python 监控摄像头 截图

#!/usr/bin/python3.6
# -*- coding: utf-8 -*-
'''
@ Copyright (C) 2019
@
@ env stetup：pip3 install opencv-python
@ 
@ 免费知识星球：[一番码客-积累交流](https://t.zsxq.com/NRVBURr)
@ 微信公众号：一番码客
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@ 网站：http://efonfighting.imwork.net
'''
import cv2
import numpy, os, sys
 
def isPicChanged(dividePar, pointDelta, judgeTh):
    '''
    通过前后帧对比，判断画面是否改变
    :param dividePar = 4 # 对比隔点，减少计算量
    :param pointDelta = 50 # 像素点的差异大于该值认为是差异点
    :param judgeTh = 64 # 判断变化画面大小的阈值：画面(1/judgeTh)
    '''
 
    capIdx = 0  # 截图命名
    camIdx = -1
    while  (int(camIdx) < 0 or int(camIdx) > 10) :
        print("enter camera index in 0 and 10:")
        camIdx = int(input())
 
    if not (os.path.isdir('cap')): # 创建存放截图的文件夹
        os.system('mkdir -p {}'.format("cap"))
 
    cap = cv2.VideoCapture(camIdx) #调整参数实现读取视频或调用摄像头
    ret, frameBak = cap.read()
    for i in range(10): #刚打开相机时，曝光不稳定，清理10张
        ret, frameBak = cap.read()
    frame = frameBak
    frameWidth = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
    frameHeight = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
    print("frameWidth:{},frameHeight:{}".format(frameWidth,frameHeight))
    if frameWidth == 0:
        exit("camera is not available.")
 
    while True:
        absCnt = 0
        frameBak = frame
        ret, frame = cap.read()
 
        for wIdx in range(int(frameWidth/dividePar)) :
            for hIdx in range(int(frameHeight/dividePar)) :
                if abs(int(frameBak[hIdx*dividePar][wIdx*dividePar][2]) - int(frame[hIdx*dividePar][wIdx*dividePar][2])) > pointDelta :
                    absCnt += 1
         
        cv2.imshow("cap", frame)
         
        if absCnt > ( frameWidth * frameHeight ) / (dividePar * dividePar) / (judgeTh * judgeTh) :
            capIdx += 2
            cv2.imwrite('cap/cap_{}.jpg'.format(capIdx), frame)
            cv2.imwrite('cap/cap_{}.jpg'.format(capIdx+1), frameBak)
            print("get a pic:{}".format(capIdx/2))
 
        if cv2.waitKey(1) & 0xff == ord('q'):
            break
 
    cap.release()
    cv2.destroyAllWindows()
 
if __name__ == "__main__":  #这里可以判断，当前文件是否是直接被python调用执行
    isPicChanged(4, 50, 64)

 

import cv2
import time
import os
# 定义摄像头对象，其参数0表示第一个摄像头
camera = cv2.VideoCapture(0)
# 测试用,查看视频size
width  = int(camera.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(camera.get(cv2.CAP_PROP_FRAME_HEIGHT))
size = width,height
#打印一下分辨率
print(repr(size))
print("ObjectTrack is running!")
#设置一下帧数和前背景
fps = 5
pre_frame = None
 
while (1):
    time.sleep(0.5)
    start = time.time()
    # 读取视频流
    ret, frame = camera.read()
    # 转灰度图
    gray_pic = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
 
    if not ret:
        print("打开摄像头失败")
        break
    end = time.time()
    #查看视频窗口
    #cv2.imshow("capture", frame)
 
    # 运动检测部分,看看是不是5FPS
    seconds = end - start
    if seconds < 1.0 / fps:
        time.sleep(1.0 / fps - seconds)
    gray_pic = cv2.resize(gray_pic, (480, 480))
    # 用高斯滤波进行模糊处理
    gray_pic = cv2.GaussianBlur(gray_pic, (21, 21), 0)
 
