def __init__(self): """ Initializes the Server class. """ # Server setup self.Helpers = Helpers() self.LogFile = self.Helpers.setLogFile( self.Helpers.confs["Server"]["Logs"] + "/Server") # Movidius setup self.Movidius = Movidius(self.Helpers.confs["Server"]["Logs"]) self.Movidius.checkNCS() self.ValidDir = self.Helpers.confs["Classifier"]["ValidPath"] self.TestingDir = self.Helpers.confs["Classifier"]["TestingPath"] self.Helpers.logMessage(self.LogFile, "Facial Recognition Server", "STATUS", "Movidius configured") # Facenet setup self.Facenet = Facenet(self.Helpers.confs["Server"]["Logs"]) self.Movidius.allocateGraph(self.Facenet.LoadGraph()) self.Facenet.PreprocessKnown(self.ValidDir, self.Movidius.Graph) self.Helpers.logMessage(self.LogFile, "Facial Recognition Server", "STATUS", "Facenet configured")
def __init__(self, LogPath): """ Initializes the Movidius class. """ self.Helpers = Helpers() self.LogFile = self.Helpers.setLogFile(LogPath+"/Movidius") self.ncsDevices = None self.ncsDevice = None
def __init__(self): """ Initializes the AML/ALL Detection System Data Helpers Class. """ self.Helpers = Helpers() self.confs = self.Helpers.loadConfs() self.fixed = tuple((self.confs["Settings"]["ImgDims"], self.confs["Settings"]["ImgDims"])) self.filesMade = 0 self.trainingDir = self.confs["Settings"]["TrainDir"]
def __init__(self): """ Initializes the Movidius NCS1 Classifier Data Class """ self.Helpers = Helpers("Data") self.confs = self.Helpers.confs self.DataProcess = DataProcess() self.labelsToName = {} self.Helpers.logger.info("Data class initialization complete.")
def __init__(self): """ Initializes the Server class. """ self.Helpers = Helpers() self.LogFile = self.Helpers.setLogFile( self.Helpers.confs["Server"]["Logs"] + "/Client") self.addr = "http://" + self.Helpers.confs["Server"]["IP"] + ':' + str( self.Helpers.confs["Server"]["Port"]) + '/Inference' self.headers = {'content-type': 'image/jpeg'}
def __init__(self): """ Initializes the Data class. """ self.ignore = [',', '.', '!', '?'] self.Helpers = Helpers() self.LogFile = self.Helpers.setLogFile( self.Helpers.confs["System"]["Logs"] + "JumpWay/") self.LancasterStemmer = LancasterStemmer()
def __init__(self): ############################################################### # # Sets up all default requirements and placeholders # needed for this class. # ############################################################### self.Helpers = Helpers() self.confs = self.Helpers.loadConfs() self.logFile = self.Helpers.setLogFile(self.confs["Settings"]["Logs"]["DataLogDir"])
def __init__(self): """ Initializes the Chatbot Client class. """ self.Helpers = Helpers() self.LogFile = self.Helpers.setLogFile( self.Helpers.confs["System"]["Logs"] + "Client/") self.apiUrl = "http://" + self.Helpers.confs["System"][ "IP"] + ":" + str(self.Helpers.confs["System"]["Port"]) + "/infer" self.headers = {"content-type": 'application/json'} self.Helpers.logMessage(self.LogFile, "CLIENT", "INFO", "Client Ready")
def __init__(self, LogPath): ############################################################### # # Sets up all default requirements and placeholders # ############################################################### self.Helpers = Helpers() self.LogFile = self.Helpers.setLogFile(LogPath + "/Movidius") self.ncsDevices = None self.ncsDevice = None
def __init__(self): """ Sets up all default requirements and placeholders needed for this class. """ self.Helpers = Helpers() self.confs = self.Helpers.loadConfs() self.fixed = tuple((self.confs["Settings"]["ImgDims"], self.confs["Settings"]["ImgDims"])) self.filesMade = 0 self.trainingDir = self.confs["Settings"]["TrainDir"]
