Python 3 OpenCV Detect People Face in Webcam and Send SMS Using Sinch API in Command Line

pip install opencv-python

# OpenCV program to detect face in real time
# import libraries of python OpenCV
# where its functionality resides

from cv2 import cv2

import clx.xms
import requests
# By creating an account in sinch sms You can get your code.
# code for sms starts here
#client is a object that carries your unique token.
client = clx.xms.Client(service_plan_id='your_service id',

create = clx.xms.api.MtBatchTextSmsCreate()
create.sender = 'sender no.'
create.recipients = {'recipients no.'}
create.body = 'This is a test message from your Sinch account'
# code for sms ends here
# Face Recognition starts from here.
# load the required trained XML classifiers
# Trained XML classifiers describes some features of some
# object we want to detect a cascade function is trained
# from a lot of positive(faces) and negative(non-faces)
# images.

detector = cv2.CascadeClassifier(

# capture frames from a camera

cap = cv2.VideoCapture(0, cv2.CAP_DSHOW)
#We want to send sms only once not until the face is there and for that we are
#initializing the counter
counter = 0
# loop runs if capturing has been initialized.

while True:
  # reads frames from a camera

  ret, img =

  if ret:
    # convert to gray scale of each frames

    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
  # Detects faces of different sizes in the input image

    faces = detector.detectMultiScale(gray, 1.1, 4)

    for face in faces:
      x, y, w, h = face
      # if there is any face and counter is zero then only it will send notification to the sender
      if(face.any() and counter ==0):
        batch = client.create_batch(create)
        except (requests.exceptions.RequestException, clx.xms.exceptions.ApiException) as ex:
          print('Failed to communicate with XMS: %s' % str(ex))
        #sms ends here
      # To draw a rectangle in a face
      cv2.rectangle(img, (x, y), (x+w, y+h), (255, 0, 0), 2)
    cv2.imshow("Face", img)
    counter = 1
  # Wait for 'q' key to stop

  key = cv2.waitKey(1)
  if key == ord("q"):
# Close the window
# De-allocate any associated memory usage


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