# draw the text and timestamp on the frame
ts = timestamp.strftime("%A %d %B %Y %I:%M:%S%p")
cv2.putText(image, "Room Status : {}".format(text), (10, 35), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
cv2.putText(image, ts, (10, image.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.35, (0, 0, 255), 1)
# Uncomment this line if the live feed is to be seen
#cv2.imshow("Security Camera", image)
if text == "Occupied":
if (timestamp - lastUploaded).seconds >= conf["min_upload_seconds"]:
motionCounter += 1
if motionCounter >= conf["min_motion_frames"]:
if len(faces): # checking if number of faces found is > 0
cv2.imwrite("Captured_Img.jpg", image)
image_path = "Captured_Img.jpg"
FaceRecognizer.train_data()
prediction, confidence = FaceRecognizer.predict(image_path)
print prediction, confidence
# now check if person belongs to known set of people or not by thresholding confidence level
if confidence < 50:
print " WELCOME :", known_people[prediction]
cv2.putText(image, "Verified User : {}".format(known_people[prediction]), (10, image.shape[0] - 30), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
cv2.imwrite("Captured_Img.jpg", image)
else:
print "ALERT! NOT VERIFIED! CALL THE POLICE!"
cv2.putText(image, "ALERT! NOT VERIFIED! CALL THE POLICE!", (10, image.shape[0] -30), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
cv2.imwrite("Captured_Img.jpg", image)
if conf["use_dropbox"]:
# check if image file was already created due to presence of faces
# else create image file due to motion detection only
