Question

我的系统（实时高清视频）的主要目的是在检测到脸部后我们可以轻松检测到眼睛，我的系统需要知道每个人每分钟闭眼的次数，并跟踪他的眼睛还有，实现这个的任何想法？

也许像这个视频，但在真实视频中 https://www.youtube.com/watch?v=JL3Gbb9aY0c

https://www.youtube.com/watch?v=R8m4ovTZSYA

Answer 1

如果您正在检测眼睛，那么您有一些描述检测质量的指标值（例如，如果使用模板，则使用相关系数，如果搜索圆圈，则使用Hough变换峰值的强度）。

您可以执行一些实验并绘制此值，以查找发生眨眼时下降的程度因此转换高值 - 低（低于某个级别） - 高（如10-10-11-9-11-10-5-2-6-11-10的情况可能表示闪烁情况。

Answer 2

这Python代码应该帮助你启动了与使用OpenCV的和Python眨眼检测。代码实现要求您下载landmarks文件并使用以下命令安装 dlib ：

pip install https://pypi.python.org/packages/da/06/bd3e241c4eb0a662914b3b4875fc52dd176a9db0d4a2c915ac2ad8800e9e/dlib-19.7.0-cp36-cp36m-win_amd64.whl

现在，您一切顺利！您可以将地标（.dat）文件与以下代码放置在同一文件夹中，并在终端中运行以下脚本

import numpy as np
import dlib
from math import hypot
import time

cap = cv2.VideoCapture(0)#camera port 0


detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")

def midpoint(p1,p2):
    return int((p1.x + p2.x)/2),int((p1.y + p2.y)/2)

font = cv2.FONT_HERSHEY_SIMPLEX

def get_blinking_ratio(eye_points, facial_landmarks):
    left_point = (facial_landmarks.part(eye_points[0]).x, facial_landmarks.part(eye_points[0]).y)
    right_point = (facial_landmarks.part(eye_points[3]).x, facial_landmarks.part(eye_points[3]).y)
    hor_line = cv2.line(frame, left_point, right_point,(0,255,0), 1)

    center_top = midpoint(facial_landmarks.part(eye_points[1]), facial_landmarks.part(eye_points[2]))
    center_bottom = midpoint(facial_landmarks.part(eye_points[5]), facial_landmarks.part(eye_points[4]))
    ver_line = cv2.line(frame, center_top, center_bottom,(0,255,0), 1)

    #length of the line
    hor_line_length = hypot((left_point[0] - right_point[0]), (left_point[1] - right_point[1]))
    ver_line_length = hypot((center_top[0] - center_bottom[0]), (center_top[1] - center_bottom[1]))
    ratio = hor_line_length/ ver_line_length, ver_line_length
    return ratio

blink = 1
TOTAL = 0
thres = 5.1
while True:
    _, frame = cap.read()
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)#for gray images(lightweight)
    faces = detector(gray)
    for face in faces:
        #x, y = face.left(), face.top()
        #x1, y1 = face.right(), face.bottom()
        #cv2.rectangle(frame, (x,y), (x1,y1), (0,255,0), 3 )# green box, thickness of box
        landmarks = predictor(gray, face)
        left_eye_ratio,_ = get_blinking_ratio([36,37,38,39,40,41], landmarks)
        right_eye_ratio, myVerti = get_blinking_ratio([42,43,44,45,46,47], landmarks)
        blinking_ratio = (left_eye_ratio+right_eye_ratio)/2
        personal_threshold = 0.67 * myVerti #0.67 is just the best constant I found with experimentation
        cv2.putText(frame, "left ratio: {:.2f}".format(left_eye_ratio), (300, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
        cv2.putText(frame, "right ratio: {:.2f}".format(right_eye_ratio), (500, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
        if (left_eye_ratio>personal_threshold or right_eye_ratio>personal_threshold) and blink == 1:
            TOTAL += 1
            time.sleep(0.3)#average persons blinking time
        if (left_eye_ratio>personal_threshold or right_eye_ratio>personal_threshold):
            blink = 0
        else:
            blink = 1

        cv2.putText(frame, "Blinks: {}".format(TOTAL), (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)

    cv2.imshow("Frame", frame)

    key = cv2.waitKey(5)
    if key == 27:
        break

cap.release()
cv2.destroyAllWindow()

它可以检测和计数任何眼睛大小的人的眨眼。不幸的是，我有检测眨眼为人与眼镜的麻烦。

Answer 3

if ear > EYE_AR_THRESH:
        COUNTER += 1        
else:           
    if COUNTER >= EYE_AR_CONSEC_FRAMES:
        TOTAL = TOTAL+1
        print(TOTAL)
        # COUNTER = 0
        # print(COUNTER)
    cv2.putText(img, "Blinks: {}".format(TOTAL), (10, 30),
        cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
    cv2.putText(img, "EAR: {:.2f}".format(ear), (300, 30),
        cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)

cv2.imshow('detect eyes blink', img)

if cv2.waitKey(1) == ord('q'):
    break

cap.release()
cv2.destroyAllWindows()

眨眼检测

3 个答案: