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# -*- coding: utf-8 -*-
# 对摄像头的当前帧与前一帧进行比对,判断是否有移动的物体。
# 代码修改自 http://python.jobbole.com/81593/
# The code is refer to `http://www.pyimagesearch.com/2015/05/25/basic-motion-detection-and-tracking-with-python-and-opencv/`
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"])
# 初始化视频流的前一帧
previousFrame = 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)
# 如果前一帧是None,对其进行初始化
if previousFrame is None:
previousFrame = gray
continue
# 计算当前帧和前一帧的不同
frameDelta = cv2.absdiff(previousFrame, gray)
previousFrame = 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)
(cnts, _) = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,
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)
key = cv2.waitKey(1) & 0xFF
# 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()