class DataCollectorService(object):
def __init__(self, comm_config, data_dirpath):
self.comm_config = comm_config
self.comm_config['subscribe'][
'berrynet/engine/tensorflow/result'] = self.update
self.comm_config['subscribe'][
'berrynet/engine/mvclassification/result'] = self.update
self.comm = Communicator(self.comm_config, debug=True)
self.data_dirpath = data_dirpath
def update(self, pl):
if not os.path.exists(self.data_dirpath):
try:
os.mkdir(self.data_dirpath)
except Exception as e:
logger.warn('Failed to create {}'.format(self.data_dirpath))
raise (e)
payload_json = payload.deserialize_payload(pl.decode('utf-8'))
jpg_bytes = payload.destringify_jpg(payload_json['bytes'])
payload_json.pop('bytes')
logger.debug('inference text result: {}'.format(payload_json))
timestamp = datetime.now().isoformat()
with open(pjoin(self.data_dirpath, timestamp + '.jpg'), 'wb') as f:
f.write(jpg_bytes)
with open(pjoin(self.data_dirpath, timestamp + '.json'), 'w') as f:
f.write(json.dumps(payload_json, indent=4))
def run(self, args):
"""Infinite loop serving inference requests"""
self.comm.run()
class DashboardService(object):
def __init__(self, service_name, comm_config):
self.service_name = service_name
self.comm_config = comm_config
self.comm_config['subscribe'][
'berrynet/engine/tensorflow/result'] = self.update
self.comm_config['subscribe'][
'berrynet/engine/mvclassification/result'] = self.update
self.comm = Communicator(self.comm_config, debug=True)
self.basedir = '/usr/local/berrynet/dashboard/www/freeboard'
def update(self, pl):
payload_json = payload.deserialize_payload(pl.decode('utf-8'))
jpg_bytes = payload.destringify_jpg(payload_json['bytes'])
inference_result = [
'{0}: {1}<br>'.format(anno['label'], anno['confidence'])
for anno in payload_json['annotations']
]
logger.debug('inference results: {}'.format(inference_result))
with open(pjoin(self.basedir, 'snapshot.jpg'), 'wb') as f:
f.write(jpg_bytes)
self.comm.send('berrynet/dashboard/snapshot', 'snapshot.jpg')
self.comm.send('berrynet/dashboard/inferenceResult',
json.dumps(inference_result))
def run(self, args):
"""Infinite loop serving inference requests"""
self.comm.run()
class DydaConfigUpdateClient(object):
def __init__(self, comm_config, debug=False):
self.comm_config = comm_config
for topic, functor in self.comm_config['subscribe'].items():
self.comm_config['subscribe'][topic] = self.handleResult
self.comm = Communicator(self.comm_config, debug=True)
def sendConfig(self, jsonPayload):
self.comm.send(self.comm_config['publish'], jsonPayload)
def handleResult(self, pl):
try:
payload_json = payload.deserialize_payload(pl.decode('utf-8'))
print(payload_json)
self.comm.stop_nb()
sys.exit(0)
except Exception as e:
logger.info(e)
def run(self, args):
"""Infinite loop serving inference requests"""
with open(args['payload']) as f:
payload = f.read()
self.sendConfig(payload)
self.comm.run()
class DydaConfigUpdateService(object):
def __init__(self, comm_config, debug=False):
self.comm_config = comm_config
for topic, functor in self.comm_config['subscribe'].items():
self.comm_config['subscribe'][topic] = self.handleConfig
self.comm = Communicator(self.comm_config, debug=True)
def sendConfig(self, jsonPayload):
self.comm.send(self.comm_config['publish'], jsonPayload)
def handleConfig(self, pl):
payload_json = ""
try:
payload_json = payload.deserialize_payload(pl.decode('utf-8'))
self.comm.send(self.comm_config['publish'], payload.serialize_payload(payload_json))
except Exception as e:
logger.info(e)
# output config file
with open(self.comm_config['configfile'], 'w') as configfile:
configfile.write(payload.serialize_payload(payload_json))
configfile.close()
# restart service
subprocess.run(["supervisorctl", "restart", "bnpipeline-bndyda"])
def run(self, args):
"""Infinite loop serving inference requests"""
self.comm.run()
class EngineService(object):
