def __init__(self, name='Document'): stdAPI.__init__(self, name) # create a mqtt client self.client = mqtt.Client() self.client.on_connect = self.on_connect self.client.connect("127.0.0.1", 1883, 60) self.client.loop_start()
def __init__(self, name='Capture'): stdAPI.__init__(self, name) self.filename = '' self.frame = [] self.streams = [] for i in range(10): sourceStr = 'sourceId' + str(i) if sourceStr in self.cfg.getConfig(self.name): if self.getCfgVal(sourceStr) != '': self.streams.append(self.getCfgVal(sourceStr))
def __init__(self, name='Model'): stdAPI.__init__(self, name) #tf.compat.v1.logging.set_verbosity(tf.compat.v1.logging.INFO) # get TF logger log = logging.getLogger('tensorflow') log.setLevel(logging.DEBUG) # create formatter and add it to the handlers formatter = logging.Formatter( '%(asctime)s - %(name)s - %(levelname)s - %(message)s') # create file handler which logs even debug messages fh = logging.handlers.RotatingFileHandler( '../projects/' + self.project + '/logs/tensorflow.log', 'a', 100000, 100) fh.setLevel(logging.DEBUG) fh.setFormatter(formatter) log.addHandler(fh) graphPb = '../common/frozen_models/frozen_' + self.getCfgVal( 'modelName') + '.pb' applyai.log("loading frozen graph " + graphPb + " ...", self.logname) self.graph = self.load_graph(graphPb) applyai.log("loaded frozen graph", self.logname) applyai.log("starting tf session ...", self.logname) self.session = tf.compat.v1.Session(graph=self.graph) applyai.log("started tf session", self.logname) self.inputTensor = self.graph.get_tensor_by_name( 'prefix/image_tensor:0') self.y1 = self.graph.get_tensor_by_name('prefix/num_detections:0') self.y2 = self.graph.get_tensor_by_name('prefix/detection_boxes:0') self.y3 = self.graph.get_tensor_by_name( 'prefix/detection_scores:0') self.y4 = self.graph.get_tensor_by_name( 'prefix/detection_classes:0') self.counter = 1
def __init__(self, name='Measure'): stdAPI.__init__(self, name) self.svg = [] #pd.DataFrame(columns=['id','x1','y1','x2','y2','cx','cy']) self.moiId = 0 self.scaleX = 1 self.scaleY = 1
def __init__(self, name='Calibrate'): stdAPI.__init__(self, name) self.objpoints = list(self.getCfgVal('objPoints')) self.imgpoints = list(self.getCfgVal('imgPoints'))
def __init__(self, name='LinesHough'): stdAPI.__init__(self, name)
def __init__(self, name='FillHoles'): stdAPI.__init__(self, name)
def __init__(self, name='Classify'): stdAPI.__init__(self, name)
def __init__(self, name='Ocr'): stdAPI.__init__(self, name)
def __init__(self, name='Edges'): stdAPI.__init__(self, name)
def __init__(self, name='TemplateMatch'): stdAPI.__init__(self, name)
def __init__(self, name='IsolateThread'): stdAPI.__init__(self, name)
def __init__(self, name='Datamatrix'): stdAPI.__init__(self, name)
def __init__(self, name='Noise'): stdAPI.__init__(self, name)
def __init__(self, name='Flir'): stdAPI.__init__(self, name) applyai.log('in init CameraFeed', self.logname) applyai.engine.subscribe('newframe', self.updateFrame)
def __init__(self, name='Circles'): stdAPI.__init__(self, name)
def __init__(self, name='BBox'): stdAPI.__init__(self, name)
def __init__(self, name='FillGap'): stdAPI.__init__(self, name) applyai.log('in init', self.logname)
def __init__(self, name='Project'): stdAPI.__init__(self, name) self.lastParamsResp = {}
def __init__(self, name='System'): stdAPI.__init__(self, name)
def __init__(self, name='Calc'): stdAPI.__init__(self, name) self.cc = 0
def __init__(self, name='Color'): stdAPI.__init__(self, name)
def __init__(self, name='Top'): stdAPI.__init__(self, name)
def __init__(self, name='GripPos'): stdAPI.__init__(self, name)
def __init__(self, name='Mask'): stdAPI.__init__(self, name)
def __init__(self, name='Screws'): stdAPI.__init__(self, name)
def __init__(self, name='Pixel2mm'): stdAPI.__init__(self, name)