    # 如果没有背景图像就将当前帧当作背景图片
    if pre_frame is None:
        pre_frame = gray_pic
    else:
        # absdiff把两幅图的差的绝对值输出到另一幅图上面来
        img_delta = cv2.absdiff(pre_frame, gray_pic)
        # threshold阈值函数(原图像应该是灰度图,对像素值进行分类的阈值,当像素值高于（有时是小于）阈值时应该被赋予的新的像素值,阈值方法)
        thresh = cv2.threshold(img_delta, 30, 255, cv2.THRESH_BINARY)[1]
        # 用一下腐蚀与膨胀
        thresh = cv2.dilate(thresh, None, iterations=2)
        # findContours检测物体轮廓(寻找轮廓的图像,轮廓的检索模式,轮廓的近似办法)
        contours, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
        for c in contours:
            # 设置敏感度
            # contourArea计算轮廓面积
            if cv2.contourArea(c) < 1000:
                continue
            else:
                print("Get It！！！")
                # 保存图像
                TFile1 = time.strftime('%Y-%m-%d', time.localtime(time.time()))
                TFile2 = time.strftime('%H.%M', time.localtime(time.time()))
                path="G:/test/objectTrack/"+TFile1+"/"+TFile2              
                isExists=os.path.exists(path)
                if not isExists:
                # 如果不存在则创建目录创建目录操作函数
                    os.makedirs(path)                
                    print (path+' Saved!')
                TI = time.strftime('%m%d-%H.%M.%S', time.localtime(time.time()))
                cv2.imwrite(path+ "/"+TI+ '.jpg', frame)
                print(TI)
                break
        pre_frame = gray_pic
 
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
 
# release()释放摄像头
camera.release()
# destroyAllWindows()关闭所有图像窗口
cv2.destroyAllWindows()

import cv2
import time
import os
# 定义摄像头对象，其参数0表示第一个摄像头
camera = cv2.VideoCapture(0)
# 测试用,查看视频size
width  = int(camera.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(camera.get(cv2.CAP_PROP_FRAME_HEIGHT))
size = width,height
#打印一下分辨率
print(repr(size))
print("ObjectTrack is running!")
#设置一下帧数和前背景
fps = 5
pre_frame = None
 
while (1):
    time.sleep(0.5)
    start = time.time()
    # 读取视频流
    ret, frame = camera.read()
    # 转灰度图
    gray_pic = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
 
    if not ret:
        print("打开摄像头失败")
        break
    end = time.time()
    #查看视频窗口
    #cv2.imshow("capture", frame)
 
    # 运动检测部分,看看是不是5FPS
    seconds = end - start
    if seconds < 1.0 / fps:
        time.sleep(1.0 / fps - seconds)
    gray_pic = cv2.resize(gray_pic, (480, 480))
    # 用高斯滤波进行模糊处理
    gray_pic = cv2.GaussianBlur(gray_pic, (21, 21), 0)
 
    # 如果没有背景图像就将当前帧当作背景图片
    if pre_frame is None:
        pre_frame = gray_pic
    else:
        # absdiff把两幅图的差的绝对值输出到另一幅图上面来
        img_delta = cv2.absdiff(pre_frame, gray_pic)
        # threshold阈值函数(原图像应该是灰度图,对像素值进行分类的阈值,当像素值高于（有时是小于）阈值时应该被赋予的新的像素值,阈值方法)
        thresh = cv2.threshold(img_delta, 30, 255, cv2.THRESH_BINARY)[1]
        # 用一下腐蚀与膨胀
        thresh = cv2.dilate(thresh, None, iterations=2)
        # findContours检测物体轮廓(寻找轮廓的图像,轮廓的检索模式,轮廓的近似办法)
        contours, hierarchy = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
        for c in contours:
            # 设置敏感度
            # contourArea计算轮廓面积
            if cv2.contourArea(c) < 1000:
                continue
            else:
                print("Get It！！！")
                # 保存图像
                TFile1 = time.strftime('%Y-%m-%d', time.localtime(time.time()))
                TFile2 = time.strftime('%H.%M', time.localtime(time.time()))
                path="G:/test/objectTrack/"+TFile1+"/"+TFile2              
                isExists=os.path.exists(path)
                if not isExists:
                # 如果不存在则创建目录创建目录操作函数
                    os.makedirs(path)                
                    print (path+' Saved!')
                TI = time.strftime('%m%d-%H.%M.%S', time.localtime(time.time()))
                cv2.imwrite(path+ "/"+TI+ '.jpg', frame)
                print(TI)
                break
        pre_frame = gray_pic
 
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break
 
# release()释放摄像头
camera.release()
# destroyAllWindows()关闭所有图像窗口
cv2.destroyAllWindows()