def run(self, context: ConsumerContext):
if not self.initialized:
self.initialize()
img = context.data
context.alert = False
if img is not None:
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = self.face_cascade.detectMultiScale(
image=img,
scaleFactor=self.parameters['scale_factor'],
minNeighbors=self.parameters['min_neighbors'])
# Take one of the faces and process that
if len(faces) > 0:
(x, y, w, h) = faces[0]
context.alert = True
context.alert_data = 'Face detected'
context.data = img[y:(y + h), x:(x + w)]
FacedetectorConsumer.LOGGER.info(context.alert_data)
else:
FacedetectorConsumer.LOGGER.debug('Could not detect any faces')
else:
FacedetectorConsumer.LOGGER.warning('No image')
time.sleep(self.parameters['timeout'])
return context
def run(self, context: ConsumerContext):
if not self.initialized:
self.initialize()
# the data is expected to be the detected face
face = context.data
context.alert = True
if face is not None:
face = cv2.resize(face, (self.parameters['size'], self.parameters['size']))
name = self.recognize(face)
if name is None:
context.alert_data = 'Cannot recognize face'
else:
context.alert = False
context.alert_data = name
else:
FacerecognizerConsumer.LOGGER.warning('Face was not provided (is None)')
return context
def run(self, context: ConsumerContext):
img = context.data
context.alert = False
if img is None:
MotiondetectorConsumer.LOGGER.debug('No image')
time.sleep(self.parameters['timeout'])
return context
frame = cv2.resize(img, (self.parameters['resize_width'], self.parameters['resize_height']))
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (21, 21), 0)
# if the first frame is None, initialize it
if self.previous_frame is None:
self.previous_frame = gray
return context
# compute the absolute difference between the current frame and previous frame
frame_delta = cv2.absdiff(self.previous_frame, gray)
(_, thresh) = cv2.threshold(src=frame_delta,
thresh=self.parameters['threshold'],
maxval=self.parameters['threshold_max_val'],
type=cv2.THRESH_BINARY)
# dilate the image to fill in holes, then find contours on image
thresh = cv2.dilate(thresh, None, iterations=self.parameters['dilate_iteration'])
(_, contours, _) = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
# loop over the contours
motion_detected = any([True for c in contours if cv2.contourArea(c) > self.parameters['area_threshold']])
if motion_detected:
context.alert = True
context.alert_data = 'Motion detected'
MotiondetectorConsumer.LOGGER.debug(context.alert_data)
else:
MotiondetectorConsumer.LOGGER.debug('No motion was detected')
self.previous_frame = gray
return context
def run(self, context: ConsumerContext):
if not self.initialized:
self.initialize()
# the data is expected to be the detected face
face = context.data
context.alert = True
if face is not None:
NnrecognizerConsumer.LOGGER.info('Running face recognition...')
if self.recognize(face):
context.alert = False
context.alert_data = 'Positive recognition'
NnrecognizerConsumer.LOGGER.info(context.alert_data)
else:
context.alert_data = NnrecognizerConsumer.img_to_str(face)
NnrecognizerConsumer.LOGGER.info('Negative recognition')
else:
NnrecognizerConsumer.LOGGER.warning(
'Face was not provided (is None)')
context.alert_data = 'No face provided'
return context
def run(self, context: ConsumerContext):
if not self.initialized:
self.initialize()
audio = None
audio = context.data
context.alert = False
zones = self.zone_manager.get_zones()
if audio:
try:
voice_recognition = self.VoiceRecognizer.recognize_google(
audio)
VoicerecognizerConsumer.LOGGER.info('You said: ' +
voice_recognition)
#Search in the zone dictionary the word that the user said
for key, value in zones.items():
if key in voice_recognition:
#search for the value in the word, whether on or off
if 'off' in voice_recognition:
if zones[key] == False:
VoicerecognizerConsumer.LOGGER.info(
key + ' is already inactive')
break
else:
self.zone_manager.toggle_zone(key)
break
if 'on' in voice_recognition:
if zones[key] == True:
VoicerecognizerConsumer.LOGGER.info(
key + ' is already active')
break
else:
self.zone_manager.toggle_zone(key)
break
except sr.UnknownValueError:
VoicerecognizerConsumer.LOGGER.info(
'Voicerecognizer could not understand audio')
except sr.RequestError as e:
print(
"Could not request results from Speech Recognition service; {0}"
.format(e))
time.sleep(3)
return context