def __init__(self, service_name, engine, comm_config):
self.service_name = service_name
self.engine = engine
self.comm_config = comm_config
for topic, functor in self.comm_config['subscribe'].items():
self.comm_config['subscribe'][topic] = eval(functor)
self.comm_config['subscribe'][
'berrynet/data/rgbimage'] = self.inference
self.comm = Communicator(self.comm_config, debug=True)
def inference(self, pl):
duration = lambda t: (datetime.now() - t).microseconds / 1000
t = datetime.now()
logger.debug('payload size: {}'.format(len(pl)))
logger.debug('payload type: {}'.format(type(pl)))
jpg_json = payload.deserialize_payload(pl.decode('utf-8'))
jpg_bytes = payload.destringify_jpg(jpg_json['bytes'])
logger.debug('destringify_jpg: {} ms'.format(duration(t)))
t = datetime.now()
rgb_array = payload.jpg2rgb(jpg_bytes)
logger.debug('jpg2rgb: {} ms'.format(duration(t)))
t = datetime.now()
image_data = self.engine.process_input(rgb_array)
output = self.engine.inference(image_data)
model_outputs = self.engine.process_output(output)
logger.debug('Result: {}'.format(model_outputs))
logger.debug('Classification takes {} ms'.format(duration(t)))
#self.engine.cache_data('model_output', model_outputs)
#self.engine.cache_data('model_output_filepath', output_name)
#self.engine.save_cache()
self.result_hook(self.generalize_result(jpg_json, model_outputs))
def generalize_result(self, eng_input, eng_output):
eng_input.update(eng_output)
return eng_input
def result_hook(self, generalized_result):
logger.debug('base result_hook')
def run(self, args):
"""Infinite loop serving inference requests"""
self.engine.create()
self.comm.run()
class PipelineRestarterService(object):
def __init__(self, service_name, comm_config):
self.service_name = service_name
self.comm_config = comm_config
self.comm_config['subscribe']['dlboxapi/config/update'] = \
self.restart_pipeline
self.comm = Communicator(self.comm_config, debug=True)
def restart_pipeline(self, pl):
logger.debug('Restart pipeline')
subprocess.call('dlbox-manager restart dlbox-pipeline.service',
shell=True)
def run(self, args):
"""Infinite loop serving pipeline restart requests"""
self.comm.run()
class DydaConfigUpdateService(object):
def __init__(self, comm_config, debug=False):
self.comm_config = comm_config
for topic, functor in self.comm_config['subscribe'].items():
self.comm_config['subscribe'][topic] = self.handleConfig
self.comm = Communicator(self.comm_config, debug=True)
idlistConfig = configparser.ConfigParser()
idlistConfig.read(self.comm_config['idlist'])
self.idlist = idlistConfig["ID"]
def sendConfig(self, jsonPayload):
self.comm.send(self.comm_config['publish'], jsonPayload)
def handleConfig(self, pl):
payload_json = ""
try:
id = pl.decode('utf-8')
if (id in self.idlist):
configFilename = self.idlist[id]
f = open(configFilename)
payload_json = payload.deserialize_payload(f.read())
self.sendConfig(payload.serialize_payload(payload_json))
else:
logger.warning("ID %s is not in idlist" % (id))
return
except Exception as e:
logger.info(e)
# output config file
with open(self.comm_config['configfile'], 'w') as configfile:
configfile.write(payload.serialize_payload(payload_json))
configfile.close()
# restart service
subprocess.run(["supervisorctl", "restart", "bnpipeline-bndyda"])
def run(self, args):
"""Infinite loop serving inference requests"""
self.comm.run()
class SnapshotService(object):
def __init__(self, comm_config):
self.comm_config = comm_config
for topic, functor in self.comm_config['subscribe'].items():
self.comm_config['subscribe'][topic] = eval(functor)
self.comm_config['subscribe'][
'berrynet/trigger/controller/snapshot'] = self.snapshot
self.comm = Communicator(self.comm_config, debug=True)
def snapshot(self, pl):
'''Send camera snapshot.
The functionality is the same as using camera client in file mode.
The difference is that snapshot client retrieves image from camera
instead of given filepath.
'''
