crop=False)
embedder.setInput(faceBlob)
vec = embedder.forward()
# perform classification to recognize the face
preds = recognizer.predict_proba(vec)[0]
j = np.argmax(preds)
proba = preds[j]
name = le.classes_[j]
cv2.imwrite('img1.jpg', frame)
if (name == "your name"):
dawsenCount += 1
if (dawsenCount == 20):
#send_sms.sendText('+friend number','Dawsen is home')
send_sms.sendText('+your number', 'Dawsen is home')
if (name == "friend name"):
dawsenCount += 1
if (mirandaCount == 20):
send_sms.sendText('+friend number', 'Miranda is home')
if (name == "unkown"):
unknownCount += 1
if (unknownCount == 50):
send_sms.sendText(
'+your number',
'**** INTRUDER ****\nuknown person in your home')
# draw the bounding box of the face along with the
# associated probability
text = "{}: {:.2f}%".format(name, proba * 100)
y = startY - 10 if startY - 10 > 10 else startY + 10
def run(self): send=sendText() send.send_text()
def handler(self,event,button_event):
print('Handler %s' % button_event)
if button_event == 'press':
send_sms.sendText()
