Return 如果面部被检测到至少 3 秒，则为真

Question

如何让网络摄像头保持打开状态并使用 haar 级联进行人脸检测仅几秒钟？

我有一个函数，这个函数returns如果已经对人脸进行了人脸检测，则为true，但不能一检测到就立即进行，而必须只进行例如，在检测到人脸至少 3 秒后。

如果我使用时间模块并等待，显然这只会减慢我的程序的执行速度，因此也会减慢 cv2.VideoCapture 的执行速度，看到不稳定的网络摄像头。

代码如下：

import cv2

def face_detect():
    video_capture = cv2.VideoCapture(0)
    while True:
        # Capture frame-by-frame
        ret, frames = video_capture.read()
        gray = cv2.cvtColor(frames, cv2.COLOR_BGR2GRAY)
        faces = faceCascade.detectMultiScale(
            gray,
            scaleFactor=1.1,
            minNeighbors=5,
            minSize=(30, 30),
            flags=cv2.CASCADE_SCALE_IMAGE
        )
        # Draw a rectangle around the faces
        for (x, y, w, h) in faces:
            cv2.rectangle(frames, (x, y), (x+w, y+h), (0, 255, 0), 2)
            return True

if __name__ == '__main__': 
    detected = face_detect()
    if detected == True:
        print("The face is detected. OK")
    else:
        print("I'm sorry but I can't detect your face")

Answer 1

简单记录检测到人脸的时间，只看到检测到人脸时绘制人脸和当前时间戳是timeout秒后记录的时间戳。

import cv2
from time import time

def face_detect(timeout):
    video_capture = cv2.VideoCapture(0)
    start_time    = 0      # Temporary value.
    face_detected = False  # Used to see if we've detected the face.
    while True:
        # Capture frame-by-frame
        ret, frames = video_capture.read()
        gray = cv2.cvtColor(frames, cv2.COLOR_BGR2GRAY)
        faces = faceCascade.detectMultiScale(
            gray,
            scaleFactor=1.1,
            minNeighbors=5,
            minSize=(30, 30),
            flags=cv2.CASCADE_SCALE_IMAGE
        )

        if not face_detected and faces:
            face_detected = True
            start_time    = time()
        elif not faces:
            face_detected = False  # Reset if we don't find the faces.
        elif face_detected and time() - start_time >= timeout:
            # Draw a rectangle around the faces
            for (x, y, w, h) in faces:
                cv2.rectangle(frames, (x, y), (x+w, y+h), (0, 255, 0), 2)
                return True

if __name__ == '__main__':
    detected = face_detect(timeout=3)
    if detected == True:
        print("The face is detected. OK")
    else:
        print("I'm sorry but I can't detect your face")

Return 如果面部被检测到至少 3 秒，则为真

Return True if the face is detected at least for 3 seconds

python

opencv

face-detection

haar-classifier