基于opencv的cv2模块实现

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>>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)

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#!/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