- 首先安装库
- 下载模型文件
- 修改model_path和vedio_path
- 运行
"""
@author:fuzekun
@file:eyes_detect.py
@time:2023/03/02
@description:
根据人眨眼次数检测是否困倦
"""
import os
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):
A = dist.euclidean(eye[1], eye[5])
B = dist.euclidean(eye[2], eye[4])
C = dist.euclidean(eye[0], eye[3])
ear = (A + B) / (2.0 * C)
return ear
EYE_AR_THRESH = 0.2
EYE_AR_CONSEC_FRAMES = 3
COUNTER = 0
TOTAL = 0
model_path = 'model/shape_predictor_68_face_landmarks.dat'
vedio_path = "d:/data/camera/"
vedio_name = "WIN_20230302_20_52_44_Pro.mp4"
print("[INFO] loading facial landmark predictor...")
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(model_path)
(lStart, lEnd) = face_utils.FACIAL_LANDMARKS_IDXS["left_eye"]
(rStart, rEnd) = face_utils.FACIAL_LANDMARKS_IDXS["right_eye"]
if not os.path.exists(vedio_path + vedio_name):
raise FileNotFoundError("没有找到该文件:" + (vedio_path + vedio_name))
videoCapture = cv2.VideoCapture(vedio_path + vedio_name)
i = 0
while True:
ret, frame = videoCapture.read()
if not ret :
break
i += 1
frame = imutils.resize(frame, width=720)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
rects = detector(gray, 0)
for rect in rects:
shape = predictor(gray, rect)
shape = face_utils.shape_to_np(shape)
leftEye = shape[lStart:lEnd]
rightEye = shape[rStart:rEnd]
leftEAR = eye_aspect_ratio(leftEye)
rightEAR = eye_aspect_ratio(rightEye)
ear = (leftEAR + rightEAR) / 2.0
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)
left = rect.left()
top = rect.top()
right = rect.right()
bottom = rect.bottom()
cv2.rectangle(frame, (left, top), (right, bottom), (0, 255, 0), 3)
'''
分别计算左眼和右眼的评分求平均作为最终的评分,如果小于阈值,则加1,如果连续3次都小于阈值,则表示进行了一次眨眼活动
'''
if ear < EYE_AR_THRESH:
COUNTER += 1
else:
if COUNTER >= EYE_AR_CONSEC_FRAMES:
TOTAL += 1
COUNTER = 0
for (x, y) in shape:
cv2.circle(frame, (x, y), 1, (0, 0, 255), -1)
cv2.putText(frame, "Faces: {}".format(len(rects)), (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
cv2.putText(frame, "Blinks: {}".format(TOTAL), (150, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
cv2.putText(frame, "COUNTER: {}".format(COUNTER), (300, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
cv2.putText(frame, "EAR: {:.2f}".format(ear), (450, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
if TOTAL >= 50:
cv2.putText(frame, "SLEEP!!!", (200, 200), cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 2)
cv2.imshow("Frame", frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
print(f"总眨眼次数为{
TOTAL}")
videoCapture.release()
cv2.destroyAllWindows()