如何在使用网络摄像头运行运动检测时连续捕获图像？ （Python）

Question

我正在考虑是否可以在运动检测使用我的笔记本电脑网络摄像头时拍照，所以我使用了 Pyimagesearch 网站上的以下代码。我想做的是在运动检测器使用网络摄像头检测到某些东西时拍照，而帧与前一个不同，然后拍照并将其保存到文件中，我尝试了 'ret, frame = cap. read()' 但效果不好，我可能把它弄错了，有人可以帮我解决这个问题吗？

代码在这里：

# import the necessary packages
from imutils.video import VideoStream
import argparse
import datetime
import imutils     #pip install imutils on terminal
import time
import cv2
# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video", help="path to the video file")    #video file is optional, if video file equals None, then opencv will use webcam
ap.add_argument("-a", "--min-area", type=int, default=500, help="minimum area size")  #500 pixels, no need to process large raw images through webcam
args = vars(ap.parse_args())
# if the video argument is None, then we are reading from webcam
if args.get('video', None) is None:
    vs = VideoStream(src=0).start()
    time.sleep(2.0)
# otherwise, we are reading from a video file
else:
    vs = cv2.VideoCapture(args["video"])
# initialize the first frame in the video stream
firstFrame = None

# loop over the frames of the video
while True:
    frame = vs.read()
    frame = frame if args.get('video', None) is None else frame[1]
    text = 'Unoccupied'
    
    if  frame is None:
        break
        
    frame = imutils.resize(frame, width=500)
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    gray = cv2.GaussianBlur(gray, (21, 21), 0)
    if firstFrame is None:
        firstFrame = gray
        continue
        
        
    frameDelta = cv2.absdiff(firstFrame, gray)
    thresh = cv2.threshold(frameDelta, 25, 255, cv2.THRESH_BINARY)[1]
    
    
    thresh = cv2.dilate(thresh, None, iterations=2)
    cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
                            cv2.CHAIN_APPROX_SIMPLE)
    cnts = imutils.grab_contours(cnts)
    
    for c in cnts:
        if cv2.contourArea(c) < args["min_area"]:
            continue

            
        (x, y, w, h) = cv2.boundingRect(c)
        cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
        text = 'Occupied'
        
        
        
    cv2.putText(frame, "Room Status: {}".format(text), (10, 20),
                cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
    cv2.putText(frame, datetime.datetime.now().strftime("%A %d %B %Y %I:%M:%S%p"),
                (10, frame.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.35, (0, 0, 255), 1)
    cv2.imshow('Motion Detector', frame)
    cv2.imshow('Thresh', thresh)
    cv2.imshow('Frame Delta', frameDelta)
    key = cv2.waitKey(1) & 0xFF
    
    if key == ord('q'):
        break
        
vs.stop()if args.get("video", None) is None else vs.release()
cv2.destroyAllWindows()

Answer 1

如果我正确理解您的问题，您想在检测到运动时拍摄图像。我建议的一种方法是不要尝试提取每一帧，而是每隔 1 秒提取一帧。因此，1 分钟的视频将提供 60 帧（图像），而您最终不会得到数千张图像（网络摄像头帧速率 * 秒）。

count = 0 # initialize counter (outside while loop)

在运动中，每 1 秒拍一张照片（我会把它放在这个 if 语句中：

如果 cv2.contourArea(c)

vs.set(cv2.CAP_PROP_POS_MSEC,(count*1000))    # wait 1 sec between each capture
cv2.imwrite('Motion_det'+str(count)+'.jpg',frame)      # save frame as JPEG file
count+=1

Answer 2

下面的调整将保存图像和视频：

# import the necessary packages
from imutils.video import VideoStream
import argparse
import datetime
import imutils     #pip install imutils on terminal
import time
import cv2
# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-v", "--video", help="path to the video file")    #video file is optional, if video file equals None, then opencv will use webcam
ap.add_argument("-a", "--min-area", type=int, default=500, help="minimum area size")  #500 pixels, no need to process large raw images through webcam
args = vars(ap.parse_args())
# if the video argument is None, then we are reading from webcam
if args.get('video', None) is None:
    vs = VideoStream(src=0).start()
    time.sleep(2.0)
# otherwise, we are reading from a video file
else:
    vs = cv2.VideoCapture(args["video"])
# initialize the first frame in the video stream
firstFrame = None

# loop over the frames of the video
sta = 0
while True:
    frame = vs.read()
    frame = frame if args.get('video', None) is None else frame[1]
    text = 'Unoccupied'

    if  frame is None:
        break
    
    frame = imutils.resize(frame, width=500)
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    gray = cv2.GaussianBlur(gray, (21, 21), 0)
    if firstFrame is None:
        firstFrame = gray
        continue
    
    frameDelta = cv2.absdiff(firstFrame, gray)
    thresh = cv2.threshold(frameDelta, 25, 255, cv2.THRESH_BINARY)[1]


    thresh = cv2.dilate(thresh, None, iterations=2)
    cnts = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
                            cv2.CHAIN_APPROX_SIMPLE)
    cnts = imutils.grab_contours(cnts)
    record = "No"
    for c in cnts:
        if cv2.contourArea(c) < args["min_area"]:
            record = "No"
            continue
       
        (x, y, w, h) = cv2.boundingRect(c)
        cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
        text = 'Occupied'
        record = "Yes"
    
    cv2.putText(frame, "Room Status: {}".format(text), (10, 20),
                cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 0, 255), 2)
    cv2.putText(frame, datetime.datetime.now().strftime("%A %d %B %Y %I:%M:%S%p"),
                (10, frame.shape[0] - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.35, (0, 0, 255), 1)
    cv2.imshow('Motion Detector', frame)
    cv2.imshow('Thresh', thresh)
    cv2.imshow('Frame Delta', frameDelta)

    if record = "Yes":
        try:
            ts = time.time()
            st = datetime.datetime.fromtimestamp(ts).strftime("%Y.%m.%d_%H.%M")
            if sta != st:
                filename = 'video-' + st + '.mp4'
                out = cv2.VideoWriter(filename, fourcc, float(fps), (1280,720))
                frame_name = filename.replace('.mp4','.png').format(frame_index)
                cv2.imwrite(frame_name,frame)
                sta = st
            frame_record = cv2.resize(frame,(1280,720),fx=0,fy=0, interpolation = cv2.INTER_CUBIC)
            out.write(frame_record)
        except Exception as e:
            print('Error on line {}'.format(sys.exc_info()[-1].tb_lineno), type(e).__name__, e)
    key = cv2.waitKey(1) & 0xFF

    if key == ord('q'):
        break
vs.stop()
vs.release()
cv2.destroyAllWindows()