def __init__(self): """ Initializes the Data class. """ self.Helpers = Helpers() self.confs = self.Helpers.loadConfs() self.fixed = tuple((self.confs["Settings"]["ImgDims"], self.confs["Settings"]["ImgDims"])) self.filesMade = 0 self.trainingDir = self.confs["Settings"]["TrainDir"] self.seed = self.confs["Settings"]["Seed"] seed(self.seed)
def __init__(self): self.Helpers = Helpers() self._confs = self.Helpers.loadConfigs() self.LogFile = self.Helpers.setLogFile(self._confs["aiCore"]["Logs"] + "Train/") self.intentMap = {} self.words = [] self.classes = [] self.dataCorpus = [] self.Model = Model() self.Data = Data()
def __init__(self): """ Initializes the Chatbot class. """ self.isTraining = False self.ner = None self.Helpers = Helpers() self.user = {} self.LogFile = self.Helpers.setLogFile( self.Helpers.confs["System"]["Logs"] + "NLU/") self.ChatLogFile = self.Helpers.setLogFile( self.Helpers.confs["System"]["Logs"] + "Chat/")
def __init__(self): """ Initializes the Training class. """ self.Helpers = Helpers() self.LogFile = self.Helpers.setLogFile( self.Helpers.confs["System"]["Logs"] + "Train/") self.intentMap = {} self.words = [] self.classes = [] self.dataCorpus = [] self.Model = Model() self.Data = Data()
def __init__(self): self.Helpers = Helpers() self.Helpers = Helpers() self.confs = self.Helpers.loadConfigs() self.LogFile = self.Helpers.setLogFile(self.confs["aiCore"]["Logs"] + "Client/") self.apiUrl = "http://" + self.confs["aiCore"]["IP"] + ":" + str( self.confs["aiCore"]["Port"]) + "/infer" self.headers = {"content-type": 'application/json'} self.Helpers.logMessage(self.LogFile, "CLIENT", "INFO", "Client Ready")
def __init__(self): ############################################################### # # Sets up all default requirements # # - Helpers: Useful global functions # - LancasterStemmer: Word stemmer # ############################################################### self.Helpers = Helpers() self._confs = self.Helpers.loadConfigs() self.stemmer = LancasterStemmer()
def __init__(self): ############################################################### # # Sets up all default requirements # # - Helpers: Useful global functions # - Data: Data functions # ############################################################### self.Helpers = Helpers() self.confs = self.Helpers.loadConfigs() self.Data = Data()
def __init__(self, LogPath): """ Initializes the Facenet class. """ # Class settings self.Known = [] self.Helpers = Helpers() self.LogFile = self.Helpers.setLogFile(self.Helpers.confs["Server"]["Logs"]+"/Facenet") # OpenCV settings self.OpenCV = OpenCV(self.Helpers) # Dlib settings self.Detector = dlib.get_frontal_face_detector() self.Predictor = dlib.shape_predictor(self.Helpers.confs["Classifier"]["Dlib"])
def __init__(self, optimizer, do_augmentation=False): """ Initializes the Data class. """ self.Helpers = Helpers("Data", False) self.optimizer = optimizer self.do_augmentation = do_augmentation if self.do_augmentation == False: self.seed = self.Helpers.confs["cnn"]["data"]["seed_" + self.optimizer] self.dim = self.Helpers.confs["cnn"]["data"]["dim"] else: self.Augmentation = Augmentation("cnn", self.optimizer) self.seed = self.Helpers.confs["cnn"]["data"]["seed_" + self.optimizer + "_augmentation"] self.dim = self.Helpers.confs["cnn"]["data"]["dim_augmentation"] seed(self.seed) random.seed(self.seed) self.data = [] self.labels = [] self.Helpers.logger.info("Data class initialization complete.")
