0003-dlib检测嘴巴是否张开

冷不防 2023-01-04 10:24 84阅读 0赞

# USAGE
    # python detect_drowsiness.py --shape-predictor shape_predictor_68_face_landmarks.dat
    # python detect_drowsiness.py --shape-predictor shape_predictor_68_face_landmarks.dat --alarm alarm.wav
    
    # import the necessary packages
    from scipy.spatial import distance as dist
    from imutils.video import FileVideoStream
    from imutils import face_utils
    from threading import Thread
    import numpy as np
    import argparse
    import imutils
    import time
    import dlib
    import cv2
    
    def mouth_aspect_ratio(mouth):
    	# compute the euclidean distances between the two sets of
    	# vertical mouth landmarks (x, y)-coordinates
    	A = dist.euclidean(mouth[2], mouth[9]) # 51, 59
    	B = dist.euclidean(mouth[4], mouth[7]) # 53, 57
    
    	# compute the euclidean distance between the horizontal
    	# mouth landmark (x, y)-coordinates
    	C = dist.euclidean(mouth[0], mouth[6]) # 49, 55
    
    	# compute the mouth aspect ratio
    	mar = (A + B) / (2.0 * C)
    
    	# return the mouth aspect ratio
    	return mar
    
    # construct the argument parse and parse the arguments
    ap = argparse.ArgumentParser()
    ap.add_argument("-p", "--shape-predictor", required=False, default='shape_predictor_68_face_landmarks.dat',
    	help="path to facial landmark predictor")
    ap.add_argument("-v", "--video", default="trump.mp4",
    	help="video path input")
    args = vars(ap.parse_args())
    
    # define one constants, for mouth aspect ratio to indicate open mouth
    MOUTH_AR_THRESH = 0.6
    
    # initialize dlib's face detector (HOG-based) and then create
    # the facial landmark predictor
    print("[INFO] loading facial landmark predictor...")
    detector = dlib.get_frontal_face_detector()
    predictor = dlib.shape_predictor(args["shape_predictor"])
    
    # grab the indexes of the facial landmarks for the mouth
    (mStart, mEnd) = (49, 68)
    
    # start the video stream thread
    print("[INFO] starting video stream thread...")
    fvs = FileVideoStream(path=args["video"]).start()
    time.sleep(1.0)
    
    frame_width = 640
    frame_height = 360
    
    # Define the codec and create VideoWriter object.The output is stored in 'outpy.avi' file.
    out = cv2.VideoWriter('outpy.avi',cv2.VideoWriter_fourcc('M','J','P','G'), 30, (frame_width,frame_height))
    time.sleep(1.0)
    
    # loop over frames from the video stream
    while True:
    	# grab the frame from the threaded video file stream, resize
    	# it, and convert it to grayscale
    	# channels)
    	frame = fvs.read()
    	frame = imutils.resize(frame, width=640)
    	gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    
    	# detect faces in the grayscale frame
    	rects = detector(gray, 0)
    
    	# loop over the face detections
    	for rect in rects:
    		# 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)
    
    		# extract the mouth coordinates, then use the
    		# coordinates to compute the mouth aspect ratio
    		mouth = shape[mStart:mEnd]
    		mar = mouth_aspect_ratio(mouth)
    
    		# compute the convex hull for the mouth, then
    		# visualize the mouth
    		mouthHull = cv2.convexHull(mouth)
    
    		cv2.drawContours(frame, [mouthHull], -1, (0, 255, 0), 1)
    		cv2.putText(frame, "MAR: {:.2f}".format(mar), (30, 30),
    			cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
    
            # Draw text if mouth is open
    		if mar > MOUTH_AR_THRESH:
    			cv2.putText(frame, "Mouth is Open!", (30,60),
    			cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0,0,255),2)
    	# Write the frame into the file 'output.avi'
    	out.write(frame)
    	# show the frame
    	cv2.imshow("Frame", frame)
    	key = cv2.waitKey(1) & 0xFF
    
    	# if the `q` key was pressed, break from the loop
    	if key == ord("q"):
    		break
    
    # do a bit of cleanup
    cv2.destroyAllWindows()
    fvs.stop()

## 参考 ##

*  [python dlib学习（十一）：眨眼检测][python dlib]

[python dlib]: https://blog.csdn.net/hongbin_xu/article/details/79033116