python-3.x - 使用dlib和opencv进行眨眼检测

Question

我已经从pyimagesearch得到了这段代码，并试图运行它，但是当我运行文件时，我得到了这些错误。谁能告诉我这里有什么问题吗？我已经安装了所有需要的软件包和库。所有conda程序包都是最新的。请查看“错误代码”部分，看看是否可以找出问题所在。

    # USAGE
    # python detect_blinks.py --shape-predictor 
    shape_predictor_68_face_landmarks.dat --video blink_detection_demo.mp4
    # python detect_blinks.py --shape-predictor 
      shape_predictor_68_face_landmarks.dat

# import the necessary packages
from scipy.spatial import distance as dist
from imutils.video import FileVideoStream
from imutils.video import VideoStream
from imutils import face_utils
import numpy as np
import argparse
import imutils
import time
import dlib
import cv2

def eye_aspect_ratio(eye):
    # compute the euclidean distances between the two sets of
    # vertical eye landmarks (x, y)-coordinates
    A = dist.euclidean(eye[1], eye[5])
    B = dist.euclidean(eye[2], eye[4])

    # compute the euclidean distance between the horizontal
    # eye landmark (x, y)-coordinates
    C = dist.euclidean(eye[0], eye[3])

    # compute the eye aspect ratio
    ear = (A + B) / (2.0 * C)

    # return the eye aspect ratio
    return ear

# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-p", "--shape-predictor", required=True,
    help="path to facial landmark predictor")
ap.add_argument("-v", "--video", type=str, default="",
    help="path to input video file")
args = vars(ap.parse_args())

# define two constants, one for the eye aspect ratio to indicate
# blink and then a second constant for the number of consecutive
# frames the eye must be below the threshold
EYE_AR_THRESH = 0.3
EYE_AR_CONSEC_FRAMES = 3

# initialize the frame counters and the total number of blinks
COUNTER = 0
TOTAL = 0

# 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 left and
# right eye, respectively
(lStart, lEnd) = face_utils.FACIAL_LANDMARKS_IDXS["left_eye"]
(rStart, rEnd) = face_utils.FACIAL_LANDMARKS_IDXS["right_eye"]

# start the video stream thread
print("[INFO] starting video stream thread...")
vs = FileVideoStream(args["video"]).start()
fileStream = True
# vs = VideoStream(src=0).start()
# vs = VideoStream(usePiCamera=True).start()
# fileStream = False
time.sleep(1.0)

# loop over frames from the video stream
while True:
    # if this is a file video stream, then we need to check if
    # there any more frames left in the buffer to process
    if fileStream and not vs.more():
        break

    # grab the frame from the threaded video file stream, resize
    # it, and convert it to grayscale
    # channels)
    frame = vs.read()
    frame = imutils.resize(frame, width=450)
    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 left and right eye coordinates, then use the
        # coordinates to compute the eye aspect ratio for both eyes
        leftEye = shape[lStart:lEnd]
        rightEye = shape[rStart:rEnd]
        leftEAR = eye_aspect_ratio(leftEye)
        rightEAR = eye_aspect_ratio(rightEye)

        # average the eye aspect ratio together for both eyes
        ear = (leftEAR + rightEAR) / 2.0

        # compute the convex hull for the left and right eye, then
        # visualize each of the eyes
        leftEyeHull = cv2.convexHull(leftEye)
        rightEyeHull = cv2.convexHull(rightEye)
        cv2.drawContours(frame, [leftEyeHull], -1, (0, 255, 0), 1)
        cv2.drawContours(frame, [rightEyeHull], -1, (0, 255, 0), 1)

        # check to see if the eye aspect ratio is below the blink
        # threshold, and if so, increment the blink frame counter
        if ear < EYE_AR_THRESH:
            COUNTER += 1

        # otherwise, the eye aspect ratio is not below the blink
        # threshold
        else:
            # if the eyes were closed for a sufficient number of
            # then increment the total number of blinks
            if COUNTER >= EYE_AR_CONSEC_FRAMES:
                TOTAL += 1

            # reset the eye frame counter
            COUNTER = 0

        # draw the total number of blinks on the frame along with
        # the computed eye aspect ratio for the frame
        cv2.putText(frame, "Blinks: {}".format(TOTAL), (10, 30),
            cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
        cv2.putText(frame, "EAR: {:.2f}".format(ear), (300, 30),
            cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)

    # 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()
vs.stop()

错误是

usage: detect_blinks.py [-h] -p SHAPE_PREDICTOR [-v VIDEO]
detect_blinks.py: error: the following arguments are required: -p/--shape- 
   predictor
An exception has occurred, use %tb to see the full traceback.

