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  • CV2 的运动检测器 修复

    # -*- coding:utf-8 -*-
    # 导入必要的软件包
    import argparse
    import datetime
    import imutils
    import time
    import cv2
    
    # 创建参数解析器并解析参数
    ap = argparse.ArgumentParser()
    ap.add_argument("-v", "--video", help="path to the video file")
    ap.add_argument("-a", "--min-area", type=int, default=500, help="minimum area size")
    args = vars(ap.parse_args())
    
    # 如果video参数为None,那么我们从摄像头读取数据
    if args.get("video", None) is None:
        camera = cv2.VideoCapture(0)
        time.sleep(0.25)
    
    # 否则我们读取一个视频文件
    else:
        camera = cv2.VideoCapture(args["video"])
    
    # 初始化视频流的第一帧
    firstFrame = None
    
    # 遍历视频的每一帧
    while True:
        # 获取当前帧并初始化occupied/unoccupied文本
        (grabbed, frame) = camera.read()
        text = "Unoccupied"
    
        # 如果不能抓取到一帧,说明我们到了视频的结尾
        if not grabbed:
            break
    
        # 调整该帧的大小,转换为灰阶图像并且对其进行高斯模糊
        frame = imutils.resize(frame, width=500)
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
        gray = cv2.GaussianBlur(gray, (21, 21), 0)
    
        # 如果第一帧是None,对其进行初始化
        if firstFrame is None:
            firstFrame = gray
            continue
        print('ok')
    
        # 计算当前帧和第一帧的不同
        frameDelta = cv2.absdiff(firstFrame, gray)
        thresh = cv2.threshold(frameDelta, 25, 255, cv2.THRESH_BINARY)[1]
        print('ai')
    
        # 扩展阀值图像填充孔洞,然后找到阀值图像上的轮廓
        thresh = cv2.dilate(thresh, None, iterations=2)
       # (_, cnts, _) = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)
        cnts, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
    
        # 遍历轮廓
        for c in cnts:
            # if the contour is too small, ignore it
            if cv2.contourArea(c) < args["min_area"]:
                continue
    
            # compute the bounding box for the contour, draw it on the frame,
            # and update the text
            # 计算轮廓的边界框,在当前帧中画出该框
            (x, y, w, h) = cv2.boundingRect(c)
            cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
            text = "Occupied"
    
        # draw the text and timestamp on the frame
        # 在当前帧上写文字以及时间戳
        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)
    
        # 显示当前帧并记录用户是否按下按键
        cv2.imshow("Security Feed", frame)
        cv2.imshow("Thresh", thresh)
        cv2.imshow("Frame Delta", frameDelta)
        amp = 0xFF
        key = cv2.waitKey(1) & amp
    
        # 如果q键被按下,跳出循环
        if key == ord("q"):
            break
    
    # 清理摄像机资源并关闭打开的窗口
    camera.release()
    cv2.destroyAllWindows()
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  • 原文地址:https://www.cnblogs.com/dgwblog/p/12996221.html
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