read_dlib.py

import dlib # dlib for accurate face detection
import cv2 # opencv
import imutils # helper functions from pyimagesearch.com

# Grab video from your webcam
stream = cv2.VideoCapture("nvcamerasrc ! video/x-raw(memory:NVMM), width=(int)1280, height=(int)720,format=(string)I420, framerate=(fraction)24/1 ! nvvidconv flip-method=2 ! video/x-raw, format=(string)BGRx ! videoconvert ! video/x-raw, format=(string)BGR ! appsink")

# Face detector
detector = dlib.get_frontal_face_detector()

# Fancy box drawing function by Dan Masek
def draw_border(img, pt1, pt2, color, thickness, r, d):
    x1, y1 = pt1
    x2, y2 = pt2

    # Top left drawing
    cv2.line(img, (x1 + r, y1), (x1 + r + d, y1), color, thickness)
    cv2.line(img, (x1, y1 + r), (x1, y1 + r + d), color, thickness)
    cv2.ellipse(img, (x1 + r, y1 + r), (r, r), 180, 0, 90, color, thickness)

    # Top right drawing
    cv2.line(img, (x2 - r, y1), (x2 - r - d, y1), color, thickness)
    cv2.line(img, (x2, y1 + r), (x2, y1 + r + d), color, thickness)
    cv2.ellipse(img, (x2 - r, y1 + r), (r, r), 270, 0, 90, color, thickness)

    # Bottom left drawing
    cv2.line(img, (x1 + r, y2), (x1 + r + d, y2), color, thickness)
    cv2.line(img, (x1, y2 - r), (x1, y2 - r - d), color, thickness)
    cv2.ellipse(img, (x1 + r, y2 - r), (r, r), 90, 0, 90, color, thickness)

    # Bottom right drawing
    cv2.line(img, (x2 - r, y2), (x2 - r - d, y2), color, thickness)
    cv2.line(img, (x2, y2 - r), (x2, y2 - r - d), color, thickness)
    cv2.ellipse(img, (x2 - r, y2 - r), (r, r), 0, 0, 90, color, thickness)

while True:
    # read frames from live web cam stream
    (grabbed, frame) = stream.read()

    # resize the frames to be smaller and switch to gray scale
    frame = imutils.resize(frame, width=700)
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # Make copies of the frame for transparency processing
    overlay = frame.copy()
    output = frame.copy()

    # set transparency value
    alpha  = 0.5

    # detect faces in the gray scale frame
    face_rects = detector(gray, 0)

    # loop over the face detections
    for i, d in enumerate(face_rects):
        x1, y1, x2, y2, w, h = d.left(), d.top(), d.right() + 1, d.bottom() + 1, d.width(), d.height()

        # draw a fancy border around the faces
        draw_border(overlay, (x1, y1), (x2, y2), (162, 255, 0), 2, 10, 10)

    # make semi-transparent bounding box
    cv2.addWeighted(overlay, alpha, output, 1 - alpha, 0, output)

    # show the frame
    cv2.imshow("Face Detection", output)
    key = cv2.waitKey(1) & 0xFF

    # press q to break out of the loop
    if key == ord("q"):
        break

# cleanup
cv2.destroyAllWindows()
stream.stop()