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.")
