def __init__(self):
self.Helpers = Helpers()
self.Logging = Logging()
self._confs = self.Helpers.loadConfigs()
self.LogFile = self.Logging.setLogFile(self._confs["AI"]["Logs"]+"Client/")
class Receiver():
def __init__(self):
self.Helpers = Helpers()
self._confs = self.Helpers.loadConfigs()
self.LogFile = self.Helpers.setLogFile(self._confs["aiCore"]["Logs"] +
"/Local")
self.OpenCV = OpenCV()
self.configureSocket()
def configureSocket(self):
###############################################################
#
# Configures the socket we will stream the frames to
#
###############################################################
context = zmq.Context()
self.tassSocket = context.socket(zmq.SUB)
self.tassSocket.bind("tcp://*:" + str(self._confs["Socket"]["port"]))
self.tassSocket.setsockopt_string(zmq.SUBSCRIBE, np.unicode(''))
self.Helpers.logMessage(
self.LogFile, "TASS", "INFO",
"Connected To Socket: tcp://" + self._confs["Socket"]["host"] +
":" + str(self._confs["Socket"]["port"]))
def __init__(self):
self._configs = {}
self.movidius = None
self.jumpwayClient = None
self.cameraStream = None
self.imagePath = None
self.mean = 128
self.std = 1/128
self.categories = []
self.graphfile = None
self.graph = None
self.reqsize = None
self.extensions = [
".jpg",
".png"
]
self.CheckDevices()
self.Helpers = Helpers()
self._configs = self.Helpers.loadConfigs()
self.startMQTT()
print("")
print("-- Classifier Initiated")
print("")
def __init__(self):
self._configs = {}
self.movidius = None
self.jumpwayClient = None
self.OpenCVCapture = None
self.graphfile = None
self.graph = None
self.CheckDevices()
self.Helpers = Helpers()
self.OpenCVHelpers = OpenCVHelpers()
self.FacenetHelpers = FacenetHelpers()
self._configs = self.Helpers.loadConfigs()
self.loadRequirements()
self.startMQTT()
self.detector = dlib.get_frontal_face_detector()
self.predictor = dlib.shape_predictor(
self._configs["ClassifierSettings"]["Dlib"])
print("")
print("-- Classifier Initiated")
print("")
def __init__(self):
###############################################################
#
# Sets up all default requirements and placeholders
# needed for the NLU engine to run.
#
# - Helpers: Useful global functions
# - JumpWay/jumpWayClient: iotJumpWay class and connection
# - Logging: Logging class
#
###############################################################
self.isTraining = False
self.ner = None
self.Helpers = Helpers()
self._confs = self.Helpers.loadConfigs()
self.user = {}
self.LogFile = self.Helpers.setLogFile(self._confs["aiCore"]["Logs"] +
"NLU/")
self.ChatLogFile = self.Helpers.setLogFile(
self._confs["aiCore"]["Logs"] + "Chat/")
self.jumpWay = JumpWay()
self.jumpWayClient = self.jumpWay.startMQTT()
self.jumpWayClient.subscribeToDeviceChannel(
self._confs["iotJumpWay"]["Channels"]["Commands"])
self.jumpWayClient.deviceCommandsCallback = self.commandsCallback
def __init__(self):
self.Helpers = Helpers()
self._confs = self.Helpers.loadConfigs()
self.mysqlDbConn = None
self.mysqlDbCur = None
self.mysqlConnect()
def __init__(self):
self.Helpers = Helpers()
self._confs = self.Helpers.loadConfigs()
self.LogFile = self.Helpers.setLogFile(self._confs["aiCore"]["Logs"] +
"/Local")
self.OpenCV = OpenCV()
self.configureSocket()
def __init__(self):
self.Helpers = Helpers()
self.Logging = Logging()
self.JumpWayREST = JumpWayREST()
self._confs = self.Helpers.loadConfigs()
self.LogFile = self.Logging.setLogFile(self._confs["AI"]["Logs"]+"Client/")
self.Logging.logMessage(
self.LogFile,
"CLIENT",
"INFO",
"GeniSys AI JumpWay REST Client Ready")
def __init__(self, user):
self.Helpers = Helpers()
self.Logging = Logging()
