opencv+python检测入侵物体

opencv+python检测入侵物体

去年暑假在家的时候，参考别人的博客，编写了这个程序，本想着继续完善一下 ，却一直没时间做。偶然翻到了这个程序，决定放上来。
因为时间太久，我也没办法把当初参考的博客放上来（其实是因为懒得找），如果大家需要，我会放上链接。
环境：opencv2.4+python2.7
编辑器：spyder

# -*- coding: utf-8 -*-
"""
Spyder Editor

This is a temporary script file.
"""

import cv2
import time
import datetime

cap = cv2.VideoCapture(0)

avg = None
lastUploaded = datetime.datetime.now()
motionCounter = 0
time.sleep(10)
while(True):
# 逐帧获取图像
    tiestamp = datetime.datetime.now()
    ret, frame = cap.read()
    text = "unoccupied"
if not ret:
break


# 对每帧图像进行操作
    gray = cv2.resize(frame,width=500)#调整大小
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)#变成灰色图像
    gray = cv2.GaussianBlur(gray,(21,21),0)#高斯滤波
if avg is None:
        avg = gray.copy().astype("float")
continue
    cv2.accumulateWeighted(gray,avg,0.5)
# 显示处理后的图像
    cv2.imshow('frame',gray)
#计算当前帧与第一帧的区别
    frameDelta = cv2.absdiff(gray,cv2.convertScaleAbs(avg))
# cv2.imshow('first2',frameDelta)
#填充孔洞
    thresh = cv2.threshold(frameDelta, 45, 255, cv2.THRESH_BINARY)[1]
    thresh = cv2.dilate(thresh, None, iterations=2)
    cv2.imshow('thresh',thresh)
#查找轮廓
    contours, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE)[-2:] 
# cv2.imshow('thresh2',thresh.copy())
for c in contours:
# if the contour is too small, ignore it
if cv2.contourArea(c) < 500:
continue

# 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)
        cv2.imshow('found',frame)
        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)
#if text == "Occupied":
# if (timestamp-lastUploaded).second>=2:
# motionCounter+=1
#if motionCounter>=23:


if cv2.waitKey(1) & 0xFF == ord('q'):
break

# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()

里面调用的是笔记本自带的摄像头来获取图像，如果想要采用别的方式，需要更改一下。如果效果要想好一点儿，可能还需要调整一下参数。程序已经测过，没有问题。