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()