self._confs = self.Helpers.loadConfigs()
self.LogFile = self.Logging.setLogFile(self._confs["AI"]["Logs"] +
"Client/")
self.apiUrl = self._confs["AI"]["FQDN"] + "/communicate/infer/" + user
self.headers = {"content-type": 'application/json'}
self.Logging.logMessage(self.LogFile, "CLIENT", "INFO",
"GeniSys AI Client Ready")
def __init__(self):
self.Helpers = Helpers()
self.Logging = Logging()
self._confs = self.Helpers.loadConfigs()
self.LogFile = self.Logging.setLogFile(self._confs["AI"]["Logs"] +
"NLU/")
self.ChatLogFile = self.Logging.setLogFile(self._confs["AI"]["Logs"] +
"Chat/")
self.Logging.logMessage(self.LogFile, "NLU", "INFO",
"NLU Classifier LogFile Set")
self.startMQTT()
def __init__(self):
###############################################################
#
# Sets up all default requirements and placeholders
#
###############################################################
self.Helpers = Helpers()
self._confs = self.Helpers.loadConfigs()
self.LogFile = self.Helpers.setLogFile(self._confs["aiCore"]["Logs"] +
"/Foscam")
self.OpenCV = OpenCV()
def __init__(self):
self.Helpers = Helpers()
self._configs = self.Helpers.loadConfigs()
self.addr = "http://"+self._configs["Cameras"][0]["Stream"]+':'+str(self._configs["Cameras"][0]["StreamPort"])
self.TASSapiUrl = self.addr + '/api/TASS/infer'
self.content_type = 'image/jpeg'
self.headers = {'content-type': self.content_type}
print("-- Client Initiated")
self.testTASS()
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):
###############################################################
#
# 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, jumpWay):
self.Helpers = Helpers()
self._confs = self.Helpers.loadConfigs()
self.LogFile = self.Helpers.setLogFile(self._confs["aiCore"]["Logs"] +
"Train/")
self.jumpwayCl = jumpWay
self.intentMap = {}
self.words = []
self.classes = []
self.dataCorpus = []
self.Model = Model()
self.Data = Data()
def __init__(self):
###############################################################
#
# Sets up all default requirements and placeholders
# needed for the NLU engine to run.
#
# - Helpers: Useful global functions
# - Logging: Logging class
#
###############################################################
self.Helpers = Helpers()
self._confs = self.Helpers.loadConfigs()
self.LogFile = self.Helpers.setLogFile(self._confs["aiCore"]["Logs"] +
"GeniSys/")
def __init__(self):
###############################################################
#
# Sets up all default requirements and placeholders
#
###############################################################
self.Helpers = Helpers()
self._confs = self.Helpers.loadConfigs()
self.LogFile = self.Helpers.setLogFile(self._confs["aiCore"]["Logs"] +
"/Local")
self.MySql = MySql()
self.OpenCV = OpenCV()
self.OCVframe = None
self.font = cv2.FONT_HERSHEY_SIMPLEX
self.fontColor = (255, 255, 255)
self.fontScale = 1
self.lineType = 1
self.identified = 0
self.Facenet = Facenet()
self.movidius, self.devices, self.device = self.Facenet.CheckDevices()
self.fgraph, self.fgraphfile = self.Facenet.loadGraph(
"Facenet", self.movidius)
self.validDir = self._confs["Classifier"]["NetworkPath"] + self._confs[
"Classifier"]["ValidPath"]
self.testingDir = self._confs["Classifier"][
"NetworkPath"] + self._confs["Classifier"]["TestingPath"]
self.detector = dlib.get_frontal_face_detector()
self.predictor = dlib.shape_predictor(
self._confs["Classifier"]["Dlib"])
self.connectToCamera()
self.tassSocket = None
self.configureSocket()
self.JumpWay = JumpWay()
self.JumpWayCL = self.JumpWay.startMQTT()
self.Helpers.logMessage(self.LogFile, "TASS", "INFO", "TASS Ready")
def __init__(self):
