[Python Study Notes]物体运动检测
Posted 刘六六
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基于opencv的cv2模块实现
\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\' >>文件: iot_client.py >>作者: liu yang >>邮箱: liuyang0001@outlook.com >>博客: www.cnblogs.com/liu66blog >>博客: liuyang1.club (抱歉,域名备案中,稍后恢复访问) \'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\'\' #!/usr/bin/env python # -*- coding: utf-8 -*- import cv2 import numpy as np import easygui import datetime from twilio.rest import Client # 打开摄像头 camera= cv2.VideoCapture(0) # 如果摄像头打开失败 if camera.isOpened() == False: # 给与友好性提示 easygui.msgbox("\\n\\n\\n\\n\\n\\n 请保证摄像头可以正常被打开,请检查硬件后重新运行",title=\'提示框\',ok_button=\'确定\') # 得到摄像头的图像尺寸 size = (int(camera.get(cv2.CAP_PROP_FRAME_WIDTH)), int(camera.get(cv2.CAP_PROP_FRAME_HEIGHT))) # 打印尺寸 print(\'size:\'+repr(size)) es = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5,4)) kernel = np.ones((5,5),np.uint8) background = None flag = 0 while True: # 有没有检测到的文本 text = "Undetected" # 读取摄像头的参数 grabbed , frame_lwpCV=camera.read() try: # 将图像转换为RGB gray_lwpCV = cv2.cvtColor(frame_lwpCV,cv2.COLOR_RGB2GRAY) # 将图像进行高斯滤波,去除噪点 gray_lwpCV = cv2.GaussianBlur(gray_lwpCV,(25,25),3) except cv2.error: break # 判断是否有标准的背景图,如果没有就将上面摄像头采集的第一帧的图像作为背景图 if background is None: background = gray_lwpCV continue # 将两个图像进行比较 diff = cv2.absdiff(background,gray_lwpCV) diff = cv2.threshold(diff,50,255,cv2.THRESH_BINARY)[1] # 进行3次膨胀 diff = cv2.dilate(diff,es,iterations=3) # 忽略掉一些很小的因素 image , contours , hierarchy = cv2.findContours(diff.copy(),cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE) for c in contours: # 如果变化的狂过小,则忽略 if cv2.contourArea(c) < 2000: continue (x, y, w, h) = cv2.boundingRect(c) cv2.rectangle(frame_lwpCV, (x, y), (x + w, y + h), (0, 255, 0), 2) # 有物体闯入到背景中,以文本标记 text = "Detected" # 如果文本标记为无 if text == "Undetected" : # 在图像上标出 cv2.putText(frame_lwpCV,"Motion: {}".format(text),(10,20), cv2.FONT_HERSHEY_SIMPLEX,0.5,(0,255,0),2) # 放置时间戳 cv2.putText(frame_lwpCV,datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"), (10,frame_lwpCV.shape[0]-10),cv2.FONT_HERSHEY_SIMPLEX,0.35,(0,255,0),2) # 如果检测到 if text == "Detected" : cv2.putText(frame_lwpCV,"Motion: {}".format(text),(10,20), cv2.FONT_HERSHEY_SIMPLEX,0.5,(0,0,255),2) cv2.putText(frame_lwpCV,datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"), (10,frame_lwpCV.shape[0]-10),cv2.FONT_HERSHEY_SIMPLEX,0.35,(0,255,0),2) # 蒋告警标志位置为1 flag=1 # 判断告警标志位 if flag == 1: # 接入一些接口,进行对用户的警示,微信,丁丁,短信 ...等等 # 然后将标志位置为0 pass # 显示图像 cv2.imshow(\'contours\',frame_lwpCV) # 灰度图像的显示 # cv2.imshow(\'dis\',diff) # 添加退出键--q # 按下退出本次监测 key = cv2.waitKey(1) & 0xff if key == ord(\'q\'): break # 退出后释放摄像头 camera.release() cv2.destroyAllWindows() # 声明:该代码源于腾讯课堂-动脑学院-Python公开课,并加以适当修改
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