duration = lambda t: (datetime.now() - t).microseconds / 1000
# WORKAROUND: Prevent VideoCapture from buffering frames.
# VideoCapture will buffer frames automatically, and we need
# to find a way to disable it.
self.capture = cv2.VideoCapture(0)
status, im = self.capture.read()
if (status is False):
logger.warn('ERROR: Failure happened when reading frame')
t = datetime.now()
retval, jpg_bytes = cv2.imencode('.jpg', im)
mqtt_payload = payload.serialize_jpg(jpg_bytes)
self.comm.send('berrynet/data/rgbimage', mqtt_payload)
logger.debug('send: {} ms'.format(duration(t)))
self.capture.release()
def run(self, args):
"""Infinite loop serving inference requests"""
self.comm.run()
class DataCollectorService(object):
def __init__(self, comm_config, data_dirpath):
self.comm_config = comm_config
for topic, functor in self.comm_config['subscribe'].items():
self.comm_config['subscribe'][topic] = eval(functor)
#self.comm_config['subscribe']['berrynet/data/rgbimage'] = self.update
self.comm_config['subscribe']['berrynet/engine/pipeline/result'] = self.save_pipeline_result
self.comm = Communicator(self.comm_config, debug=True)
self.data_dirpath = data_dirpath
def update(self, pl):
payload_json = payload.deserialize_payload(pl.decode('utf-8'))
# update UI with the latest inference result
self.ui.update(payload_json, 'bytes')
if self.data_dirpath:
if not os.path.exists(self.data_dirpath):
try:
os.mkdir(self.data_dirpath)
except Exception as e:
logger.warn('Failed to create {}'.format(self.data_dirpath))
raise(e)
jpg_bytes = payload.destringify_jpg(payload_json['bytes'])
payload_json.pop('bytes')
logger.debug('inference text result: {}'.format(payload_json))
timestamp = datetime.now().isoformat()
with open(pjoin(self.data_dirpath, timestamp + '.jpg'), 'wb') as f:
f.write(jpg_bytes)
with open(pjoin(self.data_dirpath, timestamp + '.json'), 'w') as f:
f.write(json.dumps(payload_json, indent=4))
def save_pipeline_result(self, pl):
payload_json = payload.deserialize_payload(pl.decode('utf-8'))
# update UI with the latest inference result
self.ui.update(payload_json, 'image_blob')
if self.data_dirpath:
if not os.path.exists(self.data_dirpath):
try:
os.mkdir(self.data_dirpath)
except Exception as e:
logger.warn('Failed to create {}'.format(self.data_dirpath))
raise(e)
jpg_bytes = payload.destringify_jpg(payload_json['image_blob'])
payload_json.pop('image_blob')
logger.debug('inference text result: {}'.format(payload_json))
timestamp = datetime.now().isoformat()
with open(pjoin(self.data_dirpath, timestamp + '.jpg'), 'wb') as f:
f.write(jpg_bytes)
with open(pjoin(self.data_dirpath, timestamp + '.json'), 'w') as f:
f.write(json.dumps(payload_json, indent=4))
def send_snapshot_trigger(self):
payload = {}
payload['timestamp'] = datetime.now().isoformat()
mqtt_payload = json.dumps(payload)
self.comm.send('berrynet/trigger/controller/snapshot', mqtt_payload)
def run(self, args):
"""Infinite loop serving inference requests"""
self.comm.run()
class GmailService(object):
def __init__(self, comm_config):
self.comm_config = comm_config
for topic, functor in self.comm_config['subscribe'].items():
self.comm_config['subscribe'][topic] = eval(functor)
self.comm_config['subscribe'][
'berrynet/engine/darknet/result'] = self.update
self.comm_config['subscribe'][
'berrynet/engine/tensorflow/result'] = self.update
self.comm = Communicator(self.comm_config, debug=True)
self.email = comm_config['email']
self.pipeline_compatible = comm_config['pipeline_compatible']
self.target_label = comm_config['target_label']
def find_target_label(self, target_label, generalized_result):
label_list = [i['label'] for i in generalized_result['annotations']]
logger.debug('Result labels: {}'.format(label_list))
return target_label in label_list
def update(self, pl):
payload_json = payload.deserialize_payload(pl.decode('utf-8'))
if self.pipeline_compatible:
b64img_key = 'image_blob'
else:
b64img_key = 'bytes'
jpg_bytes = payload.destringify_jpg(payload_json[b64img_key])
payload_json.pop(b64img_key)
logger.debug('inference text result: {}'.format(payload_json))
match_target_label = self.find_target_label(self.target_label,
payload_json)
logger.debug('Find target label {0}: {1}'.format(
self.target_label, match_target_label))
if match_target_label:
timestamp = datetime.now().isoformat()
notification_image = pjoin('/tmp', timestamp + '.jpg')
notification_text = pjoin('/tmp', timestamp + '.json')
with open(notification_image, 'wb') as f:
f.write(jpg_bytes)
with open(notification_text, 'w') as f:
f.write(json.dumps(payload_json, indent=4))
try:
send_email_text(self.email['sender_address'],
self.email['sender_password'],
self.email['receiver_address'],
body=('Target label {} is found. '
'Please check the attachments.'
''.format(self.target_label)),
subject='BerryNet mail client notification',
attachments=set(
[notification_image, notification_text]))
except Exception as e:
logger.warn(e)
os.remove(notification_image)
os.remove(notification_text)
else:
# target label is not in generalized result, do nothing
pass
def run(self, args):
"""Infinite loop serving inference requests"""
self.comm.run()