###############################################################
#
# Sets up all default requirements and placeholders
# needed for the NLU engine to run.
#
###############################################################
self.Helpers = Helpers()
self._confs = self.Helpers.loadConfigs()
self.LogFile = self.Helpers.setLogFile(self._confs["aiCore"]["Logs"] +
"/Foscam")
self.OpenCV = OpenCV()
self.OpenCVCapture = None
self.configureSocket()
def __init__(self):
###############################################################
#
# Sets up all default requirements and placeholders
# needed for the MySql connection.
#
# - Helpers: Useful global functions
#
###############################################################
self.Helpers = Helpers()
self._confs = self.Helpers.loadConfigs()
self.mysqlDbConn = None
self.mysqlDbCur = None
self.mysqlConnect()
def __init__(self):
self._configs = {}
self.movidius = None
self.jumpwayClient = None
self.graphfile = None
self.graph = None
self.CheckDevices()
self.Helpers = Helpers()
self._configs = self.Helpers.loadConfigs()
self.loadRequirements()
self.startMQTT()
print("")
print("-- Classifier Initiated")
print("")
def __init__(self):
self._configs = {}
self.movidius = None
self.cameraStream = None
self.imagePath = None
self.mean = 128
self.std = 1 / 128
self.categories = []
self.fgraphfile = None
self.fgraph = None
self.reqsize = None
self.Helpers = Helpers()
self._configs = self.Helpers.loadConfigs()
print("-- Server Initiated")
class Humans():
def __init__(self):
self.Helpers = Helpers()
self.Logging = Logging()
self.JumpWayREST = JumpWayREST()
self._confs = self.Helpers.loadConfigs()
self.LogFile = self.Logging.setLogFile(self._confs["AI"]["Logs"]+"Client/")
self.Logging.logMessage(
self.LogFile,
"CLIENT",
"INFO",
"GeniSys AI JumpWay REST Client Ready")
def getHumanByFace(self, response):
data = {}
headers = {'content-type': 'application/json'}
cameraEnpoint = self._confs["iotJumpWay"]["API"]["REST"] + "/TASS/0_1_0/checkCamera"
self.Logging.logMessage(
self.LogFile,
"HUMANS",
"INFO",
"Checking Camera...")
response = self.JumpWayREST.apiCall(
cameraEnpoint,
data,
headers)
self.Logging.logMessage(
self.LogFile,
"CLIENT",
"OK",
"Response: "+str(response))
if response["Response"] == "OK":
responseLength = len(response["ResponseData"])
if responseLength == 1:
message = "I detected " + str(responseLength) + " human, " + response["ResponseData"][0]["userid"]
else:
message = "I detected " + str(responseLength) + " humans, "
return message
else:
return response["ResponseMessage"]
def __init__(self):
###############################################################
#
# Sets up all default requirements and placeholders
# needed for the NLU engine to run.
#
# - Helpers: Useful global functions
# - Logging: Logging class
# - LancasterStemmer: Word stemmer
#
###############################################################
self.ignore = [',', '.', '!', '?']
