video.py

from imutils import face_utils
import dlib
import cv2
from pytictoc import TicToc
import matplotlib.pyplot as plt
t = TicToc()
# initialize dlib's face detector (HOG-based) and then create
# the facial landmark predictor
p = "/home/ubuntu/perDeep/Face_Detector_2/shape_predictor_68_face_landmarks.dat"
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(p)
cap = cv2.VideoCapture(0)

while (True):
    t.tic()
    # Capture frame-by-frame
    ret, frame = cap.read()

    # Our operations on the frame come here
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # detect faces in the grayscale image
    rects = detector(gray, 0)
    # loop over the face detections
    for (i, rect) in enumerate(rects):
        # compute the bounding box of the face and draw it on the
        # frame
        (bX, bY, bW, bH) = face_utils.rect_to_bb(rect)
        cv2.rectangle(frame, (bX, bY), (bX + bW, bY + bH),
                      (0, 255, 0), 1)
        # determine the facial landmarks for the face region, then
        # convert the facial landmark (x, y)-coordinates to a NumPy
        # array
        shape = predictor(gray, rect)
        shape = face_utils.shape_to_np(shape)

        # loop over the (x, y)-coordinates for the facial landmarks
        # and draw each of them
        for (i, (x, y)) in enumerate(shape):
            cv2.circle(frame, (x, y), 1, (0, 0, 255), -1)
            cv2.putText(frame, str(i + 1), (x - 10, y - 10),
                        cv2.FONT_HERSHEY_SIMPLEX, 0.35, (0, 0, 255), 1)
    cv2.imshow('frame', frame)
    t.toc()
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()