.set()
while True:
if self._process_buf is None:
# Waiting for data to process
time.sleep(self._processor_sleep_time)
continue
self._ask_data.clear()
if self._save_path:
f_path = os.path.join(
self._save_path,
'record_{:.0f}.wav'.format(time.time()))
wavfile.write(f_path, self._sample_rate, self._process_buf)
logger.info('"{}" saved.'.format(f_path))
logger.info('Start processing.')
predictions = proc.get_predictions(self._sample_rate,
self._process_buf)
for i in predictions:
if i[0] == "Vehicle" and (float(i[1]) > .2):
print("OBS Release")
GPIO.output(pin, GPIO.HIGH)
else:
GPIO.output(pin, GPIO.LOW)
print(i[0])
print(i[1])
#print("Type: ")
#print(type(predictions))
#logger.info(
#'Predictions: {}'.format(format_predictions(predictions))
#)
logger.info('Stop processing.')
self._process_buf = None
self._ask_data.set()