def __init__(self, optimizer, do_augmentation = False): """ Initializes the Model class. """ self.Helpers = Helpers("Model", False) self.optimizer = optimizer self.do_augmentation = do_augmentation self.testing_dir = self.Helpers.confs["cnn"]["data"]["test"] self.valid = self.Helpers.confs["cnn"]["data"]["valid_types"] self.colors = plt.rcParams['axes.prop_cycle'].by_key()['color'] if self.do_augmentation == False: self.seed = self.Helpers.confs["cnn"]["data"]["seed_" + self.optimizer] self.weights_file = self.Helpers.confs["cnn"]["model"]["weights"] self.model_json = self.Helpers.confs["cnn"]["model"]["model"] else: self.seed = self.Helpers.confs["cnn"]["data"]["seed_" + self.optimizer + "_augmentation"] self.weights_file = self.Helpers.confs["cnn"]["model"]["weights_aug"] self.model_json = self.Helpers.confs["cnn"]["model"]["model_aug"] random.seed(self.seed) seed(self.seed) tf.random.set_seed(self.seed) self.Helpers.logger.info("Model class initialization complete.")
def __init__(self): """ Initializes the class. """ self.Helpers = Helpers("Model", False) os.environ["KMP_BLOCKTIME"] = "1" os.environ["KMP_SETTINGS"] = "1" os.environ["KMP_AFFINITY"] = "granularity=fine,verbose,compact,1,0" os.environ["OMP_NUM_THREADS"] = str( self.Helpers.confs["cnn"]["system"]["cores"]) tf.config.threading.set_inter_op_parallelism_threads(1) tf.config.threading.set_intra_op_parallelism_threads( self.Helpers.confs["cnn"]["system"]["cores"]) self.testing_dir = self.Helpers.confs["cnn"]["data"]["test"] self.valid = self.Helpers.confs["cnn"]["data"]["valid_types"] self.seed = self.Helpers.confs["cnn"]["data"]["seed"] self.weights_file = self.Helpers.confs["cnn"]["model"]["weights"] self.model_json = self.Helpers.confs["cnn"]["model"]["model"] random.seed(self.seed) seed(self.seed) tf.random.set_seed(self.seed) self.Helpers.logger.info("Class initialization complete.")
def __init__(self): """ Initializes the class. """ self.Helpers = Helpers("Model", False) self.Helpers.logger.info( "Model class initialization complete.")
def __init__(self): """ Initializes the class. """ super(CamStream, self).__init__() self.Helpers = Helpers("CamStream") self.Helpers.logger.info( "CamStream Helper Class initialization complete.")
def __init__(self): """ Initializes the class. """ self.Helpers = Helpers("Sockets") self.Helpers.logger.info( "Socket Helper Class initialization complete.")
def __init__(self): """ Initializes the Movidius NCS1 Classifier Trainer Class """ self.Helpers = Helpers("Evaluator") self.confs = self.Helpers.confs self.labelsToName = {} self.checkpoint_file = tf.train.latest_checkpoint( self.confs["Classifier"]["LogDir"]) # Open the labels file self.labels = open( self.confs["Classifier"]["DatasetDir"] + "/" + self.confs["Classifier"]["Labels"], 'r') # Create a dictionary to refer each label to their string name for line in self.labels: label, string_name = line.split(':') string_name = string_name[:-1] # Remove newline self.labelsToName[int(label)] = string_name # Create a dictionary that will help people understand your dataset better. This is required by the Dataset class later. self.items_to_descriptions = { 'image': 'A 3-channel RGB coloured image that is ex: office, people', 'label': 'A label that ,start from zero' } self.Helpers.logger.info( "Evaluator class initialization complete.")
def __init__(self): """ Initializes the class. """ self.Helpers = Helpers("CamStream") super(CamStream, self).__init__() self.Helpers.logger.info("CamStream class initialized.")
def __init__(self): """ Initializes the class. """ super(RealsenseStream, self).__init__() self.Helpers = Helpers("Realsense D415 Streamer") self.Helpers.logger.info( "Realsense D415 Streamer Helper Class initialization complete.")
def __init__(self): """ Initializes the class. """ self.Helpers = Helpers("FoscamRead") super(FoscamRead, self).__init__() self.Helpers.logger.info("FoscamRead class initialized.")
def __init__(self): """ Initializes the class. """ self.Helpers = Helpers("CamRead") super(CamRead, self).__init__() self.Helpers.logger.info("CamRead Class initialization complete.")
def __init__(self): """ Initializes the class. """ self.Helpers = Helpers("Core") self.Core = OpenVINO() self.Helpers.logger.info("Class initialization complete.")