self.Helpers = Helpers()
self._confs = self.Helpers.loadConfigs()
self.LogFile = self.Helpers.setLogFile(self._confs["aiCore"]["Logs"] +
"JumpWay/")
self.LancasterStemmer = LancasterStemmer()
def __init__(self, jumpWay):
self.Helpers = Helpers()
self.Logging = Logging()
self.jumpwayCl = jumpWay
self._confs = self.Helpers.loadConfigs()
self.LogFile = self.Logging.setLogFile(self._confs["AI"]["Logs"] +
"Train/")
self.Logging.logMessage(self.LogFile, "LogFile", "INFO",
"NLU Trainer LogFile Set")
self.Model = Model()
self.Data = Data(self.Logging, self.LogFile)
self.intentMap = {}
self.words = []
self.classes = []
self.dataCorpus = []
self.setupData()
self.setupEntities()
class Receiver():
def __init__(self):
###############################################################
#
# Sets up all default requirements and placeholders
# needed for the NLU engine to run.
#
###############################################################
self.Helpers = Helpers()
self._confs = self.Helpers.loadConfigs()
self.LogFile = self.Helpers.setLogFile(self._confs["aiCore"]["Logs"] +
"/Foscam")
self.OpenCV = OpenCV()
self.OpenCVCapture = None
self.configureSocket()
def configureSocket(self):
###############################################################
#
# Configures and connects to the socket.
#
###############################################################
context = zmq.Context()
self.tassSocket = context.socket(zmq.SUB)
self.tassSocket.bind("tcp://*:" + str(self._confs["Socket"]["port"]))
self.tassSocket.setsockopt_string(zmq.SUBSCRIBE, np.unicode(''))
self.Helpers.logMessage(
self.LogFile, "Streamer", "INFO",
"Connected To Socket: tcp://" + self._confs["Socket"]["host"] +
":" + str(self._confs["Socket"]["port"]))
def __init__(self):
###############################################################
#
# Sets up all default requirements and placeholders
# needed for the NLU engine to run.
#
# - Helpers: Useful global functions
# - JumpWay/jumpWayClient: iotJumpWay class and connection
# - Logging: Logging class
#
###############################################################
self.Helpers = Helpers()
self._confs = self.Helpers.loadConfigs()
self.JumpWay = JumpWay()
self.MySql = MySql()
self.MySql.setMysqlCursorRows()
self.Logging = Logging()
self.LogFile = self.Logging.setLogFile(self._confs["aiCore"]["Logs"] +
"Client/")
class Server():
def __init__(self):
self._configs = {}
self.movidius = None
self.cameraStream = None
self.imagePath = None
self.mean = 128
self.std = 1 / 128
self.categories = []
self.fgraphfile = None
self.fgraph = None
self.reqsize = None
self.Helpers = Helpers()
self._configs = self.Helpers.loadConfigs()
print("-- Server Initiated")
def CheckDevices(self):
#mvnc.SetGlobalOption(mvnc.GlobalOption.LOGLEVEL, 2)
devices = mvnc.EnumerateDevices()
if len(devices) == 0:
print('!! WARNING! No Movidius Devices Found !!')
quit()
self.movidius = mvnc.Device(devices[0])
self.movidius.OpenDevice()
print("-- Movidius Connected")
def allocateGraph(self, graphfile, graphID):
self.fgraph = self.movidius.AllocateGraph(graphfile)
def loadRequirements(self, graphID):
with open(self._configs["ClassifierSettings"]["NetworkPath"] +
self._configs["ClassifierSettings"]["Graph"],
mode='rb') as f:
self.fgraphfile = f.read()
self.allocateGraph(self.fgraphfile, "TASS")
print("-- Allocated TASS Graph OK")
class JumpWayREST():
def __init__(self):
self.Helpers = Helpers()
self.Logging = Logging()
self._confs = self.Helpers.loadConfigs()
self.LogFile = self.Logging.setLogFile(self._confs["AI"]["Logs"]+"Client/")
def createHashMac(self, secret, data):
return hmac.new(bytearray(secret.encode("utf-8")), data.encode("utf-8"), digestmod=hashlib.sha256).hexdigest()
def apiCall(self, apiUrl, data, headers):
