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- #Import required modules
- import cv2
- import dlib
- #Set up some required objects
- video_capture = cv2.VideoCapture(0) #Webcam object
- detector = dlib.get_frontal_face_detector() #Face detector
- predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat") #Landmark identifier. Set the filename to whatever you named the downloaded file
- while True:
- ret, frame = video_capture.read()
- gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
- clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8,8))
- clahe_image = clahe.apply(gray)
- detections = detector(clahe_image, 1) #Detect the faces in the image
- for k,d in enumerate(detections): #For each detected face
- shape = predictor(clahe_image, d) #Get coordinates
- for i in range(1,68): #There are 68 landmark points on each face
- cv2.circle(frame, (shape.part(i).x, shape.part(i).y), 1, (0,0,255), thickness=2) #For each point, draw a red circle with thickness2 on the original frame
- cv2.imshow("image", frame) #Display the frame
- if cv2.waitKey(1) & 0xFF == ord('q'): #Exit program when the user presses 'q'
- break
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