Python调用OpenCV实现摄像头的运动检测，,[硬件环境]Win1

Python调用OpenCV实现摄像头的运动检测，,[硬件环境]Win1

[硬件环境]

Win10 64位

[软件环境]

Python版本：2.7.3

IDE：JetBrains PyCharm 2016.3.2

Python库：

1.1)opencv-python(3.2.0.6)

[搭建过程]

OpenCV Python库：

1. PyCharm的插件源中选择opencv-python(3.2.0.6)库安装

[相关代码]

# encoding=utf-8# 导入必要的软件包import argparseimport datetimeimport imutilsimport timeimport 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    # 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]    # 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)    thresh, contours, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) # cv2.findContours()函数返回三个值，第一个返回了你所处理的图像，第二个是轮廓本身，第三个是每条轮廓对应的属性    # 遍历轮廓    for c in contours:        # if the contour is too small, ignore it        print cv2.contourArea(c)        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)    key = cv2.waitKey(1)    # 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()

Python调用OpenCV实现摄像头的运动检测