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', token='token_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 #https://github.com/opencv/opencv/blob/master #/data/haarcascades/haarcascade_frontalface_default.xml # 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( "path") # 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 = cap.read() 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): try: 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"): break # Close the window cap.release() # De-allocate any associated memory usage cv2.destroyAllWindows()
We evaluated the performance of Llama 3.1 vs GPT-4 models on over 150 benchmark datasets…
The manufacturing industry is undergoing a significant transformation with the advent of Industrial IoT Solutions.…
If you're reading this, you must have heard the buzz about ChatGPT and its incredible…
How to Use ChatGPT in Cybersecurity If you're a cybersecurity geek, you've probably heard about…
Introduction In the dynamic world of cryptocurrencies, staying informed about the latest market trends is…
The Events Calendar Widgets for Elementor has become easiest solution for managing events on WordPress…