def add_sensor_notification(self, notification_message):
Base.metadata.create_all(engine)
session = Session()
notification = Notification(notification_message)
session.add(notification)
session.commit()
session.close()
def add_detection_result_image(self, name, detection_result_id, type_id):
Base.metadata.create_all(engine)
session = Session()
image = ImageAttachment(name, detection_result_id, type_id)
session.add(image)
session.commit()
session.close()
def add_reading(self, temperature_reading, humidity_reading):
Base.metadata.create_all(engine)
session = Session()
reading = SensorsReading(humidity_reading, temperature_reading)
session.add(reading)
session.commit()
session.close()
def add_movement(self, movement):
Base.metadata.create_all(engine)
session = Session()
session.add(movement)
session.commit()
generated_id = movement.id
session.close()
return generated_id
def add_movement_notification(self, notification_entity):
Base.metadata.create_all(engine)
session = Session()
session.add(notification_entity)
session.commit()
generated_id = notification_entity.id
session.close()
return generated_id
def add_detection_result_with_image(self, detection_result):
Base.metadata.create_all(engine)
session = Session()
session.add(detection_result)
session.commit()
generated_id = detection_result.id
session.close()
return generated_id
def get_all_people_connected_to_neural_network(self, nn_id):
result = []
Base.metadata.create_all(engine)
session = Session()
people = session.query(NeuralNetworkPerson).filter_by(neural_network_id=nn_id)
session.close()
for p in people:
result.append(p.person_id)
return result
def complete_with_error(self, id):
Base.metadata.create_all(engine)
session = Session()
requests = session.query(Detection).filter_by(id=id)
for req in requests:
req.statusId = 4
req.completionTime = datetime.datetime.now()
session.commit()
session.close()
def get_people_ids_with_images_count(self):
result = []
Base.metadata.create_all(engine)
session = Session()
people = session.query(Person)
session.close()
for p in people:
result.append([p.id, len(p.images)])
return result
def get_azure_file_connected_to_neural_network(self, nn_id):
Base.metadata.create_all(engine)
session = Session()
result = session.query(NeuralNetworkFile).filter(
NeuralNetworkFile.neuralNetworkId == nn_id,
NeuralNetworkFile.neuralNetworkTypeId ==
self.nnTypes.azure_large_group_id).first()
session.close()
return result
def complete_request(self, request_id):
Base.metadata.create_all(engine)
session = Session()
requests = session.query(Recognition).filter_by(id=request_id)
for req in requests:
req.statusId = 3
req.completionTime = datetime.datetime.now()
session.commit()
session.close()
def get_completed_neural_networks_ids_with_downloadable_files_count(self):
result = []
Base.metadata.create_all(engine)
session = Session()
neural_networks = session.query(NeuralNetwork).filter_by(statusId=3)
session.close()
for nn in neural_networks:
result.append([
nn.id,
len([x for x in nn.files if x.neuralNetworkTypeId < 4])
])
return result
def add_neural_network_file(self, neural_network_file: NeuralNetworkFile):
Base.metadata.create_all(engine)
session = Session()
session.add(neural_network_file)
session.commit()
session.close()
def get_all(self):
Base.metadata.create_all(engine)
session = Session()
people = session.query(Person)
session.close()
return people.all()
def get_by_id(self, id):
Base.metadata.create_all(engine)
session = Session()
person = session.query(Person).filter_by(id=id).first()
session.close()
return person
def get_all_not_completed(self):
Base.metadata.create_all(engine)
session = Session()
requests = session.query(Detection).filter_by(statusId=1)
session.close()
return requests
def add_recognition_result(self, recognition_result):
Base.metadata.create_all(engine)
session = Session()
session.add(recognition_result)
session.commit()
session.close()