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opencv+python检测入侵物体

2017-07-08 23:19 363 查看

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。
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