self.Logging.logMessage(
self.LogFile,
"JUMPWAY",
"INFO",
"Sending JumpWay REST Request")
response = requests.post(
apiUrl,
data=json.dumps(data),
headers=headers,
auth=HTTPBasicAuth(
self._confs["iotJumpWay"]["App"],
self.createHashMac(
self._confs["iotJumpWay"]["API"]["Secret"],
self._confs["iotJumpWay"]["API"]["Secret"])))
output = json.loads(response.content)
self.Logging.logMessage(
self.LogFile,
"JUMPWAY",
"INFO",
"JumpWay REST Response Received: " + str(output))
return output
class Client():
def __init__(self):
self.Helpers = Helpers()
self._configs = self.Helpers.loadConfigs()
self.addr = "http://"+self._configs["Cameras"][0]["Stream"]+':'+str(self._configs["Cameras"][0]["StreamPort"])
self.TASSapiUrl = self.addr + '/api/TASS/infer'
self.content_type = 'image/jpeg'
self.headers = {'content-type': self.content_type}
print("-- Client Initiated")
self.testTASS()
def testTASS(self):
print("-- Using TASS Facenet Classification")
print("")
testingDir = self._configs["ClassifierSettings"]["NetworkPath"] + self._configs["ClassifierSettings"]["TestingPath"]
for test in os.listdir(testingDir):
print("-- Testing Dir: "+testingDir)
if test.endswith('.jpg') or test.endswith('.jpeg') or test.endswith('.png') or test.endswith('.gif'):
print("-- Sending "+testingDir+test)
self.sendImage(testingDir+test,"TASS")
print("")
def sendImage(self, image, model):
img = cv2.imread(image)
_, img_encoded = cv2.imencode('.png', img)
response = requests.post(self.TASSapiUrl, data=img_encoded.tostring(), headers=self.headers)
print(json.loads(response.text))
class Streamer():
def __init__(self):
###############################################################
#
# Sets up all default requirements and placeholders
#
###############################################################
self.Helpers = Helpers()
self._confs = self.Helpers.loadConfigs()
self.LogFile = self.Helpers.setLogFile(self._confs["aiCore"]["Logs"] +
"/Local")
self.MySql = MySql()
self.OpenCV = OpenCV()
self.OCVframe = None
self.font = cv2.FONT_HERSHEY_SIMPLEX
self.fontColor = (255, 255, 255)
self.fontScale = 1
self.lineType = 1
self.identified = 0
self.Facenet = Facenet()
self.movidius, self.devices, self.device = self.Facenet.CheckDevices()
self.fgraph, self.fgraphfile = self.Facenet.loadGraph(
"Facenet", self.movidius)
self.validDir = self._confs["Classifier"]["NetworkPath"] + self._confs[
"Classifier"]["ValidPath"]
self.testingDir = self._confs["Classifier"][
"NetworkPath"] + self._confs["Classifier"]["TestingPath"]
self.detector = dlib.get_frontal_face_detector()
self.predictor = dlib.shape_predictor(
self._confs["Classifier"]["Dlib"])
self.connectToCamera()
self.tassSocket = None
self.configureSocket()
self.JumpWay = JumpWay()
self.JumpWayCL = self.JumpWay.startMQTT()
self.Helpers.logMessage(self.LogFile, "TASS", "INFO", "TASS Ready")
def connectToCamera(self):
###############################################################
#
# Connects to the Foscam device using the configs in
# required/confs.json
#
###############################################################
self.OCVframe = cv2.VideoCapture(0)
self.Helpers.logMessage(self.LogFile, "TASS", "INFO",
"Connected To Camera")
def configureSocket(self):
###############################################################
#
# Configures the socket we will stream the frames to
#
###############################################################
self.tassSocket = zmq.Context().socket(zmq.PUB)
self.tassSocket.connect("tcp://" + self._confs["Socket"]["host"] +
":" + str(self._confs["Socket"]["port"]))
self.Helpers.logMessage(
self.LogFile, "TASS", "INFO",
"Connected To Socket: tcp://" + self._confs["Socket"]["host"] +
":" + str(self._confs["Socket"]["port"]))