SystemExit: 2




%tb
Traceback (most recent call last):

  File "<ipython-input-6-55db51806586>", line 1, in <module>
    runfile('C:/Users/Rayhan/Downloads/Compressed/blink-detection/blink-detection/detect_blinks.py', wdir='C:/Users/Rayhan/Downloads/Compressed/blink-detection/blink-detection')

  File "C:\ProgramData\Anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 668, in runfile
    execfile(filename, namespace)

  File "C:\ProgramData\Anaconda3\lib\site-packages\spyder_kernels\customize\spydercustomize.py", line 108, in execfile
    exec(compile(f.read(), filename, 'exec'), namespace)

  File "C:/Users/Rayhan/Downloads/Compressed/blink-detection/blink-detection/detect_blinks.py", line 39, in <module>
    args = vars(ap.parse_args())

  File "C:\ProgramData\Anaconda3\lib\argparse.py", line 1734, in parse_args
    args, argv = self.parse_known_args(args, namespace)

  File "C:\ProgramData\Anaconda3\lib\argparse.py", line 1766, in parse_known_args
    namespace, args = self._parse_known_args(args, namespace)

  File "C:\ProgramData\Anaconda3\lib\argparse.py", line 2001, in _parse_known_args
    ', '.join(required_actions))

  File "C:\ProgramData\Anaconda3\lib\argparse.py", line 2393, in error
    self.exit(2, _('%(prog)s: error: %(message)s\n') % args)

  File "C:\ProgramData\Anaconda3\lib\argparse.py", line 2380, in exit
    _sys.exit(status)

SystemExit: 2

Answer 1

这是我的代码有效:

import numpy as np  
import cv2  
import dlib  
from scipy.spatial import distance as dist  
   
PREDICTOR_PATH = "/home/erp-next/Downloads/shape_predictor_68_face_landmarks.dat"  
   
# FULL_POINTS = list(range(0, 68))  
# FACE_POINTS = list(range(17, 68))  
   
# JAWLINE_POINTS = list(range(0, 17))  
# RIGHT_EYEBROW_POINTS = list(range(17, 22))  
# LEFT_EYEBROW_POINTS = list(range(22, 27))  
# NOSE_POINTS = list(range(27, 36))  
RIGHT_EYE_POINTS = list(range(36, 42)) 
LEFT_EYE_POINTS = list(range(42, 48))  
# MOUTH_OUTLINE_POINTS = list(range(48, 61))  
# MOUTH_INNER_POINTS = list(range(61, 68))  
   
EYE_AR_THRESH = 0.2 
EYE_AR_CONSEC_FRAMES = 2  
frame_c=0   
COUNTER_LEFT = 0  
TOTAL_LEFT = 0  
   
COUNTER_RIGHT = 0  
TOTAL_RIGHT = 0  
   
def eye_aspect_ratio(eye):  
   # compute the euclidean distances between the two sets of  
   # vertical eye landmarks (x, y)-coordinates  
   A = dist.euclidean(eye[1], eye[5])  
   B = dist.euclidean(eye[2], eye[4])  
   
   # compute the euclidean distance between the horizontal  
   # eye landmark (x, y)-coordinates  
   C = dist.euclidean(eye[0], eye[3])  
   
   # compute the eye aspect ratio  
   ear = (A + B) / (2.0 * C)  
   
   # return the eye aspect ratio  
   return ear  
   
detector = dlib.get_frontal_face_detector()  
   
predictor = dlib.shape_predictor(PREDICTOR_PATH)  
   
# Start capturing the WebCam  
video_capture = cv2.VideoCapture(0)  
   
while True:
   global frame_c   
   print(frame_c)
   frame_c +=1
   ret, frame = video_capture.read()  
   
   if ret:  
     gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)  
   
     rects = detector(gray, 0)  
   
     for rect in rects:  
       x = rect.left()  
       y = rect.top()  
      #  x1 = rect.right()  
      #  y1 = rect.bottom()  
   
       landmarks = np.matrix([[p.x, p.y] for p in predictor(frame, rect).parts()])  
   
       left_eye = landmarks[LEFT_EYE_POINTS]  
       right_eye = landmarks[RIGHT_EYE_POINTS]  
       
       left_eye_hull = cv2.convexHull(left_eye)  
       right_eye_hull = cv2.convexHull(right_eye)  
       cv2.drawContours(frame, [left_eye_hull], -1, (0, 255, 0), 1)  
       cv2.drawContours(frame, [right_eye_hull], -1, (0, 255, 0), 1)  
   
       ear_left = eye_aspect_ratio(left_eye)  
       ear_right = eye_aspect_ratio(right_eye)  
   
       cv2.putText(frame, "E.A.R. Left : {:.2f}".format(ear_left), (300, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 255), 2)  
       cv2.putText(frame, "E.A.R. Right: {:.2f}".format(ear_right), (300, 60), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 255), 2)  
   
       if ear_left < EYE_AR_THRESH:  
         COUNTER_LEFT += 1  
       else:  
         if COUNTER_LEFT >= EYE_AR_CONSEC_FRAMES:  
           TOTAL_LEFT += 1  
           print("Left eye winked")  
         COUNTER_LEFT = 0  
   
       if ear_right < EYE_AR_THRESH:  
         COUNTER_RIGHT += 1  
       else:  
         if COUNTER_RIGHT >= EYE_AR_CONSEC_FRAMES:  
           TOTAL_RIGHT += 1  
           print("Right eye winked")
         COUNTER_RIGHT = 0  
   
     cv2.putText(frame, "Wink Left : {}".format(TOTAL_LEFT), (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 255), 2)   
     cv2.putText(frame, "Wink Right: {}".format(TOTAL_RIGHT), (10, 60), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 255), 2)  
   
     cv2.imshow("Faces found", frame)  
   
   ch = 0xFF & cv2.waitKey(1)  
   
   if ch == ord('q'):  
     break  
   
cv2.destroyAllWindows()  

上面的代码使用“shape_predictor_68_face_landmarks.dat”库在脸上绘制68个预定义点。
使用这些点将跟踪眼睛，并使用欧氏距离算法检查眼睛是否眨眼。

试试这个。