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)
